Citation
Characterization of Resistance to Respiration Inhibitor Fungicides in Populations of Tangerine-Infecting Alternaria alternata

Material Information

Title:
Characterization of Resistance to Respiration Inhibitor Fungicides in Populations of Tangerine-Infecting Alternaria alternata
Creator:
Vega Jimenez, Byron Patricio
Place of Publication:
[Gainesville, Fla.]
Florida
Publisher:
University of Florida
Publication Date:
Language:
english
Physical Description:
1 online resource (12 p.)

Thesis/Dissertation Information

Degree:
Doctorate ( Ph.D.)
Degree Grantor:
University of Florida
Degree Disciplines:
Plant Pathology
Committee Chair:
DEWDNEY,MEGAN M
Committee Co-Chair:
HARMON,PHIL F
Committee Members:
PERES,NATALIA A R
ROGERS,MICHAEL E
Graduation Date:
5/3/2014

Subjects

Subjects / Keywords:
Alternaria ( jstor )
Cell death ( jstor )
Conidia ( jstor )
Cytochromes ( jstor )
Diseases ( jstor )
Fungicides ( jstor )
Rice ( jstor )
Tangelos ( jstor )
Tangerines ( jstor )
Tangors ( jstor )
Plant Pathology -- Dissertations, Academic -- UF
baseline -- fitness -- fungicides -- qoi -- resazurin -- resistance -- sdhi
City of Minneola ( local )
Genre:
bibliography ( marcgt )
theses ( marcgt )
government publication (state, provincial, terriorial, dependent) ( marcgt )
born-digital ( sobekcm )
Electronic Thesis or Dissertation
Plant Pathology thesis, Ph.D.

Notes

Abstract:
Chemical control of Alternaria brown spot (ABS), caused by Alternaria alternata, is based upon the timely application of site-specific fungicides,many of which are vulnerable to the development of fungicide resistance.Quinone outside inhibitors (QoIs) have been used for more than 10 years for ABScontrol, but in 2008 the first case of QoI resistance was detected in Floridaincreasing the concern in the tangerine industry. The purpose of this researchwas to characterize morphologically and molecularly resistance to QoI andsuccinate dehydrogenase inhibitor (SDHI) fungicides in tangerine-infecting A.alternata populations. A rapid microtiter bioassay, based on the colorimetricchanges of resazurin dye, was developed to evaluate the sensitivity of A.alternata to those respirationinhibitor fungicides. From 2008 to 2012, 817 monoconidial isolates of A.alternata from 46 citrus orchardswere examined for sensitivity to QoIs (azoxystrobin and pyraclostrobin). Of theisolates, 57.6% were resistant to both fungicides. The proportion of resistantisolates differed significantly among cultivars and with QoI applicationfrequency. Moreover, the molecular basis for QoI resistance was determined fora subset of 235 isolates. All resistant isolates showed the point mutationG143A and were further classified as profile I and profile II, based on thepresence of one or two introns, respectively. Phenotypic stability, fitness components, and the ability to cause disease ofQoI-resistant isolates were also studied. Great variability in fitnesscomponents was observed among isolates within the same sensitivity group.Results suggest that QoI resistance in A. alternata was stable in the absence of QoI selection pressure and that theresistant development did not affect the fitness of resistant isolates. Furthermore,the effect of boscalid (SDHI) on multiple physiological stages of fungaldevelopment was established. Sensitivity distribution of 419 A. alternara isolates was tested using isolates neverexposed to boscalid. The molecular characterization of the succinatedehydrogenase (SDH) genes was also determined by cloning and sequencing the SdhB,SdhC, and SdhD genes. Sequencecomparisons of the SDH complex revealed the presence of mutations in 93% ofisolates evaluated. Overall, results from this study will provide bases toimprove disease management programs against ABS in Florida. ( en )
General Note:
In the series University of Florida Digital Collections.
General Note:
Includes vita.
Bibliography:
Includes bibliographical references.
Source of Description:
Description based on online resource; title from PDF title page.
Source of Description:
This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Thesis:
Thesis (Ph.D.)--University of Florida, 2014.
Local:
Adviser: DEWDNEY,MEGAN M.
Local:
Co-adviser: HARMON,PHIL F.
Electronic Access:
RESTRICTED TO UF STUDENTS, STAFF, FACULTY, AND ON-CAMPUS USE UNTIL 2014-11-30
Statement of Responsibility:
by Byron Patricio Vega Jimenez.

Record Information

Source Institution:
UFRGP
Rights Management:
Applicable rights reserved.
Embargo Date:
11/30/2014
Resource Identifier:
907379557 ( OCLC )
Classification:
LD1780 2014 ( lcc )

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Vol. 26, No. 2, 2013 / 191 MPMI Vol. 26, No. 2, 2013, pp. 191–202. http://dx.doi.org/10.1094/MPMI-05-12-0117-R. Identification and Characterization of In planta–Expressed Secreted Effector Proteins from Magnaporthe oryzae That Induce Cell Death in Rice Songbiao Chen,1,2,3 Pattavipha Songkumarn,2 R. C. Venu,2 Malali Gowda,2 Maria Bellizzi,2 Jinnan Hu,2 Wende Liu,1 Daniel Ebbole,4 Blake Meyers,5 Thomas Mitchell,2 and Guo-Liang Wang1,2 1State Laboratory for Biology of Plant Diseases and Insect Pe sts, Institute of Plant Prot ection, Chinese Academy of Agricultural Sciences, Beijing 100193, China; 2Department of Plant Pathology, The Ohio State University, Columbus, OH 43210, U.S.A.; 3Biotechnology Research Institute, Fujian Academy of Agricultural Sciences, Fuzhou, Fujian 350003, China; 4Department of Plant Pathology and Microbiology, Texas A&M University, College Station, TX 79016, U.S.A.; 5Delaware Biotechnology Institute, University of Delaware, Newark, DE, U.S.A. Submitted 16 May 2012. A ccepted 24 September 2012. Interactions between rice and Magnaporthe oryzae involve the recognition of cellular components and the exchange of complex molecular signals from both partners. How these interactions occur in rice cells is still elusive. We employed robust-long serial analysis of gene expression, massively parallel signature sequencing, and sequencing by synthesis to examine transcriptome profiles of infected rice leaves. A total of 6,413 in planta–expressed fungal genes, including 851 genes encoding predicted effector proteins, were identified. We used a protoplast transient expression system to assess 42 of the predicted effector proteins for the ability to induce plant cell death. Ectopic expression assays identified five novel effectors that induced host cell death only when they contained the signal peptide for secretion to the extracellular space. Four of them induced cell death in Nicotiana benthamiana Although the five effectors are highly diverse in their sequences, the physiological basis of cell death induced by each was similar. This study demonstrates that our integrative genomic approach is effective for the identification of in planta–expressed cell death–inducing effectors from M. oryzae that may play an important role facilitating colonization and fungal growth during infection. Coevolution of plants and their pathogens in nature has led both sides to develop a battery of strategies to attack and defend. Plant pathogens may first use cell wall–degrading enzymes to digest the surface layers of cell walls to facilitate penetration. Successful pathogens can secrete a variety of extracellular molecules to modulate host defense circuitry. These extracellular molecules include apoplastic effectors such as virulence factors, toxins, and degradative enzymes that function as key virulence determinants to suppress host defense (Hogenhout et al. 2009). On the other hand, plants have evolved unique mechanisms to defend themselves from most microbes using physical barriers, antimicrobial compounds, and the innate immune system. The plant immune system consists of two layers (Chisholm et al. 2006; Jones and Dangl 2006). The first layer is initiated by the perception of pathogenor microbe-associated molecular patterns (PAMPs or MAMPs) by host membrane-associated pattern recognition receptors (PRR), which cause basal defense responses in plants, called PAMP-triggered immunity (Zhang and Zhou 2010). The second layer is initiated by rapid activation of a hypersensitive reaction (HR) upon recognition of the avirulence effectors by the cognate resistance (R) proteins, which causes strong race-specific resistance called effector-triggered immunity. Over the past decade, extensive studies have led to the identification of many PAMP and avirulence effectors in plant pathogens and PRR and R proteins in plants (Dodds et al. 2009). Among them the majority of the well-characterized effectors are from prokaryotic b acteria that employ a type III secretion system to deliver effectors directly into host cells. Unlike bacteria, fungal and oomycete pathogens often secrete effector proteins to the extracellular milieu through the eukaryotic secretory pathway (Panstruga and Dodds 2009). Many secreted proteins function in the apoplast of plants, and some have been shown to be translocated into plant cells (Dou et al. 2008a; Whisson et al. 2007), in which they function in the host cytoplasm (Armstrong et al. 2005; Bos et al. 2006; Catanzariti et al. 2006; Dodds et al. 2004; Rehmany et al. 2005; Yoshida et al. 2009). Recent advances in genome sequencing technologies have led to a rapid discovery of numerous effectors in oomycete pathogens and have provided a wealth of information on their structure and function. For example, analysis of the Phytophthora sojae and P. ramorum genomes led to the discovery of conserved motifs RXLR and dEER (Tyler et al. 2006), required for the translocation of oomycete effectors into plant cells (Dou et al. 2008a; Whisson et al. 2007). The large family of predicted RXLR proteins thus provided a wealth of candidates for functional studies of effector activities in oomycetes. However, secreted proteins exported by fungi appear to lack such conserved motifs, and little is known about their functions. The hemibiotrophic fungus Magnaporthe oryzae is the causal agent of rice blast, the most devastating disease that affects rice production worldwide (Dean et al. 2005; Ebbole 2007; Talbot 2003). In M. oryzae a larger number of genes (up to S. Chen, P. Songkumarn, and R. C. Venu contributed equally to this work. Corresponding author: Guo-Liang Wang; Department of Plant Pathology; Ohio State University; Telephone: +1.614.292.9280; Fax: +1.614.292.4455; E-mail: wang.620@osu.edu *The e X tra logo stands for “electroni c extra” and indicates three supplementary tables, two supplementary figures, and supplementary methods information are published online. 2013 The American Phytopathological Society e-Xt r a*

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192 / Molecular Plant-Microbe Interactions 1,306) coding for putative secreted proteins have been predicted from the genome of a laboratory strain, 70-15 (Dean et al. 2005; Yoshida et al. 2009). Seven secreted proteins, i.e., PWL1, PWL2 (Kang et al. 1995; Sweigard et al. 1995), AvrPita (Orbach et al. 2000), Avr-Pia, Avr-Pii, Avr-Pik/km/kp (Yoshida et al. 2009), and AvrPiz-t (Li et al. 2009), have been confirmed as avirulence (Avr) proteins presumably recognized by the corresponding resistance gene products. In addition, a few secreted proteins that are required for pathogenicity, i.e., MPG1 (Talbot et al. 1993), EMP1 (Ahn et al. 2004), MHP1 (Kim et al. 2005), MSP1 (Jeong et al. 2007), MC69 (Saitoh et al. 2012), and Slp1 (Mentlak et al. 2012), and four biotrophyassociated secreted proteins, BAS1 to BAS4 (Mosquera et al. 2009), have also been characterized. However, the majority of M. oryzae secreted proteins have not been experimentally tested for their functions in pathogenicity. To identify M. oryzae genes encoding predicted secreted proteins that were expressed in blast-infected leaf tissue, we developed an integrative genome expression profiling approach that includes robust-long serial analysis of gene expression (RL-SAGE) (Gowda et al. 2004), massively parallel signature sequencing (MPSS) (Brenner et al. 2000; Meyers et al. 2004; Nobuta et al. 2007), and sequencing by synthesis (SBS) (German et al. 2008; Venu et al. 2011a). Infected tissues were collected from six timepoints so that fungal transcripts expressed in planta at a late infection stage can be included in the libraries. We used a protoplast transient expression assay to identify in planta–expressed secreted proteins from M. oryzae that induce cell death in rice. Among 42 tested proteins, five cell death–inducing proteins were functionally characterized. The integrative approach described here provides an efficient strategy for functional identification of fungal cell death–inducing proteins that are involved in plant and fungal interactions. RESULTS Gene expression profiling in blast-infected rice leaves. To obtain more comprehensive gene expression profiles of M. oryzae during compatible and incompatible interactions with rice, we constructed one RL-SAGE, eleven MPSS, and seven SBS libraries for deep sequencing. The RL-SAGE library was generated from rice (cv. Nipponbare) leaves inoculated with the compatible isolate Che86061 at 96 h postinoculation (hpi) (Fig. 1A). A total of 18,154 significant signatures were obtained from the library. Among them, 3,105 (17.1%) and 12,263 (67.5%) significant signatures matched to the M. oryzae and rice genomes, respectively. The unmatched signatures may be due to sequencing errors or are located in the sequencing gaps in both the genomes. Only 14 signatures matched to both the M. oryzae and rice genomes, signifying that the majority of signatures were genome specific. We identified 3,091 signatures specifically matching to the M. oryzae genome, which correspond to 3,000 previously annotated M. oryzae genes. Eleven MPSS libraries were generated from the leaves of wild-type Nipponbare plants or transgenic Nipponbare plants carrying the blast resistance gene Pi9 (Qu et al. 2006), which were inoculated with M. oryzae isolate KJ201 during the compatible (3, 6, 12, 24, 48, and 96 hpi) or incompatible interactions (3, 6, 12, 24, and 48 hpi) (Fig. 1A). As expected, more signatures matched to the M. oryzae genome in the compatible interactions compared with that in the incompatible interactions. A total of 57,671 significant signatures were obtained from the five incompatible interaction MPSS libraries. Among these, 724 (1.2%) and 38,024 (65.9%) significant signatures uniquely matched to the M. oryzae and rice genomes, respectively. From the six compatible interaction libraries, a total of 63,132 significant signatures were obtained. Among them, 2,545 (4%) and 41,784 (66.1%) significant signatures uniquely matched to the M. oryzae and rice genomes, respectively. Altogether, 3,216 annotated M. oryzae genes were identified from both the compatible and incompatible MPSS libraries. The same leaf tissue used for the generation of the MPSS libraries (the compatible interaction at 6, 12, 24, and 96 hpi and the incompatible interaction at 6, 12, and 24 hpi) were used for the construction of the seven SBS libraries (Fig. 1A). A total of 65,299 significant signatures were obtained from the three incompatible-interaction SBS libraries. Among them, 3,492 (5.3%) and 49,706 (76.1%) significant signatures specifically matched to the M. oryzae genome and rice genome, respectively. A total of 68,825 significant signatures were obtained from the four compatible-inter action SBS libraries. Signatures matching to the M. oryzae genome numbered 5,283 (7.7%) and those matching to the rice genome numbered 50,756 (73.7%). The SBS signatures from both compatible and incompatible interactions together identified 4,781 annotated M. oryzae genes. Altogether, a total of 6,413 annotated M. oryzae genes expressed during infection process were identified using the three expression profiling technologies (Fig. 1A). Identification of genes encoding putative secreted proteins expressed during infection. Secreted proteins are known to play essential roles during fungal-plant interactions (Rep 2005; Zhang and Zhou 2010). Thus, we focused on the analysis of the secreted protein genes that were identified in the transcriptome libraries described above. To obtain most putative secreted protein genes from the in planta–expressed gene collections, we used two M. oryzae secreted protein datasets, one by Dean and associates (2005) (referred to as dataset I) and the other by Choi and associates (2010) (referred to as dataset II) as references for manual annotation. A total of 851 distinct secreted protein genes were identified from both datasets (Fig. 1A, Supplementary Table S1). About 85.7% (264/308) of the putative secreted protein genes identified in dataset I were present in dataset II (Fig. 1E). Among the three RL-SAGE, MPSS, and SBS libraries made from the rice leaves inoculated with compatible isolates at the same timepoint (96 hpi) (RL-SAGE-96 h, MPSS-96 h, and SBS-96 h), over two times more secreted protein genes were identified from the SBS-96 h library than from the other two libraries in both datasets I and II (Fig. 1C and D). To gain more insight on the function of in planta–expressed secreted proteins involved in the riceM. oryzae interaction, we conducted a gene ontology (GO)-based classification. This analysis revealed that most in planta–expressed secreted proteins are associated with metabolic process, followed by developmental process, cellular process, and multicellular organismal process (Fig. 2A). For molecular functions, most in planta– expressed secreted proteins are associated with catalytic activity and binding (Fig. 2B). Transient expression assays identified five M. oryzae apoplastic effectors that i nduce cell death in rice cells. Host cell death is a ubiquitous feature in plant-pathogen interactions. To identify M. oryzae secreted proteins involved in host cell death, we performed transient expression of M. oryzae secreted proteins in rice protoplasts, using our established method (Chen et al. 2006). In the assay, cell death is monitored by the reduced expression level of a cotransfected -glucuronidase (GUS) reporter gene in rice protoplasts (Fig. 3A) (Dou et al. 2008b; Jia et al. 2000; Mindrinos et al. 1994; Yoshida et al. 2009). A total of 42 secreted protein genes were cloned for the transient expression assay (Supplementary Table S2). For each of the selected genes, two versions of transfection plasmids were constructed, one containing the full-length

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Vol. 26, No. 2, 2013 / 193 open reading frame (ORF) (referred to as FL) and the other containing the truncated coding region without the signal peptide sequence but with an engineered ATG start codon (referred to as NS). The transient assay revealed that five out of 42 secreted protein genes of the FL version caused a significant reduction in GUS activity when expressed in rice protoplasts (Fig. 3B), suggesting that these five proteins can induce cell death in rice cells. On the other hand, transient expression of all 42 examined genes of the NS version did not result in any reduction in cell viability. We thus referred to the five secreted proteins, MGG_03356, MGG_05531, MGG_07986, MGG_ 08409, and, MGG_10234, as MoCDIP1 to MoCDIP5 ( M. oryzae cell death–inducing proteins), respectively. We further performed Agrobacterium -mediated transformation of rice calli with binary vectors containing the five MoCDIP genes to see whether it was possible to obtain stable transgenic lines with the expression of these genes for functional analysis. About 600 calli were used for the transformation of each construct. As expected, no resistant transgenic calli were obtained after transforming with FL-MoCDIP1 FL-MoCDIP2 FLMoCDIP3 or FL-MoCDIP4 individually (data not shown). By contrast, around 50 to 80 transgenic calli were obtained from the transformations with NS-MoCDIP1 NS-MoCDIP2 NS-MoCDIP3 or NS-MoCDIP4 with efficiencies similar to normal transformation efficiencies (around 8 to 15% for other constructs) in our lab. Interestingly, transformation with FLMoCDIP5 at first yielded a normal efficiency of about 40 transgenic calli with no cell-death phenotypes. However, when they were cultured on the selection medium for 2 weeks or longer, the transgenic calli expressing FL-MoCDIP5 started to show cell-death phenotypes (Fig. 3C). Similar to other NSMoCDIP no cell death was observed in the transgenic calli Fig. 1. Gene expression profiling of Magnaporthe oryzae during its interaction with rice. A, Summary statistics for gene expression profiling by robust-long serial analysis of gene expression (RL-SAGE), massively parallel signature sequencing (MPSS), and sequencing by synthesis (SBS) and identification of in planta–expressed M. oryzae genes encoding putative secreted proteins. B, Clustering analysis of all M. oryzae genes identified in the libraries of RL-SAGE96 h, MPSS-96 h, and SBS-96 h, respectively. C, Clustering analysis of putative M. oryzae secreted protein genes retrieved from dataset I (Dean et al. 2005) in RL-SAGE-96 h, MPSS-96 h, and SBS-96 h, respectively. D, Clustering analysis of putative M. oryzae secreted protein genes retrieved from dataset II (Choi et al. 2010) in RL-SAGE-96 h, MPSS-96 h, and SBS-96 h, respectively. E, Clustering analysis of putative M. oryzae secreted protein genes in all timepoints libraries retrieved from datasets I and II, respectively.

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194 / Molecular Plant-Microbe Interactions expressing NS-MoCDIP5 (Fig. 3C). These results, consistent with the transient expression assay in rice protoplasts, confirmed that the five MoCDIP induced cell death when the fulllength proteins are expressed in rice cells. To functionally investigate the predicted secretion feature of the five identified MoCDIP, a yeast secretion assay was performed, following the method previously published (Lee et al. 2006). The sequences of both FL-MoCDIP and NS-MoCDIP Fig. 3. Identification of five in planta–expressed putative s ecreted proteins that induce cell death in rice cells. A, Schematic representation of the rice protoplast transient expression assay ap proach to the identification of Magnaporthe oryzae secreted proteins that can induce rice cell death. Rice protoplasts were cotransfected with a reporter -glucuronidase (GUS) construct ( Promoter-GUS-Tnos ) and the other construct ( Promoter-M.o gene-Tnos ) carrying a M. oryzae secreted protein gene. Rice cell viability was detected based on monitoring the reduced GUS expression level. MoCDIP = M. oryzae cell death inducing protein. B, Ectopic expression of the full length of five MoCDIP in rice protoplasts resulted in reduction in cell viability. CK = protopl ast sample cotransfected with a GUS reporter and an empty vector control; 1 to 5 = protoplast samples cotransfecte d with a GUS reporter and the o ther construct carrying MoCDIP1 to MoCDIP5, respectively. Data bars show averages from three triplicate samples in one experiment. Each experiment was repeated at least three times with similar results. C, Ectopic expression of a full-length but not truncated non–sign al peptide version of MoCDIP5 resulted in cell death in transgenic rice calli. CK = rice calli transformed with empty vector; NS-MoCDIP5 =rice calli transformed with construct carrying a t runcated non–signal peptide version of MoCDIP5; FL-MoCDIP5 = rice calli transformed with cons truct carrying a truncated full-length MoCDIP5. Pictures were taken at about 20 days when the newly obtained transgenic calli were maintained on sel ection media. Transformation experiments were repeated two times and similar results were observed. D, Reverse transcription-polymerase chain reaction (RT-PCR) analysis of expression of NS-MoCDIP5 or FL-MoCDIP5 in transgenic rice calli. CK = RT-PCR result from the rice calli transformed with the empty vector control; 1 to 3 = RT-PCR result from three independent transgenic calli lines. Fig. 2. Gene ontology (GO) annotation of in planta–expressed Magnaporthe oryzae putative secreted proteins. A, Classification based on biological process. B, Classification based on molecular function.

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Vol. 26, No. 2, 2013 / 195 were fused in frame to the N-terminal end of a yeast invertase gene ( suc2 ) lacking its own signal peptide sequence. The fusion constructs were transformed into the yeast strain DBY 2445, an invertase-deficient mutant (Lee et al. 2006), and the transformed yeasts were grown directly on sucrose medium and were assayed for secretion. As expected, the yeast strain transformed with the constructs containing the NS-MoCDIP-suc2 fusions did not grow on sucrose medium (Supplementary Fig. S1), due to the lack of secreted invertase to catalyze the decomposition of sucrose into fruct ose and glucose as the carbon source. In contrast, all five constructs containing the fusions of the FL-MoCDIP-suc2 enabled the yeast mutant strain to grow on sucrose medium, confirming that the predicted signal peptides of the five MoCDIP are functional to direct the invertase fusions to the secretory pathway. These results, together with the results showing that the signal peptide is required for MoCDIP expressed in rice cells to induce rice cell death, indicate that these proteins most likely function in the plant apoplastic space. However, the exact target site of these proteins in plant cells remains to be elucidated. MoCDIP genes are expressed in infected leaves and appressoria. To experimentally confirm th at the MoCDIP genes are expressed in infected leaves and to determine their expression pattern in appressoria and myce lia, reverse transcription-polymerase chain reaction (RT-PCR) was carried out using the RNA extracted from Nipponbare rice leaves inoculated with the compatible blast isolate KJ201 and from M. oryzae appressoria and mycelia. Because of the low proportion of the fungal mass in the infected leaves at early infection stages, the Mo28S transcript was not detected before 72 hpi. Similar to the Mo28S transcript, the MoCDIP2 and MoCDIP4 transcripts were detected from the infected rice leaves only at 72 hpi, and the transcripts of MoCDIP1, MoCDIP3, and MoCDIP5 were detected from the infected rice leaves at 96 hpi (Fig. 4). This result confirmed that all five MoCDIP were expressed during infection stages. The transcripts of MoCDIP1 and MoCDIP2 were detected in both appressoria and mycelia with relatively higher expression in the former, and the transcripts of MoCDIP3, MoCDIP4, and MoCDIP5 were detected only in appressoria (Fig. 4). MoCDIP induce cell death in nonhost plant cells. Many pathogen effectors induce cell death in nonhost plant cells (Rep 2005). To determine whether the five MoCDIP have cell death effects in nonhost plant cells, we performed transient expression assays of the MoCDIP genes in the protoplasts of three model plants, maize ( Zea mays ), Arabidopsis thaliana and Nicotianna benthamiana. Consistent with the results observed in rice protoplasts, transient expression of the five FLMoCDIP but not the NS-MoCDIP induced a significant reduction in cell viability in maize protoplasts (Fig. 5A). As for transient assays in protoplasts of dicot plants Arabidopsis and N. benthamiana expression of the FL-MoCDIP except for FLMoCDIP2 caused significant cell-viability reduction. Similar to the result in rice cells, expression of all five NS-MoCDIP did not reduce cell viability in either Arabidopsis or N. benthamiana protoplasts (Fig. 5B and C). We further tested the five MoCDIP in N. benthamiana leaves via an Agrobacterium -mediated transient-expression approach. A. tumefaciens containing the empty vector pGD and a pGD recombinant expressing WtsE were used as negative and positive controls, respectively. WtsE is a bacterial type III effector that induces cell death in both host and nonhost plants (Ham et al. 2008). Consistent with results from the protoplast assays, infiltration of N. benthamiana leaves with the Agrobacterium strains expressing FL-MoCDIP1 FLMoCDIP3 FL-MoCDIP4 or FL-MoCDIP5 resulted in celldeath responses (Fig. 5D). On the contrary, infiltration of the FL-MoCDIP2 strain, as well as infiltration of the strains carrying the constructs expressing the NS-MoCDIP did not result in cell death in the infiltrated area. RT-PCR analysis was performed to examine the transient expression of the MoCDIP genes, and the results showed that both the FL-MoCDIP and NS-MoCDIP genes were expressed at similar levels in the infiltrated N. benthamiana leaves (Fig. 5E). These results confirmed that MoCDIP1, MoCDIP3, MoCDIP4, and MoCDIP5, but not MoCDIP2 induce cell death in both monocot and dicot species. The timing and appearance of the cell death in N. benthamiana leaves induced by the FL-MoCDIP strains were not as strong as that induced by the WtsE strain. The cell death symptom induced by the WtsE strain usually started at 36 to 48 h after agroinfiltration, and the symptoms induced by the FLMoCDIP1 FL-MoCDIP3 and FL-MoCDIP4 strains generally appeared at 2 to 3 days after agroinfiltration, with a severe cell death around the infiltrated site. However, the symptoms induced by FL-MoCDIP5 generally were visible at 4 to 6 days after agroinfiltration, with weak necrotic spots in the infiltrated area. This result together with the observation of cell death only in relative long-term cultured rice calli expressing FLMoCDIP5 suggests that FL-MoCDIP5 induces weak cell death in a delayed pattern. Physiological basis of the MoCDIP-induced cell death. Previous studies have shown that plant cell death induced by some microbial toxins or effectors share some conserved mechanisms (Asai et al. 2000; Qutob et al. 2006). To further characterize the physiological properties of the cell death induced by the MoCDIP, we performed inhibition assays in rice protoplasts and N. benthamiana leaves. Two cell death–inducing proteins, i.e., WtsE and Bax, were also included in the assays as the controls. Calcium signaling has been shown to play an important role in the cell death process (Boudsocq et al. 2010; Lecourieux et al. 2002). To determine whether calcium signaling is required for the MoCDIP-induced cell death, LaCl3, a calcium channel inhibitor, was applied in the inhibition assays. Application of LaCl3 blocked cell death induced by the transient expression of all MoCDIP suggesting that the cell-death process mediated by these proteins is dependent on a calcium signaling pathway. Fig. 4. In planta expression pattern of the five Magnaporthe oryzae cell death–inducing protein genes ( MoCDIP ). Total RNA samples extracted fro m infected rice leaves 0, 24, 48, 72, 96, or 120 h after inoculation, from in vitro–grown M. oryzae appresorium (A) and mycelium (M) were subjecte d to reverse transcription-polymerase chain reaction using specific primers.

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196 / Molecular Plant-Microbe Interactions Light intensity has been demonstrated to be an important factor for cell-death induction triggered by some toxins or effectors (Asai et al. 2000; Qutob et al. 2006). To test whether MoCDIPinduced cell death is light-dependent, we transfected MoCDIP in rice protoplasts in the light or in the dark. There was no difference of cell viability between the protoplast samples incubated in either condition, indicating that the cell death process induced by the MoCDIP in rice protoplasts is light-independent (Table 1). In contrast, transient expression of the MoCDIP did not induce any cell-death lesions in the leaves of N. benthamiana kept in the dark (Table 1), suggesting that the MoCDIPinduced cell death in N. benthamiana leaves is light dependent. Studies have shown that some antiapoptotic proteins such as BCL-2 family proteins and bax inhibitor-1 (BI-1) can suppress various types of cell death and are functionally conserved in yeast, plants, and mammals (Watanabe and Lam 2009). Overexpression of antiapoptotic proteins was shown to inhibit cell death induced by multiple stimuli, revealing that various types of cell death may have a common downstream mechanism (Dickman et al. 2001). We tested Bcl-xl, a member of the BCL-2 family, to determine whether MoCDIP-induced cell death can be inhibited by the antiapoptotic protein. Preinfiltration with A. tumefaciens cells harboring the Bcl-xl expression vector did not produce cell-death symptoms after infiltration Fig. 5. Transient expression of the full-length but not truncated non–signal peptide version of Magnaporthe oryzae cell death inducing pr otein (MoCDIP) induce d cell death in nonhost plant cells. A, B, and C, Transient expression assay of the fi ve MoCDIP in protoplasts of maize, Arabidopsis and Nicotiana benthamiana respectively. CK = protoplast sample cotransfected with a -glucuronidase (GUS) reporter and an empty vector control; 1 to 5 = protop last samples cotransfecte d with a GUS reporter and the ot her construct carrying MoCDIP 1to MoCDIP5, respectively. D, Transient expression assay of the five MoCDIP in N. benthamiana leaves by using an agroinfiltration approach. Agroinfiltr ation was performed on the sa me leaf side by side with Agrobacterium tumefaciens carrying an empty vector control ( pGD ), a positive control ( WtsE ), constructs with full-length MoCDIP ( FL-MoCDIP ), or constructs with non–signal peptide sequence M oCDI P ( NS-MoCDIP ), respectively. E, Reverse transcription-polymerase chain reaction (RT-PCR) analysis of MoCDIP expression in agroinfiltrated N. benthamiana leaves. Total RNA was extracted from N. benthamiana leaves at 36 h postinoculation. CK = RT-PCR result from tissues infiltrated with the empty vector control; 1 = RT-PCR result from tissues infiltrated with FL-MoCDIP ; 2 = RT-PCR result from tissues infiltrated with NS-MoCDIP Table 1. Inhibition assays of Magnaporthe oryzae cell death–inducing protei ns in rice protoplasts and Nicotiana benthamiana leavesa Applications or treatments Catalase DPI LaCl3 b Dark Bcl_xlc Effector RP NBL RP NBL RP NBL RP NBL RP NBL MoCDIP1 + + + + – – + – ND – MoCDIP2 – ND + ND – ND + ND ND ND MoCDIP3 + + + + – – + – ND – MoCDIP4 – – + + – – + – ND – MoCDIP5 – – + + – – + – ND – WtsE – – + + – – + + ND – Bax – – + + – – + + ND – a RP = rice protoplasts, NBL = N. benthamiana leaves, DPI = diphenyleneiodonium sulfate, + = cell death,–= no cell death, and ND = not determined. b LaCL3 was dissolved in distilled water, and the same volume of water was applied to rice protoplasts or N. benthamiana leaves as control. c An empty vector pGD was applied as control. No effects of controls on cell-death assays was observed.

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Vol. 26, No. 2, 2013 / 197 Fig. 6. Structural analyses of Magnaporthe oryzae cell death inducing proteins (MoCDIP). Schematic views of MoCDIP and their deletion mutants are shown on the left. The predicted domains or motifs of MoCDIP ar e represented as color rectangles The deleted regions are repre sented as dotted lines. MoCDIP and their deletion mutants were transiently expressed in Nicotiana benthamiana leaves or rice protoplasts. Assay results from agroinfiltrated N. benthamiana leaves or transfected rice protoplasts are shown on the right. The signs +, +–, and – indicate obvious cell death, weak cell death, and no cell death, respectively. Data bars of protoplast results show averag es from three triplicate samples in one experiment. Each experi ment was repeated at least three times with similar results.

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198 / Molecular Plant-Microbe Interactions with A. tumefaciens cells carrying MoCDIP WtsE or Bax In contrast, N. benthamiana leaves preinfiltrated with the culture containing the empty vector showed obvious cell-death symptoms induced by the transient expression of MoCDIP WtsE or Bax This result indicated that cell death in N. benthamiana leaves induced by MoCDIP is suppressed by the antiapoptotic protein (Table 1). Sequence and structural analysis of MoCDIP. Sequence analysis revealed that the five identified MoCDIP are highly diverse in their sequences and have no sequence homology with known cell death–inducing effectors in different pathogens, such as Nep1-like proteins (Qutob et al. 2006), INF1 (Kamoun et al. 1997), ToxA (Ciuffetti et al. 1997), ToxB (Martinez et al. 2001), or Nip (Mattinen et al. 2004). BLAST searches against the M. oryzae database and the NCBI nonredundant database revealed that MoCDIP2 and MoCDIP4 have a relatively large number of homologs in the sequenced genomes of M. oryzae and of other organisms (Supplementary Fig. S2). In contrast, MoCDIP1 and MoCDIP5 have homology to proteins only from other microorganisms (Supplementary Fig. S2), and MoCDIP3 has no homologs in the M. oryzae genome or in the sequenced genomes of other organisms. Homology searches also revealed that MoCDIP2 belonged to a family of CFEM-containing proteins that may function as a cell-surface receptor, signal transducers, or as adhesion molecules in host-fungi interactions (Kulkarni et al. 2003); MoCDIP4 was a highly conserved homolog to glycosyl hydrolase family 61 proteins (Davies and Henrissat 1995); and MoCDIP1 and MoCDIP5 shared similarity to ricin B lectin proteins, although there was no sequence similarity between the two proteins. To further delineate the properties of the MoCDIP that are involved in cell-death induction, we searched conserved domains in the proteins and performed functional analysis of deletion mutants based on domain prediction. Deletion mutant constructs of MoCDIP except for MoCDIP3 because it does not contain any predicted domain, were tested in both rice protoplasts and N. benthamiana leaves (Fig. 6). Transient expression assays revealed that a MoCDIP1 mutant of the N-terminal region, amino acids (aa) 1 to 185, was sufficient for inducing cell death in plant cells. However, the N-terminal region, aa 1 to 162, which lacks the PbH1 motif in the aa 1 to 185 fragment, lost the ability to induce cell death, suggesting that the PbH1 motif may play an important role in inducing cell death in plants. The N-terminal, CFEM domain-containing region of MoCDIP2 induced rice cell death efficiently, suggesting that the predicted GPI anchor was not required for cell-death induction. As for MoCDIP4, a deletion mutant lacking the cellulose binding domain (CBD) domain was found to induce only a weak cell death, and the mutant lacking both the linker fragment and the CBD domain failed to induce cell death, suggesting that the C-terminus of the linker fragment and the CBD domain are functionally important in inducing cell death in plants. The assays also showed that MoCDIP5 mutants lacking the C-terminus or lacking the potential zinc-binding site motif failed to induce cell death in both rice protoplasts and N. benthamiana leaves, suggesting that the full length of MoCDIP5 is required for cell-death induction in plants. DISCUSSION Transcriptome profiling in the riceM. oryzae interaction. Using different gene-prediction algorithms, about 12% of the annotated genes (1,546) are predicted to be putative effector proteins in the M. oryzae genome (Soanes et al. 2008). Whether these predicted genes are expressed in infected rice plants is largely unknown. By applying expressed sequence tag (EST) analysis, RL-SAGE, and SuperSAGE analysis to infected rice leaves at the early infection stages, the defense transcriptome in response to M. oryzae infection was characterized (Ebbole et al. 2004; Gowda et al. 2007; Kim et al. 2001; Matsumura et al. 2003; Rauyaree et al. 2001). However, these studies only identified a small number of fungal genes, mainly because the proportion of the fungal RNA in the infected tissue was relatively low and the sequencing coverage was not deep enough. Recently, improved approaches for enrichment of fungal RNA from infected plant tissues have been employed to profile the interaction transcriptome of M. oryzae and rice. Kim and associates (2010) applied EST analysis coupled with subtractive hybridization of a cDNA library from infected leaves at very late stages of infection. A total of 712 uniEST were identified from the fungus, representing up to 31% of the total uniEST. Mosquera and associates (2009) developed a procedure to produce heavily infected rice sheaths that allowed isolation of total RNAs with a high proportion of RNA (up to 20%) originating from biotrophic invasive hyphae of M. oryzae By applying microarray analysis, the authors identified 262 fungal genes and 210 rice genes that were induced up to 10 fold during biotrophic invasion. In this study, we employed three high-throughput technologies, i.e., RL-SAGE, MPSS, and SBS, to profile the transcriptome of M. oryzae –infected rice tissue. While RL-SAGE was only used to study gene-expression profiles from rice leaf tissue infected with a compatible isolate at 96 hpi, both MPSS and SBS were applied to study gene expression profiles of rice leaf tissue inoculated with either a compatible or incompatible isolate at different postinoculation timepoints. In the rice leaves at 72 hpi, inoculated with both incompatible and compatible isolates, only a very limited number of fungal genes were identified, as there were no visible symptoms or only a very few brown lesions appeared on the rice leaves. When inoculated with a compatible isolate at 96 hpi, rice leaves developed typical susceptible blast lesions. Consistently, a relatively large number of fungal transcripts were detected from heavily infected leaves. We identified 3,091 (17%), 2,327 (12.3%), and 5,099 (11.4%) significant M. oryzae tags from the libraries of RL-SAGE-96 h, MPSS-96 h, and SBS-96 h, respectively. By combining results from three technologies, we identified a total of 6,413 M. oryzae genes, including 851 genes that are predicted to encode putative secreted proteins and might be expressed in planta. Our results together with those previously reported will provide valuable information for future studies of the molecular mechanisms underlying the rice –M. oryzae interaction. Clustering analysis of the three 96-h libraries showed that the transcripts recovered from the RL-SAGE, MPSS, and SBS were partially overlapping, similar to previous results of transcriptional profiles of M. oryzae using MPSS, RL-SAGE, and oligoarray methods (Gowda et al. 2006). This result also suggests that using multiple different approaches can provide more comprehensive gene expression profiles. When considering individual technologies, SBS appeared to be the most efficient method for transcript profiling. While similar numbers of M. oryzae genes were identified from RL-SAGE-96 h and MPSS-96 h (3,008 and 2,401 unique M. oryzae genes from the two libraries, respectively), a total of 4,730 M. oryzae genes were identified from SBS-96 h (Fig. 1B), almost twice the gene numbers identified by the other two methods. Moreover, the M. oryzae transcripts recovered from SBS-96 h included most of the M. oryzae transcripts from RL-SAGE-96 h or MPSS-96 h. Our results indicated that many weakly expressed transcripts of both rice and M. oryzae were recovered in the libraries, due to the deep coverage of the transcriptome. As the sequencing cost is rapidly declining, the SBS-based ultra-fast sequencing method or other next-generation sequencing plat-

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Vol. 26, No. 2, 2013 / 199 forms will allow for more in-depth characterization of plantpathogen interaction transcriptomes. Functional identification of M. oryzae effectors using the rice protoplast transient expression system. Transcriptional analysis of the M. oryzae effector genes in infected rice plants has provided a starting point for functional analysis of the in planta–expressed genes in the rice– M. oryzae interaction. Over the past two decades, several M. oryzae avirulence or pathogenicity effector genes have been isolated by map-based cloning (Kang et al. 1995; Orbach et al. 2000; Sweigard et al. 1995), genetic association analysis (Yoshida et al. 2009), or loss-of-function (Ahn et al. 2004; Jeong et al. 2007; Kim et al. 2005; Talbot et al. 1993) approaches. The first two procedures are time-consuming, tedious, and expensive. As for loss-of-function approach, it is often hampered by the fact that many genes may have overlapping functions. For example, many knockout mutants of secreted protein genes have no identifiable phenotype (Mosquera et al. 2009). Thus, a costefficient and high-efficiency gain-of-function method would be a valuable alternative approach to the identification of M. oryzae effectors. As for gain-of-function identification, the agroinfiltration transient assay is a widely used approach for characterizing function of phytopathogen effectors in many solanaceous plants, especially in N. benthamiana and N. tabacum (Munkvold and Martin 2009). However, this agroinfiltration method is not applicable in monocot plants. We previously reported a protoplast transient expression system to perform assays directly in rice cells (Chen et al. 2009a). Recently, Yoshida and associates (2009) and Okuyama and associates (2011) detected HR in rice protoplasts coexpressing R gene and its cognate Avr gene from M. oryzae Using the system, they successfully screened the candidates of M. oryzae Avr-Pia Avr-Pii Avr-Pik/km/kp and rice blast resistance gene Pia In this study, we identified five M. oryzae effectors that induce cell death in rice cells. The results demonstrate that the rice protoplast expression assay is an efficient method for large-scale screening of putative effectors that induce cell death or HR reaction. Role of MoCDIP in the interaction between M. oryzae and rice. Unlike many bacterial pathogens that deliver effector proteins inside host cells via a ty pe III secretion system, eukaryotic plant pathogens, like oomycetes and fungi, seem to secrete a large number of extracellular proteins via the eukaryotic (type II) secretory pathway (Panstruga and Dodds 2009). Some secreted proteins are translocated into host cells and function in the host cytoplasm to suppress host defenses. Many others function in the host apoplastic space to facilitate the parasitic lifestyle of pathogens. The latter include degradative enzymes, toxins, or inhibitors of plant enzymes. More recently, a broader definition of the term effector was suggested to include these secreted proteins, as they exert some effect on plant cells (Hogenhout et al. 2009). Over the past few decades, several apoplastic effectors with toxin or elicitor activity that can induce cell death in plants have been identified from eukaryotic plant pathogens (Rep 2005). Many of these apoplastic effectors play a positive role in the virulence of the hemibiotrophic or necrotrophic plant pathogens (Ottmann et al. 2009; Qutob et al. 2006). From 42 in planta–expressed M. oryzae putative secreted proteins, we successfully identified five novel effectors MoCDIP1 to MoCDIP5 that induce plant cell death. Given the fact that these genes are expressed during infection stages, especially 96 hpi (Fig. 4), we speculate that some of these cell death-inducing effectors may facilitate the colonization of M. oryzae during the late necrotrophic phase of the blast infection, which is a common mechanism among different pathosystems (Gijzen and Nurnberger 2006). It will be interesting to identify the receptor of these effectors in rice cells and define the interactions that trigger rice cell necrosis. The five MoCDIP are highly diverse in their sequences. While MoCDIP3 does not share any significant similarity with any known proteins, MoCDIP1, MoCDIP2, MoCDIP4, and MoCDIP5 have closely related homologs from M. oryzae or other microorganisms. Our analysis also revealed that cell death induced by the five different MoCDIP share similar physiological phenotypes, such as the response to light, to inhibitors of calcium channel, and to Bcl-x1–mediated cell death suppression. These results together suggest that the cell death–inducing mechanism of the five MoCDIP might be similar, though their sequences are quite different. Among the five MoCDIP, MoCDIP4 belongs to a large family of cellulolytic enzymes from a wide variety of microorganisms. Related homologous proteins include endoglucanase, xylanase, and acetylxylan esterase. Several previous studies have observed that the expression of genes encoding members of this family of enzymes was modulated by mitogen-activated protein kinase signaling pathways, which play critical roles in regulating pathogenesis as well as other features (Lev and Horwitz 2003; Madhani et al. 1999; Roberts et al. 2000). However, because of redundancy among cellulolytic enzymes, knock-out of one or even several genes encoding cellulolytic enzymes had little or no consequences for virulence (Lev and Horwitz 2003). In this report, we demonstrate that MoCDIP4, a putative endoglucanase, induces cell death when it is expressed in plant cells. Hence, our finding provides a new clue to the mechanism by which the cellulolytic enzymes can aid invasion of microorganisms. MoCDIP4 contains two conserved domains, a glycosyl hydrolase family 61 domain and a fungal CBD. Recently, the fungal CBD have been shown to be important for the function of a Phytophthora elicitor lectin CBEL in plant cell-death induction (Gaulin et al. 2006) and for the function of a Trichoderma swollenin in plant root colonization (Brotman et al. 2008). More interestingly, the CBD domain was identified as a novel type of PAMP in microorganisms (Brotman et al. 2008; Gaulin et al. 2006). Consistent with previous reports, the CBD domain of MoCDIP4 was found to be important in inducing plant cell death (Fig. 6), strengthening the notion that the CBD plays a functionally conserved role, such as serving as a PAMP elicitor among different plant-pathosystems. MATERIALS AND METHODS Plant materials and fungal strains. Rice ( Oryza sativa ) materials used in this study were wildtype Nipponbare plants and transgenic Nipponbare plants carrying a blast resistance gene Pi9 (Qu et al. 2006). M. oryzae isolates used in this study include Che86061 and KJ201. Construction and data analyses of RL-SAGE, MPSS, and SBS libraries. RNA samples isolated from rice leaves inoculated with M. oryzae isolates were used for library construction. The RLSAGE library was constructed following previously described procedures (Gowda et al. 2004). MPSS library construction was carried out at Illumina (San Diego, CA, U.S.A.), as described (Brenner et al. 2000; German et al. 2008; Meyers et al. 2004). The same total RNAs used for the MPSS library construction (except samples from leaves collected at 3 and 48 hpi) were used for the SBS library construction using our published protocols (Venu et al. 2011a). RL-SAGE clones were sequenced at the Arizona Genome Institute (Tucson, AZ, U.S.A. ). RL-SAGE signatures were

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200 / Molecular Plant-Microbe Interactions identified using the SAGEspy program. MPSS tag processing was carried out at Illumina (Brenner et al. 2000; Meyers et al. 2004; Lu et al. 2005). The distinct RL-SAGE, MPSS, and SBS tag sequences were matched to the M. oryzae reference sequences, including the whole genomic sequences, annotated genes, and 500 bp upstream (putative 5 untranslated region [UTR]) and downstream (putative 3 UTR) regions that are available from the Broad Institute (version 6.0) (Gowda et al. 2006; Venu et al. 2007; Venu et al. 2010, 2011a and b). Rice and M. oryzae transcript signatures from RL-SAGE, MPSS, and SBS experiments were separated after matching signatures to the whole genomic sequence of both rice (Michigan State University’s Plant Biology directory) and M. oryzea To identify in planta–expressed M. oryzae genes encoding for putative secreted proteins, the experimental RL-SAGE, MPSS, and SBS signatures were matched to two computational prediction datasets of M. oryzae secreted proteins (Choi et al. 2010; Dean et al. 2005). Clustering analysis using Microsoft access was performed to identify the putative secreted protein genes expressed specifically or commonly among the three platforms. The RL-SAGE data were deposited at the Magnaporthe oryzae community annotation database and the MPSS and SBS data were deposited at Arabidopsis MPSS Plus database. Cloning of M. oryzae genes encoding putative secreted protein and construction of MoCDIP -related vectors. We first selected about 100 putative secreted protein genes with high expression levels from the libraries. We had difficulty cloning some of the genes, mainly because the proportion of fungal RNA in the total RNA from infected rice leaves was relatively low. Some of the genes were cloned from M. oryzae EST clones or from M. oryzae genomic DNA, for those with no intron. A total of 42 in planta–expressed M. oryzae putative secreted protein genes were selected for functional characterization based on the profiling data. The genes were amplified by PCR, using specific primers, and were cloned into plant expression vector pXUN (Chen et al. 2009b). MoCDIP related vectors were generated based on fragments cloned into pXUN. Protoplast transient expression assays. Transient expression assays in the protoplasts of rice, maize, Arabidopsis and N. benthamiana were carried out following previously described procedures (Chen et al. 2006; Sheen 2001). For transient assays in rice and maize cells, protoplasts were cotransfected with a maize ubiquitin1 promoter gus construct (Chen et al. 2006) and the pXUN-based construct of M. oryzae secreted protein genes, and for transient assays in Arabidopsis and N benthamiana cells, protoplasts were cotransfected with a Cauliflower mosaic virus 35S promoter gus construct (Odell et al. 1985) and the pGD-based construct (Goodin et al. 2002) of M. oryzae secreted protein genes. After transfection, protoplasts were incubated at room temperature for 16 to 24 h. GUS activity was detected essentially as described (Jefferson et al. 1987), using 4-methylumbelliferyl-D-glucuronide (Sigma-Aldrich, St Louis) as the substrate. More details of materials and methods are available in the Supplementary Materials and Methods published online. ACKNOWLEDGMENTS We are grateful to M. M. Goodin, University of Kentucky, for kindly providing the pGDG and pGDR plasmids and B. Jaffee for editing the manuscript. This project is supporte d by the National Science FoundationPlant Genome Research Program (numbers 0605017 and 0701745), and by the National Natural Science Foundation of China (number 31171808). S. Chen, P. Songkumarn, and R. C. Venu were involved in the conception and planning of the study, carried out the experiments, and drafted the manuscript. M. Gowda, M. Bellizzi, J. Hu, and W. Liu were involved in performing part of experiments; D. Ebbole, B. C. Meyers, and T. Mitchell were involved in interpretation of results and writing the manuscript. G.-L. Wang was responsible for conception a nd planning of the study, interpretation of results, and writing the manuscript. All authors read and approved the final manuscript. The authors declare that they have no competing interests. LITERATURE CITED Ahn, N., Kim, S., Choi, W., Im, K. H., and Lee, Y. H. 2004. 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AUTHOR-RECOMMENDED INTERNET RESOURCES Arabidopsis MPSS Plus database: mpss.udel.edu/#rice Broad Institute (version 6.0) download sequence webpage: www.broadinstitute.org/annotation/ genome/magnaporthe_grisea/Multi Downloads.html Illumina website: www.illumina.com Magnaporthe oryzae community annotation database: www.mgosdb.org Michigan State UniversityÂ’s Plant Biology directory: ftp.plantbiology.msu.edu/pub/data/Eukaryotic_Projects/o_sativa/annotat ion_dbs/pseudomolecules/version_6.0 SAGEspy program: www.osc.edu/research/bioinformatics/projects/sagespy/index.shtml



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1 CHARACTERIZATION OF RESISTANCE TO RESPIRATION INHIBITOR FUNGICIDES IN POPULATIONS OF TANGERINE INFECTING Alternaria alternata By BYRON PATRICIO VEGA JIM NEZ A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2014

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2 2014 Byron Patricio Vega Jim nez

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3 To my lovely wife Mar a Cristina and our daughter Daniela Elaine for always believing in me and loving me

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4 ACKNOWLEDGMENTS I am very thankful to Jesus Christ, my Lord and savior, for blessing my life, and for letting me know there is no victory in strife. begotten Son, that whosoever believeth in him should not perish, but hav (John 3:16). I would like to gratefully and sincerely thank to my committee chair Dr. Megan M. Dewdney for entrusting me with this work, for her guidance, understanding, and patience. Her mentorship was paramount in providing a well ro unded experience consistent my long term career goals. She has an insightful comment to share about most subjects. I would also like to thank to my other committee members Drs. Philip F. Harmon, Natalia A. Peres and Michael E. Rogers for all their support, input, and valuable discussion. I would also like to thank to all members working at CREC in the Dewdney lab, Katia Rodrigues, Nan Yi Wang, Naweena Thapa, Jenna Lastinger, and Katrina Nicoletta. I would like to express my sincere gratitude to Daniele Libe rti, Evan Johnson, and Jessica Ulloa who somehow willingly contributed to the accomplishment of this work. I acknowledge Dr. Davis lab members, Huiquin Chen and Mara E. Peacock for their help. Finally, and most importantly, I would like to thank my wife Mara Cristina. Her support, encouragement, quiet patience and unwavering love were undeniably the bedrock upon which the past ten years of my life have been built. I thank my parents, Marco Anto nio and Laura Judith, for their faith in me and allowing me to be a better person. Also, I thank to the International Center of Integral Theoterapy (CENTI), especially to Reverends Jos Daz and Olga Luca Hernndez for their spiritual support.

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5 TABLE O F CONTENTS page ACKNOWLEDGMENTS ................................ ................................ ................................ ............... 4 LIST OF TABLES ................................ ................................ ................................ ........................... 8 LIST OF FIGURES ................................ ................................ ................................ ....................... 10 ABSTRACT ................................ ................................ ................................ ................................ ... 13 CHAPT ER 1 LITERATURE REVIEW ................................ ................................ ................................ ....... 15 Economic Impact of Tangerine and Tangerine Hybrids in Florida ................................ ........ 15 Host Selective Toxins Produced by A. alternata ................................ ................................ ... 16 Disease Symptoms of Alternaria Brown Spot ................................ ................................ ........ 17 Biology and Life Cycle ................................ ................................ ................................ ........... 17 Disease Management ................................ ................................ ................................ .............. 18 Quinone Outside Inhibitor (QoI) Fungicides ................................ ................................ .......... 20 Biology of QoI Fungicides ................................ ................................ .............................. 21 Mode of Action of QoI Fungicides ................................ ................................ ................. 22 Resistance to QoI Fungicides ................................ ................................ .......................... 23 Alternative Respiration in Fungi ................................ ................................ ..................... 24 Succinate Dehydrogenase Inhibitor (SDHI) Fungicides ................................ ........................ 25 Biology of SDHI Fungicides ................................ ................................ ........................... 26 Mode of Action of SDHI Fungicides ................................ ................................ .............. 26 Resistance to SDHI Fungicides ................................ ................................ ....................... 27 Research Objectives ................................ ................................ ................................ ................ 28 2 A RAPID RESAZURIN BASED MICROTITER ASSAY TO EVALUATE QoI SENSITIVITY FOR Alternaria alternata ISOLATES AND THEIR MOLECULAR CHARACTERIZATION ................................ ................................ ................................ ........ 30 Introduction ................................ ................................ ................................ ............................. 30 Materials and Methods ................................ ................................ ................................ ........... 31 Fungal Isolates ................................ ................................ ................................ ................. 31 Medium Evaluation at Different Conidia and Resazurin Concentrations ....................... 32 Effect of SHAM on Alternaria Growth in the RZ Based Microtiter Assay ................... 32 RZ Based Microtiter Assay of QoI Fungicide Sensitivity ................................ .............. 33 Resazurin Reduction ................................ ................................ ................................ ........ 34 Conidia Germination Test ................................ ................................ ............................... 34 DNA Extraction and Sequence Analysis ................................ ................................ ......... 35 Statistical Analysis ................................ ................................ ................................ .......... 37 Results ................................ ................................ ................................ ................................ ..... 37 Effect of Media and Conidia Concentration ................................ ................................ .... 37

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6 Effect of SHAM on A. alternata Growth ................................ ................................ ........ 38 Assessment of Sensitivity to Azoxystrobin and Pyraclostrobin ................................ ...... 39 Cytochrome b Partial Gene Sequence Analysis ................................ .............................. 40 CAPS Analysis ................................ ................................ ................................ ................ 41 Discussion ................................ ................................ ................................ ............................... 41 3 DISTRIBUTION OF QoI RESISTANCE IN POPULATIONS OF TANGERINE INFECTING Alternaria alternata IN FLORIDA ................................ ................................ .. 58 Introduction ................................ ................................ ................................ ............................. 58 Materials and Me thods ................................ ................................ ................................ ........... 60 Isolate Collection ................................ ................................ ................................ ............. 60 Pathogenicity Tests and Monoconidial Isolates ................................ .............................. 61 Sensitivity of A. alternata Isolates to Azoxystrobin and Pyraclostrobin ........................ 62 Baseline Sensitivity of A. alternata to Azoxystrobin and Pyraclostrobin ....................... 63 DNA Extraction and Molecular Detection of the G143A Mutation ............................... 63 Statistical Analysis ................................ ................................ ................................ .......... 64 Result s ................................ ................................ ................................ ................................ ..... 65 Baseline Sensitivity to Azoxystrobin and Pyraclostrobin ................................ ............... 65 Alternaria alternata Isolate Collection ................................ ................................ ........... 65 QoI Resistance in Florida Citrus Orchards ................................ ................................ ...... 66 Sensitivity Distribution of Alternaria alternata Isolates to Azoxystrobin and Pyraclostrobin ................................ ................................ ................................ .............. 66 Cross Resistance to QoI Fungicides ................................ ................................ ................ 67 QoI Resistance Associated with Citrus Hosts and Orchard Factors ................................ 67 Detection of the G143A Mutation ................................ ................................ ................... 68 Discussion ................................ ................................ ................................ ............................... 68 4 QoI RESISTANCE STABILITY IN RELATION TO PATHOGENIC AND SAPROPHYTIC FITNESS COMPONENTS OF Alternaria alternata FROM CITRUS ..... 88 Introduction ................................ ................................ ................................ ............................. 88 Materials and Methods ................................ ................................ ................................ ........... 90 Fungal Isolates ................................ ................................ ................................ ................. 90 DNA Extraction and Molecular Detection of the G143A Mutation ............................... 91 Phenotypic Stability of QoI Resistant and Sensitive Isolates ................................ ........ 91 Saprophytic Fitness Components ................................ ................................ .................... 92 Mycelial growth ................................ ................................ ................................ ....... 92 Conidial production ................................ ................................ ................................ .. 92 Conidial germination ................................ ................................ ................................ 93 Pathogenic Fitness Components ................................ ................................ ...................... 93 Efficacy of Azoxystrobin for Control of ABS Caused by QoI Sensitive and Resistant Isolates ................................ ................................ ................................ .......... 94 Statistical Analysis ................................ ................................ ................................ .......... 95 Results ................................ ................................ ................................ ................................ ..... 95 QoI Sensitivity and Detection of the G143A Mutation ................................ ................... 95 Stability of Resistance ................................ ................................ ................................ ..... 96

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7 Saprophytic Fitness ................................ ................................ ................................ ......... 96 Pathogenic Fitness ................................ ................................ ................................ ........... 97 Correlation between Fitness an d Resistance ................................ ................................ ... 98 Efficacy of Azoxystrobin in Greenhouse Experiments ................................ ................... 98 Discussion ................................ ................................ ................................ ............................... 99 5 SENSITIVITY OF A lternaria alternata FROM CITRUS TO BOSCALID AND POLYMORPHISM IN THE IRON SULFUR AND IN THE ANCHORED MEMBRANES SUBUNITS OF SUCCINATE DEHYDROGENASE ............................... 114 Introduction ................................ ................................ ................................ ........................... 114 Materials and Methods ................................ ................................ ................................ ......... 116 Fungal Collection ................................ ................................ ................................ .......... 116 A. alterna ta Sensitivity to Boscalid Based on Mycelial Growth Inhibition with Different Culture Media ................................ ................................ ............................. 117 Evaluation of Methods to Character ize A. alternata Sensitivity to Boscalid ................ 118 Conidia germination ................................ ................................ ............................... 118 Spiral gradient ................................ ................................ ................................ ........ 118 Resazurin mi crotiter ................................ ................................ ............................... 119 Boscalid Sensitivity of Field Isolates ................................ ................................ ............ 119 Analysis of DNA Sequence of the SDH Subunits ................................ ......................... 120 Statistical Analysis ................................ ................................ ................................ ........ 121 Result s ................................ ................................ ................................ ................................ ... 121 Medium Selection for Boscalid Sensitivity for Mycelial Growth Inhibition Test ........ 121 Effect of Boscalid on Conidia Germination, Mycelial Growth, and Resazurin Reduction ................................ ................................ ................................ ................... 122 Sensitivity of A. alternata Isolates to Boscalid Using Resazurin Test .......................... 122 Molecular Characterization of the SdhB, SdhC, and SdhD Genes of Succinate Dehydrogenase ................................ ................................ ................................ ........... 123 Polymorphism Analysis of the SDHB, SDHC, and SDHD Subunits of Succinate Dehydrogenase ................................ ................................ ................................ ........... 124 Discussion ................................ ................................ ................................ ............................. 125 6 FINAL CONCLUSIONS AND SUMMARY ................................ ................................ ...... 144 APPENDIX A SUPPLEMENTAL FIGURES FOR CHAPTER 2 ................................ ............................... 147 B SUPPLEMENTAL FIGURE FOR CHAPTER 3 ................................ ................................ 151 C SUPPLEMENTAL FIGURES FOR CHAPTER 5 ................................ ............................... 152 LIST OF REFERENCES ................................ ................................ ................................ ............. 156 BIOGRAPHICAL SKETCH ................................ ................................ ................................ ....... 172

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8 LIST OF TABLES Table page 2 1 Isolates by host, location and year of collection. ................................ ............................... 48 2 2 F statistics and P values for the media effect on the growth of six Alternaria alternata isolates measured by percent resazurin reduction under different conidia and resazurin concentrations. ................................ ................................ ............................. 49 2 3 Effective concentration needed to reduce resazurin or conidia germination by 50% (EC 50 ) for azoxystrobin and pyraclostrobin by isolate. ................................ ..................... 50 2 4 Analysis of variance for effective concentration needed to reduce resa zurin or conidium germination by 50% (EC 50 values) for isolate. ................................ .................. 51 3 1 Baseline sensitivity of Alternaria alternata isolates from different hosts to azoxystrobin and pyraclostrobin. ................................ ................................ ....................... 77 3 2 Origin, history of fungicide exposure, and detection of quinone outsid e inhibitor resistance in Alternaria alternata isolates collected in Florida citrus groves from 2008 to 2012. ................................ ................................ ................................ ..................... 78 3 3 A 2 analysis of quinone outside inhibitor (QoI) resistant isolates of Alternaria alternata collected in Florida from 2008 to 2012 according to field severity, virulence class, and number of QoI applications per year. ................................ ................ 80 4 1 Molecular characterization and changes of azoxystrobin and pyraclostrobin sensitivities of Alternaria alternata isolates after ten consecutive subculture cycles on fungicide free potato dextrose agar (PDA). ................................ ................................ 105 4 2 Saprophytic fitness components of quinone outside inhibitor sensitive and resi stant isolates of Alternaria alternata ................................ ................................ ........................ 106 4 3 Pathogenic fitness components of quinone outside inhibitor sensitive and resistant isolates of Alternaria alternata in cultivar Dancy using detached leaves ....................... 107 4 4 Pathogenic fitness components of quinone outside inhibitor sensitive and resistant isolates of Alternaria alternata in cultivar Minneola using detached leaves .................. 108 4 5 Pathogenic fitness components of quinone outside inhibitor sensitive and resistant isolates of Alternaria alternata in cultivar Murcott using detached leaves ..................... 109 4 6 Pathogenic fitness components of quinone outside inhibitor sensitive and resistant isolates of Alternaria alternata in cultivar Sunburst using detached leaves ................... 110

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9 5 1 Sensitivity of Alternaria alternata isolates to boscalid according to the method and media used ................................ ................................ ................................ ...................... 133 5 2 Origin, number, and sensitivity to boscalid of Alternaria alternata isolates collected in Florida citrus groves ................................ ................................ ................................ ... 134 5 3 Primers sets used for amplification of the SdhB, SdhC, and SdhD genes from Alternaria alternata genomic DNA ................................ ................................ ................ 136 5 4 Amino acid substitutions in the succinate dehydrogenase (SDH) subunits B, C, and D in field isolates of Alternaria alternata collected in Florida citrus g roves ................. 137

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10 LIST OF FIGURES Figure page 2 1 Resazurin reduction in four liquid media influenced by Alternaria alternata conidia concentra tion and resazurin concentratio ................................ ................................ ........... 52 2 2 Effect of SHAM on resazurin reduction ................................ ................................ ............ 53 2 3 Dose response of Alternaria alternata isolates to azoxystrobin based on resazurin microtiter assay ................................ ................................ ................................ .................. 54 2 4 Relationship between azoxystrobin and pyraclostrobin sensitivity (effective concentration needed to reduce fungal growth by 50% [EC 50 ]) values as determin ed by the rezarurin based microtiter assay and the conidia germination assay ...................... 55 2 5 Partial structure at the exon intron junction in the cytochrome b gene of Alternaria alternata ................................ ................................ ................................ ............................. 56 2 6 Cleavable amplified polymorphic sequence (CAPS) analysis of the cytochrome b gene ................................ ................................ ................................ ................................ .... 57 3 1 Baseline sensitivity distribution of Alt ernaria alternata isolates (n=40) to QoI fungicides ................................ ................................ ................................ ........................... 81 3 2 Geographic distribution of QoI sensitive and resistant Alternaria alt ernata isolates collected in 46 commercial citrus orchards encompass ing 78 blocks from 2008 to 2012 ................................ ................................ ................................ ................................ .... 82 3 3 Sensitivity distribution of Alternaria alternata isolates (n=817) collected in Florida citrus orchards from 2008 to 2012 to QoI fungicides ................................ ........................ 83 3 4 Correlation of effective concentration needed to reduce fungal growth by 50% (EC 50 ) values of azoxystrobin and pyraclostrobin in quinone outside inhibitor sensitive Alternaria alternata isolates (n=346) ................................ ................................ ................ 84 3 5 Distribution of sensitive (n=346) and resistant (n=471) Alternaria alternata isolates to azoxystrobin and pyraclostrobin collected during 2008 to 2012 from Florida tangerine and tangerine hybrids orchards ................................ ................................ .......... 8 5 3 6 Restriction fragment length polymorphism analysis of the partial structure of the cytochrome b gene from Alternaria alternata isolates that are either quinone outside inhibitor sensitive or resistant ................................ ................................ ............................ 86 3 7 Frequency distribution of sensitive (n=74) and resistant (n=161) Alternaria alternata isolates to azoxystrobin and pyraclostrobin according to cytochrome b profiles .............. 87

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11 4 1 Alternaria brown spot symptoms on detached leaves of cultivars Minneola (MN), Dancy (DAN), Murcott (MUR), and Sunburst (SUN) inoculated with conidia suspension (2 10 4 conidia/ml) from a representative quinone outside inhibitor sensitive isolate ................................ ................................ ................................ ................ 111 4 2 Correlation analysis between QoI sensitivity and fitness components ............................ 112 4 3 inoculated with quinone outside inhibitor resistant and sensitive isolates of Alternaria alternata ................................ ................................ ................................ ......... 113 5 1 Boscalid amended agar technique to evaluate mycelial growth inhibition under different fungicide concentrations on three culture media ................................ .............. 138 5 2 Alternaria alternata isolates grown on spiral gradient end point dilution plates ............ 139 5 3 Relative mycelial growth of Alternaria alternata on complete medium agar (circles), minimal medium agar (squares), and potato dextrose agar (triangles) am ended with boscalid at several concentrations ................................ ................................ .................... 140 5 4 Sensitivity distribution of Alternaria alternata isolates (n= 419) to boscal id, based on effective concentration needed to reduce fungal growth by 50 % (EC 50 ) values ........... 141 5 5 Sensitivity distribution (effective concentration needed to reduce resazurin reduction by 50% [EC 50 ] values) to boscalid of Alternaria alternata isolates (n = 374), based on isolate virulence ................................ ................................ ................................ .......... 142 5 6 Partial structure at the exon intron junction in the succinate dehydrogenase (SDH) s ubunits of Alternaria alternata ................................ ................................ ....................... 143 A 1 Resazurin reduction caused by Alternaria alternata growth in complete medium at different SHAM concentrations. ................................ ................................ ...................... 147 A 2 Alignment of the amino acid residues 120 to 170 (first hot spot) of the cytochrome b gene from quino ne outside inhibitor sensitive (S) and resistant (R) isolates of Alternaria alternata ................................ ................................ ................................ ......... 148 A 3 Nucleotide sequence alignment of the cytochrome b gene between quinone outside inhibitor sensitive (S) and resistant (R): LJ 1 8 2S, LJ 3 3 2S, R3Q26 F9 2S, R3Q33 1 1S, WM 1 3S isolates of Alternaria alternata ................................ ............... 149 B 1 Frequency distribution of pyraclostrobin resistant Alternaria alternata isolates (n=471) collected during 2008 to 2012 from Florida citrus groves ................................ 151 C 1 Amino acid alignment of the succinate dehydrogenase subunit B (SDHB) from Alternaria alternata isolates ................................ ................................ ............................ 152

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12 C 2 Amino acid alignment of the succinate dehydrogenase subunit C (SDHC) from Alternaria alternata isolates ................................ ................................ ............................ 154 C 3 Amino acid alignment of the succinate dehydrogenase subunit D (SDHD) from Alternaria alternata isolates ................................ ................................ ............................ 155

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13 Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy CHARACTERIZATION OF RESISTANCE TO RESPIRATION INHIBITOR FUNGICIDES IN POPULATIONS OF TANGERINE INFECTING Alternaria alternata By Byron Patricio Vega Jimnez May 2014 Chair: Megan M. Dewdney Major: Plant Pathology Chemical control of Alternaria brown spot (ABS) caused by Alternaria alternata is based upon the timely application of site specific fungicides, many of which are vulnerable to the development of fungicide resistance. Quinone outside inhibitors (QoIs) have been used for more than 10 years to manage ABS but in 2008 the first case of QoI resistance was detected in Florida raising the concern in the tangerine industry of losing an effective chemical control tool The purpose of this research was to phenotypically and molecularly characterize resistance to QoI and succinate dehydrogenase inhibitor (SDHI) fungicides in tangerine infecting A. alternata populations. A rapid microtiter bioassay based on the colorimetric changes of the resazurin dye was developed to evaluate the sensitivity of A. alternata to those respiration inhibitor fungicides. From 2008 to 2012, 817 monoconidial isolates of A. alternata from 46 citrus orchards were examined for sensitivity to QoIs (azoxystrobin and pyraclostrobin). Of the isolates, 57.6% were resistant to b oth fungicides. The proportion of resistant isolates differed significantly among cultivars and with the number of QoI application s Moreover, the molecular basis for QoI resistance was determined for a subset of 235 isolates. All resistant isolates showed the point mutation G143A and were further classified as profile I and profile II, based on the presence of one or two introns, respectively. Phenotypic stability, fitness components, and the ability to

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14 cause disease of QoI resistant isolates were also stu died. Great variability in fitness components was observed among isolates within the same sensitivity group. Results suggest that QoI resistance in A. alternata was stable in the absence of QoI selection pressure and that the resistance development did not affect the fitness of resistant isolates. In addition the effect of boscalid (SDHI) on multiple physiological stages of fungal development was established. Sensitivity distribution of 419 A. alternara isolates was tested using isolates never exposed to b oscalid The sensitivity distribution was a unimodal curve with a mean effective concentration to inhibit 50% growth (EC 50 ) value of 0.60 g/ml. The molecular characterization of the succinate dehydrogenase (SDH) genes w as also determined by cloning and se quencing the SdhB SdhC and SdhD genes. Sequence comparisons of the SDH complex revealed the presence of mutations in 93% of isolates evaluated. Overall, r esults from this study will provide the basi s to improve disease management programs against ABS in Florida by limiting the use of QoI fungicides in places where resistance is present and by rotating different groups of fungicides

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15 CHAPTER 1 LITERATURE REVIEW Economic Impact of Tangerine and Tangerine Hybrids in Florida Citrus is one of the m ost important fruit crop produced around the world ( Bret et al., 2001 ) The most important citrus producing countries include Brazil, United States, China, European Union, Mexico, Egypt, Turkey, and South Africa, with a collective production among them close to 94% of the world production ( USDA, 2013 ) Florida is conside red the biggest citrus producing state within US with 65% of the total US citrus production ( Florida, 2013 ) During the 2011 2012 season, Florida produced 11.7 million tons, equivalent to a packinghouse door value of $ 3.44 billion, mainly focused on fruit processing ( Florida, 2013 ) However, Florida has 7000 ha of tangerine s and tangerine hybrids for the fresh fruit market, with a production valued in $ 88 million ( Florida, 2013 ) Citrus is affected by a wide v ariety of fungal pathogens that cause serious losses to the industry, especially fresh fruit, by reduc ing yield and fruit quality ( Mondal et al., 2005 ) Alternaria brown spot (ABS), caused by Alternaria alternata (Fr.) Keissl., is one of the most important fungal disease affecting tangerine s ( Citrus reticulata Blanco) and their hybrids, ( Timmer et al., 2000b ) Over the last decade, ABS incidence has increased in Florida and other citrus producing regions around the world (Cuenca et al., 2013) The disease was first observed in 1903 in Q ueensland, Australia ( Pegg, 1966 ) and in 1974 was observed for the first time in Florida, US ( Whiteside, 1976 ) After that, the disease was detected in the Mediterranean Basin ( Canihos et al., 1997 ; Vicent et al., 2000 ) Iran ( Golmohammadi et al., 2006 ) and China ( Wang et al., 2010 ) During the early 2000s,

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16 an outbreak of ABS was reported in Brazil, Argentina and Peru ( Peres et al., 2003 ; Marin et al., 2006 ) Host Selective Toxins Produced by A. alternata Within the genus Alternaria, seven different pathotypes have been identified to pro duce host selective or host specific toxins (HST). On citrus, Alternaria leaf spot of rough lemon and ABS of mandarins, both of them caused by A. alternata are associated with the production of different HST s ( Masunaka et al., 2005 ) The HS Ts are secondary metabolites that cause damage only to the host where the fungi infect ( Tsuge et al., 2013 ) The HSTs are released during conidium germination, before tissue penetration and mycelium production ( Otani et al., 1995 ) HSTs, produced by the rough lemon and the tangerine pat hotypes, are low molecular weight metabolites, highly soluble in chloroform, methylene dichloride, ethyl acetate, acetone and methanol, and moderately soluble in water ( Kohmoto et al., 1993 ) The rough lemon toxin is more stable but less lipophilic than the tangerine toxin ( Kohmoto et al., 1979 ; Otani et al., 1995 ) The toxin produced by the tangerine pathotype has the generic name of ACT (derived from A. citri tangerine pathotype) while the toxin produced by the rough lemon pathotype was named ACRL or ACR ( Kohmoto et al., 1993 ; Ohtani et al., 2002 ) The A. alternata tangerine pathotype has been shown to produce at least two ACT toxins. ACT I is toxic to citrus, while ACT II is only toxic on certain Japanese pear cultivars ( Kohmoto et al., 1993 ) The ACT toxins are esters of epoxy decatrienoic acid ( Otani et al., 1995 ) while the ACR L toxin is a dihydropyr one ring with a polyalcohol chain ( Ohtani et al., 2002 ) The genes responsible for ACT toxin production ar e tightly clustered and located on a small chromosome called the conditional dispensable chromosome ( Akamatsu et al., 1999 ; Hatta et al., 2002 ) Moreover, multiple copies of the genes responsible for ACT toxin production are present on this chromosome ( Miyamoto et al., 2008 ; Miyamoto et al., 2009b ; Ajiro et al., 2010 ) The mode of

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17 action of the ACT toxin is on cell plasma membrane s One hour after exposure to the toxin, the plasma membrane of susceptible cells deformed and subsequently electrolytes were lost ( Otani et al., 1995 ; Peever et al., 1999 ) In the other hand, the ACR L toxin disrupt the oxidative phosphorylation in the mitochondria during the cellular respiration ( Ohtani et al., 2002 ) Disease Symptoms of Alternaria Brown Spot ABS affects leaves, twigs and young fruit. The first symptom observed on young leaves is the presence of small brown to black sp ots surrounded by a yellow h alo caused by the ACT toxin, which kills the host cells ( Timmer et al., 2000b ; Akimitsu et al., 2003 ) Lesions normally expand and form irregular necrotic areas on large sect ions of the leaf. The toxin can be translocated acropetally, while the chlorosis and necrosis can be seen along the leaf veins ( Timmer et al., 2003 ) On young shoots, lesions are from 1 to 10 mm in diameter and can produce twig dieback, depending on host susceptibility ( Timmer et al., 200 3 ) On fruits, lesions may vary from small necrotic spots to large and depressed dark brown areas ( Bhatia et al., 2003 ; Vicent et al., 2007 ) Fruit are normally susceptible from petal fall until they are 4 cm in diameter, but more susceptible cultivars can be infected up to 5 to 6 cm in diameter ( Canihos et al., 1999 ) Fruit and leaf abscission occurs with high disease pressure, resulting in reduced yield ( Akimitsu et al., 2003 ; Timmer et al., 2003 ) Biology and Life Cycle The sexual stage of A. alternata has not been reported, therefore the disease cycle is relatively simp le ( Akimitsu et al., 2003 ) Conidia are produced on lesion s of mature leaves that remain in the tree canopy as well as i n the leaf litter ( Timmer et al., 1998 ) but also can occur on fruit or twigs ( Akimitsu et al., 200 3 ) A light rain or heavy dew events induce the production of conidia on mature leaves ( Timmer et al., 1998 ) The release of conidia is stimulated by rainfall or by abrupt changes in relative humidity. C onidia are dispersed by the wind and subsequently

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18 deposited on the surface of host tissues. With available leaf wetness, the conidia germinate quickly and infect the tissue. The penetration, on a susceptible leaf can occur directly or through stomata ( Timmer et al., 2003 ) Host penetration by A. alternata has been associated with appres s oria formation; but studies in Florida demonstrate d that the conidia could penetrate without the formation of appres s oria ( Akimitsu et al., 2003 ) The infection is significantly affected by environment fact ors, such as temperature and leaf wetness. The optimum temperature for infection and disease development is 27 o C, while temperatures below 15 o C and above 32 o C attenuate pathogen establishment. Leaf wetness period s of 10 12 h are optimal for infection; howe ver, even when this period is reduced to 4 8 h low levels of infection occur ( Canihos et al., 1999 ) Disease Management Different disease management strategies have been recommended to reduce the disease in new and established orchards. The use of disease free nursery stock is very important at orchard establishment, especially when s usceptible cultivars are planted. The use of less vigorous rootstock such as Cleopatra mandarin, is suggested in preference to other more vigorous rootstock like Carrizo citrange ( Dewdney, 2013b ) Additionally, the use of wide spaced planting is highly recommended for very s usceptible cultivars ( Timmer and Peever, 1997a ; Timmer et al., 2006 ) In established orchards, the use of ex cessive nitrogen fertilization, which promotes excessive vegetative g rowth, should be avoided. Moreover, the elimination of overhead irrigation and overwatering are highly recommended ( Dewdney, 2013b ) Al though cultural practices reduce disease severity, ABS is largely dependent on fungicide applications. Currently, copper based fungicides ( Fungicide Resistance Action Committee [FRAC] code M1), ferbam (FRAC code M3), the quinone outside inhibitors (QoI; F RAC code 11): Abound Gem and Headline as well as the premix ed fungicides Pristine

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19 (pyraclostrobin [QoI] + boscalid [FRAC cod e 7]) and Quadris T op (azoxystrobin [QoI] + difenoconazole [FRAC code 3]) are registered for ABS control ( Dewdney, 2013b ) Products that induce resistance in plants, such as Messenger ProPhyt and KeyPlex are also registered for use in citrus; however, they have not been shown to be effective for ABS control ( Agostini et al., 2003 ) Calendar fungicide applications have been used extensively for disease control. In Florida, the first application for ABS control is recommended when the spring flush is or of full expansion. Under heavy disease pressure a second application may be done, when the flush is near full expansion. During the spring (April and May), fungicide applications are recommended e very 10 days to once per month, depending on the frequency of rainfall and grove disease history. During the high rainfall and humid nights of June, at least two applications are recommended, while by mid July the fruit become resistant to ABS and the fun gicide applications are no longer needed ( Timmer et al., 2006 ; Dewdney, 2013b ) Phytotoxicity caused by copper applications at higher temperatures limits its use ( Dewdney, 2013b ) Additionally, copper is a protectant fungicide that frequently needs to be applied due to the rapid expansion of young fruit and leaves Therefor e QoIs have been widely used, especially when the weather conditions are hot and dry ( Timmer et al., 2006 ; Mondal et al., 2007 ) The evaluation of different fungicides spray programs on Murcott, Nova, and Minneola showed that applications of QoIs (azoxystrobin, trifloxystrobin or pyraclostrobin) rotated with copper or Serenade (product based on Bacillus subtilis ) were the most effective program s for ABS control. These programs showed less disease severity and the greatest marketability of the fruit ( Bhatia and Timmer, 2003 ; Johnston and Timmer, 2005 ; Reis et al. 2006 )

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20 To optimize f ungicide applications for ABS control, a weather based model (Alter Rater) was developed ( Timmer, 2000 ; Bhatia et al., 2003 ) The daily rainfall, leaf wetness, and average temperature are variables considered in this model. A daily point value is assigned and a threshold score is defined based on the cultivar established in the grove, disease history, and the orchard location. Due to the complexity of some environmental variables (difficulty in accurately measuring leaf wetness) used for the model, this has not been extensively adopted by growers. In Florida, growers may apply 2 to 15 fungicides sprays during the course of the g rowing season, depending on host susceptibility and weather conditions ( Vega and Dewdney, 2014 ) Quinone Outside Inhibitor (QoI) Fungicides QoI fungicides, also named strobilurins, were commercialized at th e middle of the 19 as a new class of agricultural fungicides with a novel mode of action ( Ypema and Gold, 1999 ; Bartlett et al., 2001 ; Bartlett et al., 2002 ) The origin of the QoIs date s back to the 19 two different antibiotics (strobilurins A and B) were isolated from the mycelium of the basidiomycete Strobilurus tenacellus Agar plate diffusion tests showed that both strobilurins were highly active against filamentous fungi and yeast at concentrations as low as 1 mg/l ( Anke et al., 1977 ) Similarly, the basidio mycetes Oudemansiella mucida (oudemansin) and Mycena galopoda as well as the bacterium Myxococcus fulvus (myxothiazol A) produce d analog MOAs (moa system), which was the original name of the strobilurin group ( Becker et al., 1981 ; Ypema and Gold, 1999 ; Bartlett et al., 2001 ; Bartlett et al., 2002 ) Currently, the QoI group is divided into eight different chemical classes including 19 different compounds ( FRAC, 2013a ) The physiochemical properties of QoIs, as well as the biokinetic behavior inside and on the surface of the plant, differ according to the active ingredient, the deve lopment al stage of the crop, and the formulation applied. The uptake of azoxystrobin into the leaf is considered low. It

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21 can be absorbed between 1 to 3% in grapevines and up to 25% in cereals and bananas, within 24 h of application ( Bartlett et al., 2002 ) A zoxystrobin has shown to be metabolically stable in the leaf, moves translaminarly, but also is xylem systemic ( Bartlett et al., 2002 ) On the other hand, kresoxim methyl shows a high affinity to the wax on the leaf surface due to its lipophilicity. This property allows the active ingredient to be redistributed, th roughout the waxy cuticular surface of the leaf, to distant points from the application site ( Ypema and Gold, 1999 ) The uptake of kresoxim methyl into the leaf is also co nsidered low. Radioactively labeled kresoxym methyl showed that between 5 to 10% of the compound applied penetrated into cereal leaves within 24 h ( Ypema and Gold, 1999 ) Furthermore, kresoxim methyl was shown to have low metabolic stability in the leaf and low translaminar movement. It is neither xylem nor phloem mobile ( Bartlett et al., 2002 ) Trifloxystrobin and pyraclostrobin have very l imited movement into the leaf, little translaminar movement, no systemic movement via xylem, and no systemic movement to new growth in cereals. Conversely, metominostrobin and picoxystrobin show translaminar movement, systemic movement through xylem and movement to new growth in cerea ls ( Bartlett et al., 2001 ; Bartlett et al., 2002 ) Biology of QoI Fungicides Disease management programs include QoI fungicides to control many fungal diseases due to their broad spectrum activity, effectiveness in controlling isolates resistant to unrelated fungicides, and by the low rate needed in the field. Moreover, QoI fungicides are not restricted only to foliar applications. They can be used in seed treatment s t o control soil borne diseases, such as the case of azoxy strobin controlling damping off caused by Rhizoctonia solani and Pythium spp in cotton ( Bartlett et al., 2 002 ) In general, QoI fungicides have a broad spectrum of activity against plant pathogenic fungi. This includes the most important taxonomic groups; namely, Ascomycetes,

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22 Basidiomycetes, Deuteromycetes, and Oomycetes ( Bartlett et al., 2001 ; Bartlett et al., 2002 ) The level of activity and control depend on the specific active ingredients. For example, metaminostrobin is moderately active against P. aphanidermatum and apparently was developed exclusively for rice and turf. Kresoxim methyl has moderate activity against Oomycetes, but in general it has a good control of powdery mildew s of fruits and horticultural crops ( Ypema and Gold, 1999 ) A zoxystrobin and pyraclostrobin have shown a broad spectrum of activity against many pathogens in multiple crops ( Bar tlett et al., 2002 ) QoI fungicides are very effective against the highly energy demanding stages of f ungal development, which are spore germination (preventative activity) and spore production (curative activity) ( Bartlett et al., 2002 ) Greenhouse experiments showed that applications of kresoxim methyl prior to inoculation onto many host plants, strongly inhibited spore germination and germ tube growth of V enturia inaequalis Podosphaera leucotricha Erysiphe cichoracearum E. graminis Uncinula necator among others. Similarly, i n vitro studies showed that kresoxim methyl completely inhibited the sporulation of many fungi using post infection applications ( Ypema and Gold, 1999 ) Additionally, the effect of azoxystrobin against the sexual stages of U. necator (formation of mature cleistothecia) and Plasmopara viticola (format ion of mature oospores) has been extensively studied ( Bartlett et al., 2002 ) Mode of Action of QoI Fungicides The QoI fungicides block electron transport betw een cytochrome b and cytochrome c by binding at the ubiquinol oxidation center (Qo center) of the mitochondrial bc 1 complex, also named complex III, which is a key component of the respiratory electron transfer chain ( Ypema and Gold, 1999 ; Bartlett et al., 2001 ; Bartlett et al., 2002 ) Complex III is anchored in the inner mitochondria membrane and operates as a homodimer composed by 10 or 11 polypeptides ( Fisher and Meunier, 2008 ) which include a membrane bound diheme cyto chrome b a

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23 membrane anchored cytochrome c 1 and [2Fe 2S] containing Rieske iron sulfur protein ( Cecchini, 2003 ) Some subunits of the cytochrome bc 1 are nuclear encoded; however, the cytochrome b subunit is encode d by the mitochondrial genome ( Fisher and Meunier, 2008 ) Like methoxyacrylic acid, such as oudemansin A and myxothiazol A, have the same mode of action ( Bartlett et a l., 2002 ) Resistance to QoI Fungicides QoI fungicides are classified as high risk for resistance development due to the site specific mode of action ( FRAC, 2013a ) A target site mutation of the cytochrome b gene, resulting in a specific amino acid substitution, prevents fungicide binding at the target site and causes QoI resistance ( Bartlett et al., 2002 ) Three amino acid substitutions in the cytochrome b protein have been detected in QoI resist ant plant pathogenic fungi and O omycetes ( Fernndez Ortuo et al., 2008b ) The amino acid substitution from glyc ine to alanine at position 143 (G143A) has been reported in most of the resistant pathogens, leading to a high level of resistance (resistance factor > 100). This mutation has been associated with QoI control failures ( Fisher and Meunier, 2008 ) A second, lower frequency amino acid replacement has been found at posit ion 129 with the substitution of phenylalanine with leucine (F129L), causing a reduction of QoI sensitivity ( Pasche et al., 2005 ; Fernndez Ortuo et al., 2008b ) A third change from glycine to arginine was identified at amino acid position 137 (G137R). This mutation occurs at a very low frequency and confers a level of resistance similar to the F129L mutation ( Sierotzki et al., 2007 ) Resistance to QoI fungicides was first reported in Blumeria graminis f. s p. tritici (wheat p owdery mildew) in Germany in 199 8 ( Bartlett et al., 2002 ) Thereafter, resistance was observed in many countries around the world among path ogens that affect many crops, including Mycosphaerella fijiensis in banana ( Sierotzki et al., 2000 ) P. viticola in grape ( Brent and

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24 Hollomon, 2007b ) V. inaequalis in apple ( Kller et al., 2004 ) P. fusca and Pseudoperonospora cubensis in cucumber ( Ishii et al., 2001 ) Botrytis cinerea in multiple crops ( Banno et al., 2009 ; Jiang et al., 2009 ; Bardas et al., 2010 ; Fernndez Ortuo et al., 2012 ) and A. alternata in pistachio ( Ma et al., 2003 ) Recently, A. alternata isolates recovered from Florida tangerine groves with a history of QoI use were found to be insensitive to QoI fungicides, indicating the development of resistant populations ( Mondal et al., 2009 ) Alternative Respiration in Fungi The identification of alternative redox centers, one of them is an oxidase homolog to the plant alternative oxidase (AO), in the fungal electron transport chain has been w idely studied since the launch of QoI fungicides ( Kraiczy et al., 1996 ; Joseph Horne and Hollomon, 2000 ) The alternative oxidase protein is located within the inner mitochondrial membrane and it is a nuclear encoded protein. This protein has shown sensitivity to the salicylhydroxamic acid (SHAM), one of the members of the hydroxamic acids, and n propyl gallate (alkylgallates); but is insensitive to cyanide, azide and carbon monoxide. This oxidase is constitutively expressed during the growth phase of some plant pathogenic fungi, such as Septoria tritici and B cinerea Ho wever earlier studies suggested that AO expression occur s following treatments with QoIs ( Joseph Horne and Hollomon, 2000 ) Studies with Magnaporthe grisea showed that the transcription of the AO gene was constitutively activated, while the translation and post translation were suppressed by cycloheximide sensitive transcription factor. Doubtlessly, the culture conditions as well as t he development stage of the fungus can affect the transcription of the AO in certain fungal isolates ( Joseph Horne and Hollomon, 2000 ) O ne of the most important functions of this oxidase is related to the ATP biosynthesis by a physiological bypass to complex III (Wood and Hollomon, 2003) Several fungal pathogens can avoid the deleterious effects of QoI fungicides by the activation o f AO that allow

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25 mitochondrial electron transfer from ubiquinol to bypass Complex III ( Wood and Hollomon, 2003: Avila Adame and K ller, 2003 b ). The AO allows respiration to continue in presence of QoIs during saprophytic stages of mycelium growth or conidia germination under in vitro conditions (Joseph Horne et al., 2001 ; Avila Adame and K ller, 2003b ); therefore, inhibitors of AO, such as SHAM, must be incorporated during QoI sensitivity assays. The rescue mechanism produced by AO has limited impact under f ield conditions principally due to the release of plant antioxidant compounds, during the early stage of fungal infection, that interfere with the activation of this pathway (Fern ndez Ortu o et al., 2008 a ). Succinate Dehydrogenase Inhibitor (SDHI) F un gicides The first SDHIs launched in the market as seed disinfection and foliar spray agents were c arboxin and oxycarboxin in 1969 and 1975, respectively, but they were only active against B asidiomycete fungi. The second generation of SDHIs, such as mepronil, flutolanil, furametpyr, and thifluzamide, launched between 1981 and 1997, showed a limited broad spectrum control with a focus on rice diseases ( ) However in 2003, boscalid was launched as the fi rst foliar SDHI fungicide with broad spectrum activity ( Sierotzki and Scalliet, 2013 ) Currently the SDHI group is divided into eight different chemical classes, that includes 18 different compounds ( FRAC, 2013a ) Although SDHIs have structural diversity, they share essenti al common features for fungicidal activity. The core amid e moiety is essential for hydrogen bond interactions into the binding site. T he head of the molecule has been used for classification, and it is attached to the amide moiety ( Sierotzki and Scalliet, 2013 ) Radio label ed active ingredient applied in different hosts showed that boscalid moves translaminarly into the leaf and could be transported acropetally in the xylem; therefore, untreated parts of the plant can be protected from pathogen infection ( Stammler et al., 2008 )

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26 Biology of SDHI Fungicides The new generations of SDHIs are highly active against many of the most important pathogens causing disease in fruits, nuts, ornamentals and vegetable crops. Some compounds are used exclusively to control pathogens of cereals; however, due to their broad spectrum activity, they could also be used against path ogens affecting vegetables, fiel d crops as well as fruits. So far, 19 different fungal pathogens affecting mono and dicotyledoneus plants have been effectively controlled with SDHIs ( Sierotzki and Scalliet, 2013 ) SDHI fungicides are biologically active against different stages of fungal development, such as spore germination, germ tube elongation, appresoria formation and mycelial growth ( Stammler et al., 2008 ) Mod e of Action of SDHI Fungicides SDHIs are site specific fungicides that inhibit fungal respiration by binding the enzyme succinate:quinone oxidoreductase, also known as succinate dehydrogenase (SDH), in the mitochondrial complex II ( Avenot and Michailides, 2010 ; Sierotzki and Scalliet, 2013 ) This enzyme plays an important role in the Krebs cycle and the mitochondrial electron transport chain ( Cecchini, 2003 ; Yankovskaya et al., 2003 ) The SDH enzyme is a heterotetramer composed of four nuclear encoded polypeptides ( Cecchini, 2003 ) The flavoprotein (also known as SDHA) and the iron sulfu r protein (SDHB) are hydrophilic subunits assembled into the catalytic dimer. The SDHA subunit carries a flavin adenine dinucleotide (FAD) cofactor and the substrate binding site; while, the SDHB subunit contains three iron sulfur clusters: [2Fe 2S], [4Fe 4S], and [3Fe 4S], which are connected to the substrate binding site and the ubiquinone binding site by a chain of redox center s The SDHC and SDHD subunits constitute the hydrophobic membrane anchor components, containing one heme b group and a ubiquinone binding site ( Yankovskaya et al., 2003 ; Scalliet et al., 2012 )

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27 Resistance to SDHI Fungicides SDHI fungicides are classified as medium to high risk for resistance development ( FRAC, 2013a ) Single point mutations, leading to amino acid substitutions of conserved residues in the SDH complex, confer resistance to SDHI fungicides. In the closely related specie s of A. alternata which cause s late blight of pistachio, boscalid resistance has been associated with mutations in the SdhB, SdhC, and SdhD genes. Polymorphism analysis of the SDHB protein in boscalid resistant isolates reveled the substitution of the highly conserved histidine residue loc ated in the third cysteine rich cluster by either tyrosine (H277Y) or arginine (H27 7R) ( Avenot et al., 2008b ) Additionally, analysis of the SDHC and SDHD subunits of SDHI resistant isolates showed the substitution of histidine by arginine in SDHC (H134R) and in SDHD (H133R) subunits both of them implicated in the heme b ligation, as well as a the substitution of aspartate by glutamic acid at position 123 (D123E) in SDHD ( Avenot et al., 2009 ) More recently, Miles et al. (2014) reported that, in addition to the mutations mentioned above, mutations T28A and A47 T in the SDHD subunit were also observed in some moderately resistant isolates of A. solani which cause early blight of potato. So far more than 27 mutations, conferring resistance to SDHIs, have been reported in field and laboratory isolates of different plant pathogen s ( Sierotzki and Scalliet, 2013 ) The first description of SDHI resistance was published in the 19 mutants of Ustilag o maydis and Aspergillus nidulans Resista nce factors between 20 and 100 fold were observed in different allelic mutants of the Sdh genes associated with the carboxin binding site ( Sierotzki and Scalliet, 2013 ) Recently, with the extensive use of SDHIs as foliar fungicides, multiple cases o f resistance have been reported in addition to A. alternata from pistachio ( Avenot and Michailides, 2007 ; Avenot et al., 2008a ) Those pathogens include B. cinerea from strawberry, grapes, apples and vegetables ( Zhang et al., 2007 ; Kim and Xiao,

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2 8 2010 ; Leroux et al., 2010 ; A miri et al., 2014 ) Corynespora cassicola from cucumber ( Miyamoto et al ., 2009a ; Miyamoto et al., 2010b ) Didy m ella bryoniae from watermelon ( Avenot et al., 2012 ) and Podosphaera xanthii from cucurbits ( Miyamoto et al., 2010a ) In th o se cases, sequence analyses of the Sdh genes reveled that mutations, in at least one of the target genes, were responsible for resistance. Research Objectives Given the great importance of ABS to Florida tangerine production as well as the lack of informa tion about the distribution of resistance to respiration inhibitor fungicides, the major goal for this research was to characterize phenotypically and molecularly resistance to QoIs (azoxystrobin and pyraclostrobin) and SDHIs (boscalid) in A. alternata pop ulations. The specific objectives were to: (i) develop an accurate method to measure sensitivity to respiration inhibitor fungicides, (ii) survey for QoI resistance in populations of tangerine infecting A. alternata in Florida, (iii) determine fitness comp onents for QoI resistant isolates, (iv) establish baseline sensitivity to boscalid, and (v) characterize polymorphisms in the SDH complex. To achieve the first objective, a resazurin based microtiter assay was developed and correlated with the results of c onidia germination test s for sensitivity to QoI fungicides. Different culture media, as well as conidia, and resazurin concentrations were evaluated to standardize this methodology (Chapter 2). A state wide survey was performed to achieve the second object ive. The distribution of QoI resistance in A. alternata populations, as well as baseline sensitivities for azoxystrobin and pyraclostrobin were established. Furthermore, the detection of the G143A mutation, responsible for QoI resistance, was identified us ing polymerase chain reaction restriction fragment length polymorphism (PCR RFLP) (Chapter 3). To achieve the third objective, the stability of QoI resistance was established in vitro While some saprophytic and pathogenic fitness components were assessed under laboratory conditions. In addition greenhouse experiments were used to

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29 evaluate the ability of QoI resistant isolates to cause disease on fungicide treated plants (Chapter 4). The ef fect of different culture media and methods to test boscalid sensit ivity were evaluated to achieve the fourth objective (Chapter 5). T o achieve objective five, the SdhB SdhC and SdhD genes were characterized in a group of boscalid sensitive isolates by sequence analysis (Chapter 5).

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Vega, B., Liberti, D., Harmon, P. F., and Dewdney, M. M. 2012 A rapid r esazurin based microtiter assay to evaluate QoI sensitivity for Alternaria alternata isolates and their molecular characterization. Plant Dis. 96:1262 1270. CHAPTER 2 A RAPID RESAZURIN BASED MICROTITER ASSAY TO EVALUATE QoI SENSITIVITY FOR Alternaria alternata ISOLATES AND THEIR MOLECULAR CHARACTERIZATION Introduction Traditional techniques for measuring fungicide sensitivity use fungicide amended agar to characterize inhibition of either mycelial growth or conidia germination ( Russell, 2004 ) These techniques are laborious, time consuming, require considerable space for plates, and the growth inhibition measurements can be subjective. Several automated qua ntitative methods have been developed for biocidal efficacy in the biomedical field, but their implementation has been limited by the requirement of high cost specialized equipment. These methods include bioluminescence and colorimetric tests using reagent s that could be toxic to the user and cells of interest ( Pettit et al., 2005 ; Tot et al., 2009 ) In contrast, resazurin (RZ) is a non toxic redox dye that has been used extensively to test bacteria and fungi in chemical sensitivity assays ( To et al., 1995 ; Meletiadis et al., 2002 ; Pettit et al., 2005 ) RZ is a stable, water soluble, tetrazolium based dye where the oxidized, nonfluorescent form (blue), is reduced to a fluorescent form (pink) in response to cell metabolism ( Larson et al., 1997 ; O'Brien et al., 2000 ; Fai and Grant, 2009 ) Therefore the fluorescence and color properties of this dye can be measured fluorometrically or spectrophot ometrically. RZ reduction takes place in the cytochrome oxidase region, during the final reduction of O 2 and the cytochrome a a 3 complex ( Kalina and Palmer, 1968 ) Several molecular techniques have also been developed for the rapid detection of QoI resi stant genotypes ( Sierotzki et al., 2011 ) These techniques include the use of polymerase chain reaction ( PCR ) based technologies, such as cleavable amplified polymorphic sequence PCR (CAPS PCR), quant itative real time PCR, or pyrosequencing among others ( Gisi et al., 2002 ; Sierotzki et al., 2007 ; Ishii, 2010 ) The allele specific PCR or CAPS PCR techniques are

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31 straight forward, versatile, low cost and do not require specialized PCR equipment to identify QoI resistant mutants in a fungal population. Detection of fungicide resistance based on PCR technology only detects the genotypes that the primers are designed to detect. A major disadvantage to using only a PCR based technique i s the inability to detect other causes of fungicide resistance. For example, it would not be possible to detect the F129L mutation that confers QoI resistance ( Pasche et al., 2005 ) with primers designed for the G143A mutation ( Ma et al., 2003 ) even though both cause a resistance phenotype. There can also be sil ent mutations or other DNA features that could interfere with a PCR assay that do not change the phenotype. Thus, although PCR identification is an excellent tool, it is necessary to rule out false negative. This is especially important when providing mana gement information to producers who will change their practices based on results from an assay. These are the reasons it was chosen to conduct a phenotypic assay that can detect all genotypes and has fewer risks of false negative results with confirmatory PCR assay to determine what mutations are important in the Florida citrus industry. Materials and Methods Fungal I solates Twelve monoconidial isolates of A. alternata were used in this study, varying in QoI sensitivity from baseline, field sensitive and field resistant (Table 2 1). Isolates were collected from different citrus orchards in Florida and cultured on potato dextrose agar (PDA; Becton Dickinson, Sparks, MD). Isolates were stored at 20 o C on colonized filter paper ( Peever et al., 1999 ) Conidial production was induced by transferring 3 day old mycelia on PDA to clarified V8 agar (100 ml of centrifuged V8 juice, 20 g agar and 10 g CaCO 3 /liter). Cultures were incubated at room temperature under white fluorescent light for 8 to 12 days. Conidia were

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32 harvested by flooding the plate with sterile distilled water, ge ntly rubbing the surface, and filtering through three layers of sterile cheesecloth. Medium Evaluation a t Different Conid ia and Resazurin Concentrations Six A. alternata isolates at five conidial concentrations from 10 1 to 10 5 conidia/ml were evaluated (Table 2 1). Four liquid media were used: potato dextrose broth (PDB; Becton Dickinson, Sparks, MD), yeast peptone dextrose broth (YPD; Becton Dickinson, Sparks, MD), complete medium (CM; ( Bennett and Lasure, 1991 ) ), and minimal medium (MM; ( Bennett and Lasure, 1991 ) ). Resazurin (RZ) salt (Sigma Aldrich, St. Louis, MO) was dissolved in distilled water at 5 mM, filter sterilized using 0.22 m filters (Corning Inc., Lowell, MA), and stored at 4 o C until use. To determine the optimal concentration of RZ, stock solutions of 100, 200, 300, 400, and 500 M RZ were prepared. The various combinations of liquid media, conidia and RZ concentrations we re evaluated for RZ reduction in the microtiter assay. To obtain a final volume of 200 l, 100 l of media were added to each well with 80 l of a conidia suspension at the concentrations described above, followed by 20 l of RZ solution to obtain a final RZ concentration of 10, 20, 30, 40, or 50 M. Each treatment was loaded in triplicate into a 96 well clear flat bottom, polystyrene microplate (Corning I nc., Lowell, MA). Each plate included wells of media alone and media with RZ as controls. Plates were c overed with a plastic lid, placed into a clean plastic humid chamber and incubated at 28 o C for 24 h with shaking at 400 rpm. RZ reduction was calculated based on the absorbance reading at 570 and 600 nm. Absorbance was measured with an Emax precision micr oplate reader (Molecular Devices Corp., Sunnyvale, CA). The experiment was performed twice. Effect of SHAM on Alternaria G rowth i n the RZ B ased M icrotiter A ssay To determine the effect of salicylhydroxamic acid (SHAM) on the growth of A. al ternata, 12 isol ates were evaluated (Table 2 1). SHAM was dissolved in methanol at 100 mg/ml. All

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33 media contained 0.1% (v/v) of methanol. One hundred l of CM amended with SHAM either at 0, 50, 100, 150, 200, 300, or 400 g/ml was added to each wells, followed by 80 l of 10 5 conidia/ml and 20 l of 400 M RZ. Final SHAM concentration in the wells was 0, 25, 50, 75, 100, 150, or 200 g/ml. Three wells per plate were used for each treatment. Control wells of media and RZ without conidia were included for each SHAM concentra tion. Incubation conditions as well as absorbance measurement were as described above. The experiment was performed twice. RZ B ased M icrotiter A ss ay of QoI F ungicide S ensitivity A microtiter assay was developed based on percent reduction of RZ in QoI fungi cide amended media. Technical grade azoxystrobin (Syngenta Crop Protection, Greensboro, NC) and pyraclostrobin (BASF Corp., Research Triangle Park, NC) were dissolved in acetone at 10 mg/ml (active ingredient) and 10 fold serially diluted to create stock s olutions, such that the final concentration of acetone in the media was 0.1% (v/v). Three wells of the microtiter plate contained 100 l of CM amended with fungicide at 0, 0.002, 0.02, 0.1, 0.2, 1, 2, or 20 g/ml. Eighty l of 10 5 conidia/ml and 20 l of 4 00 M RZ were added. The final concentrations of the fungicides in the wells were 0, 0.001, 0.01, 0.05, 0.1, 0.5, 1, or 10 g/ml. Incubation conditions as well as absorbance measurements were as described above. Relative percent RZ reduction for two indepe ndent experiments was expressed as the ratio of percent RZ reduction in the presence of fungicide to the percent in the absence of fungicide multiplied by 100. Isolate sensitivity expressed in g/ml was determined by the effective concentration needed to r educe RZ by 50% (EC 50 ) using an exponential decay function ( SigmaPlot, 1993 ) : ( 2 1) RZ(lc) = % resazurin reduction; lc = fungicide concentration; a = constant at initial lc value; and b = slope coefficient.

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34 Resazurin R eduction Percent RZ reduction was calculated using the E quation 2 2 following the ( Invitrogen ; Pettit et al., 2005 ) : ( 2 2) OX = molar extinction coefficient of RZ oxidized form (blue; 80586 and 117216 for 570 RED = molar extinc 1 2 = 600 nm. Since RZ measures the metabolic activity of fungal growth, the percent RZ reduction corresponds to the fungal respiration rate. Conidia G ermination T est The sensitivity of germinating A. alternata conidia to QoI fungicides also was determined for the isolates previously described. Stock solutions of azoxystrobin or pyraclostrobin were added to molten water agar (WA) to obtain the final concentrations described above. To suppress the alternative oxidase pathway during spore germination, SHAM (100 g/ml) was added to WA containing fungicide ( Ma et al., 2003 ; Russell, 2004 ) A 100 l aliquot of 5 10 3 conidia/ml was spread onto WA in each petri dish and incubated in the dark at 27 o C overnight. Fifty conidia at each concentration were arbitrarily selected in four replicates. A conidium was considered germinated if the germ tube was equal or longer than the total length of a conidium, if an appressorium was developed, or if multiple germ tubes were observed. The average number of conidia germinated for two independent experiments was converted to percent inhibition. EC 50 values were determined by the conc entration that inhibited conidia germination by 50% using the sigmoidal function ( SigmaPlot, 1993 ) :

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35 ( 2 3) I(lc) = % germination inhibition; a = % germination inhibition range; c = fungicide concentration at the maximum rate of change; b = slope coefficient; and lc as defined in E quat ion 2 1. DNA E xtraction and S equence A nalysis Mycelia were harvested from 2 to 8 day old cultures growing on PDA overlaid with cellophane sheets, and ground in liquid nitrogen. Genomic DNA extraction was performed using the DNeasy Plant Mini kit (QIAGEN, V alencia, CA) according to the manufacturers instructions. The cytochrome b gene of ten A. alternata isolates was partially amplified using the primers DTRcytb2 (5 CTA GTA TGA ACT ATT GGT AC 3`) and DTRcytb2r (5` GAG CAA AAG ATA TTC TTT 3`) in a total rea ction volume of 25 l ( Grasso et al., 2 006b ) Because isolates CPI ORI 2S and WM 1 2S were not amplified by DTRcytb2/DTRcytb2r, a new set of primers, cytb2f (5` CTA TGG ATC TTA CAG AGC AC 3`) and cytb3r (5` TGC AGG AGT TTG CAT AGG GTT TGC 3`), were designed. The PCR reaction was performed us ing primers at 0.5 M final concentration. The REDExtract N Amp PCR ready mix (Sigma Aldrich, St. Louis, MO) was used following the manufacturers directions. The quantity of extracted fungal DNA template varied from 5 to 50 ng. Cycling parameters for all primer sets used were: initial denaturation at 94C for 5 min; 35 cycles at 94C for 1 min, 57C for 1 min and 72C for 2 min with final extension at 72C for 5 min. The amplification products were visualized with UV light after electrophoresis in a 1.5% agarose gel with 1 Tris borate EDTA buffer (TBE) stained with ethidium bromide. PCR products were purified using the MiniElute PCR purification kit (QIAGEN, Valencia, CA) and cloned into the pGEM T Easy vector (Promega Corp., Madison, WI).

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36 Plasmids were transformed into Escherichia coli high efficiency competent cells JM109 (Promega Corp., Madison, WI) according to the manufacturers directions. Both strands of the cloned PCR products were sequenced by the Interdisciplinary Center for Biotechnology Research (ICBR, University of Florida). New primers, cytb2f walk (5` AAT GAA ATA TAA ATT TAT TGG TTA CA 3`) and cytb2r walk (5` GAA GGA GGT ATG GAT AAA TAT TC 3), based on the partial sequence of the cytochrome b gene of CPI ORI 2S and WM 1 2S isolates, were designed to amplify the rest of the sequence. The partial sequence of the cytochrome b gene for two representative isolates was submitted to GenBank (Accession Nos. JQ437357 and JQ446323). DNA sequences were aligned and manually edited using Sequencher (ver. 4.5; Gene Codes Co., Ann Arbor, MI). Multiple DNA sequence alignments and translation to amino acids were performed using MEGA (ver. 4.1; ( Tamura et al., 2007 ) ). Using the DTRcytb2/DTRcytb2r partial seq uence of the cytochrome b gene, an additional gene specific reverse primer DTRcytb2 INTr (5` GTA TGT AAC CGT CTC CGT C 3`) was designed and used in combination with the DTRcytb2 forward primer to amplify a 349 bp PCR fragment. PCR conditions were as descri bed above. Cleavable amplified polymorphic sequence (CAPS) analysis of the DTRcybt2/DTRcytb2 INTr PCR products was performed using the Fnu 4HI (New England Biolabs, Ipswich, MA) restriction enzyme to validate this molecular diagnostic technique and determin e if a simple molecular test could be used to confirm the mutation responsible for phenotypic results ( Ma et al., 2003 ) Purified PCR (5 l) product was digested with Fnu mmendations, and restriction fragments were separated and visualized as described above.

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37 Statistical A nalysis Analyses of the effect of medium and isolate, as well as, conidia, SHAM, and RZ concentrations were performed using PROC GLM (SAS ver. 9.1, Cary, NC). Calculation of EC 50 and the linear regression for EC 50 in conventional and RZ based microtiter assays, were performed with SigmaPlot (ver. 10.0; Systat Software Inc., San Jose, CA). To reduce inequality of variance among treatments, percent reduction of RZ was square root transformed prior to analysis. Standardized residual errors of transformed data plotted against predicted values were graphically analyzed for homogeneity of variance. Univariate analysis was used for testing normality. Homogeneity o f variance test using the ratio of variance of two independent experiments was analyzed prior to pooling the experiments. Percent RZ reduction in different media for isolates, conidia and RZ concentrations were compared by a three way analysis of variance (ANOVA) with isolate, conidia and RZ concentrations as variables. The effect of SHAM on percent RZ reduction of different isolates was analyzed by two way ANOVA with isolate and SHAM concentration as variables. Treatment means were separated using Fishers 50 values predicted by conidium germination and RZ microtiter tests were obtained by fitting the dose response to a sigmoidal and an exponential decay function, respectively. Results Effect of M edia and C onidia C oncentrat ion The growth of six A. alternata isolates in the microtiter assay at five conidia concentrations was evaluated in CM, MM, PDB and YPD at five concentrations of RZ dye. Media, isolate, conidia, and RZ concentration significantly affected ( P < 0.0001) perc ent RZ reduction 24 h after treatment ( data not shown ). Furthermore the main effects of isolate, conidia concentration, RZ concentration as well as the interaction between conidia and RZ concentration

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38 were analyzed individually by media. Data presented in table 2 2 were not pooled because the RZ doses were not identical between experiments 1 and 2; however, results shown are representative for both experiments. All main factors significantly affected ( P < 0.001) the percent RZ reduction using CM, MM and PDB (Table 2 2), with the exception of conidia concentration in YPD ( P = 0.6395). The most consistent percent RZ reduction over 24 hours was at 40 M in CM, which ranged from 11.92% at 10 1 conidia/ml to 98.04% at 10 5 conidia/ml (Fig. 2 1A). Although MM showed the same RZ reduction pattern as CM at 40 M of RZ (Fig. 2 1B), the percent reduction was much lower ranging from 4.75% at 10 1 conidia/ml to 61.83% at 10 5 conidia/ml. Much higher levels of percent RZ reduction were observed in PDB where the percent reduct ion increased with conidia concentration, but the percent change was much smaller (Fig. 2 1C). In YPD, the lowest percent RZ reduction was 175% and did not change with conidia concentration (Fig. 2 1D). The highest percent RZ reduction was observed at 10 5 conidia/ml in all media, except YPD. At 10 4 conidia/ml the percent RZ reduction increase was lower than could be considered accurate for analyses over a 24 hour period of time (Fig. 2 1A, B and C). Thus 10 5 conidia/ml and CM were selected for further work. Effect of SHAM on A. alternata G rowth To identify the effect of SHAM on the growth of A. alternata in our assay, seven SHAM concentrations were evaluated in CM. SHAM concentration, isolate and the interaction of isolate SHAM concentration significantly ( P < 0.0001) affected the fungal respiration rate (Fig. 2 2A). However whether the isolates were QoI sensitive or resistant did not significantly affect ( P = 0.2024) the fungal respiration response ( data not shown ). An inv erse relationship was found between fungal respiration rate and SHAM concentration (R 2 = 0.9861; P < 0.0001). SHAM at 25 g/ml decreased percent RZ reduction from 96.36 to 91.92% when compared to the non amended control, whereas at the highest SHAM concent ration the percent RZ reduction was

PAGE 39

39 52% (Fig. A 1). RZ reduction indicated that A. alternata grew, but growth was significantly reduced at higher SHAM concentrations in an isolate dependent manner (Fig. 2 2B). Assessment of S ensitivity to A zoxystrobin and P yraclostrobin Two methods were used to assess QoI sensitivity: the RZ microtiter assay and the conidia germination assay. Because SHAM affected fungal growth in a dose dependent response in the RZ microtiter assay, it was not included. However, SHAM at 10 0 g/ml was used for the conidia germination test to avoid false positive results from respiration by the alternative oxidase pathway ( data not shown ; M izutani et al., 1995 ) All of the evaluated isolates were classified into 50 values less than 0.80 g/ml for isolates had EC 50 values greater than 10 and 1 g/ml for azoxystrobin and pyraclostrobin, respectively (Table 2 3). Highly significant differences ( P < 0.0001) were found for isolate when either QoI fungicide was evaluated, whereas no significant dif ferences ( P = 0.4724) were observed for evaluation method and for the interaction between isolate and method ( P = 0.9616) (Table 2 4). Sensitive A. alternata isolates had EC 50 values that ranged from 0.056 to 0.502 g/ml for azoxystrobin in the conidia ger mination test, and from 0.069 to 0.761 g/ml in the RZ based microtiter assay. Resistant isolates had EC 50 values greater than 10 g/ml in both methods (Table 2 3). A. alternata isolates were more sensitive to pyraclostrobin than azoxystrobin. For sensitiv e isolates, the pyraclostrobin EC 50 values ranged from 0.001 to 0.012 g/ml and from 0.007 to 0.019 g/ml for the conidia germination test and the RZ microtiter assay, respectively. For resistant isolates EC 50 values ranged from 4.006 to 5.228 g/ml in the conidia germination test and from 1.094 to 4.49 g/ml in the microtiter assay (Table 2 3). Discrimination between isolate groups could also be visually evaluated by the color change of test wells in the microtiter plate. Isolates that developed a strong p ink color in wells with a higher concentration of

PAGE 40

40 azoxystrobin (10 g/ml) were considered resistant whereas isolates in blue colored wells at 0.5 g/ml were considered sensitive (Fig. 2 3). A strong and highly significant relationship (R 2 = 0.923; P < 0.00 01) between EC 50 values from both methods was observed (Fig. 2 4). Cytochrome b P artial G ene S equence A nalysis The partial structure of the cytochrome b The term hot spot refers to the cytochrome b region where amino acid exchange inducing mutations occurs, leading to QoI fun gicide resistance ( Grasso et al., 2006b ) A 1589 bp fragment, encoding for the amino acid residues 112 to 223, was amplified using primers DTRcytb2 and DTRcytb2r. A 2938 bp fragment, encoding for the amino acid residues 103 to 268, was amplified using primers cytb2f and cytb3r. The length an d intron positions of the partial sequence of the cytochrome b gene was determined after alignment with the reference cytochrome sequence of A. alternata (accession no. DQ209283.1). The first intron of 1187 bp was inserted after the triplet encoding for al anine at amino acid position 126 (A126) and was found only in isolates WM 1 2S (resistant) and CPI ORI 2S (sensitive). The second intron of 1252 bp was inserted after the first T of the triplet encoding for phenylalanine (TTC) at position 164 (F164) and wa s found in all evaluated isolates (Fig. 2 5). Four silent, transition mutations were found only in isolates carrying both introns at amino acid positions L134, P135 and Y136. An expected cytochrome b point mutation was identified in all QoI resistant isola tes. Protein comparisons of the partial cytochrome b coding region between isolates identified a glycine (GGT) to alanine (GCT) non synonymous point mutation at amino acid position 143 (G143A), which distinguishes sensitive from resistant isolates (Fig. A 2).

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41 CAPS A nalysis Using the cleavable amplified polymorphic sequence (CAPS) technique, it was possible to discriminate between resistant and sensitive isolates with the G143A mutation that carried only one intron and, therefore, could not discriminate amon g all isolates (Fig. A 3). A 349 bp cytochrome b fragment was amplified using primers DTRcytb2 and DTRcytb2 INTr in sensitive isolates, but two fragments of 95 and 254 bp were observed only in resistant isolates (Fig. 2 6). Discussion In this study we comp ared a microtiter assay, using the oxidation reduction dye RZ, with the standard conidia germination method to evaluate QoI fungicide sensitivity in A. alternata The standardization of media, conidia concentration and incubation time is critical for the r eproducibility of any microtiter assay ( Espinel Ingroff and Kerkering, 1991 ; Meletiadis et al., 2002 ) Culture media not only must have enough nutrients to ensure the growth of isolates, but it also m ust prevent the activation of alternative pathways for energy production in the fungus, such as alternative respiration or anaerobic fermentation ( Spiegel and Stammler, 2006 ) Furthermore, some compounds present in the media can affect the solubility and stability of fungicides ( Pijls et al., 1994 ) It is highly recommended to use a chemically defined medium or synthetic medium for sensitive bioassays and avoid the use of undefined media, like a natural media, that can give variable results ( Cuenca Estrella and Rodrguez Tudela, 2001 ; Kuhajek et al., 2003 ) Thus, many synthetic media have been evaluated in medicine for d etection of multidrug resistance in human disease causing filamentous fungi and yeasts. The National Committee for Clinical Laboratory Standard (NCCLS) has published a standard protocol for filamentous fungi and yeasts ( NCCLS, 2002b a ) However the diversity of fungi found in agricultural crops, as well as the many registered fungicides makes the selection of a specific

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42 media for fungicide sensitivity assays difficult. Thus, an optimal medium must be evaluated prior to a bioassay for each fungal species. Conidia germination and A. alternata growth in CM were optimal compared to MM, PDB and YPD; thus CM was chosen for our experiments. Although MM allowed germination and growth as well, their levels were suboptimal and lower values of RZ reduction were observed over a 24 h incubation period. Nutrient requirements for A. alternata growth are quite simple: glucose source (0.2 to 4%), nitrate salts (less than 1%) and an optimum carbon/nitrogen ratio ( Misaghi et al., 1978 ) ; nevertheless the addition of micro elements, vitamins and an extra nitrate source, present in CM, adequately supported growth of A. alternata during the first 24 hours of the microtiter assay. CM also was pH stable post sterilization which ensured optimal RZ performance since RZ is pH sensitive ( Promega 2009 ) On the other hand, both PDB and YPD showed inconsistent RZ reduction levels produced by post sterilization media ac idification that caused RZ to become a colorless compound ( Larson et al., 1997 ; Bueno et al., 2002 ) Thus, media that develop a low pH post sterilization, like PDB and YPD, should be avoided in RZ based microtiter assays. However media based on yeast extract and peptone have bee n used successfully in similar bioassays ( Stammler and Speakman, 2006 ; Stammler et al., 2007 ; Fai and Grant, 2009 ) Conidia concentration is also an important variable to be considered in a microtiter assay. Cox et al. (2009) and Rampersad (2011) found a strong correlation between RZ reduction and conidia concentration in Monilinia fructicola and Verticillium dahliae respectively, testing concentrations from 10 1 to 10 6 conidia/ml with optimal final concentrations between 5 10 4 to 1 10 5 conidia/ml per microtiter well. In our study, the great est percent RZ reduction was obtained with 10 5 conidia/ml that resulted in a final concentration of 5 10 4 conidia/ml per each

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43 microtiter well which is consistent with previous reports ( Cox et al., 2009 ; Rampersad, 2011 ) However, with a high cell density or prolonged incubation time, the RZ reduction reaches a plateau, caused by a second redox step, followed by a diminution of RZ fluorescence, where the RZ (blue color) is reduced first to resorufin (pink color) and finally to colorless hydroresorufin ( Larson et al., 1997 ; Byth et al., 2001 ) A diminution of RZ fluorescence was observed in our study when incubation was extended to 48 h. Here the presence of a colorless compound was clearly observed, especially when conidia concentration was greater than 10 4 conidia/ml ( unpublished data ). For an optimal result with the microtiter assay, RZ reduction must be measured during the logarithmic growth phase of the fungus ( Rampersad, 20 11 ) In our experiment this phase occurred 24 h after the incubation. Shorter incubation times gave suboptimal levels of RZ reduction and an underestimation of the dye response curve ( unpublished data ). EC 50 values obtained with the microtiter assay and the conidia germination test were not significantly different for the QoI fungicides evaluated. The conidia germination test estimates only the proportion of conidia germinated after exposure to specific fungicide concentrations, whereas the microtiter as say measures the metabolic activity of fungal growth during conidial germination and germ tube elongation. EC 50 values obtained by RZ based microtiter assay also were consistent with values obtained in QoI sensitivity tests for pistachio infecting A. alter nata and potato infecting A. solani ( Pasche et al., 2004 ; Pasche et al., 2005 ; Avenot et al., 2008a ; Rosenzweig et al., 2008a ; Rosenzweig et al., 2008b ; K araoglanidis et al., 2011 ) Thus a R Z based microtiter assay can determine the sensitivity of field isolates to QoI fungicides. To date, no correlation has been made between the results of the microtiter assay and field control failures but this work is on going and will be presented subsequ ently.

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44 To monitor the QoI sensitivity of citrus infecting A. alternata isolates over time, the baseline sensitivity to azoxystrobin and pyraclostrobin must be identified because it is unclear thus far. When Mondal et al. ( Mondal et al., 2005 ) conducted a baseline sensitivity study for A. alternata in citrus they found EC 50 values greater than 100 g/ml for azoxystrobin and 0.87 g/ml for pyraclostrobin, based on mycelial growth inhibition tests, which demonstrated that A. alternata mycelium is insensitive to azoxystrobin. Moreover, in our study, we fo und mean EC 50 values of 0.443 g/ml for azoxystrobin and 0.012 g/ml for pyraclostrobin in isolates never exposed to QoI. The presence of resistant isolates also was confirmed in our study, since the mean EC 50 values between QoI sensitive and resistant iso lates shifted more than 100 fold, which corresponded with values previously reported for different pathogens ( Steinfeld et al., 2001 ; Pasche et al., 2004 ; Stevenson et al., 2004 ; Rosenzweig et al., 2008a ) Azoxystrobin and pyraclo strobin are broad spectrum fungicides that inhibit mitochondrial respiration by blocking the electron transfer in the bc 1 cytochrome complex ( Ypema and Gold, 1999 ; Bartlett et al., 2001 ; Bartlett et al., 2002 ) Several fungal plant pathogens can avoid the deleterious effects of mitochondrial inhibitors through alternative oxidase (AOX) ( Ziogas et al., 1997 ; Joseph Horne and Hollomon, 2000 ; Joseph Horne et al., 2001 ) The AOX reaction takes place within the inner mitochondrial membrane and involves a nuclear encoded protein ( Vanlerberghe and McIntosh, 1997 ) This protein is sensitive to salicylhydroxamic acid (SHAM) an d n propyl gallate ( Joseph Horne and Hollomon, 2000 ) SHAM prevents AOX from masking QoI sensitivity in assays during saprophytic s tages of mycelium growth or conidia germination. Avila Adame and Kller (2003b) reported an isolate dependent inhibition of conidia germination in Magnaporthe grisea ranging from 3% to 14% in response to 100 g/ml of SHAM. They also found a rescue factor ( ratio between EC 50 values

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45 without SHAM and with SHAM for the same isolate) from azoxystrobin, at the same concentration of SHAM, ranging from 7 to 140 for mycelia growth and greater than 580 for conidia germination. Thus, SHAM has a developmental regulatio n effect where conidia germination has shown a higher rescue potential than mycelia growth. In our study, we found an isolate dependent dose response on fungal respiration caused by SHAM. The level of RZ reduction ranged from 5% to 45% at 25 g/ml and 200 g/ml of SHAM, respectively. This response was independent of whether the isolates were sensitive or resistant to azoxystrobin or pyraclostrobin; therefore, SHAM was not used for the microtiter assay. The RZ microtiter technique cannot be used for fungi th at do not readily sporulate in culture or fungi that are not able to grow in liquid media ( Tremblay et al., 2003 ) However, it has several advantages over traditional assays. The time needed to measure the RZ test is reduced to less than 30 min for a group of 12 isolates after 24 h of incubation, compared to conventional conidia germination tests that required betwee n 45 min to 1 h per isolate after incubation. Another advantage is the evaluation of multiple isolates and multiple fungicide concentrations at the same time in a conventional microtiter plate. Furthermore, different platforms such as spectrophotometer and fluorometer could be used to measure RZ reduction (based on the light absorbance and fluorescence properties of RZ), in response to the metabolic activity of the fungus ( Rampersad, 2011 ) RZ based microtiter assays and conidia germination tests are methods developed to quantify fungicide sensitivity at a phenotypic level. To identify the genes responsible for resistant phenotypes, DNA b ased methods must be used. The specific primers previously described ( Grasso et al., 2006b ) for the cytochrome b gene of A. alternata failed to amplify the gene of two isolates (one susceptible and one resistant), which required the development of a

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46 new set of primers. The presence of two in trons, the first one at amino acid position 126 (A126), and the second one at amino acid position 164 (F164) was unexpected, because it had been reported that the A. alternata cytochrome b gene did not have any introns ( Ma et al., 2003 ; Ma and Michailides, 2004 ; Grasso et al., 2006b ) Grasso et al. (2006b) reported that the presence of an intron between the codons 143 and 144 may prevent a QoI resistant mutation at this position. However, the introns A126 and F164 in A. alternata do not appear to affect QoI resistance ( Grasso et al., 2006b ; Banno et al., 2009 ) Moreover, the gene structure of the cytochrome b was found to be diverse among isolates, due to the presence of introns, although the coding regions of the gene were highly conserved. In our study, the amino acid substitution G143A was correlated with an azoxystrobin and pyraclostrobin resistant phenotype in A. alternata. This mutation was reported in other plant pathogen species ( Brent and Hollomon, 2007b ; Ishii, 2010 ) Additionally a rapid molecular test was developed, based on the CAPS PCR technique, to identify QoI resistant isolates in A. alternata that contain a single intron Moreover, due to the genetic variability of the cytochrome b gene of A. alternata isolates, a different technique, such as allele specific PCR, could be validated for a rapid molecular diagno stic test. However, a new set of primers must be developed prior the implementation of allele specific PCR Molecular techniques have also been used for a rapid detection of QoI resistant isolates from field samples. Ma and Michailides (2004) developed an allele specific PCR assay for a rapid detection of QoI resistant pistachio infecting A. alternata; however, the presence of PCR inhibitors constitutes an obstacle for an accurate detection of resistant isolates. Thus, additional steps must be implemented d uring PCR to avoid the deleterious effects of PCR inhibitors ( Ma and Michailides, 2004 )

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47 In summary, the findings presented here showed that the colorimetric microtiter assay based on RZ dye is a simple, rapid, reliable and accurate technique to measure the sensitivity of A. alternata to azoxystrobin and pyraclostrobin, and could be used for large scale surveys for resistance screening as suggested for a similar assay ( Cox et al., 2009 ) It seems likely that it could be adapted for other plant pathogens and fungicides. This method shoul d be combined with molecular diagnostic tools to confirm the genotype associated with fungicide resistance.

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48 Table 2 1. Isolates by host, location and year of collection Isolate a Abbreviation Host b Location Sensitivity c Year BL 17 4 3S* BL Minneola tangelo Lake Alfred S 2008 BLK 17 S 10S* BLK Minneola tangelo Lake Alfred S 2008 CPI ORI 2S CPI Murcott tangor Immokalee BL 1996 EV 3 1S EV Minneola tangelo Lake Alfred BL 1996 LJ 1 8 2S* LJ1 8 Minneola tangelo Oviedo R 2009 LJ 3 3 2S LJ3 3 Minneola tangelo Oviedo R 2009 LOR ORI 1 3S LOR Sunburst tangerine Lorida BL 1997 R3Q26 F9 2S* R3Q26 Dancy mandarin Winter Haven R 2008 R3Q33 1 1S* R3Q33 Dancy mandarin Winter Haven R 2008 VB RQF 3S* VB Grapefruit Vero Beach BL 1997 WM 1 2S WM1 2 Minneola tangelo Oviedo R 2009 WM 1 3S WM1 3 Minneola tangelo Oviedo R 2009 a Asterisk (*) indicates isolates used to determine percent resazurin reduction for different media, conidia and resazurin concentrations b Tangelo = Citrus paradisi C. reticulata mandarin or tangerine = C. reticulata grapefruit = C. paradisi. c S = field sensitive, BL = baseline, R = field resistant.

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49 Table 2 2 F statistics and P values for the media effect on the growth of six Alte rnaria alternata isolates measured by percent resazurin reduction under different conidia and resazurin concentrations Factor a df b Complete medium Minimal medium Potato dextrose agar Yeast peptone dextrose F P F P F P F P Isolate 5 4.33 <0.01 208.72 <0.01 118 <0.01 42.05 < 0. 01 Conidia (C) 4 1572.44 < 0. 01 14785.09 < 0. 01 559.13 < 0. 01 0.63 0.64 Resazurin (R) 4 77.76 < 0. 01 210.46 < 0. 01 1080.73 < 0. 01 330.54 < 0. 01 C R 16 11.18 < 0. 01 4.8 < 0. 01 1.68 0.0471 0.33 0.99 a Data from the second experiment. b Degrees of freedom.

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50 Table 2 3 Effective concentration needed to reduce resazurin or conidia germination by 50% (EC 50 ) for azoxystrobin and pyraclostrobin by isolate EC 50 (g/ml) a Azoxystrobin Pyraclostrobin Isolate GT RZ GT RZ BL 17 4 3S 0.056 0.692 0.001 0.011 BLK 17 S 10S 0.502 0.385 0.012 0.019 CPI ORI 2S 0.060 0.069 0.004 0.013 EV 3 1S 0.071 0.761 0.007 0.015 LJ 1 8 2S > 10 > 10 5.214 3.142 LJ 3 3 2S > 10 > 10 4.542 2.701 LOR ORI 1 3S 0.254 0.594 0.004 0.007 R3Q26 F9 2S > 10 > 10 5.162 1.094 R3Q33 1 1S > 10 > 10 4.006 4.490 VB RQF 3S 0.064 0.346 0.011 0.013 WM 1 2S > 10 > 10 4.246 4.693 WM 1 3S > 10 > 10 5.228 2.072 a Average of two independent experiments. GT = germ tube assay and RZ = resazurin assay.

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51 Table 2 4 Analysis of variance for effective concentration needed to reduce resazurin or conidium germination by 50% (EC 50 values) for isolate Factor a df SS MS F value P value Isolate 11 1075.73 97.79 24.57 <0.0001 Fungicide b 1 247.65 247.65 62.21 <0.0001 Method c 1 2.08 2.08 0.52 0.4724 Isolate Method 11 16.42 1.49 0.37 0.9616 Error 70 278.66 3.98 Total 94 1634.89 a Data were pooled from two independent experiments. b Azoxystrobin and pyraclostrobin. c Resazurin based microtiter assay and conidia germination assay.

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52 Figure 2 1 Resazurin reduction in four liquid media influenced by Alternaria alternata conidia concentration and resazurin concentration. A) Complete medium, B) Minimal medium C) Potato dextrose broth and D) Yeast peptone dextrose. Values are the mean and standard error of six isolates after 24 hours of incubation at 28 o C. I n C and D som e values exceed 100% resazurin reduction caused by the formation of a colorless compound during the microtiter assay.

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53 Figure 2 2. Effect of SHAM on resazurin reduction. A) Effect of SHAM concentration on Alternaria alternata respiration as measured by % resazurin reduction by isolates. Columns are the mean and error bars are the standard error of three replicates for four representative SHAM concentrations. Effect of SHAM concentration on isolates with the same letter are not significantly different ac cording to the Fishers protected LSD = 0.05. B) Colorimetric reaction of resazurin dye showing the effect of SHAM on different isolates of A. alternata

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54 Figure 2 3. Dose response of Alternaria alternata isolates to azoxystrobin based on resazuri n microtiter assay. Columns 1 6 and 7 12 showed the typical RZ reduction for sensitive or resistant isolates, respectively.

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55 Figure 2 4. Relationship between azoxystrobin an d pyraclostrobin sensitivity (effective concentration needed to reduce fungal growth by 50% [ EC 50 ]) values as determined by the rezarurin based microtiter assay and the conidia germination assay. Circles represent azoxystrobin and stars represent pyraclost robin.

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56 Figure 2 5. Partial structure at the exon intron junction in the cytochrome b gene of Alternaria alternata. Boxes indicate exons and lines indicate introns. The length of the exons and introns are not to scale. A) Isolates BLK 17 S 10S, R3Q33 1 1S, LJ 1 8 2S, VB RQF 3S, R3Q26 F9 2S, BL 17 4 3S, WM 1 3S, LOR ORI 1 3S, LJ 3 3 2S and EV 3 1S. B) Isolates WM 1 2S and CPI ORI 2S.

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57 Figure 2 6. Cleavable amplified polymorphic sequence (CAPS) analysis of the cytochrome b gene. The restriction enzyme Fnu 4HI produced two fragments of 254 bp and 95 bp in resistant isolates. Fragments are indicated by arrows. Sizes of molecular mass standard are indicated to the left of the panel (100 bp marker, Promega Corp.). Lane 1 = EV 3 1S, lane 2 = VB RQF 3S, lane 3 = LOR ORI 1 3S, lane 4 = BL 17 4 3S, lane 5 = BLK 17 5 10S, lane 6 = LJ 1 8 2S, lane 7 = LJ 3 3 2S, lane 8 = R3Q26 F9 2S, lane 9 = R3Q33 1 1S, lane 10 = WM 1 3S

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Vega, B., and Dewdney, M. M. 2014. Distribution of QoI resistance in populations o f tangerine infecting Alternaria alternata in Florida. Plant Dis. 98:67 76. CHAPTER 3 DISTRIBUTION OF QoI RESISTANCE IN POPULATIONS OF TANGERINE INFECTING Alter naria alternata IN FLORIDA Introduction Management of ABS includes the use of cultural methods, such as disease free nursery stock, wide tree spacing, reduction of excessive vegetative growth, the elimination of overhead irrigation, and fungicide applicati ons ( Timmer and Peever, 1997b ; Dewdney, 2013b ) Although cultural practices reduce disease severity, ABS contro l is largely dependent on fungicide applications ( Timmer et al., 2000b ; Bhatia et al., 2003 ; Dewdney, 2013b ) Copper based fungicides (Fungicide Resistance Action Committee [FRAC] code M1), ferbam (FRAC code M3), and quinone outside inhibitors (QoI, FRAC code 11) have been widely used in Florida over the last decade. Recently, Pristine (pyraclostrobin [QoI] + bo scalid [FRAC code 7]) and Quadris Top (azoxystrobin [QoI] + difenoconazole [FRAC code 3]) were registered for use in citrus, increasing the options for fungicide rotations. To optimize fungicide applications for ABS control, a weather based model (Alter Ra ter) was developed ( Timmer, 2 000 ; Bhatia et al., 2003 ) ; however, due to the complexity of some environmental variables (difficulty in accurately measuring leaf wetness) used for the model, this has not been extensively adopted by growers. In Florida, growers may apply from two to fifteen fungicide sprays during the course of the growing season, depending on host susceptibility and weather conditions. In general, QoI fungicides have a broad spectrum of activity against plant pathogenic fungi. This includes the most important taxonomic groups; namely Ascomycetes, Basidiomy cetes, Deuteromycetes and Oomycetes ( Bartlett et al., 2001 ; Bartlett et al., 2002 ) QoI fungicides are classified as high risk for resistance development due to the site specific mo de of action. The QoI fungicides block electron transfer between cytochrome b and cytochrome c by

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59 binding to the quinol oxidation (Qo) site of the mitochondrial cytochrome bc 1 enzyme complex, which is a key component of the respiratory electron transfer chain ( Ypema and Gold, 1999 ; Bartlett et al., 2002 ) Resistance to QoI fung icides was first reported in Blumeria graminis f. sp. tritici (wheat p owdery mildew) in Germany in 199 8 ( Bartlett et al., 2002 ) Thereafter, resistance was obs erved in many countries around the world among pathogens that affect many crops, including Mycosphaerella fijiensis in banana ( Sierotzki et al., 2000 ) Plasmopara viticola in grapes ( Brent and Hollomon, 2007b ) Venturia inaequalis in apple ( Kller et al., 2004 ) P odosphaera fusca and Pseudoperonospora cubensis in cucumber ( Ishii et al., 2001 ) and A. alternata in pistachio ( Ma et al., 2003 ) A target site mutation of the cytochrome b gene, resulting in a specific amino acid substitution, prevents fungicide binding at the target site, and causes QoI resistance ( Bartlett et al., 2002 ) Three amino acid substitutions in the cytochrome b protein have been detected in QoI resistant plant pathogenic fungi and oomycetes ( Fernndez Ortuo et al., 2008b ) The amino acid substitution from glycine to alan ine at position 143 (G143A) has been reported in most of the resistant pathogens, leading to a high level of resistance (Resistant factor [RF] > 100). This mutation has been associated with QoI control failures ( Fisher and Meunier, 2008 ) The other two amino acid substitutions, from phenylalanine to leucine at positi on 129 (F129L) and glycine to arginine at position 137 (G137R), have been associated with moderate levels of resistance, and pathogen populations are usually controlled with recommended field rates of QoI fungicides ( Sierotzki et al., 2007 ; Fernndez Ortuo et al., 2008b ) In 2008, a commercial tangerine grower located in Central Florida (Polk County) observed ABS control failure following several QoI applications. The isolates were screened for QoI sensitivity, and a large proportion of isolates tested wer e QoI resistant ( Mondal et al., 2009 )

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60 Several more suspected control failures were reported in 2009, leading to the hypothesis that QoI resistance of A. alternata could be widely distributed throughout the state. Materials and Methods Isolate C ollection From 2008 to 2009, five commercial tangerine hybrid orchards, encompassing eight blocks, were sampled from Central Florida. Groves were s ampled based on information provided by growers about ABS control failure using QoI fungicides. A more systematic statewide survey was initiated from 2010 to 2012 in commercial tangerine and tangerine hybrid orchards in 11 tangerine producing counties, com prising the 79% of the tangerine production area in Florida. In 2010, 13 citrus orchards (121 ha) encompassing 18 blocks were sampled; whereas during 2011 and 2012, 12 orchards (125 ha in 23 blocks) and 18 orchards (345 ha in 29 blocks), respectively, were sampled. Disease severity was visually evaluated in the field based on symptom distribution and classified as low, moderate and high. Low disease severity was characterized by small scattered lesions on old leaves; moderate disease severity corresponded t o mild coalescing lesions on young leaves and fruit; while, high disease severity showed abundant lesions in young and old leaves as well as fruit. Samples consisted of 60 to 80 Alternaria infected leaves or fruit arbitrarily selected per block from diffe rent trees. Samples were kept in sealed plastic bags on ice until pathogen isolation. Individual young lesions of approximately 4 mm 2 were surface disinfested with 50% ethanol for 30 s, followed by 5 min with 5% sodium hypochlorite, rinsed with sterile deionized water (SDW), blotted dry on sterile filter paper and plated on potato dextrose agar (PDA; Becton Dickinson, Sparks, MD) amende d with benomyl (10 g/ml; DuPont Crop Protection, Wilmington, DE), rifampicin (10 g/ml; Fisher Scientific, Pittsburgh, PA) and ampicillin (250 g/ml; Fisher Scientific). Plates were incubated at 24 o C for 5 to 7 days. Individual colonies of A.

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61 alternata we re transferred to PDA overlaid with sterilized filter paper for long term storage ( Peever et al., 1999 ) Once the filter paper was colonized (5 to 7 days ), it was lifted from the medium surface, placed in sterile coin envelopes, and dried for at least 6 h in a laminar flow hood. Envelopes were stored at 20 o C until further studies. Conidial prod uction for either pathogenicity or fungicide sensitivity tests was induced by transferring 4 day old mycelia from PDA to clarified V8 agar (100 ml of centrifuged V8 juice, 20 g agar and 10 g CaCO 3 /L). Cultures were incubated at room temperature under white fluorescent light for 7 to 12 days. Conidia were harvested by flooding the plates with 15 to 20 ml of SDW, gently rubbing the surface, and filtering through three layers of sterile cheesecloth. Pathogenicity T ests and M onoconidial I solates To differentiate between saprophytes and other A. alternata pathotypes, patho genicity to in vitro spray technique, as previously described ( Canihos et al., 1999 ) In total, 1258 A. alternata isolates were tested for pathogenicity. For each fungal isolate, three replicate leaves we re sprayed with 10 5 conidia/ml using a chromatography sprayer (TLC Crown North American Professional Products, Woodstock, IL). Leaves were placed in racks inside a clean 30 20 10 cm humid chamber and incubated at room temperature for 2 to 3 days. Pathog enicity was evaluated after the second or third day. Isolate virulence was determined by rating the leaf area covered by lesions on a scale of 1 to 3; where 1 = < 25% leaf area diseased, 2 = between 25 to 50% leaf area diseased and 3 = > 50% leaf area dise ased. An isolate was considered pathogenic if at least two leaves showed symptoms 3 days after inoculation. To produce monoconidial cultures of pathogenic isolates, 100 l of conidial suspension (5 10 3 conidia/ml) was spread on 2% water agar (Becton Dick inson, Sparks, MD) and

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62 incubated in the dark at 24 o C for 16 to 20 h. After incubation, one germinated conidium was transferred to PDA overlaid with sterilized filter paper for long term storage, following the procedure described above ( Peever et al., 1999 ) Sensitivity of A. alternata I solates to A zoxystrobin and P yraclostrobin In total, 817 A. alternata monoconidial isolates were tested from the 2008 to 2012 sample collections. In vitro fungicide sensitivity was determined using the resazurin based microtiter assay, as previously described ( Vega et al., 2012 ) Briefly, technical grade azoxystrobin (Syngenta Crop Protection, Greensboro, NC) and pyraclostrobin (BASF Corp., Research Triangle Park, NC) were dis solved in acetone at 10 mg/ml and 10 fold serially diluted. The final concentration of acetone in complete medium ( Bennett and Lasure, 1991 ) was 0.1% by volume. Resazurin salt (Sigma Aldrich, St. Louis, MO) was dissolved in distilled water at 4 mM and filter sterilized (0.22 m filter; Corning Inc., Lowell, MA). Each isolate was added in triplicate into a 96 well, flat bottom, microplate (Corning Inc.). The final concentrations per well of either azoxystrobin or pyraclostrobin were 0, 0.001, 0.01, 0.05, 0.1, 0.5, 1 or 10 g/ml; and 0, 0.001, 0.005, 0.01, 0.05, 0.1, 1, or 10 g/ml, respectively. The final conidia and resazurin concentrations (per well) were 4 10 4 conidia/ml and 40 M, respectively. Plates were c overed with plastic lids, placed into a clean plastic humid chamber, and incubated in the dark at 27 o C for 24 h with shaking at 400 rpm. Fungal respiration was determined by measuring the resazurin reduction at 570 and 600 nm, as previously described ( Vega et al., 2012 ) Absorbance was read with a microplate spectrophotometer (Bio Rad, Hercules, CA). Isolate sensitivity was determined by the effective concentration needed to reduce resazurin by 50% (EC 50 ) using either a sigmoidal or exponential decay functions ( Vega et al., 2012 ) Isolates with EC 50 values higher than 5 or 0.5 g/ml of azoxystrobin and pyraclostrobin, respectively, were classified as resistant. Isolates with EC 50 values lower than those values we re classified as sensitive.

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63 Baseline S ensitivity of A. alternata to A zoxystrobin and P yraclostrobin In total, 40 A. alternata isolates were obtained from the Dewdney lab culture collection (Table 3 1). These isolates were collected from tangerine hybrids and grapefruit groves where there was no history of QoI fungicide applications prior to 2000. Sensitivity to azoxystrobin and pyraclostrobin was determined using the resazurin based microtiter assay, as described above. DNA E xtraction and M olecular D etecti on of the G143A M utation A subsample of 161 A. alternata isolates, phenotypically identified as QoI resistant were arbitrarily selected to confirm the presence of the G143A mutation using polymerase chain reaction restriction fragment length polymorphism (PCR RFLP) analysis ( Vega et al., 2012 ) Additionally, 74 QoI sensitive isolates were also arbitrarily selected to validate the lack of the G143A mutation. Genomic DNA was extracted from 3 day old mycelia cultured on PDA overlaid with cellophane sheets. Mycelia were transferred into a 2 ml microcentrifuge tube containing a 5 mm diameter stainless steel bead (Qiagen, Valencia, CA) and disrupted with a TissueLyser II (Qiagen) twice for 30 s and an oscillation frequency of 30/s. DNA was extracted DNA concentration was measured using a NanoDrop ND 1000 spectrophotometer (Nano Drop Technologies, Wilmington, DE). The cytochrome b gene of A. alternata isolates was partially CTA TGG ATC TTA CAG AGC AC INTr (5` GTA TGT AAC CGT CTC CGT C ltier Thermal cycler (MJ research Inc., Watertown, MA) in a final volume of 25 l containing 1 unit of HotStart Taq Plus polymerase (Qiagen), 2.5 l of 10 PCR buffer, 200 M of each dNTP, 0.3 M of each primer, and 0.5 to 20 ng of fungal DNA template. Cyc ling parameters were performed as previously described ( Vega et al., 2012 ) PCR products were visualized with UV

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64 light after electrophoresis in 1.2% agarose gel with 1 Tris acetate EDTA stained with SYBR DNA gel stain (Invitrogen life technologies, Grand Island, NY). PCR products were purified using the MiniElute PCR purification kit (Qiagen) following the enzyme Fnu 4HI (New England Biolabs, Ipswich, MA) at 37 o C for 1 h, according to the y electrophoresis in 1.6% agarose gel. Statistical A nalysis Absorbance values from resazurin reduction tests were plotted against the log 10 transformed fungicide concentration and EC 50 values, expressed as g/ml, were calculated for each isolate using eit her sigmoidal or exponential decay functions ( Vega et al., 2012 ) with SigmaPlot (ver. 11.0; Systat Softwa re Inc., San Jose, CA). EC 50 values were log 10 transformed prior to testing for normality using the Shapiro Wilk test in PROC UNIVARIATE (ver. 9.3; SAS Institute, Cary, NC) and graphically analyzed. Probabilistic distributions of baselines were calculated with InfoStat (ver. 2004; InfoStat, Cordoba, Argentina). To determine if EC 50 values of QoI fungicides from sensitive and resistant isolates were significantly higher than those from baseline isolates, a two sample t test were performed using PROC TTEST (S AS). Chi square 2 ) tests were performed to examine if the proportion of QoI resistant isolates was distributed randomly over cultivars, field disease severity, virulence class, and number of QoI applications per year using PROC FREQ (SAS). Cross resistan ce between azoxystrobin and pyraclostrobin was determined by calculating a Pearson correlation coefficient using PROC REG and PROC CORR (SAS).

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65 Results Baseline S ensitivity to A zoxystr obin and P yraclostrobin The 40 monoconidial A. alternata isolates were log normally distributed for both azoxystrobin ( W = 0.9621 ; P = 0.1969) and pyraclostrobin ( W = 0.9451 ; P = 0.0516). The range of EC 50 values for azoxystrobin was 0.0124 to 0.3561 g/ml, with mean and median EC 50 values of 0.1352 and 0.098 g/ml (Table 3 1 and Fig. 3 1A), respectively. Pyraclostrobin had a higher intrinsic activity than azoxystrobin. EC 50 values for pyraclostrobin ranged from 0.0031 to 0.0531 g/ml, with mean and median EC 50 values of 0.0228 and 0.0205 g/ml (Table 3 1 and Fig. 3 1B), respectively. The probability of an isolate from the baseline population sampled showing an EC 50 value greater than 5 and 0.5 g/ml, proposed as discriminatory concentrations to differentiate sensitive and resistant isolates for azoxystrobin an d pyraclostrobin respectively, was 2.011 10 6 for azoxystrobin and 8.739 10 6 for pyraclostrobin. A significant positive correlation ( r = 0.8001; P < 0.0001) was observed between azoxystrobin and pyraclostrobin EC 50 values. Alternaria alternata I solate C ollection From 2008 to 2012, 2653 A. alternata isolates were collected in Florida from 46 commercial citrus orchards, encompassing 78 blocks. Of 2653 isolates, 1258 were tested for pathogenic isolates was 84% and 68%, respectively.

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66 QoI R esist ance in Florida C itrus O rchards Among the 817 field isolates evaluated, 471 (57.6%) were resistant to both azoxystrobin and pyraclostrobin (Table 3 2). A complete ly QoI resistant population was observed in 19 orchards, encompassing 25 blocks; mixed populations of QoI resistant and sensitive isolates were observed in 24 orchards (39 blocks); whereas a completely sensitive population was observed in nine orchards (1 4 blocks). The frequency of QoI resistant isolates in orchards with mixed populations varied from 7 to 95%. The presence of QoI resistant isolates was widespread and very common across tangerine producing counties in Florida (Fig. 3 2). Sensitivity D istrib ution of Alternaria alternata I solates to A zoxy strobin and P yraclostrobin The sensitivity distribution of A. alternata isolates showed a clear division between QoI sensitive and resistant populations (Fig. 3 3). The EC 50 values of the sensitive populations for azoxystrobin and pyraclostrobin ranged from 0.0121 to 0.8361 g/ml and from 0.0024 to 0.1162 g/ml, respectively, resulting in respective mean EC 50 values of 0.139 and 0.0201 g/ml. The mean EC 50 values of sensitive populations for both azoxystrobin and pyraclostrobin was not significantly different ( t = 0.51; P = 0.6095 and t = 1.79; P = 0.0739, respectively) than the baseline populations. EC 50 values of the resistant populations ranged from 6.6256 to > 10 g/ml fo r azoxystrobin and from 1.1303 to > 10 g/ml for pyraclostrobin, with a median EC 50 value of > 10 and 5.507 g/ml for azoxystrobin and pyraclostrobin, respectively. Resistance factor (RF), expressed as the ratio of the EC 50 value of a pyraclostrobin resist ant isolate to the mean EC 50 for pyraclostrobin baseline sensitive isolates, was unimodally distributed (Fig. B 1). The RF ranged from 50 to > 439, with a median of 241.5.

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67 Cro ss R esistance to QoI F ungicides Pearson correlation analysis of 346 QoI sensitive isolates showed that EC 50 values for azoxystrobin and pyraclostrobin were highly correlated ( r = 0.8655; P < 0.0001), suggesting a high level of cross resistance between the two QoI fungicides (Fig. 3 4). QoI R esistance A ssociated with C itrus H osts and O r chard F actors 2 = 97.5345; P < 0.0001) among cultivars (Fig. 3 2 = 0.051; P = 0.822). Moreover, the proportion of resistance isolates was 2 = 4.33; P (Fig. 3 5). The proportion of re sistant isolates was not significantly different (Table 3 3) among the field disease severity categories (low, moderate, and high) evaluated. In orchards with low disease severity, 47% of the isolates were resistant. In orchards with moderate disease sever ity, the proportion of resistant isolates was 55%, whereas in orchards with high disease severity, 60% of the isolates tested were resistant (Table 3 3). No significant differences in the proportion of resistant isolates were observed when A. alternata vir ulence class was examined (Table 3 2 = 24.5544; P < 0.0001) among virulence hereas in other cultivars the proportion of resistance was evenly distributed ( data not shown ). A positive correlation was found between number of QoI applications and frequency of resistance ( r = 0.9381; P = 0.0056). Resistant isolates were found more fre quently in orchards with more than four QoI applications per year (Table 3 3). On the other hand, in orchards with

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68 no QoI exposure, no resistant isolates were detected. In general, the proportion of resistant isolates increased with number of QoI applicati ons per year. Detection of the G143A M utation A PCR RFLP analyses was used to differentiate between isolates carrying the wild type GGT codon (glycine) at amino acid 143, and those with the mutant allele GCT (alanine) in the A. alternata population. Two distinct cytochrome b gene structures were identified based on the presence of one or two introns ( Vega et al., 2012 ) A 377 bp fragment was amplified in isolates carrying one intron, designated as profile I, whereas a 1564 bp fragment was amplified in isolates carrying two introns, designated as profile II. The restriction enzyme Fnu 4HI gener ated two fragments in isolates carrying the mutant allele G143A. The length of the fragments was 123 bp and 254 bp for profile I isolates; and, 254 bp and 1310 bp for profile II isolates (Fig. 3 6). The fragments of 377 bp and 1564 bp remained undigested i n wild type isolates profile I and profile II, respectively (Fig. 3 6B). The amino acid substitution G143A was present in all 161 QoI resistant isolates tested and absent in all 74 sensitive isolates tested. Between sensitive and resistant isolates, the pr oportion of isolates carrying the cytochrome b 2 = 118.8239; P < 0.0001). The proportion of profile II isolates was 54% in resistant isolates and only 1% in sensitive isolates (Fig. 3 7). The proportion of profile I isolates among the populations tested was less skewed. Thirty one percent of sensitive isolates and 14% of resistant isolates were profile I (Fig. 3 7). Discussion Quinone outside inhibitors (QoI) have been used for more than a decade in Flor ida for ABS control ( De wdney, 2013b ) Due to their effectiveness against A. alternata and good weathering properties, growers adopted them very quickly. Despite their excellent characteristics, resistance to QoI fungicides has been detected in many plant pathogens within a

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69 fe w years of their introduction to a cropping system ( FRAC, 2013b ) QoI resistance in Alternaria populations has been identified in vegetables as well as fruit and nuts such as pistachio ( Ma et al., 2003 ) pear ( Ishii, 2010 ) apple ( Lu et al., 2003 ) and potato ( Pasche et al., 2004 ) In 2008, QoI resistance of tangerine infecting A. alternata isolates was detected in Polk County, Florida ( Mondal et al., 2009 ) making ABS management considerably more difficult and costly. Tangerine production in Florida is mainly for the fr esh fruit market; thus, the production of disease free fruit is paramount and is heavily reliant on fungicides, thus increasing the risk for resistance development. This is particularly true for the site specific fungicides such as the QoIs. Our study repr esents the first report of the statewide QoI sensitivity distribution in the tangerine infecting A. alternata population of Florida using both phenotypic and molecular approaches. In the current study, the baseline distribution of A. alternata to azoxystrobin and pyraclostrobin was established using never exposed isolates collected before the introduction of QoIs to citrus. In fungicide resistance monitoring programs, the establishment of baseline sensitivity is of great importance. It can be us ed to monitor for changes in the sensitivity profiles of target populations exposed to the tested modes of action over time. Comparisons of new populations to the baseline can give evidence of increasing frequency of resistance in the population that could lead to future control failure ( Russell, 2004 ) The baseline distribution of azoxystrobi n and pyraclostrobin was log normally distributed within a relatively narrow range. The mean EC 50 value for azoxystrobin, obtained in our baseline study (0.135 g/ml), was a little higher than the mean EC 50 value observed in other wild type Alternaria spec ies. For 14 pistachio infecting A. alternata isolates, the mean EC 50 value was 0.023 g/ml ( Ma et al., 2003 ) whereas in 32 A. solani isolates from potato, the mean EC 50 value was 0.038 g/ml ( Pasche et al., 2004 ; Rosenzweig et al., 2008a ) Some differences are expected because two different

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70 methods were used to determine the EC 50 s, resazurin based microtiter test versus spore germination assay, and the intrinsic inter species variati on in fungicide sensitivity. Our baseline result for azoxystrobin did not match the study done by Mondal et al. (2005) in which the mean EC 50 value from five wild type A. alternata citrus isolates was > 100 g/ml. However, this is likely because Mondal et al. (2005) determined the EC 50 with a mycelial growth inhibition test and it appears that A. alternata mycelium is insensitive to azoxystrobin but not to pyraclostrobin. The sensitivity distribution of the A. alternata population from the 2008 to 2012 surv ey to azoxystrobin and pyraclostrobin shows two clear populations of QoI sensitive and resistant isolates. This type of distribution suggests a disruptive, monogenic resistance as expected for site specific fungicides like QoIs ( Br ent and Hollomon, 2007b ) Our results revealed that A. alternata isolates continued to be more sensitive to pyraclostrobin than azoxystrobin, consistent with previous studies on several pathogens from citrus and vegetable crops ( Mondal et al., 2005 ; Rebollar Alviter et al., 2007 ; Amiri et al., 2010 ; Bradley and Pedersen, 2010 ) A positive correlation was found between azoxystrobin and pyraclostrobin, demonstrating cross resistance between these two QoI fungicides as previously described in other systems ( Sierotzki et al., 200 0 ; Chin et al., 2001 ; Kim et al., 2003 ; Kller et al., 2004 ; Fernndez Ortuo et al., 2008a ) Based on the EC 50 values of sensitive and resistant populations, we established discriminatory concentrations for both QoI fungicides for rapid identification of resistant isolates. We suggest the discriminatory concentrations of 5 g/ml and 0.5 g/ml for azoxys trobin and pyraclostrobin, respectively, which approximately corresponds to the lowest EC 50 values of resistant isolates. The EC 50 values for pyraclostrobin resistant population had a left skewed distribution; where 88% of resistant isolates had a RF greater than 100, and all carried the G143A mutation in the cytochrome b gene.

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71 Our study shows that A. alternata resistance to azoxystr obin and pyraclostrobin is widespread in commercial citrus orchards in Florida; QoI resistant isolates were found in 64 of 78 blocks sampled. The proportion of resistant isolates was greater than 25% in 73% of the blocks sampled, indicating that QoI resist ance is likely to continue to increase with continued selection. Similarly, selection for QoI resistance was observed in almond and pistachio infecting A. alternata where 36 of 41 orchards sampled in 2005 showed more than 90% azoxystrobin resistant isola tes ( Luo et al., 2007 ) The resistant population was most prevalent in the Indian River region on the east coast of Florida. This region comprises 12% of the total tangerine commands a high fresh fruit market price, but of the commercial tangerine cultivars grown in this area, it also the most suscepti ble to ABS ( Solel an d Kimchi, 1997 ; Timmer et al., 2003 ) To obtain good fruit quality and premium prices, more fungicide applications are often needed to manage disease on this cultivar compared to less susceptible, low er value cultivars such as the Sunburst tangerine. In the Indian River region, growers have us ing QoI fungicides more than three times per year, suggesting that the QoI resistant population has been selected over time as previously described in pistachio i nfecting A. alternata ( Ma et al., 2003 ) In contrast, the central region (Polk, Lake, Highlands and Osceola Counties) is the largest tangerine production area, comprising 48% of the total tangerine production a rea, and the cultivar diversity is higher compared with other regions so a lower number of QoI applications per year occur. In Florida, disease management programs, and hence QoI selection pressure, has varied according to the level of cultivar susceptibil ity to ABS. Sunburst tangerine is one of the least susceptible cultivars; oI

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72 some groves still showed a considerable proportion of resistant isolates (> 30%), suggesting that only a few QoI applications are needed to start the selection of a resistant population. resistance to ABS is controlled by a recessive allele ( Hutton and Mayers, 1988 ; Dalkilic et al., 2005 ) Many of the grapefruit tangerine and tangerine sweet orange hybrids are the result of tangerine, and therefore susceptible to ABS. We observed higher disease severity in the most susceptible cultivars, Minneola and Dancy, compared to the less susceptible cultivars Murcott or Sunburst. In fact, 97% of isolates recovered from brown spot lesi ons on consistent with previous reports ( Peever et al., 1999 ) Culti var susceptibility to ABS was closely associated with QoI resistance frequency and may be contributing to decreased efficacy of fungicide programs in some citrus orchards. The most susceptible cultivars, Minneola and Dancy, had a higher proportion of QoI resistant isolates than the other cultivars. At least two leaf litter as we ll as infected leaves still in the canopy leading to increase the inoculum density and disease pressure ( Timmer et al., 1998 ) ; and, second, the selection pressure on QoI resistant population. Growers tend to apply fungicides more frequently when disease pressure is high, putting greater selection pressure on the pathogen population, which over subsequent generations can lead to higher frequencies of resistance. Lat er, control failure was observed as a result of the dominance of resistant isolates in the population. Growers observed QoI control failure when the proportion of resistance in a population was greater than 65%. On average, more than three QoI applications

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73 used in the less susceptible cultivars Murcott, Sunburst, Orlando and Lee. Consequently, QoI selection pressure was higher in the most susceptible cultivars, increasing the f requency of resistant population over time. Regardless of cultivar, QoI resistance was not related to the disease severity levels observed in the field. This result implies that QoI resistance in the A. alternata population did not impose a negative effect on pathogenic fitness over time; and thus, resistant isolates are able to compete under similar conditions with wild type isolates. Previous studies indicated no fitness effects for QoI resistant isolates of Magnaporthe grisea ( Avila Adame and Kller, 2003a ) Plasmopara viticola ( Corio Costet et al., 2011 ) Erysiphe graminis f. sp. tritici ( Chin et al., 2001 ) A. alternata ( Karaoglanidis et al., 2011 ) among others, and they successfully competed with the sensitive isolates for the same ecological niche. No relationship was observed between QoI exposures per year and field disease severity categories. Nevertheless, the greatest proportion of resistant isolates (60%) was obtained from orchards with high disease severity which implies that resistant isolates were selected and a resistant population built up over time Likewise, our results showed a lack of relationship between resistant isolates and virulence. Peever et al. (2000) found that virulenc e was similar in different citrus cultivars inoculated with A. alternata isolates depend on the production of the host specific ACT toxin ( Kohmoto et al., 1991 ; Peever et al., 2002 ) controlled by a gene cluster involved in the biosynthesis of the toxin ( Akimitsu et al., 2003 ) Ther efore, QoI resistance and virulence are two unrelated mechanisms present in A. alternata population and not necessarily expected to be related to each other. Only the amino acid substitution of glycine for alanine at codon 143 (G143A) in the cytochrome b w as found in the QoI resistant population. This mutation has been identified in

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74 many plant pathogens ( FRAC, 2013b ) and confers a high level of resistance (RF higher than 100). The G143A mutation is related to control failure of QoI fungicides ( Fisher and Meunier, 2008 ) such as observed for A. alternata in pistachio ( Ma et al., 2003 ) Venturia inaequalis in apple ( Lesniak et al., 2011 ) Erysip he necator in grape ( Mile s et al., 2012 ) Cercospora beticola in sugar beet ( Bolton et al., 2013 ) and Botrytis cinerea in multiple crops ( Jiang et al., 2009 ; Leroux et al., 2010 ; Fernndez Ortuo et al., 2012 ) and others. Overall, th e G143A mutation was observed in isolates with EC 50 values greater than 6 g/ml for azoxystrobin and greater than 1 g/ml for pyraclostrobin, which corresponded to a RF greater than 50. The RF lower than 100 observed in 12% of resistant isolates could be a ttributed to the method used to determine the EC 50 value. Since the resazurin based microtiter assay is a very sensitive test, the resazurin reduction measurement could be affected by the conidial germination rate of individual isolates, giving a lower EC 5 0 value ( Vega et al., 2012 ) In fact, the rate of resazurin reduction of some of the resistant isolates w ith an RF below 100 was lower than 62%, compared with the normal range (between 85 and 95%) observed in the majority of all isolates. A lower conidial germination rate could underestimate the overall dye reduction produced by specific isolate, decreasing t he EC 50 value. Two A. alternata genotypes, profile I and profile II, were evenly distributed in Florida. The genotype designation was based on the presence of one or two introns in the amino acid region of 103 to 268 in the cytochrome b gene ( Vega et al., 2012 ) Profile I isolates had only one intron at amino acid position 164 (F164). Profile II isolates had two introns, the first one at amino acid position 126 (A126), and the second one at position F164 ( Vega et al., 2012 ) The cytochrome b gene structures of A. alternata from sunflower and A. solani from potato were characterized previously ( Grasso et al., 2006b ) No introns were observed in the cytochrome b of

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75 A. alternata whereas four introns at positions A126, G143, V146 and F164 were observ ed in the cytochrome b of A. solani ( Gr asso et al., 2006b ) The high level of identity (> 82%) observed between the sequence of both A. alternata cytochrome b introns (A126 and F164) and their homologs in A. solani leads us to a hypothesis of recombination events within this particular regi on of the A. alternata genome ( unpublished data ). Heterogeneity in the cytochrome b gene (isolates with two or three introns) has been described previously in B. cinerea from cucumber and tomato ( Banno et al., 2009 ) ; however this is the first description of cytochrome b heterogeneity in a n imperfect fungus such as Alternaria Genetic variation of A. alternata populations in citrus was documented previously using RAPD markers and endo polygalacturonase gene sequencing ( Peever et al., 2002 ) Two well defined phylogenetic ( Stewart et al., 2013 ) revealing an unexpected level of genetic variability within this clonally reproducing species. Nevertheless, the implications of cytochrome b heterogeneity and the genetic diversity of A. alternata populations are unknown. Sequence analysis of the cytochrome b gene in several fungal plant pathogens revealed differences in the intron/exon structure among species ( Fisher and Meunier, 2008 ) Furthermore, the presence of a bi group I intron between amino acids 143 and 144 appears to prevent the G143A mutation in the cytochrome b ( Grasso et al., 2006b ; Grasso et al., 2006a ) But, our A. alternata population did not have an intron in that location; therefore the intrinsic risk to evolve G143A mutation is high as observed in this study. Interestingly, the majority of resistant isolates that we evaluated (127 of 161 ) belong to isolate profile II. However, it is unknown whether cytochrome b structure is related to the evolution of QoI resistance in tangerine infecting A. alternata or why the frequency of the mutant allele was

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76 higher in isolates carrying two introns. Further studies are needed to elucidate the effect of QoI fungicides on the population structure of both groups of isolates. In summary, after testing a large collection of A. alternata isolates for azoxystrobin and pyraclostrobin sensitivity, we concluded that QoI resistance is widespread in Florida and it is a real concern for tangerine producers. QoI control failure detected in some groves was produced by the dominance of a resistant population possessing the amino acid substitution G143A. Therefore, re gardless of ABS susceptibility, growers must be careful with the use of QoI fungicides to avoid the selection and development of resistance, especially in orchards where resistance has not been identified yet. Our study also identified two groups of isolat es with different cytochrome b gene structures, where the majority of resistant isolates were in the group carrying two introns. Finally, more effective disease management strategies, such as fungicide rotation with different modes of action and the exclus ion of QoI fungicides where resistance has been detected, are fundamental in ABS control programs. Newer fungicides (difenoconazole and boscalid) in mixtures with QoI have been recently registered and can be used in rotation with copper and ferbam for ABS control. However, further research is needed to establish baseline sensitivities for those new active ingredients so that they can be monitored for resistance development.

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77 Table 3 1. Baseline sensitivity of Alternaria alternata isolates from different hosts to azoxystrobin and pyraclostrobin Isolate group Location, county Year Host b N c Mean EC 50 (g/ml) a Azoxystrobin Pyraclostrobin AR Arcadia, DeSoto 1997 Sunburst tangerine 4 0.2087 (0.0976) b 0.0311 (0.0096) CPI Immokalee, Collier 1996 Murcott tangor 3 0.2092 (0.0896) 0.0362 (0.0133) EV Lake Alfred, Polk 1996 Minneola tangelo 4 0.0579 (0.0173) 0.0097 (0.0031) FM Fort Meade, Polk 1996 Minneola tangelo 2 0.1342 (0.0322) 0.0289 (0.0070) IMK Immokalee, Collier 1997 Minneola tangelo 2 0.1485 (0.1924) 0.0267 (0.0332) LOR Lorida, Highlands 1997 Orlando tangelo 3 0.1070 (0.1116) 0.0292 (0.0147) RAN Immokalee, Collier 1997 Sunburst tangerine 5 0.0696 (0.0388) 0.0153 (0.0075) SH Polk C ity, Polk 1996 Minneola tangelo 6 0.1781 (0.1267) 0.0320 (0.0174) VB Vero B each, Indian River 1997 Grapefruit 6 0.1672 (0.1209) 0.0203 (0.0133) WP West Palm Beach, Palm Beach 1996 Minneola tangelo 5 0.0815 (0.0428) 0.0104 (0.0065) a EC 50 = effective concentration needed to reduce fungal growth by 50%. Values in parentheses denote standard deviation. b Tangerine = Citrus reticulata tangor = C. reticulata C. sinensis tangelo = Citrus paradisi C. reticulata grapefruit = C. paradisi c Number of isolates tested.

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78 Table 3 2 Origin, history of fungicide exposure, and detection of quinone outside inhibitor resistance in Alternaria alternata isolates collected in Florida citrus groves from 2008 to 2012 Group Location, C ounty Year N a Host b Severity c Class d T e R f 1 Fort Meade, Polk 2010 1 Murcott tangor Low 1.5 14 1 2 Haines City, Polk 2010 4 Minneola tangelo Low 2.5 16 16 2010 4 Murcott tangor Low 2 14 6 3 Umatilla, Lake 2011 2 Minneola tangelo N.A. e 3 12 12 4 Tavares, Lake 2012 2 Minneola tangelo Moderate 2 10 0 5 Fort Myers, Lee 2012 3 Murcott tangor Moderate 2 24 5 2012 3 Sunburst tangerine Low 1 2 1 6 Avon Park, Highlands 2011 2 Minneola tangelo Moderate 2 16 13 Avon Park, Highlands 2011 2 Murcott tangor Moderate 2 27 25 Babson Park, Polk 2011 2 Murcott tangor Low 2 15 14 Fort Meade, Polk 2011 2 Murcott tangor Moderate 2 16 14 Frostproof, Polk 2009 2 Murcott tangor High 2.5 10 5 Frostproof, Polk 2011 2 Minneola tangelo Moderate 2 16 6 Frostproof, Polk 2011 2 Murcott tangor Low 2 8 7 7 Crooked Lake, Polk 2010 1 Murcott tangor Low 2 14 1 8 Bartow, Polk 2012 1 Murcott tangor Moderate 2 11 8 9 Davenport, Polk 2010 2 Murcott tangor High 3 15 2 10 Bartow, Polk 2012 1 Sunburst tangerine Low 2 12 0 11 Winter Haven, Polk 2010 1 Dancy mandarin High 3 15 8 12 Clermont, Lake 2012 2 Murcott tangor High 2 12 6 2012 2 Sunburst tangerine Low 2 11 10 13 Felda, Hendry 2012 2 Murcott tangor Moderate 3 12 6 14 Dundee, Polk 2009 2 Murcott tangor High 2 23 23 15 Lake Wales, Polk 2010 2 Minneola tangelo N.A. 3 13 13 16 Fort Pierce, St. Lucie 2012 2 Murcott tangor Low 3 2 0 17 Fort Meade, Polk 2012 4 Murcott tangor Moderate 2 9 9 2012 1 Sunburst tangerine Moderate 2 10 4 18 Fort Pierce, St. Lucie 2011 4 Minneola tangelo Moderate 2 10 10 19 Fort Pierce, St. Lucie 2010 N.A. Minneola tangelo N.A. 3 14 14 20 Immokalee, Collier 2012 > 1 Murcott tangor Low 2 11 2 21 Vero Beach, Indian River 2011 4 Minneola tangelo High 3 30 30 22 Vero Beach, Indian River 2011 N.A. Sunburst tangerine Low 2 3 2 23 Venus, Highlands 2012 2 Murcott tangor Low 2.5 12 3 24 Immokalee, Collier 2012 2 Murcott tangor Moderate 3 12 2 25 Lake Wales, Polk 2010 2 Murcott tangor Moderate 2 15 5 26 Zolfo Springs, Hardee 2011 2 Minneola tangelo High 2 10 10 27 St. Cloud, Osceola 2010 1 Sunburst tangerine Moderate 1 9 5 28 Polk City, Polk 2012 > 3 Sunburst tangerine Moderate 2 12 8 29 Clermont, Lake 2012 1 Orlando tangelo High 1 11 0 2012 1 Sunburst tangerine Moderate 1 11 3 30 Oviedo, Seminole 2009 > 4 Minneola tangelo High 3 2 2 31 Fort Meade, Polk 2010 0 Murcott tangor Moderate 1 11 0 2010 0 Sunburst tangerine Moderate 2 10 0 32 Lake Wales, Polk 2011 3 Minneola tangelo Moderate 2 11 11 33 Nokomis, Sarasota 2011 2 Minneola tangelo Moderate 2 9 9 34 Vero Beach, Indian River 2011 4 Minneola tangelo Low 2 10 10 35 Bartow, Polk 2012 2 Murcott tangor Low 2 1 1 36 Fort Pierce, St. Lucie 2011 4 Minneola tangelo High 2 23 23 2011 4 Murcott tangor Low 1 1 1 37 Eustis, Lake 2012 2 Minneola tangelo High 2 10 0

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79 Table 3 2 Continued. Group Lo cation, C ounty Year N a Host b Severity c Class d T e R f 2012 2 Orlando tangelo Moderate 2 9 0 38 Immokalee, Collier 2012 2 Sunburst tangerine Moderate 2 20 17 39 Haines City, Polk 2010 > 3 Murcott tangor Moderate 3 16 14 2010 > 3 Orlando tangelo Low 2 16 12 40 Winter Haven, Polk 2008 > 6 Dancy mandarin High 3 20 19 2010 > 5 Dancy mandarin High 2 16 12 41 Vero Beach, Indian River 2011 N.A. Minneola tangelo Moderate 3 10 10 42 Haines City, Polk 2010 2 Lee citrus hybrid High 2 9 0 2010 2 Minneola tangelo High 2 10 0 2010 2 Murcott tangor High 2 9 0 43 Wauchula, Hardee 2011 1 Murcott tangor N.A. 2 12 12 44 Mt. Dora, Lake 2012 N.A. Minneola tangelo High 2 11 0 2012 N.A. Murcott tangor Low 2 10 0 45 Grand Island, Lake 2012 2 Lee citrus hybrid Moderate 3 12 1 2012 2 Murcott tangor Moderate 3 12 3 2012 2 Sunburst tangerine Low 2.5 12 0 46 Oviedo, Seminole 2009 > 4 Minneola tangelo High 3 6 5 a QoI exposures per year; NA = not available. b Tangor = Citrus reticulata C. sinensis tangelo = C. reticulata C. paradisi tangerine or mandarin = C. reticulata citrus hybrid = C. reticulata tangelo c Field severity was evaluated based on symptom distribution, where Low = small scattered lesion s on old leaves, M oderate = mild coalescing lesions on young leaves and fruits, and H igh = abundant lesions in young and old leaves as well as fruits ; NA = not available d Med ian virulence class. Virulence tested by spray inoculati o n of detached tangerine leaves and rat ed 48 to 72 h after incubation, where 1 = < 25%, 2 = 25 to 50%, and 3 = > 50% leaf area e Number of isolates tested f Number of resistant isolates Resistant isolates grew on complete medium in resazurin based microtiter assay amended with azoxystrobin > 5 g/ml or pyraclostrobin > 0.5 g/ml. Sensitive isolates did not grow at those fungicide concentrations

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80 Table 3 3 A 2 analysis of quinone outsi de inhibitor (QoI) resistant isolates of Alternaria alternata collected in Florida from 2008 to 2012 according to field severity, virulence class, and number of QoI applications per year Response variable, levels # isolates tested # resistant isolates a 2 df b P value Field severity c Low 184 87 2.021 2 0.3641 Moderate 340 188 High 242 145 Virulence class d 1 163 81 1.849 2 0.370 2 341 192 3 300 186 QoI exposures e 0 21 0 38.225 5 <0.0001 1 119 42 2 391 209 3 37 17 4 157 139 >5 44 38 a Resistant isolates grew on complete medium in resazurin based microtiter assay amended with azoxystrobin > 5 g/ml or pyraclostrobin > 0.5 g/ml. Sensitive isolates did not grow at those fungicide concentrations b Degrees of freedom c Field severity was evaluated based on symptom distribution, where Low = small scattered lesion s on old leaves, M oderate = mild coalescing lesions on young leaves and fruits, and H igh = abundant lesions in young and old leaves as well as fruits ; NA = not available d Virulence tested by spray inoculati o n of detached tangerine leaves and rat ed 48 to 72 h after incubation; 1 = < 25%, 2 = 25 to 50%, and 3 = > 50% leaf area e Number of app lications per year

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81 Figure 3 2 Baseline sensitivity distribution of Alternaria alternata isolates (n=40) to QoI fungicides. A) azoxystro bin. B) Pyraclostrobin. Values are based on EC 50 values (effective concentration needed to reduce fungal growth by 50%).

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82 Figure 3 2. Geographic distribution of QoI sensitive and resistant Alternaria alternata isolates collected in 46 commercial citrus orchards encompassing 78 blocks from 2008 to 201 2

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83 Figure 3 3. Sensitivity distribution of Alternaria alternata isolates (n=817) collected in Florida citrus orchards fro m 2008 to 2012 to QoI fungicides. A) A zoxystrobin B) P yraclostrobi n. Values are based on effective concentration needed to reduce fungal growth by 50% (EC 50 ) values Black circles denote EC 50 values for individual isolates; while small gray dots denote resistant isolates with EC 50 values > 10 g/ml.

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84 Figur e 3 4. Correlation of effective concentration needed to reduce fungal growth by 50% (EC 50 ) values of azoxystrobin and pyraclostrobin in quinone outside inhibitor sensitive Alternaria alternata isolates (n=346).

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85 Figure 3 5. Distribution of sensitive (n=346) and resistant (n=471) Alternaria alternata isolates to azoxystrobin and pyraclostrobin collected during 2008 to 2012 from Florida tangerine and tangerine hybrids orchards. Isolates were considered resistant when they grew on complete medium in resazurin based microtiter assay amended with fungicide at concentrations > 5 g/ml or > 0.5 g/ml for azoxystrobin and pyraclostrobin, respectively

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86 Figure 3 6. Restriction fragment length polymorphism analysis of the partial structure of the cytochrome b gene from Alternaria alternata isolates that are either quinone outside inhibitor sensitive or resistant. A) R estriction enzyme Fnu 4HI produced two fragments of 123 and 254 bp in resistant isolates (G143A) carrying the cytb profile I whereas in isolates carrying the cytb profile II, the fragments obtained were of 254 and 1,310 bp. Boxes indicate exons and lines indicate introns. Lengths of exons and introns ar e not to scale. B) Detection of the G143A mutation with the restriction enzyme Fnu 4HI, followed by electrophoresis on 1.6% agarose gels. Lane M = 100 bp DNA ladder (Invitrogen Technologies); la nes 1, 2, 3, 4, 6, 9, 10, 11, 13, 14, 15, 16, 17, 18, 19, 21, 2 2, 23, 24, 25, 26, 27, 28, 30, and 38 denotes resistant isolates carrying the cytb profile II; lanes 5, 7, 8, 12, 20, and 37 denotes resistant isolates carrying the cytb profile I; and lanes 29, 31, 32, 33, 34, 35, and 36 denotes sensitive isolates carryin g the cytb profile I

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87 Figure 3 7. Frequency distribution of sensitive (n=74) and resistant (n=161) Alternaria alternata isolates to azoxystrobin and pyraclostrobin according to cytochrome b profiles. Profile I isolates had one intron at amino acid F164. Profile II isolates had two introns at amino acid positions A 126 and F164. Isolates were considered resistant when they grew on complete medium in resazurin based microtiter assay amended wit h fungicide at concentrations > 5 g/ml or > 0.5 g/ml for azoxystrobin and pyraclostrobin, respectively; and, showed the G143A point mutation in the cytochrome b gene

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88 CHAPTER 4 QoI RESISTANCE STABILITY IN RELATION TO PATHOGENIC AND SAPROPHYTIC FITNESS C OMPONENTS OF Alternaria alternata FROM CITRUS Introduction Fungicide resistance is a serious problem for disease management programs, especially if there is intensive use of site specific fungicides. The development, stability, and evolution of resistance in fungal populations are dependent on the parasitic and pathogenic fitness of the resistant members of the population ( Cox et al., 2007 ; Bardas et al., 2008 ) Fitness is defined as the survival and reproductive success of an allele, individual, or group ( Pringle and Taylor, 2002 ) The use of fungicides on a plant pathogen population can generate a selective pressure for resistant isolates, in a fungicide treated environment, if there is an appropriate level of resistance variation in the population ( Peever and Milgroom, 1994 ) Under thi s scenario, resistant isolates will be selected and the population frequency will increase in subsequent generations, leading to fungicide control failure over time. Cases of field resistance, especially to quinone outside inhibitors (QoI), have been widel y documented ( FRAC, 2013b ) since the first report in Blumeria graminis f. sp. tritici in Germany after two years of QoI use, suggesting that resistance and stability were not associated with fitness cost ( Bartlett et al., 2002 ) Even though mos t of the mathematical models used in theoretical studies of fungicide resistance assume a fitness cost associated with resistance ( van den Bosch and Gilligan, 2008 ) fitness penalties in resistant isolates seem to be dependent on the pathogen and possibly on the mode of action of the fungicide. For example, methyl benzimidazole carbamate (MBC) resistant isolates are as fit as sensitive isolates in many fungal species ( Penrose et al., 1979 ; Schepp and Kng, 1981 ; Chen et al., 2007 ) Similarly, mefenoxam resistant isolates of Phytophthora erythroseptica ( Chapara et al., 2011 ) and anili nopyrimidine resistant isolates of Botrytis cinerea did not differ in aggressiveness from sensitive isolates ( Bardas et al., 2008 ) In contrast, the

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89 sclerotia of dicarboximide resistant isolates of B. cinerea were less viable and had less sporulation than sensitive isolates ( Raposo et al., 2000 ) Also, dicarboximide resistant isolates of Monilinia fructicola produced smaller lesions and sporulated less on peach fruit than sensitive isolates ( Ritchie, 1983 ) In some studies, fitness components w ere evaluated with resistant isolates generated in the laboratory to assess the risk for fungicide resistance ( Brent and Hollomon, 2007a ) Although fitness parameters of laboratory generated mutants can be used to make estimates, it is unknown if labo ratory induced resistant mutants are representative of those found in the field. Furthermore, laboratory resistant mutants could incorporate several mutations, produced by the mutagenesis process, which could potentially mask the real impact of the target mutant allele ( Brent and Hollomon, 2007a ) Therefore, the study of fitness of fungicide resistant isolates should be done using field resistant isolates when possible. Resistance stability is also an important element for estimation and prediction of resistance risks. Therefore, it has been studied in multiple pathogens under different selection pressure environments. Resistance stability could be defined as the ability of the pathogen to retain the same level of fungicide insensitivity after successiv e generation of either exposure or no exposure to the target fungicide ( Brent and Hollomon, 2007a ) Instability of resistance to demethylation inhibitor (DMI) fungicides has been reported in Cercospora beticola ( Karaoglanidis and Thanassoulopoulos, 2002 ) Venturia inaequalis ( Kller et al., 1991 ) and M. fruti cola ( Cox et al., 2007 ) It was shown that some environmental factors, such as cold, may exacerbate the instability. In those cases, the frequency and the levels of change in DMI sensitivity were commonly observed in isolates with moderate to high levels of resistance. For QoI fungicides, resistance stability has been detected in some field and laboratory mutants after many consecutive propagations ( Chin et al., 2001 ; Avila Adame and Kller, 2003a ; Malandrakis

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90 et al., 2006 ; Kim and Xiao, 2011 ) However, a reduction in QoI resistance, or a complete loss of resistance, has been also detected in field and laboratory mutants ( Zheng et al., 2000 ; Ziogas et al., 2002 ; Miguez et al., 2004 ; Markoglou et al., 2006 ; Ishii et al. 2007 ) Because generalizations about QoI resistance stability cannot be mad e, it should be evaluated individually for each fungus using field resistant isolates. Alternaria alternata (Fr.) Keissl. causes Alternaria brown spot (ABS) of tangerines ( Citrus reticulata Blanco) and their hybrids, which is the most important foliar fung al disease of tangerines in Florida. ABS management has been largely dependent on the use of fungicides, especially the QoIs. Due to the specific mode of action of QoIs, blocking electron transport by binding to the Qo site of the mitochondrial cytochrome bc 1 complex, the risk for development resistance is high ( Bartlett et al., 2002 ) Multiple cases of QoI resistance, including A. alternata from tangerines, hav e been reported ( FRAC, 2013b ) A high frequency of QoI resistant isolates was found in the most important tangerine producing counties in Florida ( Vega and Dewdney, 2014 ) suggesting that QoI resistance in A. alternata populations may not be associated with a fitness cost. Currently, little is known about the fitness components and stability of QoI resistance in the tangerine pathotype of A. alternata Since QoIs are still important tools for ABS management, the study of stability and f itness of QoI resistant isolates merits investigation. Materials and Methods Fungal I solates Ten QoI resistant and ten sensitive monoconidial isolates of A. alternata were used in this study (Table 4 1). The isolates were collected from tangerine and tang erine hybrid orchards in Florida for a study conducted from 2008 2012 to determine the fungicide sensitivity of A. alternata isolates to azoxystrobin and pyraclostrobin ( Vega and Dewdney, 2014 ) The effecti ve

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91 concentrations needed to reduce the fungal growth by 50% (EC 50 values) were determined using the resazurin based microtiter assay, according to a previously described procedure ( Vega et al., 2012 ) Details on isolate sensitivity to azoxystrobin and pyraclostrobin and host of isolation are given (Table 4 1). Isolates were maintained for long term storage on sterile filter paper at 20 o C, as previously described ( Peever et al., 1999 ) DNA E xtraction and M olecular D etection of the G143A M utation Genomic DNA w as extracted from 3 day old mycelia cultured on PDA overlaid with cellophane sheets following previously described procedures ( Vega and Dewdney, 2014 ) The cytochrome b gene of A. alternata isolates was par CTA TGG ATC TTA CAG AGC AC GTA TGT AAC CGT CTC CGT C described ( Vega and Dewdney, 2014 ) PCR products were purified and digested with the restriction enzyme Fnu 4HI to identify the sequence GCTGC at codon 143 and 144 of the cytochrome b gene only observed in resistant isolates ( Vega and Dewdney, 2014 ) Restriction fragments were separated and visualized by electrophoresis in a 1.6% agarose gel. Phenotypic S tability of QoI R e sistant and S ensitive I solates To measure the stability of resistance, QoI sensitive and resistant isolates were subcultured on fungicide free potato dextrose agar (PDA; Becton Dickinson, Sparks, MD). Isolates were initially transferred from stock cultures on sterile filter paper to PDA to obtain act ively growing cultures. Mycelial plugs from the margin of actively growing colonies were transferred to fresh PDA and incubated for 5 days at 24 o C to be used as the starting material. Isolates were subcultured every 7 days by transferring a 5 mm mycelial p lug onto fresh PDA plates and incubated at the conditions described above for a total of 10 times. The sensitivity to azoxystrobin and pyraclostrobin was tested at the initial and final generation of each isolate,

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92 using the resazurin based microtiter assay ( Vega et al., 2012 ) Briefly, technical grade azoxystrobin (Syngenta Crop Protection, Greensboro, NC) an d pyraclostrobin (BASF Corp., Research Triangle Park, NC) were dissolved in acetone at 10 mg/ml (active ingredient) and serially diluted 10 fold. The final concentrations evaluated of azoxystrobin or pyraclostrobin were 0, 0.001, 0.01, 0.05, 0.1, 0.5, 1 or 10 g/ml; and 0, 0.001, 0.005, 0.01, 0.05, 0.1, 1, or 10 g/ml, respectively. The experiment was performed twice. Sapro phytic F itness C omponents The following fitness components were evaluated in vitro for ten QoI resistant and ten sensitive A. alternata isolates: (i) mycelial growth on PDA, (ii) conidial production on V 8 agar, and (iii) germination on water agar. All the experiments were performed twice. Mycelial growth Isolates were retrieved from stock cultures as mentioned above. After 5 days of growth, mycelial plugs (5 mm diameter) were transferred from the margin of actively growing cultures to the center of fresh PDA plates. The plates were incubated at 24 o C for 7 days in the dark and then the colony diameters were measured at two perpendicula r points. For each isolate, four replicate plates were used. Conidial production Mycelial plugs were transferred from 5 day old PDA cultures to the center of clarified V8 agar (100 ml of centrifuged V8 juice, 20 g agar and 10 g CaCO 3 /L) plates. Plates were incubated for 7 days at room temperature (approximately 22 o C) under cool white fluorescent light. Conidia were harvested by flooding each plate with 15 ml of sterile deionized water, gently rubbing the surface, and filtering through three layers of steril e cheesecloth. Conidial concentration was estimated with a hematocymeter and expressed as the number of conidia per

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93 mm 2 of the colonized medium. Four replicate plates were used for each isolate, and four droplets (10 l) of the conidial suspension were cou nted per plate. Conidial germination After the measurement of conidial production, a 10 l aliquot of the conidial suspension (1 10 5 conidia/ml) was deposited onto the surface of 2% water agar coated glass slides, placed into individual petri dishes with moistened filter paper, and incubated at 24 o C for 18 h. Germination was quantified by counting 100 conidia per slide on four replicate slides per isolate. A conidium was considered germinated if the germ tube was at least the length of the conidium, if an appressorium was present, or if multiple germ tubes were observed. Pathogenic F itness C omponents Incubation period (the time from inoculation to initial symptom appearance), the number of lesions per cm 2 of leaf, and the virulence of five QoI sensitive and five resistant isolates were in vitro detached leaf assay. For each fungal isolate, ten replicate leaves of each cultivar were sprayed with 2 10 4 conidia/ml using a chromatography sprayer (TLC Crown North American Professional Products, Woodstock, IL) as previously described ( Canihos et al., 1999 ) Inoculated leaves were placed in racks inside a clean humid chamber and incubated at room temperature (ap proximately 22 o C). Leaves were monitored every hour (after the first 12 h post inoculation) for the appearance of brown spot symptoms. Mean incubation period for each isolate was calculated based on observations of 10 leaves per cultivar. Two days after in oculation, the number of lesions per leaf was counted and isolate virulence was determined by rating the leaf area covered by lesions on a scale of 1 to 3; where 1 = < 25% leaf area diseased, 2 = between 25 to 50% leaf area diseased, and 3 = > 50% leaf are a diseased. Leaf area was assessed by scanning individual leaves in a JPEG file format

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94 using a flatbed scanner with 7000 dpi 5100 dpi (Epson, Long Beach, CA). The image was converted into binary form via 8 bit gray scale image before analysis. JPEG image files were loaded into the ImageJ platform (National Institute of Health, USA, http://rsbweb.nih.gov/ij ) for digital image analysis to determine the leaf area. Data were expressed as the number of lesions per cm 2 o f leaf. The e xperiment was performed twice. Efficacy of A zoxystrobin for C ontrol of ABS C aused by QoI S e nsitive and R esistant I solates Potted 2 year evaluate the protective activity of a zoxystrobin for ABS control using five QoI sensitive and five resistant isolates. Plants were grown in 3.4 liter containers in the greenhou se to a height of 0.75 to 1.0 m. Prior to the initiation of the experiments, plants were pruned to produce new flush of uniform size and age. One day prior to inoculation (3 to 6 weeks after pruning), azoxystrobin as Abound (Syngenta Crop Protection) or water as a control were applied. Abound was applied at the full rate recommended by the manufacturer for ABS control (242 mg a.i./liter). Plants were sprayed to run off using a hand pump sprayer. Three single plant replications were used for each treatment. The experiment was performed twice. One day after fungicide or water applications, plants were individually inocul ated with a conidial suspension (1 10 5 conidia/ml) of five selected QoI resistant or sensitive isolate each isolate per plant Inoculum was produced as described above. Inoculations were conducted by spraying the new flush to run off with conidial susp ensions using a chromatography sprayer (TLC Crown). Plants were covered with pre moistened plastic bags and placed in a mist bed in the greenhouse at ambient temperature (20 to 30 o C) and light conditions. The bags were misted for 20 s every 5 min to keep t he plants and bags moist for 16 to 20 h, then the plants were placed on greenhouse benches for symptom development. Five days after inoculation, the number of

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95 lesions per leaf was counted on 20 leaves of each replicate plant and the mean number of lesions per leaf was calculated for each isolate. Statistical A nalysis The EC 50 values for azoxystrobin and pyraclostrobin were calculated using either sigmoidal or exponential decay functions by plotting the percent resazurin reduction relative to the control ag ainst the log 10 transformed fungicide concentration with SigmaPlot (ver. 11.0; Systat Software Inc., San Jose, CA). For the stability experiment, a two t test was performed using PROC TTEST (ver. 9.3; SAS Institute, Cary, NC) to determine differences between the initial and final EC 50 values of each isolate evaluated. Data for each fitness component were subjected to analysis of variance (ANOVA) using PROC GLM (SAS), except for virulence, for which the nonparametric Kruskal Wallis H test wa s performed using PROC NPAR1WAY (SAS). The homogeneity of variance was analyzed using the ratio of variance of two independent experiments prior to pooling the experiments. Mean values of each isolate nificance test, whereas mean values among phenotype groups were compared by two sample t test. Percentage data were arcsine square root transformed, whereas the number of lesions per leaf was square root transformed prior to analysis. Correlation coefficients between mean fitness components and the EC 50 log 10 transformed values were estimated by calculating a Pearson correlation coefficient using PROC REG and PROC CORR (SAS). Isolates with EC 50 values higher than 10 g/ml were not included in the c orrelation and regression analyses. Results QoI S ensitivity and D etection of the G143A M utation The mean EC 50 value of ten QoI sensitive isolates for azoxystobin and pyraclostrobin was significantly different ( t = 37.77; P < 0.0001 and t = 42.04; P < 0.000 1, respectively) from

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96 the mean EC 50 value of ten QoI resistant isolates. In general, isolates were more sensitive to pyraclostrobin than azoxystrobin, as previously reported ( Vega and Dewdney, 2014 ) The EC 50 values for sensitive isolates ranged from 0.015 to 0.236 g/ml for azoxystrobin and from 0.005 to 0.041 g/ml for pyraclostrobin (Table 4 1). Resistant isolates had EC 50 values higher than 10 g/ml for azoxystrobin, whereas EC 50 values of the same group of isolates for pyraclostrobin ranged from 2.0 to 6.3 g/ml (Table 4 1). Using the PCR restriction fragment length polymorphism (RFLP), the point mutation of glycine (GGT) to alanine (GCT) at amino acid 143 (G143A) was identified exclusively in resistant isolates. Between sensitive and resistant isolates, the proportion of isolates carrying the cytochrome b 2 = 8.5714; P = 0.0034), as previously reported ( Vega an d Dewdney, 2014 ) All sensitive isolates belonged to cytochrome b profile I; whereas, four and six resistant isolates belonged to cytochrome b profile I and profile II, respectively (Table 4 1). Stability of R esistance Isolates of both QoI sensitive and resistant phenotypes maintained their initial azoxystrobin and pyraclostrobin sensitivity levels after ten consecutive transfers on PDA with few exceptions (Table 4 1). Isolates G31 R2 L1 and G40 R7 F2 showed a slight increase in the EC 50 value of azoxys trobin after 10 consecutive transfers on artificial media. Despite the marginal decrease in azoxystrobin sensitivity, these two isolates remained QoI sensitive. None of the QoI resistant isolates became sensitive after 10 consecutive transfers on PDA. Sapr ophytic F itness Three saprophytic fitness components were evaluated in vitro for a representative group of QoI sensitive and resistant isolates. Great variability among isolates within the same

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97 sensitivity group was found in mycelial growth, conidial prod uction and conidial germination (Table 4 2). The mean mycelial growth of both sensitivity groups were not significantly different ( P = 0.5375). In the sensitive group, the mycelial growth ranged from 29.9 to 69.4 mm with a mean of 47.7 mm; whereas in the resistant group, the mycelial growth ranged from 29.9 to 60.9 mm with a mean of 48.8 mm (Table 4 2). Similarly, mean conidial production for the sensitive group, which was 2.1 10 3 conidia/mm 2 of medium, was not significantly different ( P = 0.6462) from that of the resistant group, which was 2.2 10 3 conidia/mm 2 of medium (Table 4 2). For conidial germination, no significant differences ( P = 0.3769) were detected between the sensitivity groups. In general, isolates showed a conidial germination percentag e higher than 80% with few exceptions (Table 4 2). Isolate G40 R7 F2 had a significantly lower conidial germination percentage than other isolates. Pathogenic F itness Incubation period, disease virulence, and number of lesions per leaf area were evaluated in four citrus cultivars inoculated with five QoI sensitive and five resistant isolates (Fig 4 1) The mean incubation period for cultivars Minneola (15.0 h) and Dancy (15.2 h) were significantly shorter ( P < 0.0001) than that for cultivars Murcott (17.4 h) and Sunburst (16.2 h). Within cultivars, no significant differences for incubation period were detected between sensitivity groups ( data not shown ). The mean number of lesions per cm 2 of leaf was not significantly different between sensitivity groups f or cultivars Dancy ( P = 0.4089 ; Table 4 3 ), Minneola ( P = 0.5589 ; Table 4 4 ), and Murcott ( P = 0.9072 ; Table 4 5 per cm 2 of leaf was significantly higher ( P = 0.0012) for resistant isolates (15.6 lesion/ cm 2 ) than for sensitive isolates (11.9 lesion/cm 2 ) (Table 4 6 ). In general, the number of lesions observed in

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98 P < 0.0001) than in the other cultivars. Cultivars Minneola and Dancy did not show significant differences betw een them in the number of lesions with means of 15.8 and 15.1 lesion/cm 2 respectively ( P = 0.3321). Virulence was significantly higher ( P < 0.05) for the resistant group than for the sensitive group in cultivars Dancy (Table 4 3) Minneola (Table 4 4) and Sunburst (Table 4 6) but was not significantly different ( P 5 ). Within cultivars, slight variability in virulence among isolates within the same sensitivity group was detected (Table 4 3 to Table 4 6 ). Correlation between F itness and R esistance Correlation coefficients between fitness components and sensitivity to azoxystrobin and pyraclostrobin were estimated. For all fitness components including mycelial growth (Fig. 4 2 A), conidial production (Fig. 4 2 B), conidial germination (Fig. 4 2 C), incubation time (Fig. 4 2 D), disease severity (Fig. 4 2 E), and number of lesions (Fig. 4 2 F), the correlation coefficients were not significantly different from 0 ( P > 0.05), indicating that no relationship existed between the level of sensitivity to azoxystrobin or pyraclostrobin and the respective fitness components. Efficacy of A zoxyst robin in G reenhouse E xperiments Greenhouse inoculation experiments demonstrated tha t azoxystrobin ( Abound ) applied at full rate one day before inoculation, using five QoI resistant and five sensitive isolates, significantly reduced ( P < 0.0001) the number of lesions produced by sensitive isolates than to the nonsprayed control (Fig. 4 3 ). On the other hand, the number of lesions observed on plants previously exposed to azoxystrobin and inoculated with resistant isolates was not significantly reduced ( P = 0.0651) compared to the unsprayed control (Fig. 4 3 ). The efficacy of azoxystrobin in controlling disease caused by those resistant isolates was significantly lower than that caused by sensitive isolates.

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99 Discussion The recent discovery of mixed QoI resistant and sensitive isolates in tangerine infecting A. alternata populations in Flor ida, as well as the dominance of resistant isolates in many citrus orchards, causing field resistance, increases the concern about the continued use of QoI fungicides in the tangerine industry. It is imperative to implement resistance management strategies in the Florida tangerine industry to delay the selection of QoI resistant isolates in locations where resistance has not been identified yet, as well as to reduce the proportion of resistance in populations where resistant isolates are present. Informatio n about the biological and ecological fitness components of QoI resistant isolates, reported in this study, will help provide the basis for the development of such resistance management strategies. In our study, the phenotypic stability of QoI resistant A. alternata isolates was investigated using artificial medium in the absence of QoI selection pressure. After 10 consecutive transfers, none of the resistant isolates had a reduction or loss of resistance, indicating that QoI resistance in the A. alternata tangerine pathotype is stable. This stability suggests that the dominance of QoI resistant populations, observed in the most important tangerine producing counties in Florida ( Vega and Dewdney, 2014 ) was n ot a temporary adaptation of the pathogen to the fungicide that could be lost in the absence of selection pressure, but rather be a long term threat for the tangerine industry. A similar resistance stability was also observed in other pathosystems in field and laboratory mutants of Magnaporthe grisea ( Avila Adame and Kller, 2003a ) B. cinerea ( Kim and Xiao, 2011 ) C beticola ( Malandrakis et al., 2006 ) and Erysi phe graminis ( Chin et al., 2001 ) However, a reduction in the resistance levels, or a complete loss of QoI resistance, following consecutive transfers using in vitro or in vivo tests, has been observed in field isolates of Plasmopara viticola ( Genet et al., 2006 ) Corynespora cassiicola Mycovellosiella nattrassii Colletotrichum gloeosporioides ( Ishii et al.,

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100 2007 ) and Mycosphaerella graminicola ( Miguez et al., 2004 ) as well as in laboratory mutants of B. cinerea ( Markoglou et al., 2006 ) Ustilago maydis ( Ziogas et al., 2002 ) and V. inaequalis ( Zheng et al., 2000 ) In some of these cases, resistance instability was attributed to the presence of a heteroplasmic state in the mitochondrial cytochrome b ; where, mitochondria containing both mutant and wild type alleles reverted to the wild type cytochrome b at very high frequency, during growth on fungicide free media ( Zheng et al., 2000 ; Ishii et al., 2007 ) Resistance to QoI fungicides associated with the G143A mutation affect the structure of the Qo site and in turn might decrease the activity of the cytochrome bc 1 complex, influencing the fitness o f pathogens differentially ( Fisher et al., 2004 ; Fisher and Meunier, 2008 ) In fact, laboratory mutants of B. cinerea and C. beticola resistant to Qo Is exhibited a significant fitness reduction compared to the wild type parental isolates ( Malandrakis et al., 2006 ; Markoglou et al., 2006 ) However, those differences could be attributed to the impact of several mutations, in different metabolic pathways, produced by the mutagenesis process instead of a pleiotropic effect of the G143A mutation. Our study shows that QoI resistant A. alternata isolates did not develop any significant vegetative or reproductive fitness penalties, based on the saprophytic fitness components evaluated. The group of resistant isolates tested in this study showed similar mycelial growth, conidial production, and co nidial germination to isolates in the sensitive group. However, within each sensitivity group, great variation was found between isolates for each fitness component studied, suggesting that the variability observed could be attributed to the genetic backgr ound of individual isolates within the sensitivity group rather than to the fitness cost, given the fact that there is a great genetic variability among tangerine infecting A. alternata isolates, as previously reported ( Peever et al., 2002 ; Peever et al., 2004 ; Stewart et al., 2013 ) Moreover, our results

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101 were similar to those reported on field QoI resistant isolates of B. cinerea from apple ( Kim and Xiao, 2011 ) and A. alternata from pistachio ( Karaoglanidis et al., 2011 ) where no differences in any saprophytic fitness components were found between resistant and sensitive isolates. Similarly, our results showed that some pathogenic fitness components, such as lat ent period and number of lesions per leaf area, did not suffer any fitness penalty from being QoI resistant. Resistant isolates were more aggressive than sensitive isolates on the highly susceptible cultivars, such as Dancy and Minneola. However, for the l east susceptible cultivar evaluated in this study, Murcott tangor, there was no difference in virulence levels between resistant and sensitive isolates. This could have been caused by the long incubation time and the low rate of disease symptom expansion o bserved in Murcott, but also because Murcott is heterozygous for the locus responsible for ABS susceptibility, whereas Minneola and Dancy are homozygous ( Cuenca et al., 2013 ) It is known that cultivars with the homozygous ABSr loci (associated with susceptibility to ABS) are more susceptible to the ACT toxin than are the heterozygotes ( Tsuge et al., 2013 ) Great disease severity in Alternaria spp. has been found in QoI resistant isolates carrying both the G143A ( Karaoglanidis et al., 2011 ) and the F129L mutations ( Pasche and Gudmestad, 2008 ) demonstrating that aggressiveness is independent of the G143A mutation. In A. alternata tangerine pathotype, the main virulence and pathogenicity factors are dependent on the production of the ACT toxin ( Kohmoto et al., 1979 ; Kohmoto et al., 1991 ; Kohmoto et al., 1993 ) The genes responsible for ACT toxin production are tightly clustered and located on a small chromosome called the conditional dispensable chromosome ( Akamatsu et al., 1999 ; Masunaka et al., 2000 ; Hatta et al., 2002 ) Multiple copies of the genes responsible for ACT toxin production are present on this chromosome ( Miyamoto et al., 2008 ; Miyamoto et al.,

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102 2009b ; Ajiro et al., 2010 ) ; therefore, highly virulent isolates might have more copies of the genes controlling the toxin production than low virule nce isolates ( Akimitsu et al., 2003 ) In fact, a dose response study revealed that toxin concentrations as low as 2 10 8 M caused brown veinal necrosis w ith a rapid loss of electrolytes from host cells of susceptible leaves ( Kohmoto et al., 1993 ) The higher virulence observed in res istant isolates suggest that in the field, where those isolates were exposed to QoIs, a possible selection of QoI resistant isolates with high fitness (expressed as isolates with higher number of copies of the ACT toxin production genes) could have occurre d, as previously reported ( Uyenoyama, 1986 ) Correlation analysis is one of the most powerful tools used to estimate fitness cost associated with fungicide resistance. In a previous study ( Peever and Milgroom, 1993 ) the cross resistance to five DMIs in Pyrenophora teres isolates was estimated using component correlation analyses, which involves the use of analysis of variance and covariance by p artitioning variation and covariation into different categories. It was found that correlation coefficients calculated with component correlation were similar to those generated by the Pearson correlation coefficient, which involves the mean of fungicide r esistance phenotype, expressed as an EC 50 value or growth inhibition response, and the mean of fitness components ( Peever and Milgroom, 1994 ) Therefore, in the present study, we estimated the correlations between phenotypic sensitivities to QoI fungicides and mean fitness component s by calculating Pearson correlation coefficients. This approach was previously used successfully to estimate the correlation between fitness components and resistance to DMIs ( Karaoglanidis et al., 2001 ) anilinopyrimidines (AP) ( Bardas et al., 2008 ) succinate dehydrogenase inhibitors (SDHI), and QoIs ( Kim and Xiao, 2011 ) Our study showed no evidence of fitness costs associated with resistance to azoxystrobin and pyraclostrobin. Moreover, the correlation coefficient values between sensit ivity to QoIs and

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103 any saprophytic or pathogenic fitness components showed no significant correlation. The absence of fitness cost associated with QoI resistance in the tangerine infecting A. alternata populations could explain the rapid emergence of QoI re sistance in the field. Regardless of the stability and competitive ability of QoI resistant isolates, permanent monitoring programs to determine the sensitivity of populations are required to track any changes in the resistance frequency around the state. To evaluate the protective effect of Abound against QoI sensitive and resistant isolates, immature leaves of young citrus trees were inoculated one day after the fungicide application. As expected, Abound was only able to control ABS caused by sensitive isolates showing that, under optimal conditions for disease development, QoI fungicides were not effective for control of ABS caused by resistant isolates. QoI resistance associated with the G143A mutation may cause complete control failure in a relativel y short period of time ( Fisher and Meunier, 2008 ) especially when the resistant isolates dominate the population. In the case of tangerine infecting A. alternata growers have observed QoI control failure when the proportion of resistance in the population exceeded 60% ( Vega and Dewdney, 2014 ) The lack of disease control caused by resistant isolates was also reported in other pathosystems where qualitative resistance was detected using different fungicide groups. In Alternaria that infects pistachio, boscalid failed to control disease caused by resistant isolates ( Avenot and Michailides, 2007 ) Similarly, the AP cyprodinil w as only effective in controlling gray mold of strawberry caused by sensitive isolates of B. cinerea ( Fernndez Ortuo et al., 2013 ) In barley plants treated with carboxin, the percentage infection was significantly higher in plants inoculated with resistant isolates o f Ustilago nuda than in plants inoculated with sensitive isolates ( Newcombe and Thomas, 2000 )

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104 The evidence presented in this study about the stability of QoI resistant A. alternata isolates from tangerine, the higher aggressiveness of resistant isolates, as well as the lack of fitness costs associated with resistance has important implications for disease management. Some strat egies, such as the rotation of fungicides with different modes of action, the management of application doses, or the use of fungicide mixtures, have been proposed to prevent or delay the problems associated with fungicide resistance ( Peever and Milgroom, 1995 ; van den Bosch et al., 2011 ) Due to th e widespread and high frequency of QoI resistance in tangerine infecting Alternaria populations in Florida, the use of QoIs in mixtures and in rotation with protectant fungicides, such as copper and ferbam, could reduce the selection of the resistant allel es. Recently, new fungicides (difenoconazole and boscalid) in mixtures with QoIs were registered and should be incorporated to disease management programs. However, studies of baseline sensitivities for those new active ingredients are necessary to monitor resistance development. Finally, further research is required to investigate the competitive ability of resistant isolates mixed in different proportions with sensitive isolates under experimental conditions.

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105 Table 4 1. Molecular characterization and changes of azoxystrobin and pyraclostrobin sensitivities of Alternaria alternata isolates after ten consecutive subculture cycles on fungicid e free potato dextrose agar (PDA) Isolate Host a Type b cyt b gene profile c EC 50 (g/ml) of azoxystrobin EC 50 (g/ml) of pyraclostrobin Initial Final P d Initial Final P d G6 R3 L1 Minneola tangelo S I 0.043 0.048 0.886 0.007 0.007 0.747 G6 R10 F2 Murcott tangor R II > 10 > 10 2.205 2.415 0.684 G7 R7 L2 1S Murcott tangor S I 0.025 0.029 0.567 0.012 0.011 0.471 G10 R7 F4 1S Sunburst tangerine S I 0.034 0.035 0.837 0.005 0.005 0.698 G11 R10 L3 Dancy mandarin R I > 10 > 10 2.029 2.779 0.616 G14 L11 1S Murcott tangor R II > 10 > 10 4.553 4.369 0.551 G19 R5 L1 Minneola tangelo R II > 10 > 10 3.414 4.097 0.717 G22 R28 F1 Sunburst tangerine R II > 10 > 10 3.308 3.840 0.328 G27 B3T L2 Sunburst tangerine S I 0.236 0.267 0.866 0.031 0.038 0.555 G28 R14 L1 1S Sunburst tangerine R II > 10 > 10 6.273 6.079 0.893 G29 R9 F1 1S Orlando tangelo S I 0.087 0.096 0.659 0.022 0.021 0.256 G31 R2 L1 Murcott tangor S I 0.015 0.019 0.035 0.005 0.006 0.445 G34 R4 F5 Minneola tangelo R II > 10 > 10 2.049 2.277 0.861 G37 R5 L1 1S Orlando tangelo S I 0.100 0.082 0.484 0.041 0.038 0.729 G39 R9 L2 1S Orlando tangelo R I > 10 > 10 3.612 3.744 0.630 G40 F5 1S Dancy mandarin R I > 10 > 10 5.488 5.459 0.946 G40 R7 F2 Dancy mandarin S I 0.076 0.097 0.027 0.012 0.012 0.942 G42 R6 3 L2 Minneola tangelo S I 0.097 0.117 0.736 0.010 0.010 0.745 G45 R12 L1 1S Lee citrus hybrid R I > 10 > 10 4.603 4.249 0.523 G45 R13 F1 1S Lee citrus hybrid S I 0.038 0.034 0.755 0.019 0.017 0.511 a Tangelo = Citrus paradisi C. reticulata tangor = C. reticulata C. sinensis tangerine or mandarin = Citrus reticulata citrus hybrid = C. reticulata tangelo b S = sensitive and R = resistant c cyt b profile I contains one intron ( amino acid position F164 ), and cyt b profile II contains two introns ( amino acid positions A126 and F164 ) d The two sample t test was performed to determine if the differences in sensitivity between the initial generation and the tenth transfer in PDA

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106 Table 4 2 Saprophytic fitness components of quinone outside inhibitor sensitive and resistant isolates of Alternaria alternata a Isolate In vitro fitness components Mycelial growth (mm) Conidia production (10 3 /mm 2 ) Conidia germination (%) Sensitive G6 R3 L1 44.9 ef 1.45 efgh 91.3 abcdefg G7 R7 L2 1S 48.7 de 3.19 abcd 95.4 abc G10 R7 F4 1S 38.1 g 0.05 h 93.8 abcd G27 B3T L2 41.9 fg 2.80 abcde 88.8 cdefg G29 R9 F1 1S 29.9 h 1.44 efgh 95.9 abc G31 R2 L1 69.4 a 3.39 abc 76.3 gh G37 R5 L1 1S 54.6 cd 2.55 abcdef 96.1 abc G40 R7 F2 51.1 de 4.03 a 62.6 h G42 R6 3 L2 62.1 b 1.09 fgh 92.8 abcdef G45 R13 F1 1S 36.8 g 1.26 fgh 96.5 abcd Mean 47.7 A 2.12 A 82.4 A Resistant G6 R10 F2 47.8 ef 2.00 cdefg 89.0 cdefg G11 R10 L3 60.9 bc 3.23 abcd 85.4 defg G14 L11 1S 50.1 de 2.01 cdefg 97.4 abc G19 R5 L1 49.6 de 2.08 bcdefg 83.0 fgh G22 R28 F1 59.1 bc 0.95 gh 90.6 bcdefg G28 R14 L1 1S 29.9 h 2.36 bcdefg 95. 0 abcde G34 R4 F5 46.7 ef 1.76 defg 83.9 efg G39 R9 L2 1S 47.4 ef 3.60 ab 98.6 a G40 F5 1S 47. 2 ef 1.84 defg 93.4 abcdef G45 R12 L1 1S 48.4 def 2.34 bcdefg 98.2 ab Mean 48.8 A 2.22 A 86.4 A a Means of individual isolates designated by the same lowercase letter within groups are not significantly different Mean values of groups within columns designated by the same uppercase letter are not significantly different according to t

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107 Table 4 3 Pathogenic fitness components of quinone outside inhib itor sensitive and resistant isolates of Alternaria alternata in cultivar Dancy using detached leaves a Isolate Incubation period (h) Lesions b Virulence c Sensitive G6 R3 L1 15.7 10.4 d 1.3 d G27 B3T L2 15.2 16.5 abc 1.3 d G31 R2 L1 15.3 20.3 a 1.5 cd G40 R7 F2 15.1 14.2 bcd 2.0 ab G42 R6 3 L2 15.0 12.6 cd 2.0 ab Mean 15.3 A 14.8 A 1.6 B Resistant G6 R10 F2 15.1 18.9 ab 1.4 d G11 R10 L3 15.0 14.3 bcd 2.4 a G19 R5 L1 15.4 17.0 abc 2.0 ab G22 R28 F1 15.1 14.5 bcd 1.8 bc G34 R4 F5 15.2 12.6 cd 1.8 bc Mean 15.2 A 15.5 A 1.9 A a Means of individual isolates designated by the same lowercase letter within sensitivity groups Mean values between sensitivity groups designated by the same uppercase letter are not significantly different t Mean values for virulence designated by the same lowercase or uppercase letter within or between sensitivity groups, respectively, ar e not significantly different according to Krustal Wallis H b Number of lesions per cm 2 of leaf. c Virulence based on 3 scale index, where 1 = <25%, 2 = 25 to 50%, and 3 = >50% leaf area diseased.

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108 Table 4 4 Pathogenic fitness components of quinone outside inhibitor sensitive and resistant isolates of Alternaria alternata in cultivar Minneola using detached leaves a Isolate Incubation period (h) Lesions b Virulence c Sensitive G6 R3 L1 15.1 12. 1 b 1.3 e G27 B3T L2 15.1 14.2 ab 1.6 de G31 R2 L1 15.1 14.0 ab 1.7 cde G40 R7 F2 15.0 18.5 ab 1. 8 cd G42 R6 3 L2 15.0 18.7 ab 2.4 ab Mean 15.1 A 15. 5 A 1.7 B Resistant G6 R10 F2 15.1 13.6 ab 1.6 cde G11 R10 L3 15.0 20.2 a 1.9 bcd G19 R5 L1 15.0 15.0 ab 2.4 a G22 R28 F1 15.0 15.9 ab 1.6 cde G34 R4 F5 1 5.0 15.9 ab 2.1 abc Mean 15.0 A 16.1 A 2.0 A a Means of individual isolates designated by the same lowercase letter within sensitivity groups are not significantly different according Mean values between sensitivity groups designated by the same uppercase letter are not significantly different t Mean values for virulence designated by the same lowercase or uppercase le tter within or between sensitivity groups, respectively, are not significantly different according to Krustal Wallis H b Number of lesions per cm 2 of leaf. c Virulence based on 3 scale index, where 1 = <25%, 2 = 25 to 50%, a nd 3 = >50% lea f area diseased.

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109 Table 4 5 Pathogenic fitness components of quinone outside inhibitor sensitive and resistant isolates of Alternaria alternata in cultivar Murcott using detached leaves a Isolate Incubation period (h) Lesions b Virulence c Sensitive G6 R3 L1 20.0 a 7. 5 c 1.0 b G27 B3T L2 17.8 ab 8.9 c 1.0 b G31 R2 L1 18.6 ab 9.6 c 1.0 b G40 R7 F2 15.8 b 17.0 a 1.2 ab G42 R6 3 L2 15.6 b 16.2 a 1.3 ab Mean 17. 6 A 11.8 A 1. 1 A Resistant G6 R10 F2 18.7 ab 7.9 c 1.0 b G11 R10 L3 15.6 b 19.3 a 1.8 a G19 R5 L1 16.6 b 10.0 c 1.1 b G22 R28 F1 18. 2 ab 10. 7 bc 1.0 b G34 R4 F5 17.3 ab 10.7 bc 1.1 b Mean 17.3 A 11.7 A 1.2 A a Means of individual isolates designated by the same lowercase letter within sensitivity groups are not Mean values between sensitivity groups designated by the same uppercase letter are not significantly different t Mean values for virulence designated by the same lowercase or uppercase letter within or between sensitivity groups, respectively, are not significantly different according to Krustal Wallis H b Number of lesions per cm 2 of leaf. c Virulence based on 3 scale index, where 1 = < 25%, 2 = 25 to 50%, a nd 3 = >50% leaf area diseased.

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110 Table 4 6 Pathogenic fitness components of quinone outside inhibitor sensitive and resistant isolates of Alternaria alternata in cultivar Sunburst using detached leaves a Isolate Incubation period (h) Lesions b Virulence c Sensitive G6 R3 L1 17.4 a 7.6 b 1.0 c G27 B3T L2 16.8 ab 10.6 ab 1.1 bc G31 R2 L1 17 .0 ab 13.1 ab 1.1 bc G40 R7 F2 15.3 b 15.4 ab 1. 2 abc G42 R6 3 L2 15.4 ab 12.8 ab 1.2 abc Mean 16.4 A 11.9 B 1.1 B Resistant G6 R10 F2 16.3 ab 17.7 a 1.2 abc G11 R10 L3 15.3 b 14.2 ab 1 .6 a G19 R5 L1 15. 8 ab 14.9 ab 1.4 ab G22 R28 F1 15.8 ab 14.1 ab 1.0 c G34 R4 F5 16.4 ab 17.1 a 1. 2 abc Mean 15.9 A 15.6 A 1.3 A a Means of individual isolates designated by the same lowercase letter within sensitivity groups Mean values between sensitivity groups designated by the same uppercase letter are not significantly different t t Mean values for virulence designated by the same lowercase or uppercase letter within or between sensitivity groups, respectively, are not significantly different according to Krustal Wallis H b Number of lesions per cm 2 o f leaf. c Virulence based on 3 scale index, where 1 = <25%, 2 = 25 to 50%, and 3 = >50% leaf area dis eased.

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111 Figure 4 3 Alternaria brown spot symptoms on detached leaves of cultivars Minneola (MN), Dancy (DAN), Murcott (MUR), and Sunburst (SUN) inoculated with conidia suspension (2 10 4 conidia/ml) from a representative quinone outside inhibitor sensitive isolate. Numbers of lesions per leaf were recorded 48 hours after inoculation.

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112 Figure 4 2. Correlation analysis between QoI sensitivity and fitness components. A) Correlation between the level of sensitivity to azoxystrobin and pyraclostrobin and mycelial growth, B) conidial production, C) conidial germination of Alternaria alter nata isolates, and D) incubation time, E) disease severity, and F) number of lesions caused by Alternaria alternata isolates. Filled circles represent pyraclostrobin whereas open circles represent azoxystrobin.

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113 Figure 4 inoculated with quinone outside inhibitor resistant and sensitive isolates of Alternaria alternata Black bars represent the nontreated water control whereas white ba rs represent azoxystrobin based (Abound ) treatment. Vertical bars are the mean and error bars are the standard error of the number of lesions per leaf.

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114 CHAPTER 5 SENSITIVITY OF Alternaria alternata FROM CITRUS TO BOSCALID AND POLYMORPHISM IN THE IRON SU LFUR AND IN THE ANCHORED MEMBRANES SUBUNITS OF SUCCINATE DEHYDROGENASE Introduction Over the last decade, quinone outside inhibitor (QoI) fungicides have become a key component for ABS management. However since 2008, QoI resistance has been detected at high frequencies in tangerine citrus orchards in Florida, increasing the concern in the tangerine industry ( Dewdney and Vega, 2012 ; Vega and Dewdney, 2014 ) Isolates recovered from orchards exposed to QoI fungicides, and with de monstrated control failure, were phenotypically and molecularly analyzed. As expected, the proportion of resistant isolates exceeded 50% of the total isolates analyzed in the state Moreover, the QoI resistant phenotype was associated to the amino acid sub stitution G143A in the cytochrome b ( Vega and Dewdney, 2014 ) Therefore, ABS control, via QoI fungicides, has been compromised during the last few years The fungicide boscalid, in a premixed formulation wi th the QoI pyraclostrobin, was registered in 2011 for use on citrus. This mixture is used particularly against ABS and melanose, caused by Diaporthe citri ( Dewdney, 2013a ; Dewdney, 2013b ) Boscalid is a broad spectrum fungicide belonging to the succinate dehydrogenase inhibitors (SDHI). It has been used against a broad range of plant pathogens belonging to the Ascomycete s and Deuteromycetes affecting fruits, nuts, ornamentals and vegetable crops ( Matheron and Porchas, 2004 ; Stammler and Speakman, 2006 ; Stammler et al., 2007 ; Stammler et al., 2008 ; Hu et al., 2011 ) Boscalid is biologically active against different stages of fungal development, such as spore germination, germ tube elongation, appresoria formation and mycelial growth ( Stammler et al., 2008 ) Currently, the SDHI group is divided into eight different chemical classes including 18 different compounds ( FRAC, 2013a ) SDHIs are sing le site fungicides that inhibit fungal

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115 respiration by binding the enzyme succinate:quinone oxidoreductase, also known as succinate dehydrogenase (SDH), in the mitochondrial complex II ( Avenot and Michailides, 2010 ; Sierotzki and Scalliet, 2013 ) This enzyme plays an important role in the Krebs cycle and the mitochondrial electron transport chain ( Cecchini, 2003 ; Yankovskaya et al., 2003 ) Single point mutations leading to amino acid substitutions of conserved residues in the SDH complex, confer resistance to SDHI fungicides. In A. alternata fr om pistachio, boscalid resistance has been associated with mutations in the Sdh B Sdh C and Sdh D genes. Polymorphism analysis of the SDHB protein in boscalid resistant isolates reveled the substitution of the highly conserved histidine residue, located in the third cysteine rich cluster, by either tyrosine (H277Y) or arginine (H277R) ( Avenot et al., 2008b ) Additionally, analysis of the SDHC and SDHD subunits of SDHI resistant isolates showed the substitution of histidine by arginine in SDHC (H134R) and in SDHD (H133R) subunits, both of them implicated in the heme b ligation, as well as a the substitution of aspartate by glutamic acid at position 123 (D123E) in SDHD ( Avenot et al., 2009 ) More recently, Miles et al. (2014) reported that, in addition to the mutations mentioned above, mutations T28A and A47 T in the SDHD subunit were also observed in some mod erately resistant isolates of A. solani. So far, more than 27 mutations conferring resistance to SDHIs have been reported in field and laboratory isolates of different plant pathogen s ( Sierotzki and Scalliet, 2013 ) Recently, different methods to measure the antifungal acti vity at different fungal stages have been proposed for testing sensitivity to SDHIs, such as a microtiter test ( Spiegel and Stammler, 2006 ; Stammler and Speakman, 2006 ) and a spiral gradient end point dilution method ( Miles et al., 201 4 ; Amiri et al., 2014 ) In addition to the standard techniques, such as fungicide amended agar plates, used to measure the inhibition of mycelial grow th or conidia germination

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116 the microtiter test could be used for a rapid phenotypic characterization using automated equipment that quantitatively measures the fungicide activity Although there are multiple benefi ts of using modern techniques for testing fungicide sensitivity, a standard protocol for boscalid has not been established yet due to the complex responses of many fungi exposed to the fungicide. Indeed, for some fungi the most critical stage for testing b oscalid is the spore germination and germ tube elongation ( Spiegel and Stammler, 2006 ; Leroux, 2010 ) whereas for others the most sensitive stage is the mycelial growth ( Avenot and Michailides, 2007 ; Avenot et al., 2012 ) Boscalid has a different mode of acti on than other fungicides currently used for ABS control, and could play a significant role in disease management programs. However, A. alternata represents a classical high risk pathogen for fungicide resistance development, especially for single site fung icides, such as QoIs ( Vega and Dewdney, 2014 ) and SDHIs ( Avenot and Michailides, 2007 ) Therefore the main objective of the present study was to determine the sensitivity level to boscalid of A. alternata isolates obtained from commercial citrus orchards in Florida Materials and Methods Fungal C ollection All of the A. alternata isolates used in this study were recovered from leaves and fruits of tangerine and tangerine hybrids showing ABS symptoms for a study to determine the distribution of resistance to QoI fungicides in Florida from 2008 to 2012 ( Vega and Dewdney, 2014 ) These isolates were collected and stored at 20 o C as monoconidial cultures Additionally, 39 isolates collected from 1996 to 1997 were also included in this study. Isolates were initiall y transferred from stock cultures on sterile filter paper to potato dextrose agar (PDA) to obtain actively growing cultures.

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117 Details on the isolation procedure and pathogenicity tests have been previously described ( Vega and Dewdney, 2014 ) Isolate virulence was determined by rating the leaf area covered by lesions (48 to 72 h after inoculation) on a scale of 1 to 3, as previously described ( Vega and Dewdney, 2 014 ) A. alternata S ensitivity to B oscalid B ased on M ycelial G rowth I nhibitio n with Di fferent C ulture M edi a The effect of boscalid on mycelial growth of 16 isolates (Table 5 1) was evaluated using three agar based media: PDA ( Becton Dickinson, Sparks, MD ; Fig. 5 1A ), complete medium (CM; Bennett and Lasure, 1991 ; Fig. 5 1B ), and minimal medium (MM; Bennett and Lasure, 1991 ; Fig. 5 1C ). Technical grade boscalid (B ASF Corp., Research Triangle Park, NC) was dissolved in acetone at 100 mg/ml and 10 fold serially diluted to create stock solutions, such that the final concentration of acetone in the media was 0.1% by volume. The final concentration of boscalid in each m edia was 0, 0.001, 0.01, 0.1, 1, 10 and 100 g/ml. Mycelial plugs (5 mm dia.) from the actively growing area of the 4 day old fungal colony were placed upside down on the center of each plate. Three replicate plates were used for each fungicide concentrati on, and each experiment was repeated once. Plates were incubated at 24 o C for 7 days, and colony diameter of each isolate was determined by calculating the mean of two perpendicular measurements. The diamet er of the mycelial plug was sub tracted from the col ony diameter before calculating the mean. The percent inhibition was calculated by dividing the mean colony diameter on each fungicide amended plate by the mean colony diameter of the un amended control. The effective concentration to reduce growth by 50% ( EC 50 ) for individual isolates was calculated by regressing the mycelial growth inhibition against the log 10 transformed fungicide concentration using a sigmoidal function with SigmaPlot (Ver11.0; Systat Software Inc., San Jose, CA).

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118 Evaluation of M ethods t o C haracterize A. alternata S ensitivity to B oscalid The following methods were evaluated to measure boscalid sensitivity of 16 isolates used in the media assay (Table 5 1): (i) conidia germination, (ii) spiral gradient end point dilution, and (iii) resazurin based microtiter. All the experiments were performed twice. Conidia germination Conidial suspension was produced according to the procedure previously described ( Vega and Dewdney, 2014 ) Two 10 l aliquots of the conidial suspension (1 10 4 conidia/ml) were deposited onto the surface of glass slides coated with 2% water agar amended with boscalid. Boscalid concentrations were the same as described above. Each slide was placed into individual petri dishes with moistened filter paper, and incubated at 24 o C for 18 h. At 100 magnification, 100 conidia per slide, with three replicate slides per isolate, were examined for germination. A conidium was considered germinated if the germ tube was at least th e length of the conidium, if an appressorium was present, or if multiple germ tubes were observed. The percent conidia inhibition was calculated by dividing the number of germinated conidia on each fungicide amended slide by the mean number of germinated c onidia on the un amended control. The effective concentration to inhibit 50% of conidia germination (EC 50 ) was calculated for every isolate using a sigmoidal function as described above. Spiral gradient The sensitivity of isolates was determined using the method developed by Frster et al. (2004), with modifications done by Amiri et al. (2003). Briefly, 50 ml of PDA was poured into 15 cm petri dishes. For each isolate, 500 l of conidial suspension (1 10 5 conidia/ml) was spread onto PDA and incubated for three days at 24 o C. After that, an agar slicer ( Amiri et al., 2013 ) was pressed into the PDA to generate 32 agar strips (45 mm 6 mm). A boscalid stock solution was prepared at 1.28 mg/ml in 50% acetone and applied spirally on to 15 cm PDA plates

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119 using an automated spiral plater (Autoplate 4000, Spiral Biotech, Norwood, MA). The conc entration at which the fungicide was applied ranged from 0.1 to 10 l/ml. For each isolate, a duplicate mycelium covered agar strip was radially placed upside down across the fungicide gradient dilutio n plate. Three replicate plates and six agar strips per isolate were used for each experiment. Plates were sealed with parafilm and incubated at 24 o C for 4 days (Fig. 5 2) The EC 50 value for each isolate was estimated using the Spiral Gradient Endpoint (SGE) software (Spiral Biotech), as previously described ( Frster et al., 2004 ) Resazurin microtiter Fungicide sensitivity was determined using the method previously developed ( Vega et al., 2012 ; Vega and Dewdney, 2014 ) Briefly, CM broth amended with fungicide (100 l) was added in triplicate into a 96 well, flat bottom, microplate (Corning Inc.), followed b y 80 l of conidial suspension and 20 l of resazurin solu tion. The final concentrations of boscalid were 0, 0.001, 0.01, 0.1, 0.316, 1, 10 or 100 g/ml. While the final conidia and resazurin concentrations were 4 10 4 conidia/ml and 40 M resazurin. Incu bation conditions were as previously described ( Vega and Dewdney, 2014 ) Fungal respiration was determined by measuring the resazurin reduction at 570 and 600 nm, as previously described ( Vega et al., 2012 ) Absorbance was read with a microplate spectrophotometer (Bio Rad, Hercules, CA). Isolate sensitivity wa s determined by the effective concentration needed to reduce resazurin by 50% (EC 50 ) using a sigmoidal function ( Vega et al., 2012 ) Boscali d S ensitivity of F ield I solates In total, 419 A. alternata isolates were screened for fungicide sensitivity using the resazurin based microtiter assay, as described above. Out of th e 419 isolates, 380 were obtained from the 2008 to 2012 sample collection; while, 39 isolates collected from 1996 to 1997, were obtained from the Dewdney lab culture collection (Table 5 2).

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120 Analysis of D NA S equence of the SDH S ubunits A subset of 15 isolat es, corresponding to a broad range of sensitivity to boscalid, were selected for molecular characterization of the SDH complex. Genomic DNA was extracted from 3 day old mycelia cultures on PDA overlaid with cellophane sheets, following the procedures previ ously described ( Vega and Dewdney, 2014 ) using the DNeasy Plant Mini kit (Qiagen, the SDHB, SDHC and SDHD subun its, a different set of primers were developed (Table 5 3). PCR reactions were carried out in a Peltier Thermal cycler (MJ research Inc., Watertown, MA) in a final volume of 25 l containing 1 unit of HotStart Taq Plus polymerase (Qiagen), 2.5 l of 10 PC R buffer, 200 M of each dNTP, 0.3 M of each primer, and 1 to 15 ng of fungal DNA template. Amplification conditions consisted of an initial pre heat for 5 min at 95 o C, followed by 40 cycles of denaturation at 94 o C for 40 s, annealing at 51 o C for 50s, ext ension at 72 o C for 1 min, and a final DNA extension at 72 o C for 10 min. PCR products were separated in SYBR DNA gel stained 1.4% agarose gel run in 1 Tris acetate EDTA (TAE) buffer and exposed to UV light to visualize DNA fragments. PCR products were eith er excised from the gel or purified directly using the MinElute gel extraction kit (Qiagen) or the QIAquick PCR purification kit (Qiagen), respectively, and cloned into the pGEM T Easy vector (Promega Corp., Madison, WI). Plasmids were transformed into Esc herichia coli high efficiency competent cells JM109 products were sequenced by the Interdisciplinary Center for Biotechnology Research (University of Florida). SDH subunits sequences were submitted to GenBank (accession numbers KJ426258 to KJ426276). DNA sequences for every SDH subunit were assembled into a single contiguous sequence using Geneious (ver. 6.1.6; Biomatters Ltd.). Multiple DNA sequence alignments a nd translation to amino acids were performed using MEGA (ver. 5.2).

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121 Statistical A nalysis Homogeneity of variance test using the ratio of variance of two inde pendent experiments was performed prior to pooling the experiments. EC 50 values were log 10 transformed prior to testing for normality, using the Shapiro Wilk test in PROC UNIVARIATE (ver. 9.3; SAS Institute, Cary, NC), and graphically analyzed. Data from methods evaluated to characterize sensitivity to boscalid were subjected to analysis of var iance (ANOVA) using PROC GLM were estimated by calculating a Pearson correlation coefficient using PROC REG and PROC CORR (SAS). Results Medium S election for B o scalid S ensitivity for M ycelial G rowth I nhibition T est The growth of 16 A. alternata isolates was significantly affected ( P < 0.0001) by boscalid unamended media. The mycelial growth rate on PDA was significantly higher (7.63 mm/day) than that on CM (6 .15 mm/day) and MM (6.05 mm/day ). The EC 50 values for boscalid, based on mycelial growth inhibition, were log normally distributed ( P > 0.05) for each medium evaluated. The mean EC 50 value in MM was significantly higher (5.59 g/ml) than CM (1.96 g/ml) and PD A (1.97 g/ml); however, between CM and PDA no significant differences were found ( P > 0.05). C omplete inhibition of mycelial growth was not observed (Fig. 5 3 ), even at a higher boscalid concentration (100 g/ml), for any of the three media evaluated. For PDA, the range of EC 50 values was 0.31 to 4.70 g/ml. For CM, the range of EC 50 values was 0.69 to 4.92 g/ml; while, for MM the EC 50 values ranged from 2.08 to 12.66 g/ml (Table 5 1). Great variability of boscalid sensitivity among isolates within media was observed.

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122 Effect of B oscalid on C onidia G ermination, M ycelial G rowth, and R esazurin R eduction Conidia germination of A. alternata was not affected by boscalid even at higher concentrations (> 50 g/ml). Out of 16 isolates used in this study, 13 showed EC 50 values higher than 50 g/ml, and only one isolate had an EC 50 value lower than 10 g/ml (Table 5 1). The two remaining isolates had EC 50 values between 10 and 40 g/ml. T he mean EC 50 value generated by the spiral gradient endpoint dilution method was significantly ( P < 0.0001) higher (2.34 g/ml) than that generated by the resazurin based microtiter test (0.91 g/ml); however, the mean EC 50 of the spiroplate was no t significantly different than that of the mycelium growth inhibition test using either PDA or CM (Table 5 1). For the spiroplate test the range of EC 50 values was 1.07 to 3.82 g/ml; while, for the resazurin test the EC 50 values ranged from 0.07 to 2.38 g/ml (Table 5 1). Sensitivity of A. alternata I solates to B oscalid Using Resazurin Test The frequency of the EC 50 values was log normally distributed ( W = 0.988, P = 0.0513). The EC 50 values ranged from 0.07 to 5.84 g/ml, with mean and median EC 50 values of 0.60 and 0.44 g/ml, respectively (Table 5 2; Fig. 5 4 ). The mean EC 50 value of isolates collected from 1996 to 1997 was not significantly different ( P = 0.2583) than the mean EC 50 value of isolates collected from 2008 to 2012. The mean EC 50 values of isolates collected from different cultivars were not significantly differe nt ( P 50 values were 0.60, 0.66, 0.84, 0.58, 0.54, 0.88, and 0.70 g/ml, respectively. No correlation was found between isolate virulence and sensitiv ity to boscalid ( r = 0.0381, P = 0.4628). The frequency of EC 50 values was log normally distributed within isolate virulence categories ( P > 0.05), except for moderately virulent isolates, where the EC 50 distribution was s lightly right skewed (Fig. 5 5 ).

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123 Two isolates (G23 R2 L1 1S and G38 B30 R3 L1 1S) showed EC 50 values greater than 100 g/ml, typically observed in resistant isolates, therefore they were further subject to verification using mycelial growth inhibition The EC 50 values obtained by mycelium growth inhibition were 1.64 and 0.95 g/ml for G23 R2 L1 1S and G38 B30 R3 L1 1S respectively Molecular C haracterization of the SdhB, SdhC, and SdhD G enes of S uccinate D ehydrogenase A subset of 15 A. alternata isolates, with a great variability in bosca lid sensitivity, were selected to clone and sequence the three subunits of the SDH complex involved in the interaction with SDHIs. The partial gene structure of the SDHB subunit contained an open reading frame (ORF) coding a predicted protein of 306 amino acids interrupted by three putative introns (Fig. 5 6A) The first intron of 58 bp was inserted after the G of the triplet encoding for alanine (GCC) at amino acid position 16 (A16). The second intron had a predicted length of 52 bp (in 4 isolates) or 57 b p (in 11 isolates) and was located after the T of the triplet encoding for cysteine (TGC) at amino acid position 149 (C149). The third intron of 52 bp was inserted after the triplet encoding for aspartic acid at amino acid position 199 (D199). At the nucle otide level, the SdhB gene of A. alternata tangerine pathotype showed high homology with the mitochondrial iron sulfur subunit gene of A. alternata from pistachio (98% identity), A. solani (92%), Pyrenophora tritici repentis (87%), and Mycosphaerella grami nicola (78%). The assembled DNA of the partial SdhC gene contained an ORF coding for 178 amino acids and one putative intron of 89 bp inserted after the G of the triplet encoding for arginine (AGA) at amino acid position 31 (R31) (Fig. 5 6B) A BLAST searc h of the nucleotide sequences revealed an identity between 97 to 100% of the mitochondrial succinate dehydrogenase cytochrome b560 subunit C (SDHC) gene of A. alternata from pistachio. The sequence of the partial SdhD gene contained one ORF coding for 193 amino acids, interrupted by

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124 one putative intron of 51 bp located after the A of the triplet encoding for glutamic acid (GAG) at amino acid position 139 (E139) (Fig. 5 6C) At the nucleotide level, the SdhD gene showed high homology with the mitochondrial s uccinate dehydrogenase cytochrome b560 subunit D (SDHD) gene of A. alternata from pistachio (96 to 99% identity). Polymorphism A nalys is of the SDHB, SDHC, and SDHD S ubunits of S ucci nate D ehydrogenase To identify mutations in the coding region of the SdhB SdhC and SdhD genes, multiple amino acid alignments were performed using the 15 A. alternata isolates previously selected for the sequence analysis (Table 5 4). Mutations leading to amino acid substitutions in the target protein were detected in 14 out of 15 selected isolates (93.3%). Target mutations were identified in all three subunits of the SDH complex, and as many as 21 different substitution types were identified. Double amino acid substitutions were observed in SDHC and SDHD, and multiple substitut ions were observed only in SDHD (Table 5 4). Isolates carrying mutations in more than one subunit were observed in five isolates (33.3%), and only one isolate (G37 R2 L3 1S) did not have amino substituti on s in any of the SDH subunits. In SDHB, four substit utions were observed (Fig. C 1) ; while in SDHC and SDHD, five (Fig. C 2) and 12 (Fig. C 3) substitutions were detected, respectively (Table 5 4). All amino acid substitutions were derived from single nucleotide mutations at the respective codon. In SDHB, t he amino acid substitutions include d : I54T, S94L, K207R, and E218G. Additionally, when a multiple comparison test included a reference A. alternata isolate (Accession number EU178851.1), the mutation R93Q, in the subunit B, was observed in all 15 isolates. A lack of correlation between the number of mutations in the SDH complex and the level of sensitivity to boscalid was found ( r = 0.1175, P = 0.6766).

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125 Discussion Mycelial growth inhibition has been used traditionally for fungicide sensitivity tests in many fungal species. However the se lection of a suitable medium to test SDHI sensitivity specifically for boscalid, is paramount given the fact that the fungicide sensitivity ca n be increased by using acetate as a substitute to glucose for a carbon source in the medium ( Shima et al., 2009 ; Leroux et al., 2010 ) A Medium based on yeast extract, peptone, and sodium acetate (YBA) was used for boscalid sensitivity tests for multiple fungi ( Spiegel and Stammler, 2006 ; Stammler and Speakman, 2006 ; Stammler et al., 2007 ; Miyamoto et al., 2009a ; Veloukas and Karaoglanidis, 2012 ; Avenot et al., 2013 ) However, Hu et al. ( Hu et al., 2011 ) demonstrated that YBA did not support mycelial growth of Monilinia fructicola isolates, and therefore could not be used to test fungicide sensitivity f or this species Despite this result s the fungal growth inhibition for SDHIs has been performed using conventional medi a such as PDA ( Zhang et al., 2007 ; Avenot et al., 2009 ; Avenot et al., 2012 ; Miles et al., 2013 ; Amiri et al., 2014 ) MM ( Hu et al., 2011 ; Amiri et al., 2014 ) and Sabouraud dextrose ( Fraaije et al., 2012 ) Due to the inconsistent and sometimes contradictory information published, the validation of different nutrient media and methods to be used for boscalid sensitivity tests is necessary before screening a large set of isolates of the target population in a system that has never been previously tested. In this study, mycelial growth inhibition of A. alternata isolates was compared using three culture media H igher EC 50 values and a higher EC 50 range were observed on MM compared to PDA and CM. Interestingly, complete mycelial inhibition was not observed on any medium evaluated even at the higher concentrations of boscalid. S imilar results were observed in Botrytis cinere a where it was not possible to obtain the minimum inhibitory concentrations for fluopyram on PDA or succinate medium ( Veloukas and Karaoglanidis, 2012 ) In contrast, in other fungal species, such as Didymella bryoniae and A. alternata from pistachio, complete

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126 mycelial inhibition was observed on PDA amended with boscalid and penthiopyrad ( Avenot et al., 2008b ; Avenot et al., 2012 ) Even though CM support ed optimal growth and sporulation of A. alternata isolates ( Vega et al., 2012 ) PDA was chosen for further experiments with the spiral gradient end point dilution method, because it was less costly and time consuming for medium prepa ration. Our study showed that boscalid was not able to inhibit A. alternata conidia germinatio n even at higher concentrations. This is in contrast to previous reports where different SDHIs were evaluated using spore germination tests including A. alternat a from pistachio ( Avenot and Michailides, 2007 ; Leroux, 2 010 ; Yin et al., 2011 ; Veloukas and Karaoglanidis, 2012 ; Gudmestad et al., 2013 ; Mallik et al., 2013 ) Therefore, conidia germination should be avoided for boscalid sensitivity in tangerine infecting A. alternata isolates. On the other hand mycelial growth of D. bryoniae ( Avenot et al., 2012 ) and A. alternata fro m pistachio ( Avenot and Michailides, 2007 ) was more sen sitive to boscalid than conidia germination, and theref ore used in subsequent studies to screen SDHIs sensitivity. T he effect of SDHIs on conidia germination appears to be specie s specific. Ascospores of D. bryoniae were two to three times less sensitive than conidia, demonstrating the differential effect of b oscalid between different spore types of the same fungus ( Keinath, 2012 ) On the other hand, Spiegel a nd Stammler ( Spiegel and Stammler, 2006 ) observed that conidia of Monilinia sp. germinated at higher concentrations of boscalid, but the germ tube elongation was complete ly inhibited. Similarly, the effect of SDHIs on germ tube elongation was also observed in B. cinerea ( Stammler and Speakman, 2006 ; de Miccolis Angelini et al., 2010 ; Veloukas and Karaoglanidis, 2012 ) Apparently germ tube elongation is the most sensitive stage to SDHIs in some fungi. Indeed, we observed in A. alternata that EC 50

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127 values for boscalid from the res azurin based microtiter test were lower than those from the mycelium growth inhibition tests using either the spiral gradient end point dilution method or the amended agar technique. The resazurin assay measures the metabolic activity of fungal growth during conidial germination and germ tube elongation ( Vega et al., 2012 ) and could explain the results obtained in this study. Resazurin is a straight forward and ver y accurate technique that has been used successfully to measure the QoI sensitivity of tangerine infecting A. alternata populations ( Vega and Dewdney, 2014 ) and it was used in this study to characterize th e sensitivity to boscalid for a large set of isolates. A total of 419 isolates, which were not previously exposed to boscalid and therefore considered as baseline, were tested for fungicide sensitivity. In fungicide resistance management, baseline sensitiv ity data can be used to detect any change s in the sensitivity profile of the population exposed to the fung icide and to provide evidence that disease control failures could be due to the presence of resistance isolates in the pathogen population ( Russell, 2004 ) The s ensitivity distribution to boscalid was log normally distributed with a relat ive ly wide sensitivity range. In the current baseline study, there was an 83 fold difference in sensitivity from the most sensitive isolate to the least sensitive, in agreement with a baseline sensitivity study in A. solani ( Gudmestad et al., 2013 ) It is possible that the genetic diversity of tangerine infecting A. alternata popu lations ( Peever et al., 2002 ; Stewart et al., 2013 ) may include isolates with different levels of fungicide sensitivity as previously observed in isolates of Phytophthora capsici sensitive to fluopicolide (Keinath and Kousik, 2011) To our knowledge this is the first report of the baseline sensitivity of A. alternata tangerine pathotype to boscalid, using populations recovered over multiple years.

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128 The mean EC 50 value obtained in our study (0.60 g/ml) was lower than the mean EC 50 va lue (1.36 g/ml) observed in wild type A. alternata isolates from pistachio ( Avenot and Michailides, 2007 ) but higher than the mean EC 50 value (0.33 g/ml) observed in baseline A. solani isolates ( Gudmestad et al., 2013 ) The different methods used to measure boscalid sensitivity (conidia germination vs. resazurin microtiter), as well as the intrinsic interspecies variation in fungicide sensitivity may have influenced the results. Furth ermore, EC 50 values for boscalid were not correlated with cultivar, or isolate virulence. In general, boscalid showed lower intrinsic activity than azoxystrobin and pyraclostrobin in A. alternata isolates ( Veg a and Dewdney, 2014 ) Although the resazurin test is a reliable and accurate method to measure sensitivity to the re spirator inhibitor fungicides, false positive response s w ere detected in two out of the 419 isolates evaluated. In those isolates the l evel of resazurin reduction was low for all boscalid concentrations, which caused high EC 50 values (> 100 g/ml). Because the resazurin tes t is a very sensitive assay, resazurin reduction for both isolates could be affected by their conidial germination an d mycelial growth rates, giving an overestimation of the EC 50 value. In order to confirm the presence of resistance, both isolates were further characterized phenotypically and molecularly using mycelial growth inhibition and sequencing the SdhB SdhC and SdhD genes The EC 50 values obtained by mycelial growth inhibition were with in the range of the baseline sensitivity population Additionally, the molecular analyses showed that there were no amino acid substitutions in any of the SDH subunits (corresponding to the SDHI binding site); therefore, those isolates were classified as sensitive. One hundred percent accuracy cannot be claimed for any method that determines fungicide sensitivity; however, the overall estimated accuracy of the resazurin based microtiter test was greater than 98%

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129 The polymorphism observed in the SDH subunits of boscalid sensitive A. alternata isolates demonstrates the high diversity of the Florida population. The iron sulfur subunit (SDHB) has a high degree of sequence ho mology across species, whereas the membrane anchored subunits (SDHC and SDHD) have a much lower degree of sequence conservation ( Cecchini, 2003 ; Horsefield et al., 2006 ) This is in agreement with our results, where the highest polymorphism was observed in the SDHD subunit T he occurrence of multiple mutations in the SDH complex of individual isolates has been previously reported in resistant isolates of A. solani ( Miles et al., 201 4 ) and M. graminicola ( Fraaije et al., 2012 ) In contrast, multiple mutations in individual A. alternata isolat es from pistachio w ere not identified ( Avenot et al., 2008b ; Avenot et al., 2009 ) In a previous study, Miles et al. (2014) reported that mutations T28A and A47T in SDHD were associated with resistance; however, based on phenotypic and molecular analysis of our isolates, we conclude that those mutations are natural variants of wild type A. alternata isolates and did not correlate with SDHI sensitivity We observed that the T28A mutation was present in 47% of the isolates a nalyzed, wh ereas the A47T mutation was present in 67% of the isolates, and that those mutations could occur independently. In our study, we did not f ind any boscalid resistant isolate. Nevertheless, Avenot and Michailides ( Avenot and Michailides, 2010 ) found between 2 to 16% A. alternata resistant isolates from pistachio orchards with no history of boscalid exposure. T he proportion of boscalid resistant genotypes appeared to be at a higher frequency in pistachio infecting A. alternata populations than in tangerine infecting A. alternata populations. Resistance to SDHIs has been related to amino acid substitutions in the SDHB, SDHC and SDHD subunits of the SDH complex ( Avenot and Michailides, 2010 ; Sierotzki and Scalliet, 2013 ) So far more than 27 mutations conferring resistance to SDHIs have been reported in field and laboratory mutants of

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130 different fungal pathogens ( Sierotzki and Scalliet, 2013 ) The most frequent mutation has been found in the SDHB subunit at amino acid position 277 (in A. alternata from pistachio), with the substitution of histidine (H) to tyrosine (Y) or arginine (R) ( Avenot et al., 2008b ) However, at the corresponding amino acid position, the change t o leucine (L) has also been observed in Ustilago maydis ( Keon et al., 1991 ) Asp ergillus oryzae ( Shima et al., 2009 ) and Mycosphaerella graminicola ( Scalliet et al., 2012 ) Additionally, mutations in the SDHC and SDHD subunits have been identified in resi stant isolates of many pathogens ( Sierotzki and Scalliet, 2013 ) Whe ther a specific mutation confers a selective advantage over different SDHIs is unknown; however, there are specific preferences for some mutations, depending on the fungal specie s displaying different resistance profile within SDHIs ( Sierotzki and Scalliet, 2013 ) Sequence analyses of boscalid resistant A. alternata from pistachio showed that 39% of the isolates analyzed had mutations in the SDHB subunit, wh ereas 52.6% and 7.9% had mutations in the SDHC and SDHD subunits, respectively ( Avenot and Michailides, 2010 ) In contrast, more than 80% of SDHI resistant isolates of A. solani ( Mallik et al., 2013 ) and B. cinerea ( Leroux et al., 2010 ; Amiri et al., 2014 ) had mutations in the SDHB subunit. Tridimentional structures of the SDH complex using co crystallography with different competitive inhibitors of ubiquinone; as well as docking predictions using computational models, showed that the u biquinone binding (Qp) site is located in a cavity close to the [3Fe 4S] cluster and composed of residues from SDHB, SDHC, and SDHD subunits ( Yankovskaya et al., 2003 ; Fraaije et al., 2012 ; Scalliet et al., 2012 ) The Qp site is connected with different redox centers including FAD, [2Fe 2S], [4Fe 4S], and [3Fe 4S] clusters that contribute to the electron transfer chain within the mitochondrial complex II ( Cecchini, 2003 ; Yankovskaya et al., 2003 ) SDHI bind to the Qp site blocking the access of the substrate and preventing further oxidation of

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131 succinate ( Sierotzki and Scalliet, 2013 ) The amino acid proline (P) at position 225 in th e SDHB of B. cinerea, equivalent to P230 in A. alternata, is part of the Qp site and contribute s to carboximide binding t h rough hydrophobic contacts ( ) T he substitution of P to phenylalanine (F), threonine (T) or L could result in a decrease affinity for SDHIs, such as observed in B. cinerea ( Leroux et al., 2010 ) Additionally the amino acids H267, Serine (S) 221, and isoleuc ine (I) 269 in the SDHB subunit of M. graminicola (equivalent to SDHB H277, S231, and I279 in A. alternata ), as well as the aspartic acid (D) at position 129 in the SDHD subunit (equivalent to SDHD D144 in A. alternata ) are directly involved in SDHI binding site ( Matsson et al., 1998 ; Fraaije et al., 2012 ) Field and laboratory mutants resistant to SDHIs have showed some amino acid substitutions in at least one of those residues ( Sierotzki and Scalliet, 2013 ) However; in our study, none of those substitutions was observed Amino acid replacements of the highly conserved histidine residue of A. alternata isolates, located in the SDHC and SDHD subunits at positions 134 and 133, respectively, may result in some structural changes in the SDH complex, affecting the topology of the Qp site; and therefore, the affinity to SDHIs ( et al., 2011 ) The amino acid substitutions in SDHC and SDHD observed in our isolates, did not correspond with any of those histidine replacements, and therefore did not relate to the potential rearrangement of the SDH complex that is associated with SDHI resistance. The re sults presented here showed that resazurin based microtiter assay is a reliable and accurate technique to measure the sensitivity of A. alternata to boscalid, and potentially new SDHIs, and could be used in the future for large scale surveys as demonstrate d in a previous study ( Vega and Dewdney, 2014 ) Overall, the sensitivity distribution of baseline A. alternata isolates can be used as a reference in the future. It is important to note the high risk of A. alternata resistant genotypes to be rapidly selected after few applications of single site

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132 fungicides, such as SDHIs and QoIs. Indeed, only 2 years after the introduction of boscalid to control Alternaria late blight of pistachio, a considerable proportion of isolates were resistant ( Avenot and Michailides, 2007 ) It should be expected that SDHI resistant isolates will eventually arise from current commercial use of boscalid for ABS control. Therefore, the sensitivity of A. alternata isolates to boscalid should be carefully monitored to track sensitivity profile variations in populations exposed to this fungicide. Rotations of boscalid with fungicides with different mode s of action should be used, particularly in areas where QoI resistance has been identified, in order to prolong the useful life of boscalid present in the fungicide Pristine (registered for ABS con trol in Florida). The use of protectant fungicides, such as copper and ferbam, as well as the DMI difenoconazole (in pre mixture with azoxystrobin marketed as Quadris Top ) may be suitable rotation options for ABS management. Although QoI and SDHI fungicid es have different mode s of action, the risk of development multi fungicide resist ance is high, as previously observed (Avenot et al., 2008a), giving the fact that the presence of QoI resistance in tangerine infecting A. alternata popul ations is widespread (Vega and Dewdney, 2014) The polymorphism of the SDH subunits, observed in wild type A. alternata isolates, corroborates the high diversity of the populations present in Florida. Finally, the molecular characterization of boscalid resistant induced mutant s will help to assess the risk for SDHI resistance in tangerine infecting A. alternata populations.

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133 Table 5 1 Sensitivity of Alternaria alternata isolates to boscalid according to the method and media used Isolate H ost a EC 50 for boscalid (g/ml) according to method Mycelial growth inhibition b Spiroplate c Conidia d RZ e PDA CM MM BL 17 4 3S Minneola tangelo 1.64 3.22 6.88 3.82 >50 0.35 BLK 17 5 10S Minneola tangelo 2.67 4.18 8.68 1.61 11.99 0.12 CPI ORI 2S Murcott tangor 0.57 1.34 2.92 3.36 >50 1.42 EV 3 1S Minneola tangelo 0.67 1.88 12.35 1.65 >50 0.94 G11 R1 F1 1S Dancy mandarin 1.81 1.55 6.97 1.07 >50 1.81 G11 R4 F1 1S Dancy mandarin 1.6 0 0.76 2.29 2.19 7.08 0.41 G11 R9 F1 1S Dancy mandarin 1.86 1.46 6.01 3.01 >50 0.58 G11 R11 F1 1S Dancy mandarin 3.49 1.72 3.28 2.29 >50 0.71 G11 R12 F3 1S Dancy mandarin 2.82 1.4 0 2.88 1.67 39.80 2.21 G42 R1 2 L2 1S Minneola tangelo 1.82 1.66 9.25 1.84 >50 0.52 G42 R2 L1 1S Murcott tangor 3.13 1.15 3.99 2.65 >50 1.22 G42 R3 4 L3 1S Minneola tangelo 2.36 1.55 2.55 1.76 >50 1.15 G42 R7 L2 1S Murcott tangor 1.88 3.07 8.11 2.87 >50 0.16 G42 R9 L2 1S Murcott tangor 2.35 3.53 4.17 3.04 >50 0.51 LOR ORI 1 3S Sunburst tangerine 1.18 1.75 2.92 2.01 >50 0.07 VB RQF 3S Grapefruit 1.66 1.22 6.25 2.55 >50 2.38 Mean f 1.97 B 1.96 B 5.59 C 2.34 B >50 0.91 A a Tangelo = Citrus reticulata C. paradisi tangor = C. reticulata C. sinensis tangerine or mandarin = C. reticulata and grapefruit = C. paradisi b PDA = potato dextrose agar, CM = complete medium, and MM = minimal medium c Spiral gradient end point dilution method d Conidia germination test e Resazurin based micro titer assay f t

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134 Table 5 2 Origin, number, and sensitivity to boscalid of Alternaria alternata isolates collected in Florida citrus groves Isolate Group Location, County Year Host a # isolates tested Mean EC 50 (g/ml) Range (g/ml) AR Arcadia, DeSoto 1997 Sunburst tangerine 4 0.33 (0.07) b 0.29 to 0.43 BLK Lake Alfred, Polk 2008 Minneola tangelo 2 0.32 (0.28) 0.13 to 0.52 EV Lake Alfred, Polk 1996 Minneola tangelo 3 0.45 (0.20) 0.30 to 0.67 FM Fort Meade, Polk 2006 Minneola tangelo 2 0.45 (0.15) 0.34 to 0.55 LOR Lorida, Highlands 1997 Sunburst tangerine 3 0.36 (0.28) 0.07 to 0.62 VB Vero Beach, Indian River 1997 Grapefruit 6 0.66 (0.85) 0.26 to 2.38 WP West Palm Beach, Palm Beach 1996 Minneola tangelo 5 0.29 (0.13) 0.11 to 0.47 1 Fort Meade, Polk 2010 Murcott tangor 6 0.34 (0.27) 0.15 to 0.86 2 Haines City, Polk 2010 Minneola tangelo 6 0.26 (0.10 0.12 to 0.39 Murcott tangor 5 0.39 (0.14) 0.28 to 0.62 3 Umatilla, Lake 2011 Minneola tangelo 5 1.05 (0.81) 0.36 to 2.42 4 Tavares, Lake 2012 Minneola tangelo 5 1.27 (1.73) 0.13 to 4.33 5 Fort Myers, Lee 2012 Murcott tangor 10 0.46 (0.30) 0.14 to 0.88 Sunburst tangerine 2 0.32 (0.12) 0.23 to 0.40 6 Avon Park, Highlands 2011 Minneola tangelo 5 0.43 (0.22) 0.20 to 0.69 Avon Park, Highlands Murcott tangor 10 0.51 (0.30) 0.13 to 0.97 Babson Park, Polk Murcott tangor 5 0.26 (0.11) 0.16 to 0.44 Fort Meade, Polk Murcott tangor 6 0.23 (0.10) 0.10 to 0.37 Frostproof, Polk 2009 Murcott tangor 10 0.39 (0.18) 0.17 to 0.74 Frostproof, Polk 2011 Minneola tangelo 5 0.41 (0.37) 0.12 to 1.04 Frostproof, Polk Murcott tangor 6 0.31 (0.14) 0.17 to 0.54 7 Crooked Lake, Polk 2010 Murcott tangor 6 0.30 (0.17) 0.15 to 0.61 8 Bartow, Polk 2012 Murcott tangor 5 0.78 (0.61) 0.30 to 1.55 9 Davenport, Polk 2010 Murcott tangor 5 0.61 (0.31) 0.32 to 1.12 10 Bartow, Polk 2012 Sunburst tangerine 2 0.35 (0.25) 0.17 to 0.52 11 Winter Haven, Polk 2010 Dancy mandarin 9 0.88 (0.66) 0.30 to 2.21 12 Clermont, Lake 2012 Murcott tangor 5 0.71 (0.42) 0.25 to 1.30 Sunburst tangerine 5 1.25 (1.27) 0.37 to 3.35 13 Felda, Hendry 2012 Murcott tangor 5 0.79 (0.58) 0.20 to 1.50 Immokalee, Collier 1996 Murcott tangor 3 0.86 (0.52) 0.40 to 1.42 14 Dundee, Polk 2009 Murcott tangor 12 0.54 (0.38) 0.20 to 1.53 15 Lake Wales, Polk 2010 Minneola tangelo 5 0.55 (0.16) 0.32 to 0.74 16 Fort Pierce, St. Lucie 2012 Murcott tangor 2 1.19 (1.42) 0.18 to 2.20 17 Fort Meade, Polk 2012 Murcott tangor 4 0.25 (0.11) 0.16 to 0.41 Sunburst tangerine 6 0.43 (0.32) 0.14 to 0.98 18 Fort Pierce, St. Lucie 2011 Minneola tangelo 7 0.36 (0.10) 0.28 to 0.53 19 Fort Pierce, St. Lucie 2010 Minneola tangelo 5 0.71 (0.21) 0.57 to 1.09 20 Immokalee, Collier 2012 Murcott tangor 5 1.24 (0.86) 0.24 to 2.41 21 Vero Beach, Indian River 2011 Minneola tangelo 18 0.32 (0.13) 0.15 to 0.63 22 Vero Beach, Indian River 2011 Sunburst tangerine 3 0.41 (0.37) 0.16 to 0.83 23 Venus, Highlands 2012 Murcott tangor 5 0.65 (0.64) 0.13 to 1.64 24 Immokalee, Collier 1997 Minneola tangelo 2 0.33 (0.24) 0.16 to 0.50 2012 Murcott tangor 5 0.91 (0.46) 0.42 to 1.65 25 Lake Wales, Polk 2010 Murcott tangor 6 0.37 (0.24) 0.18 to 0.80 26 Zolfo Springs, Hardee 2011 Minneola tangelo 5 0.63 (0.27) 0.36 to 0.97 27 St. Cloud, Osceola 2010 Sunburst tangerine 5 0.90 (0.58) 0.22 to 1.69 28 Polk city, Polk 2012 Sunburst tangerine 5 0.57 (0.32) 0.24 to 1.04 29 Clermont, Lake 2012 Orlando tangelo 5 1.15 (0.59) 0.74 to 2.16 Sunburst tangerine 5 1.26 (1.00) 0.17 to 2.64 30 Oviedo, Seminole 2009 Minneola tangelo 4 0.50 (0.11) 0.39 to 0.64

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135 Table 5 2 Continued. Isolate Group Location, County Year Host a # isolates tested Mean EC 50 (g/ml) Range (g/ml) 31 Fort Meade, Polk 2010 Murcott tangor 5 0.42 (0.21) 0.18 to 0.69 Sunburst tangerine 5 0.54 (0.33) 0.22 to 0.91 32 Lake Wales, Polk 2011 Minneola tangelo 5 0.49 (0.10) 0.38 to 0.63 33 Nokomis, Sarasota 2011 Minneola tangelo 5 0.57 (0.22) 0.34 to 0.94 34 Vero Beach, Indian River 2011 Minneola tangelo 5 0.34 (0.12) 0.18 to 0.47 35 Bartow, Polk 2012 Murcott tangor 1 0.35 36 Fort Pierce, St. Lucie 2011 Minneola tangelo 11 0.65 (0.24) 0.28 to 0.98 37 Eutis, Lake 2012 Minneola tangelo 5 1.14 (0.54) 0.51 to 1.87 Orlando tangelo 5 0.94 (0.73) 0.37 to 2.13 38 Immokalee, Collier 1997 Sunburst tangerine 5 0.45 (0.25) 0.21 to 0.87 2012 Sunburst tangerine 15 0.93 (0.43) 0.26 to 1.93 39 Haines City, Polk 2010 Murcott tangor 5 0.68 (0.55 ) 0.17 to 1.59 Orlando tangelo 5 0.55 (0.25) 0.25 to 0.81 40 Winter Haven, Polk 2008 Dancy mandarin 6 0.43 (0.21) 0.20 to 0.76 2010 Dancy mandarin 5 0.27 (0.14) 0.16 to 0.51 41 Vero Beach, Indian River 2011 Minneola tangelo 5 0.62 (0.28) 0.33 to 0.96 42 Haines City, Polk 1996 Minneola tangelo 6 0.64 (0.26) 0.30 to 1.10 2010 Lee citrus hybrid 5 0.71 (0.17) 0.47 to 0.88 Minneola tangelo 7 0.47 (0.34) 0.14 to 1.14 Murcott tangor 8 0.39 (0.37) 0.12 to 1.22 43 Wauchula, Hardee 2011 Murcott tangor 5 0.51 (0.35) 0.12 to 1.02 44 Mt. Dora, Lake 2012 Minneola tangelo 5 1.65 (2.36) 0.23 to 5.84 Murcott tangor 5 0.44 (0.38) 0.15 to 0.87 45 Grand Island, Lake 2012 Lee citrus hybrid 5 0.97 (1.22) 0.09 to 3.12 Murcott tangor 5 1.00 (0.87) 0.24 to 2.00 Sunburst tangerine 5 0.51 (0.39) 0.25 to 1.20 TOTAL 419 0.60 (0.03) 0.07 to 5.84 a Tangerine or mandarin = Citrus reticulata tangelo = C. reticulata C. paradisi tangor = C. reticulata C. sinensis citrus hybrid = C. reticulata x tangelo, and grapefruit = C. paradisi b Values in parentheses denote standard deviation

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136 Table 5 3 Primers sets used for amplification of the SdhB, SdhC, and SdhD genes from Alternaria alternata genomic DNA SD H (gene) Primer Reference a Tm ( o C) b Amplified DNA fragment c Iron sulfur protein ( SdhB ) SDHB F1 TAC GAG CTC GAC CTC AAC AAG AC 1 58.4 341 to 1049 SDHB R1 CTC GGC AAC GCG GGG TTC AGT C 1 65.0 SDHB F2 GTG GCG TCG AAG GGC CGA AGA AGC CG 1 68.9 33 to 349 SDHB R2 CAG CAT CAT GGG TCC GGT CTT GTT GA 1 62.7 SDHB F4 CGA CGG ACT CTA CGA ATG C 1 55.4 801 to 1020 SDHB R4 GCA TGT CCT TGA GCA GTT GAG 1 56.3 CybL protein ( SdhC ) SDHC F2 ATG GCT TCT CAG CGG GTA TTT CAG 2 59.1 1 to 623 SDHC R3 TCA TCC GAG GAA GGT GTA GTA AAG GCT G 2 60.3 SDHC F4 CCA GCG GAG GTA TGT CAT AAT AG This study 54.6 84 to 570 SDHC R4 TCC ATC CAG TGC GGA TAA CC This study 56.9 CybS protein ( SdhD ) SDHD F1 ATG GCC TCC GTC ATG CGT This study 59.9 1 to 636 SDHD SeqR2 TAT CTA TGC GTG CCA CAA CC 2 55.1 SDHD F2 CTG CGA CAT CGA CCA TGA A This study 55.2 77 to 596 SDHD R2 CCA ACA TCG TTT GTC TCG AAA G This study 54.3 a Reference 1: Avenot et al., 2008 b and reference 2: Avenot and Michailides. 2009 b Primer melting temperature c Fragment numbering corresponds to nucleotide positions in the SDH subunits B, C and D of Alternaria alternata with th e first nucleotide of the start codon at position 1

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137 Table 5 4 Amino acid substitutions in the succinate dehydrogenase (SDH) subunits B, C, and D in field isolates of Alternaria alternata collected in Florida citrus groves Isolate Host a EC 50 (g/ml) Succinate dehydrogenase subunit b SDHB SDHC SDHD AR SBL 4S Sunburst tangerine 0.31 K207R none M23T, A59V FM MIL 4S Minneola tangelo 0.55 S94L none Q18H, T28A, M31I, A47T G4 R1 F1 1S Minneola tangelo 4.33 none none V131A G9 R6 1S Murcott tangor 1.12 none none Q18H, T28A, M31I, A47T, V132A G12 C2 R13 F1 1S Sunburst tangerine 3.35 none D145G Q18H, T28A, M31I, A47T G14 7 2S Murcott tangor 1.53 none G84S, P130A none G20 R3 L1 1S Murcott tangor 2.41 I54T F129L V17A, Q18H, A47T, T156A G23 R2 L1 1S Murcott tangor 1.64 none none V17A, Q18H, A47T, T156A G27 B2B L2 1S Sunburst tangerine 1.69 none none V17A, Q18H, A47T, L130Q, T156A G29 R9 F1 1S Sunburst tangerine 2.64 none none Q18H, T28A, M31I, A47T G37 R2 L3 1S Orlando tangelo 2.13 none none none G38 B30 R3 L1 1S Sunburst tangerine 0.95 none none V17A, Q18H, A47T, T156A G40 R2Q12 F5 1S Dancy mandarin 0.30 none none Q18H, T28A, M31I, A47T, F57L G44 R1 L1 1S Minneola tangelo 5.84 none none Q18H, T28A, M31I, A47T G45 R10 L1 1S Lee citrus hybrid 3.12 E218G F150Y Q18H, T28A, M31I, A47T a Tangerine or mandarin = Citrus reticulata tangelo = C. reticulata C. paradisi tangor = C. reticulata C. sinensis and citrus hybrid = C. reticulata tangelo b Amino acid replacement at respective codon

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138 Figure 5 1 Boscalid amended agar technique to evaluate mycelial growth inhibition under different fungicide concentrations on three culture media. A) Potato dextrose agar (PDA). B) C omplete medium agar (CM ). C) M inimal medium agar (MM).

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139 Figure 5 2. Alternaria a lternata isolates grown on spiral gradient end point dilution plates A ) I solates growing on boscalid amended plate. Black arrow shows boscalid concentrations ranged from 10 g/ml in the center to 0.1 g/ml at the edge of the plate. B ) I solates growing on unamended boscalid control plate. C) M agnification of boscalid sensitive isolate growing on fungicide amended plate. D) M agnification of isolate growing on fungicide free control plate.

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140 Figure 5 3. Relative mycelial growth of Alternaria alternata on complete medium agar (circles), minimal medium agar (squares), and potato dextrose agar (triangles) amended with boscalid at several concentrations. Values are the mean and standard error of 16 isolates

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141 Figure 5 4. Sensitivity distribution of Alternaria alternata isolates (n= 419) to boscalid, based on effective concentration needed to reduce fungal growth by 50 % (EC 50 ) values

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142 Figure 5 5. Sensitivity distribution (effective concentration needed to reduce resazurin reduction by 50% [EC 50 ] values) to boscalid of Alternaria alternata isolates (n = 374), based on isolate virulence. Virulence was tested by spray inoculation of detached tangerine leaves and rated 48 to 72 h after inoculation (low = <25%, medium = 25 to 50%, and high = >50% leaf area diseased). For each box, the dashed line represents mean, the solid line represents median, the top of each box represents the 75 th percentile, and the bottom of each box the 25 th percentile of EC 50 values. Error bars represent the 90 th percentile (top) and the 10 th percentile (bottom) of EC 50 values. Dotes represent outliers

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143 Figure 5 6. Partial structure at the exon intron junction in the succinate dehydrogenase (SDH) subunits of Alternaria alternata. Boxes indicate exons and lines indicate introns. The length of the exons and introns are not to scale. A) I ron sulfur protein (SDHB) B) Cy bL protein (SDHC) C) CybS protein (SDHD).

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144 CHAPTER 6 FINAL CONCLUSIONS AND SUMMARY Chemical control is a critical aspect of the management of Alternaria brown spot (ABS). However, one of the greatest concerns surrounding the use of site specific fungici des, such as quinone outside inhibitors (QoI ) and succinate dehydrogenase inhibitors (SDHI ), is the development of resistant populations The QoI fungicides azoxystrobin (AZ) and pyraclostrobin (PYR) have been used against ABS for more than 10 years, while the SDHI boscalid was recently registered for disease control. Due to the high efficacy of QoIs in controlling ABS, growers adopted them very quickly and intensively used them in disease management programs. During 2008 2009, QoI resistant isolates were recovered from commercial tangerine groves located in central Florida, leading the hypothesis that QoI resistance could be widely distributed through out the state. Therefore, a state wide survey was implemented to detect QoI resistance in A. alternata populations and also to establish a baseline sensitivity to boscalid. A novel technique, the resazurin based microtiter assay was optimized to evaluate the sensitivity of A. altern ata to QoIs. Complete medium at 10 5 conidia/ml and 40 M of resazurin were identified as optimal for measuring resazurin reduction caused by A. alternata respiration With this information, the effective concentration of AZ and PYR needed to reduce resazur in by 50% (EC 50 ) was calculated and compared with those obtained from conidia germination tests on fungicide amended media. Concordant EC 50 values were observed (R 2 =0.923; P < 0.0001) from both methods. Therefore, this method was used to screen QoI sensiti vity in a large set of isolates. In total, 817 A. alternata isolates collected from 46 citrus orchards during 2008 to 2012 were tested for sensitivity to AZ and PYR. QoI resistance was confirmed in 57.6% of isolates tested, with EC 50 values greater than 5 g/ml for AZ and 1 g/ml for PYR. The mean EC 50 values for sensitive isolates were 0.139 and 0.020 g/ml for AZ and PYR, respectively. The EC 50

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145 values of both fungicides were highly correlated ( P < 0.0001), indicating cross resistance. Interestingly, the p roportion of resistant isolates differed significantly ( P < 0.0001) among cultivars and with the number of QoI applications. However, resistance was not significantly related ( P = 0.364) to disease severity observed in the field or isolate virulence ( P = 0 .397). Moreover, the G143A mutation, conferring QoI resistance, was identified in a subset of 161 isolates. Based on the presence of one or two introns, isolates were classified as profile I or profile II, respectively. The resistance frequency was signifi cantly higher ( P < 0.0001) in isolates profile II, suggesting a higher selection pressure for resistant population profile II. The stability of QoI resistance, fitness components, and the ability to cause disease of QoI resistant isolates were also studie d. Results showed that sensitivity to QoIs did not change significantly after 10 transfers on potato dextrose agar (PDA) compared to the initial sensitivity. Fitness components evaluated in vitro were: mycelial growth, conidial germination, and conidia pro duction. I ncubation period, number of lesions per leaf area, and virulence were determined with detached leaf assay using four cultivars: Dancy, Minneola, Murcott, and Sunburst. As a group, no significant differences in the mean values of these fitness com ponents were observed between resistant and sensitive phenotypes, except for disease virulence. Resistant isolates were significantly ( P < 0.05) more virulent than the sensitive isolates in cultivars Dancy, Minneola, and Sunburst, but not in Murcott ( P = 0 .3506). Furthermore, preventive applications of Abound (commercial formulation of AZ) at full field concentration failed to control disease caused by QoI resistant isolates under greenhouse conditions. It is suggested that QoI resistance is stable and tha t the resistant development will not affect the fitness of resistant isolates, increasing the likelihood of QoI resistance emergence of A. alternata Further investigations are needed to determine the competitive ability of resistant isolates mixed with se nsitive isolates.

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146 The final study was concerned with sensitivity of A. alternata to boscalid and the effect of the polymorphism s in the iron sulf ur and in the anchored membrane subunits of the succinate dehydrogenase (SDH) complex. A total of 419 isolates were tested for boscalid sensitivity using the resazurin based microtiter assay. The sensitivity distribution was a unimodal curve with a mean EC 50 value of 0.60 g/ml with a r ange of 0.07 to 5.84 g/ml. Moreover, the molecular characterization of the SDH genes ( SdhB, SdhC, and SdhD ) was determined in a subset of 15 isolates. In total, 21 mutations were identified. Double and multiple mutations were observed in SDHC and SDHD, re spectively. No mutations were found in the highly conserved histidine residue at positions 277 in SDHB, 134 in SDHC, and 133 in SDHD, typically observed in SDHI resistant isolates. These results suggest that A. alternata populations are sensitive to boscal id and that it can continue to be used in AB S spray programs In conclusion, a fter testing statewide A. alternata populations for QoIs and SDHI sensitivity, nearly 60% of isolates were QoI resistant wh ereas all of them were SDHI sensitive Given that new fungicides register ed or in the registration process, are premix tures of QoI and SDHI and that A. alternata represents a classical high risk pathogen for fungicide resistance development, the concern of the development of multi fungicide resistance in pop ulations of Alternaria infecting tangerines is a reality Therefore, anti resistance strategies and permanent monitoring programs to determine the sensitivity of populations, especially to SDHIs, are required.

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147 APPENDIX A SUPPLEMENTAL FIGURES FOR CHAPTER 2 Figure A 1. Resazurin reduction caused by Alternaria alternata growth in complete medium at different SHAM concentrations. Columns are the mean, error bars are the standard error of 12 isolates. Columns with the same letter are not significantly different = 0.05

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148 S: BL 17 4 3S IFILMMATAFLGYVLPYGQMSLWGATVITNLMSAIPWVGQDIVEFIWGGFS S: BLK 17 S 10S IFILMMATAFLGYVLPYGQMSLWGATVITNLMSAIPWVGQDIVEFIWGGFS S: CPI ORI 2S IFILMMATAFLGYVLPYGQMSLWGATVITNLMSAIPWVGQDIVEFIWGGFS S: EV 3 1S IFILMMATAFLGYVLPYGQMSLWGATVITNLMSAIPWVGQDIVEFIWGGFS R: LJ 1 8 2S IFILMMATAFLGYVLPYGQMSLWAATVITNLMSAIPWVGQDIVEFIWGGFS R: LJ 3 3 2S IFILMMATAFLGYVLPYGQMSLWAATVITNLMSAIPWVGQDIVEFIWGGFS S: LOR ORI 1 3S IFILMMATAFLGYVLPYGQMSLWGATVITNLMSAIPWVGQDIVEFIWGGFS R: R3Q26 F9 2S IFILMMATAFLGYVLPYGQMSLWAATVITNLMSAIPWVGQDIVEFIWGGFS R: R3Q33 1 1S IFILMMATAFLGYVLPYGQMSLWAATVITNLMSAIPWVGQD IVEFIWGGFS S: VB RQF 3S IFILMMATAFLGYVLPYGQMSLWGATVITNLMSAIPWVGQDIVEFIWGGFS R: WM 1 2S IFILMMATAFLGYVLPYGQMSLWAATVITNLMSAIPWVGQDIVEFIWGGFS R: WM 1 3S IFILMMATAFLGYVLPYGQMSLWAATVITNLMSAIPWVGQDIVEFIWGGFS Figure A 2. Alignment of the amino acid residues 120 to 170 (first hot spot) of the cytochrome b gene from quinone outside inhibitor sensitive (S) and resistant (R) isolates of Alternaria alternata. The star indicates the change of the amino acid glycine (G) to alanine (A) at position 143 in resistant i solates

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149 S: CTAGTATGAACTATTGGTACTGTTATCTTTATCTTAATGATGGCTACAGCTTTCTTGGGA [ 60] R: CTAGTATGAACTATTGGTACTGTTATCTTTATCTTAATGATGGCTACAGCTTTCTTGGGA [ 60] S: TACGTCTTGCCATACGGGCAAATGTCATTATGAG G TGCAACAGTTATTACTAACCTTATG [ 120] R: TACGTCTTGCCATACGGGCAAATGTCATTATGAG C TGCAACAGTTATTACTAACCTTATG [ 120] S: AGTGCTATACCTTGAGTAGGTCAAGATATTGTTGAGTCAAATAATTTTACAGAAAACTAC [ 180] R: AGTGCTATACCTTGAGTAGGTCAAGATATTGTTGAGTCAAATAATTTTACAGAAAACTAC [ 180] S: ACTACAGTTTATTGCTTATCTAGTTTACTACCTACGATAGGTACTGTTAGTGCTAACGCA [ 240] R: ACTACAGTTTATTGCTTATCTAGTTTACTACCTACGATAGGTACTGTTAGTGCTAACGCA [ 240] S: TTAAAAAAAGGAAATAAAAATGTTAGATGTAACAAAAAAGAATATTTATCCATACCTCCT [ 300] R: TTAAAAAAAGGAAATAAAAATGTTAGATGTAACAAAAAAGAATATTTATCCATACCTCCT [ 300] S: TCTTTTCTGTCTTTTTTAGCAGGATTGATAGACGGAGACGGTTACATACAAATAACAAAA [ 360] R: TCTTTTCTGTCTTTTTTAGCAGGATTGATAGACGGAGACGGTTACATACAAATAACAAAA [ 360] S: ACAACTAAAGGATTTATAGCCATTAAGCTAGTTATATCTATTCATTTAAAGGATATTTCA [ 420] R: ACAACTAAAGGATTTATAGCCATTAAGCTAGTTATATCTATTCATTTAAAGGATATTTCA [ 420] S: ACTTTAGAGTATATACGTTCCGTTCTAAATTTAGGTAAGATTACTATATATAAAGATAAT [ 480] R: ACTTTAGAGTATATACGTTCCGTTCTAAATTTAGGTAAGAT TACTATATATAAAGATAAT [ 480] S: AAAAGTCCAACTTGTAAATTGATTATTAACAAAACTGATTTACAAGAAATTCTGTTCCCA [ 540] R: AAAAGTCCAACTTGTAAATTGATTATTAACAAAACTGATTTACAAGAAATTCTGTTCCCA [ 540] S: TTATTATTACACCATAACATATTTTTTTTAACTGAAACAAGAAATAACCAATTTAACACT [ 600] R: TTATTATTACACCATAACATATTTTTTTTAACTGAAACAAGAAATAACCAATTTAACACT [ 600] S: GCTATGGTAATACTAGATAAAGACATAAAAAGGTTTGATCTTATACCAGATATAAATAAT [ 660] R: GCTATGGTAATACTAGATAAAGACATAAAAAGGTTTGATCTTATACCAGATATAAATAAT [ 660] S: ATGGTTAAAATATTTAACTTACCAGTAGATGCAGTAGATT ATGTTAAATTAAGTTTCTTT [ 720] R: ATGGTTAAAATATTTAACTTACCAGTAGATGCAGTAGATTATGTTAAATTAAGTTTCTTT [ 720] S: AAAAATTGAATAGTTGGTTTTACAATGGCAGAAGGGTCATTTTTTATAAAAAGTAATAAT [ 780] R: AAAAATTGAATAGTTGGTTTTACAATGGCAGAAGGGTCATTTTTTATAAAAAGTAATAAT [ 780] S: GACGGTTGTT TTCAATTGAAACAAAGAATGCATCCTAGTTTATTTGAATCATTTAAATTA [ 840] R: GACGGTTGTTTTCAATTGAAACAAAGAATGCATCCTAGTTTATTTGAATCATTTAAATTA [ 840] Figure A 3 Nucleotide sequence alignment of the cytochrome b gene between quinone outside inhibitor sensitive (S): EV 3 1S, VB RQF 3S, LOR ORI 1 3S, BL 17 4 3S, BLK 17 5 10S and resistant (R): LJ 1 8 2S, LJ 3 3 2S, R3Q26 F9 2S, R3Q33 1 1S, WM 1 3S isolates of Alternaria alternata. The primers locations are delimited by boxes. ion is shown by arrows. The star above the small box shows the restriction site recognized by the enzyme Fnu 4HI. The intron starts at position 158 and ends at position 1409. DTRcytb DTRcytb2 INTr

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150 S: GTGTTTGATACAAGTAGAAAGATAGATATTGAAAAAAATATGTATAATCAGTTTTCTGTA [ 900] R: GTGTTTGA TACAAGTAGAAAGATAGATATTGAAAAAAATATGTATAATCAGTTTTCTGTA [ 900] S: TCTTCCAAAGCTGACATACAAACTGTTATAAATTTCTTTTCTTTTTCAGGTTTACATTCT [ 960] R: TCTTCCAAAGCTGACATACAAACTGTTATAAATTTCTTTTCTTTTTCAGGTTTACATTCT [ 960] S: TTGATAGGACTTAAAGGTATTTCTTATATAAAATGATTAAATGATTTAAGAAATAGCAAT [1020] R: TTGATAGGACTTAAAGGTATTTCTTATATAAAATGATTAAATGATTTAAGAAATAGCAAT [1020] S: CGTTATGGTAATCTTAATTTTCCTTCCAACAAATAATTACATTCTTTCATTTTTATTTTC [1080] R: CGTTATGGTAATCTTAATTTTCCTTCCAACAAATAATTACA TTCTTTCATTTTTATTTTC [1080] S: TTTTATCTGTATTAATGGGCTCCTTTGAATGGTAACATTCAATAGGCAAATGGGGAGAAT [1140] R: TTTTATCTGTATTAATGGGCTCCTTTGAATGGTAACATTCAATAGGCAAATGGGGAGAAT [1140] S: TGCAAGAACATCTATAAATAATAACCTCCGATTTATAGATTACTTGCAGCGAAGCTTGAT [1200] R: TGCAAGAACAT CTATAAATAATAACCTCCGATTTATAGATTACTTGCAGCGAAGCTTGAT [1200] S: TCGGTATTATAAATGGATCAAGAACGTTCAACGACTAATGAGTGAGTAATACCAACAATA [1260] R: TCGGTATTATAAATGGATCAAGAACGTTCAACGACTAATGAGTGAGTAATACCAACAATA [1260] S: AGCTCGACACGAGTACCCCACAACCAATCATTAAAAACTATAGTTAATGATG CTTGGTTG [1320] R: AGCTCGACACGAGTACCCCACAACCAATCATTAAAAACTATAGTTAATGATGCTTGGTTG [1320] S: AAGACATAGTCTAAACACCAAATATATATAAAATTGGTGAAAATAGGGATTAAATGCCCT [1380] R: AAGACATAGTCTAAACACCAAATATATATAAAATTGGTGAAAATAGGGATTAAATGCCCT [1380] S: ATTAAAACGATTAATATTCGTT TATATCGTCATTTGAGGAGGTTTCAGTGTTAACAATGC [1440] R: ATTAAAACGATTAATATTCGTTTATATCGTCATTTGAGGAGGTTTCAGTGTTAACAATGC [1440] S: AACATTAAATAGATTCTTCTCATTACATTTCGTTTTACCTTTCGTATTAGCTGCTTTAGC [1500] R: AACATTAAATAGATTCTTCTCATTACATTTCGTTTTACCTTTCGTATTAGCTGCTTTAGC [1500] S: ACTAATGCACTTAATCGTTTTACACGATACAGCTGGATCAGGAAATCCTTTAGGTGTATC [1560] R: ACTAATGCACTTAATCGTTTTACACGATACAGCTGGATCAGGAAATCCTTTAGGTGTATC [1560] S: AGGAAACTATGAAAGAATATCTTTTGCTC [1589] R: AGGAAACTATGAAAGAATATCTTTTGCTC [1589] Figure A 3 Continued DTRcytb2r

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151 APPENDIX B SUPPLEMENTAL FIGURE FOR CHAPTER 3 Figure B 1. Frequency distribution of pyraclostrobin resistant Alternaria alternata isolates (n=471) collected during 2008 to 2012 from Florida citrus groves. Isolates were considered resistant when they grew i n complete medium in a resazurin based microtiter assay amended with pyraclostrobin at concentrations > 0.5 g/ml. Resistance fact or is expressed as the ratio of the effective concentrations needed to reduce fungal growth by 50% (EC 50 ) of a pyraclostrobin resistant isolate to the mean EC 50 for pyraclostrobin baseline population

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152 APPENDIX C SUPPLEMENTAL FIGURES FOR CHAPTER 5 1B MASIRAFTRLATQRTAVRPAVFSRGFASVNDVHARDPISKTAEKIAPDASRSPIPESKTSTIQEPEPSKD [ 70] 2B MASIRAFTRLATQRTAVRPAVFSRGFASVNDVHARDPISKTAEKIAPDASRSPIPESKTSTIQEPEPSKD [ 70] 3B MASIRAFTRLATQRTAVRPAVFSRGFASVNDVHARDPISKTAEKIAPDASRSPIPESKTSTIQEPEPSKD [ 70] 4B MASIRAFTRLATQRTAVRPAVFSRGFASVNDVHARDPISKTAEKIAPDASRSPIPESKTSTIQEPEPSKD [ 70] 5B MASIRAFTRLATQRTAVRPAVFSRGFASVNDVHARDPISKTAEKIAPDASRSPIPESKTSTIQEPEPSKD [ 70] 6B MASIRAF TRLATQRTAVRPAVFSRGFASVNDVHARDPISKTAEKIAPDASRSPIPESKTSTIQEPEPSKD [ 70] 7B MASIRAFTRLATQRTAVRPAVFSRGFASVNDVHARDPISKTAEKIAPDASRSPIPESKTSTIQEPEPSKD [ 70] 8B MASIRAFTRLATQRTAVRPAVFSRGFASVNDVHARDPISKTAEKIAPDASRSPIPESKTSTIQEPEPSKD [ 70] 9B MASIRAFTRLATQR TAVRPAVFSRGFASVNDVHARDPISKTAEKIAPDASRSPIPESKTSTIQEPEPSKD [ 70] 10B MASIRAFTRLATQRTAVRPAVFSRGFASVNDVHARDPISKTAEKIAPDASRSPIPESKTSTIQEPEPSKD [ 70] 11B MASIRAFTRLATQRTAVRPAVFSRGFASVNDVHARDPISKTAEKIAPDASRSPIPESKTSTIQEPEPSKD [ 70] 12B MASIRAFTRLATQRTAVRPAV FSRGFASVNDVHARDPISKTAEKIAPDASRSPIPESKTSTIQEPEPSKD [ 70] 13B MASIRAFTRLATQRTAVRPAVFSRGFASVNDVHARDPISKTAEKIAPDASRSPIPESKTSTIQEPEPSKD [ 70] 14B MASIRAFTRLATQRTAVRPAVFSRGFASVNDVHARDPISKTAEKIAPDASRSP T PESKTSTIQEPEPSKD [ 70] 15B MASIRAFTRLATQRTAVRPAVFSRGFAS VNDVHARDPISKTAEKIAPDASRSPIPESKTSTIQEPEPSKD [ 70] AaY16 MASIRAFTRLATQRTAVRPAVFSRGFASVNDVHARDPISKTAEKIAPDASRSPIPESKTSTIQEPEPSKD [ 70] ** 1B AKTKTFHIYRWNPDEPTSKPKM Q SYTLDLNKTGPMMLDALIRIKNEVDPTLTFRRSCREGICGSCAMNID [140] 2B AKTK TFHIYRWNPDEPTSKPKM Q L YTLDLNKTGPMMLDALIRIKNEVDPTLTFRRSCREGICGSCAMNID [140] 3B AKTKTFHIYRWNPDEPTSKPKM Q SYTLDLNKTGPMMLDALIRIKNEVDPTLTFRRSCREGICGSCAMNID [140] 4B AKTKTFHIYRWNPDEPTSKPKM Q SYTLDLNKTGPMMLDALIRIKNEVDPTLTFRRSCREGICGSCAMNID [140] 5B AKTKTFHIYRW NPDEPTSKPKM Q SYTLDLNKTGPMMLDALIRIKNEVDPTLTFRRSCREGICGSCAMNID [140] 6B AKTKTFHIYRWNPDEPTSKPKM Q SYTLDLNKTGPMMLDALIRIKNEVDPTLTFRRSCREGICGSCAMNID [140] 7B AKTKTFHIYRWNPDEPTSKPKM Q SYTLDLNKTGPMMLDALIRIKNEVDPTLTFRRSCREGICGSCAMNID [140] 8B AKTKTFHIYRWNPDEPTS KPKM Q SYTLDLNKTGPMMLDALIRIKNEVDPTLTFRRSCREGICGSCAMNID [140] 9B AKTKTFHIYRWNPDEPTSKPKM Q SYTLDLNKTGPMMLDALIRIKNEVDPTLTFRRSCREGICGSCAMNID [140] 10B AKTKTFHIYRWNPDEPTSKPKM Q SYTLDLNKTGPMMLDALIRIKNEVDPTLTFRRSCREGICGSCAMNID [140] 11B AKTKTFHIYRWNPDEPTSKPKM Q SYTLDLNKTGPMMLDALIRIKNEVDPTLTFRRSCREGICGSCAMNID [140] 12B AKTKTFHIYRWNPDEPTSKPKM Q SYTLDLNKTGPMMLDALIRIKNEVDPTLTFRRSCREGICGSCAMNID [140] 13B AKTKTFHIYRWNPDEPTSKPKM Q SYTLDLNKTGPMMLDALIRIKNEVDPTLTFRRSCREGICGSCAMNID [140] 14B AKTKTFHIYRWNPDEPTSKPKM Q SYTLDLN KTGPMMLDALIRIKNEVDPTLTFRRSCREGICGSCAMNID [140] 15B AKTKTFHIYRWNPDEPTSKPKM Q SYTLDLNKTGPMMLDALIRIKNEVDPTLTFRRSCREGICGSCAMNID [140] AaY16 AKTKTFHIYRWNPDEPTSKPKMRSYTLDLNKTGPMMLDALIRIKNEVDPTLTFRRSCREGICGSCAMNID [140] Figure C 1 Amino acid alignment of the succinate dehydrogenase subunit B (SDHB) from Alternaria alternata isolates The star above the gray box shows the amino acid replacement.

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153 1B GVNTLACLCRIPTDTTKESRIYPLPHMYVVKDLVP DMTLFYKQYRSVKPYLQRTTAAPDGREFRQS R EDR [210] 2B GVNTLACLCRIPTDTTKESRIYPLPHMYVVKDLVPDMTLFYKQYRSVKPYLQRTTAAPDGREFRQSKEDR [210] 3B GVNTLACLCRIPTDTTKESRIYPLPHMYVVKDLVPDMTLFYKQYRSVKPYLQRTTAAPDGREFRQSKEDR [210] 4B GVNTLACLCRIPTDTTKESRIYPLPHMYVVKDLVPDMTLFYK QYRSVKPYLQRTTAAPDGREFRQSKEDR [210] 5B GVNTLACLCRIPTDTTKESRIYPLPHMYVVKDLVPDMTLFYKQYRSVKPYLQRTTAAPDGREFRQSKEDR [210] 6B GVNTLACLCRIPTDTTKESRIYPLPHMYVVKDLVPDMTLFYKQYRSVKPYLQRTTAAPDGREFRQSKEDR [210] 7B GVNTLACLCRIPTDTTKESRIYPLPHMYVVKDLVPDMTLFYKQYRSVKP YLQRTTAAPDGREFRQSKEDR [210] 8B GVNTLACLCRIPTDTTKESRIYPLPHMYVVKDLVPDMTLFYKQYRSVKPYLQRTTAAPDGREFRQSKEDR [210] 9B GVNTLACLCRIPTDTTKESRIYPLPHMYVVKDLVPDMTLFYKQYRSVKPYLQRTTAAPDGREFRQSKEDR [210] 10B GVNTLACLCRIPTDTTKESRIYPLPHMYVVKDLVPDMTLFYKQYRSVKPYLQRTTA APDGREFRQSKEDR [210] 11B GVNTLACLCRIPTDTTKESRIYPLPHMYVVKDLVPDMTLFYKQYRSVKPYLQRTTAAPDGREFRQSKEDR [210] 12B GVNTLACLCRIPTDTTKESRIYPLPHMYVVKDLVPDMTLFYKQYRSVKPYLQRTTAAPDGREFRQSKEDR [210] 13B GVNTLACLCRIPTDTTKESRIYPLPHMYVVKDLVPDMTLFYKQYRSVKPYLQRTTAAPDGREF RQSKEDR [210] 14B GVNTLACLCRIPTDTTKESRIYPLPHMYVVKDLVPDMTLFYKQYRSVKPYLQRTTAAPDGREFRQSKEDR [210] 15B GVNTLACLCRIPTDTTKESRIYPLPHMYVVKDLVPDMTLFYKQYRSVKPYLQRTTAAPDGREFRQSKEDR [210] AaY16 GVNTLACLCRIPTDTTKESRIYPLPHMYVVKDLVPDMTLFYKQYRSVKPYLQRTTAAPDGREFRQSKEDR [210] 1B KKLDGLYECILCACCSTSCPSYWWNQEEYLGPAVLLQSYRWIADSRDEKKAERQDALNNSMSLYRCHTIL [280] 2B KKLDGLYECILCACCSTSCPSYWWNQEEYLGPAVLLQSYRWIADSRDEKKAERQDALNNSMSLYRCHTIL [280] 3B KKLDGLYECILCACCSTSCPSYWWNQEEYLGPAVLLQSYRWIADSRDEKKAERQDALNNSMS LYRCHTIL [280] 4B KKLDGLYECILCACCSTSCPSYWWNQEEYLGPAVLLQSYRWIADSRDEKKAERQDALNNSMSLYRCHTIL [280] 5B KKLDGLYECILCACCSTSCPSYWWNQEEYLGPAVLLQSYRWIADSRDEKKAERQDALNNSMSLYRCHTIL [280] 6B KKLDGLYECILCACCSTSCPSYWWNQEEYLGPAVLLQSYRWIADSRDEKKAERQDALNNSMSLYRCHTI L [280] 7B KKLDGLYECILCACCSTSCPSYWWNQEEYLGPAVLLQSYRWIADSRDEKKAERQDALNNSMSLYRCHTIL [280] 8B KKLDGLYECILCACCSTSCPSYWWNQEEYLGPAVLLQSYRWIADSRDEKKAERQDALNNSMSLYRCHTIL [280] 9B KKLDGLYECILCACCSTSCPSYWWNQEEYLGPAVLLQSYRWIADSRDEKKAERQDALNNSMSLYRCHTIL [280] 10B KKLDGLYECILCACCSTSCPSYWWNQEEYLGPAVLLQSYRWIADSRDEKKAERQDALNNSMSLYRCHTIL [280] 11B KKLDGLYECILCACCSTSCPSYWWNQEEYLGPAVLLQSYRWIADSRDEKKAERQDALNNSMSLYRCHTIL [280] 12B KKLDGLY G CILCACCSTSCPSYWWNQEEYLGPAVLLQSYRWIADSRDEKKAERQDALNNSMSLYRCHTIL [280] 13B KKLDGLYECILCACCSTSCPSYWWNQEEYLGPAVLLQSYRWIADSRDEKKAERQDALNNSMSLYRCHTIL [280] 14B KKLDGLYECILCACCSTSCPSYWWNQEEYLGPAVLLQSYRWIADSRDEKKAERQDALNNSMSLYRCHTIL [280] 15B KKLDGLYECILCACCSTSCPSYWWNQEEYLGPAVLLQSYRWIADSRDEKKAERQDALNNSMSLYRCHTIL [280] AaY16 KKLDGLY ECILCACCSTSCPSYWWNQEEYLGPAVLLQSYRWIADSRDEKKAERQDALNNSMSLYRCHTIL [280] 1B NCSRTCPKGLNPALAIAEIK KSMAFT [306 ] 2B NCSRTCPKGLNPALAIAEIKKSMAFT [306 ] 3B NCSRTCPKGLNPALAIAEIKKSMAFT [306 ] 4B NCSRTCPKGLNPALAIAEIKKSMAFT [306 ] 5B NCSRTCPKGLNPALAIAEIKKSM AFT [306 ] 6B NCSRTCPKGLNPALAIAEIKKSMAFT [306 ] 7B NCSRTCPKGLNPALAIAEIKKSMAFT [306 ] 8B NCSRTCPKGLNPALAIAEIKKSMAFT [306 ] 9B NCSRTCPKGLNPALAIAEIKKSMAFT [306 ] 10B NCSRTCPKGLNPALAIAEIKKSMAFT [306 ] 11B NCSRTCPKGLNPALAIAEIKKSMAFT [306 ] 12B NCSRTCPKGLNPALAIAEIKKSMAFT [306 ] 13B NCSRTCPKGLNPALAIAEIKKSMAFT [306 ] 14B NCSRTCPKGLNPALAIAEIKKSMAFT [306 ] 15B NCSRTCPKGLNPALAIAEIKKSMAFT [306 ] AaY16 NCSRTCPKGLNPALAIAEIKKSMAFT [306 ] Figure C 1 Continued.

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154 1C MASQRVFQLGLRRAAAPSLRVQPAGRMVQRRLAA TEHASQSEAAEILAKQRVNRPVSPHLAIYKPQITWY [ 70] 2C MASQRVFQLGLRRAAAPSLRVQPAGRMVQRRLAATEHASQSEAAEILAKQRVNRPVSPHLAIYKPQITWY [ 70] 3C MASQRVFQLGLRRAAAPSLRVQPAGRMVQRRLAATEHASQSEAAEILAKQRVNRPVSPHLAIYKPQITWY [ 70] 4C MASQRVFQLGLRRAAAPSLRVQPAGRMVQRRLAATEHASQS EAAEILAKQRVNRPVSPHLAIYKPQITWY [ 70] 5C MASQRVFQLGLRRAAAPSLRVQPAGRMVQRRLAATEHASQSEAAEILAKQRVNRPVSPHLAIYKPQITWY [ 70] 6C MASQRVFQLGLRRAAAPSLRVQPAGRMVQRRLAATEHASQSEAAEILAKQRVNRPVSPHLAIYKPQITWY [ 70] 7C MASQRVFQLGLRRAAAPSLRVQPAGRMVQRRLAATEHASQSEAAEILA KQRVNRPVSPHLAIYKPQITWY [ 70] 8C MASQRVFQLGLRRAAAPSLRVQPAGRMVQRRLAATEHASQSEAAEILAKQRVNRPVSPHLAIYKPQITWY [ 70] 9C MASQRVFQLGLRRAAAPSLRVQPAGRMVQRRLAATEHASQSEAAEILAKQRVNRPVSPHLAIYKPQITWY [ 70] 10C MASQRVFQLGLRRAAAPSLRVQPAGRMVQRRLAATEHASQSEAAEILAKQRVNRP VSPHLAIYKPQITWY [ 70] 11C MASQRVFQLGLRRAAAPSLRVQPAGRMVQRRLAATEHASQSEAAEILAKQRVNRPVSPHLAIYKPQITWY [ 70] 12C MASQRVFQLGLRRAAAPSLRVQPAGRMVQRRLAATEHASQSEAAEILAKQRVNRPVSPHLAIYKPQITWY [ 70] 13C MASQRVFQLGLRRAAAPSLRVQPAGRMVQRRLAATEHASQSEAAEILAKQRVNRPVSPHLAI YKPQITWY [ 70] 14C MASQRVFQLGLRRAAAPSLRVQPAGRMVQRRLAATEHASQSEAAEILAKQRVNRPVSPHLAIYKPQITWY [ 70] 15C MASQRVFQLGLRRAAAPSLRVQPAGRMVQRRLAATEHASQSEAAEILAKQRVNRPVSPHLAIYKPQITWY [ 70] AaY16 MASQRVFQLGLRRAAAPSLRVQPAGRMVQRRLAATEHASQSEAAEILAKQRVNRPVSPHLAIYKPQITWY [ 70] ** 1C ASSLNRITGITLSGSLYLFGIAYLIAPYTGWHLETQSMVATVAAWPAAVKAGLKAFYAFPFFFHSFNGLR [140] 2C ASSLNRITGITLSGSLYLFGIAYLIAPYTGWHLETQSMVATVAAWPAAVKAGLKAFYAFPFFFHSFNGLR [140] 3C ASSLNRITGITLSGSLYLFGIAYLIAPYTGWHLETQSMVATVAAWPAAVKAGLKAFYAFPFFFHSFNGLR [140] 4C ASSLNRITGITLS S SLYLFGIAYLIAPYTGWHLETQSMVATVAAWPAAVKAGLKAFYAF A FFFHSFNGLR [140] 5C ASSLNRI TGITLSGSLYLFGIAYLIAPYTGWHLETQSMVATVAAWPAAVKAGLKAFYAFPFFFHSFNGLR [140] 6C ASSLNRITGITLSGSLYLFGIAYLIAPYTGWHLETQSMVATVAAWPAAVKAGLKAFYAFPFFFHSFNGLR [140] 7C ASSLNRITGITLSGSLYLFGIAYLIAPYTGWHLETQSMVATVAAWPAAVKAGLKAFYAFPFFFHSFNGLR [140] 8C ASSLNRITGITLSG SLYLFGIAYLIAPYTGWHLETQSMVATVAAWPAAVKAGLKAFYAFPFFFHSFNGLR [140] 9C ASSLNRITGITLSGSLYLFGIAYLIAPYTGWHLETQSMVATVAAWPAAVKAGLKAFYAFPFFFHSFNGLR [140] 10C ASSLNRITGITLSGSLYLFGIAYLIAPYTGWHLETQSMVATVAAWPAAVKAGLKAFYAFPFFFHSFNGLR [140] 11C ASSLNRITGITLSGSLYLFGI AYLIAPYTGWHLETQSMVATVAAWPAAVKAGLKAFYAFPFFFHSFNGLR [140] 12C ASSLNRITGITLSGSLYLFGIAYLIAPYTGWHLETQSMVATVAAWPAAVKAGLKAFYAFPFFFHSFNGLR [140] 13C ASSLNRITGITLSGSLYLFGIAYLIAPYTGWHLETQSMVATVAAWPAAVKAGLKAFYAFPFFFHSFNGLR [140] 14C ASSLNRITGITLSGSLYLFGIAYLIAPY TGWHLETQSMVATVAAWPAAVKAGLKAFYA L PFFFHSFNGLR [140] 15C ASSLNRITGITLSGSLYLFGIAYLIAPYTGWHLETQSMVATVAAWPAAVKAGLKAFYAFPFFFHSFNGLR [140] AaY16 ASSLNRITGITLSGSLYLFGIAYLIAPYTGWHLETQSMVATVAAWPAAVKAGLKAFYAFPFFFHSFNGLR [140] * 1C HLAWDVGIGFKNQQVIRT GWTAVGLTVAFSLYYTFLGW [178] 2C HLAWDVGIGFKNQQVIRTGWTAVGLTVAFSLYYTFLGW [178] 3C HLAWDVGIGFKNQQVIRTGWTAVGLTVAFSLYYTFLGW [178] 4C HLAWDVGIGFKNQQVIRTGWTAVGLTVAFSLYYTFLGW [178] 5C HLAWDVGIGFKNQQVIRTGWTAVGLTVAFSLYYTFLGW [178] 6C HLAWDVGIGFKNQQVIRTG WTAVGLTVAFSLYYTFLGW [178] 7C HLAWDVGIGFKNQQVIRTGWTAVGLTVAFSLYYTFLGW [178] 8C HLAWDVGIGFKNQQVIRTGWTAVGLTVAFSLYYTFLGW [178] 9C HLAWDVGIGFKNQQVIRTGWTAVGLTVAFSLYYTFLGW [178] 10C HLAWDVGIGFKNQQVIRTGWTAVGLTVAFSLYYTFLGW [178] 11C HLAW G VGIGFKNQQVIRTGWTAVGLTVAFSLYYTFLGW [178] 12C HLAWDVGIG Y KNQQVIRTGWTAVGLTVAFSLYYTFLGW [178] 13C HLAWDVGIGFKNQQVIRTGWTAVGLTVAFSLYYTFLGW [178] 14C HLAWDVGIGFKNQQVIRTGWTAVGLTVAFSLYYTFLGW [178] 15C HLAWDVGIGFKNQQVIRTGWTAVGLTVAFSLYYTFLGW [178] AaY16 HLAWDV GIGFKNQQVIRTGWTAVGLTVAFSLYYTFLGW [178] Figure C 2 Amino acid alignment of the succinate dehydrogenase subunit C (SDHC) from Alternaria alternata isolates The star above the gray box shows the amino acid replacement.

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155 ** * * * 1D MASVMRPGLLRQACPPVQQSQR T LSTATSTMNRPLVQQLRPAFQRS A IQKSTRIAAFH V TQRNQILPPLP [ 70] 2D MASVMRPGLLRQACPPV H QSQRMLSTA A ST I NRPLVQQLRPAFQRS T IQKSTRIAAFHATQRNQILPPLP [ 70] 3D MASVMRPGLLRQACPPV H QSQRMLSTA A ST I NRPLVQQLRPAFQRS T IQKSTR IAA L HATQRNQILPPLP [ 70] 4D MASVMRPGLLRQACPPVQQSQRMLSTATSTMNRPLVQQLRPAFQRS A IQKSTRIAAFHATQRNQILPPLP [ 70] 5D MASVMRPGLLRQACPPV H QSQRMLSTA A STINRPLVQQLRPAFQRS T IQKSTRIAAFHATQRNQILPPLP [ 70] 6D MASVMRPGLLRQACPP A H QSQRMLSTATSTMNRPLVQQLRPAFQRS T IQKSTRIAAFHAT QRNQILPPLP [ 70] 7D MASVMRPGLLRQACPP A H QSQRMLSTATSTMNRPLVQQLRPAFQRS T IQKSTRIAAFHATQRNQILPPLP [ 70] 8D MASVMRPGLLRQACPPVQQSQRMLSTATSTMNRPLVQQLRPAFQRS A IQKSTRIAAFHATQRNQILPPLP [ 70] 9D MASVMRPGLLRQACPPVQQSQRMLSTATSTMNRPLVQQLRPAFQRS A IQKSTRIAAFHATQRNQILPPLP [ 70] 10D MASVMRPGLLRQACPP A H QSQRMLSTATSTMNRPLVQQLRPAFQRS T IQKSTRIAAFHATQRNQILPPLP [ 70] 11D MASVMRPGLLRQACPPV H QSQRMLSTA A ST I NRPLVQQLRPAFQRS T IQKSTRIAAFHATQRNQILPPLP [ 70] 12D MASVMRPGLLRQACPPV H QSQRMLSTA A ST I NRPLVQQLRPAFQRS T IQKSTRI AAFHATQRNQILPPLP [ 70] 13D MASVMRPGLLRQACPPV H QSQRMLSTA A ST I NRPLVQQLRPAFQRS T IQKSTRIAAFHATQRNQILPPLP [ 70] 14D MASVMRPGLLRQACPP A H QSQRMLSTATSTMNRPLVQQLRPAFQRS T IQKSTRIAAFHATQRNQILPPLP [ 70] 15D MASVMRPGLLRQACPPV H QSQRMLSTA A ST I NRPLVQQLRPAFQRS T IQKSTRIAAFHATQ RNQILPPLP [ 70] AaY16 MASVMRPGLLRQACPPVQQSQRMLSTATSTMNRPLVQQLRPAFQRS A IQKSTRIAAFHATQRNQILPPLP [ 70] *** 1D QKIIGTTNDPVPVPDPDYAHGSYHWSFERIVSAGLIPLTIAPFAAGSLNPLTDSILCALLVVHSHIGFES [140] 2D QKIIGTTNDPVPVPDPDYAHGSYHWSFERIVSAGLIPLTIAPFAAGSLNPLTDSILCALLVVHSHIGFES [140] 3D QKIIGTTNDPVPVPDPDYAHGSYHWSFERIVSAGLIPLTIAPFAAGSLNPLTDSILCALLVVHSHIGFES [140] 4D QKIIGTTNDPVPVPDPDYAHGSYHWSFERIVSAGLIPLTIAPFAAGSLNPLTDSILCALLVVHSHIGFES [140] 5D QKIIGT TNDPVPVPDPDYAHGSYHWSFERIVSAGLIPLTIAPFAAGSLNPLTDSILCALLV A HSHIGFES [140] 6D QKIIGTTNDPVPVPDPDYAHGSYHWSFERIVSAGLIPLTIAPFAAGSLNPLTDSILCAL Q VVHSHIGFES [140] 7D QKIIGTTNDPVPVPDPDYAHGSYHWSFERIVSAGLIPLTIAPFAAGSLNPLTDSILCALLVVHSHIGFES [140] 8D QKIIGTTNDPVPV PDPDYAHGSYHWSFERIVSAGLIPLTIAPFAAGSLNPLTDSILCALL A VHSHIGFES [140] 9D QKIIGTTNDPVPVPDPDYAHGSYHWSFERIVSAGLIPLTIAPFAAGSLNPLTDSILCALLVVHSHIGFES [140] 10D QKIIGTTNDPVPVPDPDYAHGSYHWSFERIVSAGLIPLTIAPFAAGSLNPLTDSILCALLVVHSHIGFES [140] 11D QKIIGTTNDPVPVPDPDYAH GSYHWSFERIVSAGLIPLTIAPFAAGSLNPLTDSILCALLVVHSHIGFES [140] 12D QKIIGTTNDPVPVPDPDYAHGSYHWSFERIVSAGLIPLTIAPFAAGSLNPLTDSILCALLVVHSHIGFES [140] 13D QKIIGTTNDPVPVPDPDYAHGSYHWSFERIVSAGLIPLTIAPFAAGSLNPLTDSILCALLVVHSHIGFES [140] 14D QKIIGTTNDPVPVPDPDYAHGSYHWSF ERIVSAGLIPLTIAPFAAGSLNPLTDSILCALLVVHSHIGFES [140] 15D QKIIGTTNDPVPVPDPDYAHGSYHWSFERIVSAGLIPLTIAPFAAGSLNPLTDSILCALLVVHSHIGFES [140] AaY16 QKIIGTTNDPVPVPDPDYAHGSYHWSFERIVSAGLIPLTIAPFAAGSLNPLTDSILCALLVVHSHIGFES [140] 1D CIIDYFPSKRV PKTRTAAMWALRAGTVALGLALYSFETNDVGITEAVARLWHA [193 ] 2D CIIDYFPSKRVPKTRTAAMWALRAGTVALGLALYSFETNDVGITEAVARLWHA [193 ] 3D CIIDYFPSKRVPKTRTAAMWALRAGTVALGLALYSFETNDVGITEAVARLWHA [193 ] 4D CIIDYFPSKRVPKTRTAAMWALRAGTVALGLALYSFETNDVGITEAVARLWHA [193 ] 5D CII DYFPSKRVPKTRTAAMWALRAGTVALGLALYSFETNDVGITEAVARLWHA [193 ] 6D CIIDYFPSKRVPKTR A AAMWALRAGTVALGLALYSFETNDVGITEAVARLWHA [193 ] 7D CIIDYFPSKRVPKTR A AAMWALRAGTVALGLALYSFETNDVGITEAVARLWHA [193 ] 8D CIIDYFPSKRVPKTRTAAMWALRAGTVALGLALYSFETNDVGITEAVARLWHA [193 ] 9 D CIIDYFPSKRVPKTRTAAMWALRAGTVALGLALYSFETNDVGITEAVARLWHA [193 ] 10D CIIDYFPSKRVPKTR A AAMWALRAGTVALGLALYSFETNDVGITEAVARLWHA [193 ] 11D CIIDYFPSKRVPKTRTAAMWALRAGTVALGLALYSFETNDVGITEAVARLWHA [193 ] 12D CIIDYFPSKRVPKTRTAAMWALRAGTVALGLALYSFETNDVGITEAVARLWHA [193 ] 13D CIIDYFPSKRVPKTRTAAMWALRAGTVALGLALYSFETNDVGITEAVARLWHA [193 ] 14D CIIDYFPSKRVPKTR A AAMWALRAGTVALGLALYSFETNDVGITEAVARLWHA [193 ] 15D CIIDYFPSKRVPKTRTAAMWALRAGTVALGLALYSFETNDVGITEAVARLWHA [193 ] AaY16 CIIDYFPSKRVPKTRTAAMWALRAGTVALGLALYSFETNDVGITEAVARLWHA [193] Figure C 3 Amino acid alignment of the succinate dehydrogenase subunit D (SDHD) from Alternaria alternata isolates The star above the gray box shows the amino acid replacement.

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172 BIOGRAPHICAL SKETCH Byron Vega was born in Q uito, Ecuador, in 1976. He obtained the tittle of Agronomist Engineer from the Central University of Ecuador in 2002. While still at the University, he got involved in research and development activities in BASF Ecuatoriana, where he first started working in disease management programs in ornamentals and vegetables. From 2004 to 2006, Byron was lecturer of basic statistics and laboratory of Microbiology at Agronomy Department, Central University of Ecuador. In 2006, he was admitted for the Ma ster of Science program in the Crop P rotection department at University of Puerto Rico, under the supervision of Dr. Consuelo Estvez de Jensen. During his m aster he was involved in several research projects, but mainly focused on the etiology of the American soybean rust, caused by Phakopsora meibomiae In 2009, he joined to the Citrus R esearch and Education Center (CREC) at University of Florida, to pursue a PhD degree in plant pathology. Under the guidance of Dr. Megan M. Dewdney he conducted research on phenotypic and molecular characterization of resistance to respiration inhibitor fungicides in Alternaria alternata a necrotrophic fungal pathogen of citrus.