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Genetics of Tree Architecture in Peach (Prunus persica (L.) Batsch)

Permanent Link: http://ufdc.ufl.edu/UFE0043530/00001

Material Information

Title: Genetics of Tree Architecture in Peach (Prunus persica (L.) Batsch)
Physical Description: 1 online resource (150 p.)
Language: english
Creator: Carrillo-Mendoza, Omar
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2012

Subjects

Subjects / Keywords: branching -- breeding -- development -- meristem -- paradormancy -- pruning -- sequencing
Horticultural Science -- Dissertations, Academic -- UF
Genre: Horticultural Science thesis, Ph.D.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: Little effort has been made to understand the genetic control of tree architecture in peach. In addition, the occurrence of blind nodes is a critical factor that affects peach tree architecture and productivity in subtropical climates. In this study, a branching index was developed to facilitate the assessment of branching intensity of the trees. Seven backcross families were developed using 'Flordaguard' peach x P. kansuensis or 'Tardy Nonpareil' almond F1s backcrossed to 'AP00-30wbs', 'UFSharp' or 'UF97-47' peach selections and evaluated for branching index and blind node frequency during the winters of 2010 and 2011. P. kansuensis backcrosses presented increased branching and lower blind node incidence whereas almond backcrosses presented less branching and higher blind node incidence, resembling the P. kansuensis and almond F1 parents. There was also broad variability for branching and blind nodes within the P. kansuensis and TNP almond backcross families influenced by the peach parents that were used to generate the backcross populations. The moderate heritability and year-to-year correlation for these traits indicate that they are affected by the environment, but selection for reduced branching and lower blind node incidence is feasible. SSRs and a set of 14 candidate genes related with branching and bud development in Arabidopsis were used to map QTLs associated with these two traits in the seven backcrosses. SNPs were found within the candidate gene sequences in the different Prunus parents. Genetic maps containing the selected SSRs and candidate genes were obtained for each backcross family and a combined map for all the P. kansuensis families and all the almond families. Branching and blind nodes QTL were detected in the individual backcross family analysis, and the combined P. kansuensis and 'Tardy Nonpareil' almond families analysis. The candidate genes tested did not map to the location of the major QTLs, PpCUC1 and PpBRC2 mapped to minor QTL for branching and blind nodes, respectively. The QTLs found in this study represent the first steps toward marker assisted selection for reduced branching and reduced incidence of blind nodes in commercial peach cultivars.
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.
Statement of Responsibility: by Omar Carrillo-Mendoza.
Thesis: Thesis (Ph.D.)--University of Florida, 2012.
Local: Adviser: Chaparro, Jose.
Electronic Access: RESTRICTED TO UF STUDENTS, STAFF, FACULTY, AND ON-CAMPUS USE UNTIL 2012-11-30

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2012
System ID: UFE0043530:00001

Permanent Link: http://ufdc.ufl.edu/UFE0043530/00001

Material Information

Title: Genetics of Tree Architecture in Peach (Prunus persica (L.) Batsch)
Physical Description: 1 online resource (150 p.)
Language: english
Creator: Carrillo-Mendoza, Omar
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2012

Subjects

Subjects / Keywords: branching -- breeding -- development -- meristem -- paradormancy -- pruning -- sequencing
Horticultural Science -- Dissertations, Academic -- UF
Genre: Horticultural Science thesis, Ph.D.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: Little effort has been made to understand the genetic control of tree architecture in peach. In addition, the occurrence of blind nodes is a critical factor that affects peach tree architecture and productivity in subtropical climates. In this study, a branching index was developed to facilitate the assessment of branching intensity of the trees. Seven backcross families were developed using 'Flordaguard' peach x P. kansuensis or 'Tardy Nonpareil' almond F1s backcrossed to 'AP00-30wbs', 'UFSharp' or 'UF97-47' peach selections and evaluated for branching index and blind node frequency during the winters of 2010 and 2011. P. kansuensis backcrosses presented increased branching and lower blind node incidence whereas almond backcrosses presented less branching and higher blind node incidence, resembling the P. kansuensis and almond F1 parents. There was also broad variability for branching and blind nodes within the P. kansuensis and TNP almond backcross families influenced by the peach parents that were used to generate the backcross populations. The moderate heritability and year-to-year correlation for these traits indicate that they are affected by the environment, but selection for reduced branching and lower blind node incidence is feasible. SSRs and a set of 14 candidate genes related with branching and bud development in Arabidopsis were used to map QTLs associated with these two traits in the seven backcrosses. SNPs were found within the candidate gene sequences in the different Prunus parents. Genetic maps containing the selected SSRs and candidate genes were obtained for each backcross family and a combined map for all the P. kansuensis families and all the almond families. Branching and blind nodes QTL were detected in the individual backcross family analysis, and the combined P. kansuensis and 'Tardy Nonpareil' almond families analysis. The candidate genes tested did not map to the location of the major QTLs, PpCUC1 and PpBRC2 mapped to minor QTL for branching and blind nodes, respectively. The QTLs found in this study represent the first steps toward marker assisted selection for reduced branching and reduced incidence of blind nodes in commercial peach cultivars.
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.
Statement of Responsibility: by Omar Carrillo-Mendoza.
Thesis: Thesis (Ph.D.)--University of Florida, 2012.
Local: Adviser: Chaparro, Jose.
Electronic Access: RESTRICTED TO UF STUDENTS, STAFF, FACULTY, AND ON-CAMPUS USE UNTIL 2012-11-30

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2012
System ID: UFE0043530:00001


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1 GENETICS OF TREE ARCHITECTURE IN PEACH ( Prunus persica (L.) Batsch) By OMAR CARRILLO MENDOZA 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 2012

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2 2012 Omar Carrillo Mendoza

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3 To my wife Patricia and my Mom Marcela with love

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4 ACKNOWLEDGMENTS I am thankful to my advisor Dr. Jose Chaparro and retired professor Dr. Wayne Sherma n, it has been a pleasure to learn from them and be part of the Stone Fruit Breeding Program. To the members of my committee: Dr. Rebecca Darnell, Dr. Kevin Folta, Dr. Matias Kirst and Dr. Jeffrey Williamson for all the guidance during my research. To Dr. James W. Olmstead for allowing me and Patricia for teaching me how to use the real time PCR machine. To Bruce Topp, Jean Clement Marceillou, Jose Gandia, Jorge Rodriguez, Mohamed Benzit, Paul Lyrene and Thomas Beckman for sharing their experience. To Mark Gal, Cecil Shine, and John Thomas for their valuable help on the farm. To Valerie for her support in the lab. To Elia Ulivi and Dario Chavez for helping me to take field data. To my friends, Andres, Aparna, Divya, Marga, Mitra, Octavio, Preeti Silvia,Yuan and especially Kendra for their friendship and kindness. To my Mexican fellows : Alberto, Aurora, Miriam, Nicacio, Oscar, Paola, Paula and Sebastian for helping me to adjust to my new home and reminding me my beloved home country. I am especially grateful to CONACYT and the people of Mexico for granting me with a scholarship that made possible this achievement.

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5 TABLE OF CONTENTS page ACKNOWLEDGMENTS ................................ ................................ ................................ .. 4 LIST O F TABLES ................................ ................................ ................................ ............. 7 LIST OF FIGURES ................................ ................................ ................................ ........ 10 LIST OF ABBREVIATIONS ................................ ................................ ........................... 12 ABSTRACT ................................ ................................ ................................ .................... 14 CHAPTER 1 LITERATURE REVIEW ................................ ................................ ........................... 16 Introduction ................................ ................................ ................................ .............. 1 6 Plant Architecture ................................ ................................ ................................ .... 16 Axillary Meristem Development and Branching ................................ ....................... 17 Apical Dominance ................................ ................................ ................................ .... 18 Plant Architecture and Agriculture ................................ ................................ ........... 20 Temperate Fruit Tree Architecture ................................ ................................ .......... 20 Peach Tree Architecture ................................ ................................ .......................... 22 2 DEVELOPMENT OF A BRANCHING INDEX FOR EVALUATION OF PEACH SEEDLINGS USING INTERSPECIFIC HYBRIDS ................................ ..... 26 Introduction ................................ ................................ ................................ .............. 26 Materials and Methods ................................ ................................ ............................ 27 Branching Index Formula ................................ ................................ .................. 27 Plant Material ................................ ................................ ................................ .... 29 Data Collection ................................ ................................ ................................ .. 29 Statistical Analysis ................................ ................................ ............................ 30 Results and Discussion ................................ ................................ ........................... 30 3 BRANCHING AND BLIND NODE INCIDENCE IN INTERSPECIFIC BACKCROSS FAMILIES OF PEACH ................................ ................................ ..... 44 Introduction ................................ ................................ ................................ .............. 44 Branching in different Prunus species ................................ ............................... 44 Blind nodes in peach ................................ ................................ ......................... 46 Materials and Methods ................................ ................................ ............................ 48 Plant Material ................................ ................................ ................................ .... 48 Plant Management ................................ ................................ ............................ 48 Branching Index Data Collection ................................ ................................ ....... 49 Blind node data collection ................................ ................................ ................. 50

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6 Identification of Selfs ................................ ................................ ......................... 50 Statistical Analysis ................................ ................................ ............................ 51 Results and Discussion ................................ ................................ ........................... 52 Branching Index ................................ ................................ ................................ 52 Blind Nodes ................................ ................................ ................................ ....... 55 Heritability for Branching and Blind Nodes ................................ ........................ 57 4 MAPPING CANDIDATE GENES and QTLs ASSOCIATED WITH BRANCING AND BLIND NODES IN Prunus sp. INT ERSPECIFIC BACKCROSS FAMILIES ................................ ................................ ......................... 66 Introduction ................................ ................................ ................................ .............. 66 Materials and Methods ................................ ................................ ............................ 71 Plant Material ................................ ................................ ................................ .... 71 DNA Extraction ................................ ................................ ................................ 72 Candidate Gene Primer Design ................................ ................................ ........ 73 Branching Index Data Collection ................................ ................................ ....... 73 Blind Node Data Collection ................................ ................................ ............... 73 Candidate Gene Primer PCR Optimization ................................ ....................... 74 Candidate Gene Sequencing ................................ ................................ ............ 74 Genotyping ................................ ................................ ................................ ........ 75 SSR markers ................................ ................................ .............................. 75 Candidate gene genotyping with restriction enzymes ................................ 76 Candidate gene genotyping with high resolution melt analysis ................... 77 Statistical Analysis ................................ ................................ ............................ 77 Results and Discussion ................................ ................................ ........................... 78 Phenotypic Differences within and amo ng Backcross Families ........................ 78 Polymorphism in Branching and Blind Node Candidate Genes ........................ 79 Genetic Maps ................................ ................................ ................................ .... 82 Branching Index QTLs ................................ ................................ ...................... 86 Blind Node QTLs ................................ ................................ ............................... 88 Allelic effects from QTLs ................................ ................................ ................... 89 Relationships between Branching and Blind Node QTLs ................................ .. 91 QTLs Detection by Candidate Genes ................................ ............................... 92 5 CONCLUSIONS ................................ ................................ ................................ .... 110 APPENDIX: COMPLEMENTARY TABLES AND FIGURES ................................ ........ 115 LIST OF REFERENCES ................................ ................................ .............................. 136 BIOGRAPHICAL SKETCH ................................ ................................ .......................... 150

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7 LIST OF TABLES Table page 2 1 Mean total branch number per tree and branching index values in peach x almond and peach x P. kansuensis F1 hybrid populations. ................... 36 2 2 Mean number of first order branches, and the mean number of second, third and fourth order branches. ................................ ............................ 36 2 3 Mean total branch number per tree and branching index means for first, second, third and fourth order branching clusters ................................ ....... 37 3 1 Total number of p rogeny and number of contaminating self pollinated progeny in the interspecific backcross families ................................ ................ 60 3 2 Mean branching index (BI) and blind node incidence values for the main axis (BNM) and lateral branches (BNL) ................................ .................... 60 3 3 Mean branching index (BI) and blind node incidence values for the main axis (BNM) and lateral branches (BNL). ................................ ..................... 60 3 4 Mean branching index (BI) and blind node incidence for the main axis (BNM) and lateral branches (BNL) in the interspecific backcross ...................... 61 3 5 Orthagonal contrasts of backcross families by parent for branching index (BI) and blind node incidence in the main axis (BNM) .............................. 61 3 6 Mean bran ching index (BI) and blind node incidence values for the main axis (BNM) and lateral branches (BNL) in the interspecific backcross .. ................................ ................................ ................................ .......... 61 3 7 Orthagonal contrasts of b ackcross families by parent for branching index (BI) and blind node in cidence in the main axis (BNM) .............................. 62 3 8 Covariates measured in the inter specific backcross families (winter of 2010). ................................ ................................ ................................ ................. 62 3 9 Covariates measured in the interspecific backcross f amilies (winter of 2011). ................................ ................................ ................................ ................. 62 4 1 Interspecific backcross families used for studies in tree architecture. ................ 95 4 2 Mean branching index (BI) and blind node incidence for the main axis (BNM) and lateral branches (B NL) in the interspecific backcross .. ..................... 95 4 3 Mean branching index (BI) and blind node incidence values for the main axis (BNM) and lateral branches (BNL) .. ................................ .................... 95

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8 4 4 Statistics for single nucleotide polymorphic positions (SNP) within each branching and blind node candidate gene ................................ ................. 96 4 5 Number of heterozygous single nucleotide polymorphic positions (SNP) within different Prunus genotype sequences .. ................................ .......... 97 4 6 Haplotypes found in single nucleotide polymorphic positions in branching and blind nodes candidate genes ................................ ...................... 98 4 7 QTLs associated with branching index (BI) in P. kan ) combined families ................................ ..................... 99 4 8 QTLs associated with branching index (BI) in ................................ ........................ 99 4 9 QTLs associated with branching ind ex (BI) in P. kan ) ................................ ................................ ................................ ................ 99 4 10 QTLs associated with blind nodes in main axis (BNM) and lateral branches (BNL) in P. kan ) ..................... 100 4 11 QTLs associated with blind nodes in main axis (BNM) and lateral ........................ 101 A 1 Microsatellite markers used to identify self pollinated in the interspecific backcross populations studied. ................................ .................... 115 A 2 Specific primers designed to amplify candidate genes associated with axillary meristem formation (AMF) and outgrowth (AMO). ................................ 116 A 3 Single nucleotide polymorphisms detected in PpAXR1 amplicon ................... 117 A 4 Sin gle nucleotide polymorphi sms detected in PpBRC1 amplicon ................... 117 A 5 Single nucleotide polymorphisms detected in PpBRC2 amplicon ................... 118 A 6 Single nucleotide polymorphisms detected in PpCUC1 amplicon ................... 118 A 7 Single nucleotide polymorphisms detected in PpCUC2 amplicon ................... 119 A 8 Single nucleotide polymorphisms detected in PpCUC3 amplicon .................. 119 A 9 Single nucleotide polymorphisms detected in PpLAS amplicon ........................ 120 A 10 Single nucleotide polymorphisms detected in PpMAX1 amplicon ................... 120 A 11 Single nucleotide polymorphisms detected in PpMAX2 amplicon .................... 121 A 12 Single nucleotide polymorphisms detected in PpMAX3 amplicon .................... 121

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9 A 13 Single nucleotide polymorphisms detected in PpMAX4 amplicon .................... 122 A 14 Single nucleotide pol ymorphisms detected in PpPIN amplicon ........................ 122 A 15 Single nucleotide polymorphisms detected in PpRE V amplicon ..................... 123 A 16 Single nucleotide polymorphisms detected in PpSPS amplicon ...................... 123 A 17 SSR and morphological markers selected to use in the mapping of backcross populations. ................................ ................................ ...................... 124 A 18 Candidate genes genotyped with restriction enzymes ................................ ...... 125 A 19 Candidate genes genotyped with high resolution melt analysis ....................... 126

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10 LIST OF FIGURES Figure page 2 1 Branching index values generated (TNP) ................................ ................................ ................................ 38 2 2 Reduced branching typical of a three year old ................................ ............. 39 2 3 Profuse branching typical of a three year P. kansuen sis hybrid in winter of 2008. ................................ ................................ .. 39 2 4 P. kansuensis ................................ .......................... 40 2 5 P. kansuensis ................................ ......................... 41 2 6 Branching index values calculated in 2007 as a predictor for branching number in year 2008 ................................ ................................ .......................... 42 2 7 Branching index values calc ulated in 2008. ................................ ........................ 43 3 1 Branching index values of inte rspecific backcro ss progenies .............................. 63 3 2 Distribution of blind node incidence in lateral branches within interspecific backcross families in 2010. ................................ ............................. 64 3 3 Distribution of blind node incidence in lateral branches within inter specific backcross families in 2011. ................................ ............................. 65 4 1 Genes involved in axillary meristem formation and outgrowth and their interactions.. ................................ ................................ ................................ ...... 102 4 2 P. kansuensis ) backcross combined linkage map. ................................ ................................ ... 103 4 3 backcross combined linkage map. ................................ ................................ ... 104 4 4 UF97 P. kansuensis ) backcross linkage map. .................... 105 4 5 ilies. ....................... 106 4 6 ................................ ... 106

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11 4 7 QTLs associated with branch ing index (BI) in P. kansuensis ) ................................ ................................ ................................ 107 4 8 QTLs associated with blin d nodes in main axis (BNM) and lateral branches (BNL) in ................................ .............. 108 4 9 QTLs associated with blind nodes in main axis (BNM) and lateral branches (BNL) in ................................ ............ 108 4 10 QTLs associated with blind nodes in main axis (BNM) and lateral branches (BNL) in P. kan ) ................................ ........ 109 A 1 Individual interspecific Prunus backcross genetic maps. ................................ 129 A 2 QTLs associated with branching index (BI) in P. kan 3) .. ................................ ................................ ................................ ........... 130 A 3 QTLs associated with branching index (BI) in P. kan 6) ................................ ................................ ................................ ............... 130 A 4 QTLs associated with branching index (BI) in P. kan 3) .. ................................ ................................ ................................ ............. 131 A 5 QTLs associated with branching index (BI) in P. kan 6) ................................ ................................ ................................ ............... 131 A 6 QTLs associated with branching index (BI) in TNP) .. ................................ ................................ ................................ ............... 132 A 7 QTLs associated with branching index (BI) in TNP) ................................ ................................ ................................ ................ 132 A 8 QTLs associated with blind nodes in main axis (BNM) and lateral branches (BNL) in P. kan 3) ................................ ....... 133 A 9 QTLs associated with blind nodes in main axis (BNM) and lateral branches (BNL) in P. kan 6) ................................ .......... 133 A 10 QTLs associated with blind nodes in main axis (BNM) and lateral branches (BNL) in P. kan 3) ................................ .............. 134 A 11 QTLs associated with blind nodes in main axis (BNM) and lateral branches (BNL) P. kan 6) ................................ .................. 134 A 12 QTLs associated with blind nodes in main axis (BNM) and lateral branches (BNL) ................................ ................. 135 A 13 QTLs associated with blind nodes in main axis (BNM) and lateral branches (BNL) ................................ .................... 135

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12 LIST OF ABBREVIATION S AM Apical meristem AMF Axillary meristem formation AMO Axillary meristem outgrowth AP Attapulgus AT Annealin g temperature AXR Auxin resistant BC Backcross BI Branching index BLAST Basic local alignment search tool BNM Blind nodes in the main axis BNL Blind nodes in the lateral shoots BRC Branched BP Base pair CAPS Cleaved amplified polymorphism sequence cM Cent imorgan CUC Cup shaped cotyledon DNA Deoxyribonucleic acid FG Flordaguard FP Foliar primordia HRMA High resolution melt analysis LAS Lateral suppressor LG Linkage group LOD Logarithm of odds MAX More axillary growth

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13 OKI Okinawa PCR Polymerase chain reacti on PS Peach selection P. kan Prunus kansuensis QTL Quantitative trait loci PIN Pinhead SMS Shoot multiplication signal RAX Regulator of axillary growth REV Revoluta SNP Single nucleotide polymorphism SPS Supershoot SSR Simple sequence repeat TF Terminal flower TNP Tardy Nonpareil UF University of Florida

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14 A bstract 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 GENETICS OF TREE ARCHITECTURE IN PEACH ( Prunus persica (L.) Batsch) By Omar Carrillo Mendoza February 2012 Chair: Jose X. Chaparro Major: Horticultural Science L ittle effort has been made to understan d the genetic control of tree architecture in peach In addition, t he occ urrence of blind nodes is a critical factor that affects peach tree architecture and productivity in subtropical climates. In this study, a branching index was developed to facilitate the assessment of branching intensity of the trees. Seven backcross families were developed using P kansuensis 1 s evaluated for br anching index and blind node frequency during the winters of 2010 and 2011. P kansuensis backcrosses presented increased branching and lower blind node incidence whereas almond backcrosses presented less branching and higher blind node incidence, resembli ng the P. kansuensis and almond F 1 parents. There was also broad variability for branching and blind nodes within the P. kansuensis and TNP almond backcross families influenced by the peach parents that were used to generate the backcross populations. The moderate heritability and year to year c orrelation for these traits indicate that they are affected by the environment, but selection for reduced branching and

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15 lower blind node incidence is feasible. SSRs and a set of 14 candidate genes related with branching and b ud development in Arabidopsis were used to map QTLs associated with these two traits in the seven backcrosses. SNPs were found within the candidate gene sequences in the different Prunus parents. Genetic maps containing the selected SSRs and candidate genes were obtained for each backcro ss family and a combined map for all the P. kansuensis families and all the almond families. Branching and blind nodes QTL were detected in the individu al backcross family analysis, and the combined P. kansuensis The candidate genes tested did not map to the location of the major QTLs, PpCUC1 and P pBRC2 mapped to minor QTL for branching and blind nodes, respectively. The QTLs found in this study represent the first steps toward marker assisted selection for reduced branching and reduced incidence of blind nodes in commercial peach cultivars.

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16 CHAP TER 1 LITERATURE REVIEW Introduction Most temperate fruit tree breeding programs pay major attention to aspects such as fruit quality, chilling requirement, crop load a nd tolerance to some diseases. L imited effort has been devoted to tree architecture and tree branching patterns (Laurens et al 2000). As labor and pruning costs of fruit trees have increased, size control and architecture has gained importance. Tree architecture will continue to increase in value as a major trait for tree fruit breeders (Se gura et al 2008) Plant Architecture Plant architecture can be considered as the organization of plant components in space that may change over time (Godin et al 1999). It is the result of endogenous growth processes and exogenous constraints (Barthel emy and Caraglio, 2007), Higher plants exhibit a variety of architectures that are defined in great part by growth determinacy, branching patterns and node elongation ( Wang and Li, 2008 ). These are the most important morphological traits to depict and analyze plant architecture ( Barthelemy and Caraglio, 2007 ). Growth is determinate when the meristem dies or becomes a specialized structure after a period of growth such as a flower, losing any further capacity to develop. Indeterminate growth occurs when the meristem never loses the capacity to grow (Halle et al 1978). Branching can be defined by several sub traits: S YLLEPTIC OR PROLEPTI C Sylleptic bran ching occurs when the axillary meristem elongates immediately after its initiation and prolleptyc when the axillary meristem remains dormant for a time before elongating (Wu and Hinckley, 2001).

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17 M ONOPODIAL OR SYMPODI AL Monopodial is defined by the presen ce of one main axis and sympodial is defined by the presence of several axes ( Barthelemy and Caraglio, 2007 ). R HYTHMIC OR CONTINUOU S Alternation of branched and unbranched nodes within the main axis is rhythmic branching and diffuse generation of axillary shoots along the entire axis is continuous branching ( Halle et al 1978 ). A CROTONIC MESOTONIC AND BASITO NIC This sub trait depicts the preferen tial position for the generation of lateral branches within the plant axis being the basal part (basitonic) conferring the bushy appearance, median (mesotonic) and superior (acrotonic) giving arborescent form ( Barthelemy and Caraglio, 2007 ). Node elongation and number determine the longitude of the plant axis and therefore the exploration of the plant in the vertical space (orthotropy) and the horizontal space (plagiotropy) (King and Maindonald, 1999; Tomlinson, 1978). Also, the concept of reiteration is used to describe the natural repetition of the branching patterns at different organizational levels of the plant body (Costes et al 2006). Several other quantitative and qualitative traits and sub t raits have been used as a reference for depicting and analyzing plant architecture according to the objective of the study. Some examples are: complexity of branching order within a plant, the insertion angle of the lateral shoots, the preformation or neof ormation of the organs (Barthelemy and Caraglio, 2007). This large list of traits and sub traits is a consequence of the complexity of plant architecture and the multiple approaches to the study of this topic. Axillary Meristem Development a nd Branching Pl ant architecture is the result of the activity of meristems (Costes et al 2006). Branch development consists of two distinct steps: the initiation of an axillary meristem and its succeeding growth (Wang and Li, 2008). Axillary meristems, which afterward

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18 function as shoot apical meristems (SAMs), grant plants with unlimited growth potential (Alvarez et al 2006) Axillary meristems are derived from the peripheral zone of the axillary meristem (Wang and Li, 2008). The lateral organ primordium is induced by local auxin accumulation in the peripheral zone of the apical meristem. The subsequent primordia are formed in distant zones where auxin has not been depleted by the preexisting primordial determining leaf and associated axillary meristem arrangement or p hyllotaxis (Fleming, 2005; Reinhardt et al., 2000; Reinhardt et al., 2003). Once initiated, the axillary meristem develops into a lateral bud and whether that bud outgrows to form a new shoot or stays dormant dictates branching patterns (Aguilar Martinez et al 2007). There are three types of dormancy in lateral buds: 1) e ndodormancy which is growth regulation by the internal factors within the bud; 2) e codormancy which is growth regulation by environmental factors that limit plant growth such as water nutrients and temperature ; and 3) p aradormancy which is growth regulation by an external organ or tiss ue other than the dormant bud, for example apical dominance (Lang et al 1985). Apical D ominance Apical dominance is the inhibiting control exerted by the shoot tip over axillary meristems maintaining the lateral buds in a paradormant stage (Cline, 1997). It is known that auxin and cytokinin are related to the maintenance of apical dominance; auxin synthesized in the apical meristem is known to retain a nd cytokinin is known to release apical dominance (Hartig and Beck, 2006). Nevertheless, several hypotheses have been formulated to explain apical dominance that might be incorporated in a single model (Dun et al 2006): 1) the

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19 classical hypothesis which affirms regulation by auxin levels and secondary messengers like cytokinin; 2) the auxin transport hypothesis which suggests auxin movement in a transport stream as the regulatory operator; and 3) the bud transition hypotheses which postulates different b ud developmental stages having variable levels of sensitivity to auxins and other signals. Auxin does not enter directly into the bud (Booker et al 2003), and some studies suggest the existence of an additional messenger suppressing axillary meristem out growth (Booker et al ., 2004; Stirnberg et al., 2007; Stirnberg et al., 2002). The second messenger has been referred to as a graft transmissible shoot multiplication signal (SMS) (Johnson et al 2006). Gomez Roldan et al (2008) and Umehara et al (2008) simultaneously but separately identified a third group of important compounds working with branching mutants; these compounds are strigolactones. Strigolactones belong to the group of terpenoid lactones and are signaling molecules involved in the promotion of seed germination of the parasitic plants Striga Orobanche and Phelipanche spp.. They are also implied as a factor for hyphal branching in arbuscular mycorrhizal fungi (Bouwmeester et al 2007). Arabidopsis mutants that had profuse branching were defe ctive in strigolactone production and the two genes causing the profuse branching phenotype ( MAX3 and MAX4 ) encoded carotenoid cleaving dioxygenases. Other genes involved in branching are AXR1 (auxin resistant) which encodes a protein that is required for response to auxins in Arabidopsis (Stirnberg et al., 1999) and TB 1 ( teosinte branched 1 ) from maize (Doebley et al., 1997), which is considered responsible for the differences in the suppression of axillary branches between maize and its wild ancestor

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20 teosi nte. Additional recently discovered genes that encode transcription factors involved with axillary meristem formation include REV ( R evoluta), LAS ( lateral suppressor ) and the CUC (cup shaped cotyledon) genes (Otsuga et al., 2001). Plant A rchitecture and A g riculture Understanding and manipulating plant architecture has had great impact on agriculture. During the green revolution, yield potential was increased by breeding for ideotypes or plants with improved architecture in cereal crops (Khush, 2001). Rice and wheat cultivars were tall and leafy, had weak stems and a harvest index of 0.3; they were not suitable for high fertilization regimes because plants grew too tall and lodged (Slafer et al 1999). The sd gene in rice (Yang and Hwa, 2008) and Rht in whe at (Keyes and Sorrells, 1989) were incorporated to successfully reduce plant height and increase tillering. Dwarf plants did not lodge when fertilizers were applied, increasing harvest index by 60% (Slafer et al 1999). In the case of maize, breeding has focused on erect leaves that allow higher plant densities and shorter plants in tropical climates (Johnson et al 1986). Temperate Fruit Tree Architecture Tree fruit architecture has been managed by means of cultural practices and breeding. The aim, as in other crops, is to increase light interception and therefore yield and quality in addition to facilitating orchard management (Tworkoski et al 2006). Cultural practices for controlling growth and vigor in perennial fruit trees has been achieved primaril y by the use of dwarfing rootstocks (Lockard and Schneider, 1981), pruning and training (Stephan et al 2007), application of growth regulators (Erez, 1986), fertilization (Jordan et al 2009) and deficit irrigation (Chalmers et al 1981).

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21 Dwarfing root stocks have been widely used in apples. The M.9, M.26, M.27 and the MM rootstock series from East Malling, UK, and their progenies have benefited apple production by decreasing plant height and inducing precocity in fruit production. The reduction in plant stature has permitted the development of high intensity planting systems (Webster et al 2003). Dwarfing rootstocks for sweet cherry have also been et al 2009) rootstock reduces tree size up to 50% (Schmidt and Gruppe, 1988). However, dwarfing rootstocks for commercial peach production are not available (DeJong et al 2001; Masabni et al 2007). Pruning and training techniques together with rootstocks are the main tree size control techniques used in moder n fruit production, the evolution of these has been more rapid in apples and pears than in peaches (Loreti and Massai, 2002; Stephan et al 2007). Tree training systems, besides open center, with specialized pruning Massai, 2002; Porter et al 2002). Summer pruning has also been implemented to control vegetative shoot development (Marini and Barden, 1987). Nonetheless, pruning and training represents a great cost for growers (DeJong et al 2005). Different growth retardants such as cloromequat chloride, uniconazol and Paclobutrazol have been used to favor a reproductive response on the tree at the expense of vegetative development (Bahadori and Arzani, 2008; Erez, 1986). Pac lobutrazol is not registered for peach production in the United Sates and in other tree fruit crops in different countries (Loreti and Massai, 2002). Paclobutrazol is used to control tree height in commercial peach production in Australia (Erez, 1986).

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22 In addition, fertilization practices can affect tree architecture. Fall N increases proleptic branches but decreases sylleptic shoots in peach (Jordan et al 2009). Reduced N application is suggested as a mean to reduce vegetative growth and excessive branch ing (Weinbaum et al 1992). Deficit irrigation to control vegetative growth is a potential alternative for certain edafic and climatic conditions such as semi arid or Mediterranean areas (Chalmers et al 1981). Nevertheless, extra care must be taken in o rder to not compromise accumulation of reserves, fruit quality and flower bud differentiation (Johnson et al 1992). Deficit irrigation is not an option for summer rainy areas like Florida. Breeding for tree form and size has been hindered by a poor under standing of genetics on these traits (Segura et al 2007). However, several QTL studies in apple have been carried out to dissect tree architecture into genetic and environmental effects (Segura et al 2007; Segura et al 2008). Breeding for unconventio nal fruit tree architecture has been very limited, and most of the effort invested and success obtained has been in apples for compact spur types (Barthelemy and Caraglio, 2007). One nar type with compact internodes, reduced lateral branching and augmented production of spurs, optimal for high density orchards (Kelsey and Brown, 1992). Peach Tree Architecture Peach trees are vigorous and are propagated on vigorous rootstocks. High den sity orchards require severe pruning that induces strong vegetative growth resulting in shading and reduction of flower bud formation and fruit quality (Marini and Corelli Grappadelli, 2006). The peach industry has lower productivity and does not have high density production systems when compared to the apple industry (Scorza et al 2006).

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23 Peaches with predominant basal and intermediate branching, resulting in a somewhat branched but open tree architecture that permits fruit hanger production without exces sive shading of the internal part of the tree, are wanted for commercial purposes (Cook et al 1999). Peach mutants with contrasting growth habits have been identified. These altered types can potentially be planted in higher density as they have better l ight interception and need less pruning, increasing the potential for productivity (Scorza, 1984; Scorza et al 1986). These different growth types are controlled by single genes (Niu et al 2004). There are three horticultural classes (Bassi et al 199 4). The first class groups the standard shapes with differences in size: 1) Standard type, which is typical of commercial peaches, has vigorous acropetal growth, moderately strong apical dominance and one year old fruiting shoots ( Marini and Corelli Grappadelli, 2006 ); 2) Brachytic dwarf ( dwdw ) has significantly reduced internodes and dense canopy. The density of second order branches is high (Fideghelli et al 2003). Dwarf cultivars have been developed (Hansche, 1989), but the dense canopy complicates fruit thinning, harvesting and reduces fruit quality (Giovannini and Liverani, 2005); 3) Semidwarf corresponds to trees that are intermediate between standard and dwarf. Internode length can be equal or sho rter than standard type a double recessive gene ( b1b1b2b2 incomplete dominance ( Nn ) (Hu and Scorza, 2009); 4) Spur t ype are trees with a high production of fruit spurs. Internode length and tree size is similar to the standard peach (Scorza, 1987); 5) Compact trees ( Ct ) are smaller than standard but have a denser

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24 canopy, wide branch angles, relatively short internodes a nd longer lateral shoots ( Bassi et al 1994 ). They have a higher number of second and third order twigs ( Scorza, 1984 ). The second and the third class have different shapes than the standard class. The second class includes: 1) Columnar or pillar ( brbr ), which has a small canopy with branches growing in upright fashion with very close angles and reduced number of lateral branches (Scorza, 1984); 2) Uprig ht type, which is intermediate between standard and columnar and is heterozygous for the Br gene that shows incomplete dominance ( Niu et al 2004 ). The third class corresponds to the weeping type ( plpl ) wh ich is used for ornamental purposes, and is shorter than standard, compact and semidwarf trees due to the pendulous nature of its branches, although canopy size is similar to standard type ( Bassi et al 19 94 ). Weeping peach tree branches contain less lignin in the proximal part of the shoot and the formation of secondary xylem is delayed compared to standard branches resulting in less physical support and downward growth (Shen et al 2008). There are also interactions between these growth forms (Scorza et al 2002). Dwarfed pillar trees can be obtained after hybridizing dwdw and brbr trees, and compact pillar trees ( Ct_brbr ) that have potential for ornamental use. Some commercial peach cultivars with thes e altered architectures have been bred and released; however, they have had little impact commercially. Other than use o f these single gene growth variants, little effort has been made to understand the genetic control of tree architecture or branching in peach. At the University of Florida Peach Breeding Program, previous observations have detected the existence of twiggy (more

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25 branching) and non twiggy (less branching) standard peach genotypes that would require less pruning, besides branching difference s in peach relatives such as almond ( P. dulcis (Mill.) D.A. Webb ) and kansu peach ( P. kansuensis Rehder). B ranching in peach depends on physiological functions, but intensity lev els vary from one cultivar to another; the environment (light, humidity, nutri tion, temperature and plant density) alters plant architecture but it is mainly rul ed by the genetics of the plant (Genard et al 1994). On the other hand, peach tree architecture is as well influenced by failure in the development of axillary meristems that reduces the potential for lateral branching and later flowering and fruiting (Richards et al 1994). Bud development failure has been summers (Boonprakob and Byrne, 2003; Richards et al., 1994). Nevertheless there is genetic variability for incidence of blind nodes in a range of 0 90% depending on the genotype (Richards et al 1994; Wert et al 2007). The objective of this study was to understand the genetics for br anching and blind nodes in peach interspecific backcrosses by developing a method to evaluate branching, evaluating distinct parents and progenies and doing QTL and candidate gene analysis.

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26 CHAPTER 2 DEVELOPMENT OF A BRA NCHING INDEX FOR EVA LUATION OF PEAC H SEEDLINGS USING INTE RSPECIFIC HYBRIDS I ntroduction Tools for the evaluation and early selection of architectural traits expressed early and late in plant development would represent a major advancement for fruit tree breeders (Laurens et al 2000) S everal means to depict plant growth or plant models have been developed with differences in the complexity according to the end use or application. In the last two decades enormous progress has been made in the fields of agriculture, forestry and environm ental sciences (Fourcaud et al 2008) A group of growth models consider environmental factors and their interactions, physiological processes such as nutrient uptake, photosynthesis and carbon allocation. This group is known as the process based model (B attaglia and Sands, 1998). Another group, the functional and structural models, link growth process to plant morphogenesis ( Fourcaud et al 2008 ), where three dimensional reconstruction of plant structu res by AMAP simulation software has been developed. (Prusinkiewicz, 2004). Digital 3 D representations of tree trunk and branches have been obtained from a single 2 D picture by means of geometric models in computer graphics (Cheng et al 2007). The drawb ack for these methods is that often calculations are time consuming and are restricted to a few individuals (Fourcaud et al 2008). Simpler crop and forest growth models are used for making predictions on plant development in agriculture and forestry. Man y of these models apply functions to fitted data without considering physiological processes involved in growth and morphogenesis

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27 and can be used efficiently in breeding programs where hundreds or thousands of trees have to be evaluated (Fourcaud et al 2 008). Analysis of lateral branching has been used to study architectural traits, since branches determine tree architecture and the shape of the tree crown ( Cheng et al 2007 ). I n apple, lateral branching variability is heritable and used as a decisive factor for selection (Godin et al 1999; Segura et al 2006) Plant indexes have been developed to describe branching (Morita and Collins, 1990). An index based on the plastochron development of Glecoma h ederacea L. was used to analyze stolon growth and branching (Birch and Hutchings, 1992) An index based on length and density or number of first order and second order roots was used to describe quantitatively the degree of branching in maize roots (Morita et al 1992) The hypotheses tested for this study is that a branching index based on the number of first and higher order branch es in a tree, is a tool that can help to evaluate, characterize and predict branching in Prunus seedling trees. The aim of this research was to develop a simple fast, non destructive, reliabl e branching index that could be used to evaluate the architecture of peach seedlings, thus facilitating the early selection of individuals with desirable tree architecture or less twiggy phenotypes and for mapping genes related to branching intensity in peach Materials and Methods Branching Index Formula A branching index (BI) equation categorizing plants into twiggy, intermediate and non twiggy phenotypes while at same time maintaining quantitative differences within these categories was desired. The branching index was specifically designed for the evaluation of peach and interspecific Prunus seedlings in the high density fruiting

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28 nursery management of the University of Florida stone fruit breeding program. The branching index value is the multiplication of partial index values for each branching order existent within the plant: 1 st order branches that arise from the main axes, second order branches arising from first order branches a nd so on. The branching index (BI) formula is: BI = Where: x = Absence ( x =0) or presence ( x =1) of first, second, third, or subsequent order branches, n = number of branches within a branching order and k = the maximum order of branching For illustration purposes we mention the next cases: p lants having no branches have BI values of 1. Plants having only first order branches; first and second order branches; and first, second and third order branches would have values of 2
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29 representing different branching orders showing qualita tive contrasts. For this reason, the first equation was chosen for the index. Plant Material The germplasm used to generate the populations for validating the branching index equation represents 3 sexually compatible Prunus species with differing growth h abits: Kansu peach ( P. kansuensis Rehder), almond ( P. dulcis (Mill.) D.A. Webb ) and peach ( P. persica (L .) Batsch) Kansu peach, a wild peach relative, has a dense canopy with profuse branching under the growing conditions of the southeastern United State s. In contrast, almond has reduced branching, an open tree canopy and can produc e short branches or spurs. Commercial peach germplasm typically has a branching architecture that is intermediate to the two described previously, but includes both twiggy and non twiggy phenotypes. F1 hybrid populations of peach X P. kansuensis and peach x P. dulcis were generated and planted in Gainesville, Florida; 0.5 meters apart in a single row. The plants were lightly pruned the first growing season by cutting off sucker s from the basal part while the main axis was maintained throughout the entire experiment. Data Collection Data was collected on the total number of branches represented by total number of tips, number of first order branches, and the number of second, th ird and fourth order branches from three randomly selected first order branches on 2 and 3 year old seedlings of 97 47 x P. kansuensis P. kansuensis and FG peach x TNP almond. These sample branches were located at the basal, intermediate and upper third of the tree in years 2007 and 2008. Trees were between 1.5 and 2 meters tall when 2

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30 years old and ranged from 4 to 5 meters tall when 3 years old. The 1 st 2 nd 3 rd and 4 th order branching data were used to calculate an index value to estimate and predict the number of branches. A comparison of the accuracy of branching index based on one branch per tree (randomly selected in the basal, intermediate or uppe r third of each tree) versus the mean of three branches per tree was performed to determine if data from only one first order branch were sufficient to obtain a good correlation between the branching index and the total number of branches represented by to tal number of tips. Statistical Analysis The statistical analysis consisted of power regression, analysis of variance, Tukey mean test between the different families evaluated and the clusters formed by trees that reached the same branching order (1st, 2n d, 3rd and 4th order) for both years. The statistical analysis was performed using SAS version 9.1. Results and Discussion UF97 47 total number of branches and lowest branching index in both years (Table 2 1 and Figure 2 1). Peach x TNP hybrids also had fewer 1 st and 2 nd order branches in 2007 and fewer 1 st 2 nd and 3 rd order branches in 2008. Therefore, branch production in peach x almond hybrids is reduced at all levels ( F igure 2 2 ). These results agree with casual observations in Byron, GA where peach x almond F1 hybrids tend to have reduced branching whe n compared to peach seedlings. Gradziel et al (2002) have also reported that branching hybrids and that the trait is dominant in crosses. Although the mean total number of

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31 branches was higher in 97 47 x TNP than in FG x TNP in both 2007 and 200 8, the means wer e not significantly different. Among peach x almond hybrids, analysis of 1 st 2 nd and 3 rd order branch data indicated that 97 47 x TNP had the most 1 st order branches in both 2007 and 2008, and the most 2 nd and 3 rd order branches in 200 8, yet the differences were significant only for 2007 1 st order branch data. The largest number of total branches and branching index was observed in peach x P. kansuensis T able 2 1 and F igure 2 3). Increased branching was also observed for hi gher order branching in P. kansuensis hybrids (T able 2 2 ). The 3 rd order cluster in 2007 and the 4 th order cluster in 2008 were composed entirely of peach x P. kansuensis hybrids (F igure 2 1) In addition all but three data points in the 3 rd order cluster for 2008 were peach x P. kansuensis hybrids. P. kansuensis F1 hybrids had the greatest total branches in both 2007 and 2008. However, Oki x P. kansuensis was significantly different from FG x P. kansuensis only in 2007. Comparison of the FG x TNP and FG x P. kansuensis F1 families shows that the FG x P. kansuensis F1 family had greater than 4 fold the mean total number of branches in both 2007 and 2008, and approximately 5 fold more 1 st order and 2 fold more 2 nd order branches tha n the FG x TNP family. FG can be compared to 97 47 as both were crossed to TNP. FG can also be compared to Oki as both were crossed to P. kansuensis In these comparisons, FG consistently produced progeny with the smallest mean total number of branch es and lowest branching index value when compared to 97 47 and Oki for both the TNP and P. kansuensis F1 hybrids. FG is characterized by long, whippy branches and reduced branching (Sherman et al 1991) while Oki and produce d shorter

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32 and t wiggier branches. The variation in branching observed in the hybrid populations indicates that there is a large genetic component to branching propensity in peach and related species. Genard et al (1994) reported that branching in peach depends on physiol ogical factors, although induction levels varied from one cultivar to another. Similarly, the number of lateral shoots in apricot was significantly affected by genotype in cumulative data for the first two years while three years were required to differe ntiate between tree architectures (Legave et al 2006) They proposed that it is necessary to observe the expression of genetic contrasts in growth and branching on appropriate parts of the limbs, and use the early expression of these traits to allow earl y selection of preferred tree architecture (Legave et al 2006) The values generated by the branching index equation plotted against the total number of meristem tips grouped the progeny into clusters of seedlings that were differentiated by the presenc e or absence of 1 st order, 2 nd order, 3 rd order and 4 th order branches (F igure 2 1 ). The 1 st order cluster in 2007 and the 1 st and 2 nd order clusters in 2008 consisted entirely of peach x TNP hybrids. The 3 rd order branching cluster in 2007 and the 4 th o rder branching cluster in 2008 consisted of peach x P. kansuensis hybrids. Only the 2 nd order branching cluster for 2007 and the 3 rd order branching cluster for 2008 contained both peach x TNP almond and peach x P. kansuensis hybrids. Although the distri butions of the observed total number of branches overlapped between clusters, the mean total number of branches was different between the first, second and third order groups in 2007 and between the second, third and fourth order groups i n 2008 (T able 2 3) The mean number of branches in the first order and second order branching groups were not si gnificantly different in 2008. This lack of significance

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33 in 2008 between the first order and second order groups may have resulted because only three trees had no t undergone second order branching in the sampled limbs. The first order branching cluster consisted of trees with index values between roughly 2 and 4, second order branching cluster between 4 and 8, third order branching cluster between 8 and 16, and fo urth order bran ching cluster greater than 16 (F igures 2 4 and 2 5). The regression lines for 2007 (F igure 2 4a) and 2008 (Fig ure 2 5a) demonstrate the general trend of the groups generated by the index. The regression between the index values and the total number of apical meristems were 0.72 and 0.78 for 2007 and 2008, respectively. However, these regression lines do not show the within cluster progression of branch number as the index values increase. In 2007, trees that developed first, second and third order b ranching were tightly grouped. It was possible to fit regression lines with high r 2 values, indicating that the index values were good predictors of branching intensity within each cluster (F igure 2 4b). The number of plants with third order branche s increased and plants with fourth or der branches appeared in 2008 (F igure 2 5b). Index values increased from 2007 to 2008 as the trees inc reased in size and complexity (F igures 2 4a and 2 5a). Furthermore, branch index values became more dispersed as bran ch number and branching complexity increased resulting in a decrease in the goodness of fit of the 2008 regression lines (F igure 2 5). However, the lowest index values within each branching cluster identified the plants with the fewest number of branches. The regression of the 2007 branching index values and the total number of branc hes observed in 2008 was 0.71 (F igure 2 6), indicating that the index values generated in 2007 were good predictors of branching in 2008.

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34 Counting the number of 1 st order, 2 nd order, and 3 rd order branches on each seedling requires a significant time investment. Therefore, we compared the linear regressions generated by using data from each of the first order branches sampled versus the mean of t hree sampled branches in 2008. Th e results indica te that the three branch data (F igure 2 5a) generates index values that are better estimators of tree branching than individual branch data for a basal, intermediate and upper branch (F igures 2 7a, 2 7b and 2 7c respectively). Among indiv idual branches, those in the basal and upper third of the canopy ( F igures 2 7a and 2 7c) give more accurate indexes (r 2 = 0.62 and 0.65) than those in the intermediate third of the canopy (r 2 = 0.52) (Fi gure 2 7b). The upper branch gives the highest regres sion value and the best separation of the branching clusters of the individual branches ( F igure 2 7c). In conclusion, the developed index revealed differences in branching patterns among interspecific hybrids over two growing seasons and the index values c alculated in two year old trees were good predictors of the number of branches observed in the third year. Furthermore, the index was more precise when three first order branches were sampled per tree rather than one. The results indicate that selection of trees with an index value below 8 at two years and below 12 at three years of age would select trees with reduced branching. Operationally, the index would be based on the mean from three first order branches and used to select trees within the branching clusters generated by the index. The lowest index values within each branching cluster typically have the fewest branches. This index could be used in peach breeding as a quantitative way of selecting individuals with decreased branching and less twiggy t ree architecture. Further

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35 research is necessary to evaluate the ability of this index to pred ict branching in larger trees. However, the close tree spacing used in this experiment will prevent the further analysis of this population due to shading and com petition between trees.

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36 Table 2 1. Mean total branch number per tree and branching index values in peach x almond and peach x P. kansuensis F1 hybrid populations in years 2007 and 2008. Family z 2007 2008 Branches (#) Branching index value Branches (# ) Branching index value Oki x P. kan 97.20 a y 10.34 a 245.16 a 19.56 a FG x P. kan 63.80 b 8.32 b 235.33 a 13.20 a 97 47 x TNP 15.63 c 2.48 c 45.00 b 5.06 b FG x TNP 5.80 c 2.44 c 26.75 b 5.05 b z Flordaguar d ( P. kan ) P. kansuensis and (Oki) y ). Table 2 2 Mean number of first order branches, and the mean number of second, third and fourth order branches in three first order branches sampled per tree of peach x almond and peach x P. kansuensis F1 hybrids. Family z Year Progeny evaluated (#) First order (#) Second order (#) Third order (#) Fourth order (#) 2007 Oki x P. kan 10 26.40 a y 8.36 a 2.00 a 0.0 0 FG x P. kan 10 22.40 a 5.76 a 1.33 a 0.00 97 47 x TNP 8 11.37 b 2.73 b 0.00 a 0.00 FG x TNP 5 4.40 c 2.60 b 0.00 a 0.00 2008 Oki x P. kan 31 43.23 a 25.17 a 13.96 a 0.65 a FG x P. kan 8 32.22 b 15.26 b 12.41 a 0.11 a 97 4 7 x TNP 8 19.88 c 4.92 c 2.46 b 0.00 a FG x TNP 4 12.25 c 3.25 c 0.25 b 0.00 a z P. kan ) P. kansuensis and (Oki) y Means followed by different letters are significantly different, Tukey (

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37 Table 2 3. Mean total branch number per tree and branching index means for first, second, third and fourth order branching clusters in peach x almond and peach x P. kansuensis F1 hybrid populations in years 2007 and 2008. Branching cluster z 200 7 2008 Branches (total #) Branching index value Branches (total #) Branching index value First order 11.33 c y 2.12 c 11.64 c 2.15 c Second order 42.80 b 4.72 b 43.00 c 4.70 c Third order 83.65 a 10.09 a 194.79 b 12.85 b Fourth order 0 .00 ND x 314.01 a 27.78 a z Cluster was assigned upon the branching order reached by the tree. y Means followed by different letters are significantly different, Tukey x ND=No data, no trees reached fourth order branching in year 2007.

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38 1 st order 2 nd order 3 rd order A B Figure 2 1. Branching index values generated for A) year 2007 and B) 2008 in 97 47 P. kansuensis P. kan ) P. kansuensis Vertical lines show borders between trees having different branching order. 1 st order 2 nd order 3 rd order 4 th order

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39 Figure 2 2. Reduced branching typical of a three year ol N Photo courtesy of author. Figure 2 3. Profuse branching typical of a three year P. kansuensis hybrid in winter of 2008. P hoto courtesy of author.

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40 A B Figure 2 4. Branching index values generated for year 2007 in 97 47 P. kansuensis x P. kansuensis A) regression line generated for the entire 2007 data set. B) regression lines generated for the 1 st 2 nd and 3 rd order clusters formed by the index.

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41 A B Figure 2 5. Branching index values generated for ye ar 2008 in 97 47 P. kansuensis P. kansuensis A) regression line generated for the entire 2008 data se B) regression lines generated for the 2 nd 3 rd and 4 th order clusters formed by the index.

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42 Figure 2 6. Branching index values calculated in 2007 as a predictor for branching number in year 2008 using 97 47 (Oki) x P. kansuensis ( P. kan ) P. kansuensis and A y = 9.7655x 1.4004 r 2 = 0.7166 y = 8.1441x 1.1742 r 2 = 0.6263

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43 B C Figure 2 7. Branching index values calculated in 2008. Index value was calculated using total number of first order branches per tree and the number of second, third and fourth order branches within a randomly selected first order branch in A) basal, B) intermediate and C) upper third of the canopy. y = 6.307x 1.472 r 2 = 0.6545 y = 15.19x 1.0 424 r 2 = 0.5262

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44 CHAPTER 3 BRANCHING AND BLIND NODE INCIDENCE IN INTERSPECIFIC BACKCROSS FAMILIES OF PEA CH Introduction Branching in different Prunus species Peach is a member of the family Rosaceae, subfamily Prunoidae, within the subgenus Amygdalus which includes peaches, peach relatives and almond s although Prunus mira Koehne, P. kansuensis Rehd., and P. davidiana (Carr.) Franch are considered to be the most closely related species to peach (Bielenberg et al 2009). Amygdalus subgenus members are sexually compatible and produce viable and fertile F 1 hybrids (Mowrey et al 1990; Martinez Gomez et al 20 03) Consequently t hese species have been used to expand the genetic resources in peach scion and rootstock breeding for insect, pathogen, and nematode resistance Interspecific hybrids have also been used as a source of polymorphisms for genetic studies i n peach (Guillaumin et al 1991; Gradziel, 2002; Martinez Gomez et al 2003; Ledbetter and Sisterson, 2008) which has a narrow genetic pool (Mowrey et al 1990; Gradziel, 2002). Although growth forms in peach, such as dwarf, pillar, weeping and compact have been studied (Scorza et al 2006), little effort has been devoted to the study of tree architecture and branching. The standard peach tree has vigorous acropetal growth, moderately strong apical dominance and one year old fruiting shoots ( Marini and Corelli Grappadelli, 2006 ). Nonetheless variation in tree structure can be observed in peach cultivars released from the University of Florida breeding program. Cultivars such e a spreading growth habit while cultivars such as

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45 There is additional genetic diversity for tree structure in closely related Prunus species that could be used to modify the architecture of pe ach trees (Scorza and Okie, 1990). For instance, the root has remarkably long pendulous branches, is a sixth generation descendant from the related species P. davidiana C 26712, (Sherman et al 1991). P. kansuensis A1 trees grown in Byron, GA are short stature d and highly branched trees Peach x P. kansuensis hybrids are vigorous and intermediate in characteristics, with a higher production of lateral branches than standard peach trees (Grassell, 1974) Almond develops lateral branches similar to peach and perennial spurs (Gradziel, 2002) although a great diversity of tree architecture can be found in this species (Kester and Gradziel, 1990). Gradziel et al (2002) deve loped a classification system for branch architecture in almond based on the suppression of lateral shoot development using categorized as having limited branching in cur rent and previous season growth, meaning that laterals developed only on the basal half to two thirds of the shoot. In addition, most hybrids of this cultivar tended to express this growth habit, showing that it is heritable and has a propensity towards do minance of this trait. Analysis of peach x almond F 1 s backcrossed to almond indicated that tree size was larger than peach and the bearing habit was similar to peach but with some prevalence of fruiting spurs (Gradziel, 2002). For apricot there is an influ ence from the genotype in sylleptic branching for three locations. This influence was greater when considering cumulative effects after three

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46 years of growth (Legave et al 2006). In 1 year old progeny high broad sense heritability was found to be 0.54 fo r number of axillary shoots (Segura et al 2006; Segura et al 2007). Blind nodes in peach The occurrence of blind nodes is an additional factor affecting peach tree architecture and productivity A blind node is defined as a node lacking axillary flowe r and vegetative buds (Boonprakob et al 1996). Blind nodes can make the training of young trees difficult and decrease s potential yields in areas prone to late frosts where the crop depends on higher flower bud density to escape from poor fruit set (Rich ards et al 1994) Differences in blind node frequency among cultivars and locations can have a large impact on the pruning and potential yield in peach (Wert et al 2007). A wide range of blind node frequency has been reported for the University of Flor ida peach germplasm demonstrating that there is genetic variability for blind node incidence, and breeding against this disorder should be feasible if its mode of inheritance can be determined (Richards et al 1994) Blind node incidence is associated w ith high temperatures during bud development in the mid summer (Richards et al 1994; Boonprakob and Byrne, 2003). Low chill peaches typically ripen before the summer and the growing conditions are conducive to rapid growth and high blind node frequency ( Byrne et al 2000). Higher rates of blind nodes are observed in warmer sites like central and southwest Florida than in north central Florida (Wert et al 2007) Trees grown in the highlands of the subtropics or coastal climates that have cool summers do not show blind nodes, but when taken to warm humid climates such as Florida often exhibit this

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47 disorder (Richards et al 1994). Additionally, susceptible varieties do not present blind nodes in locations with hot dry summers like Sevilla, Spain or Hermos illo, Mexico, where climatic conditions inhibit vegetative growth during the summer (Byrne et al 2000). Boonprakob et al (2006) studied anatomical differences between normal and blind the early spring (Mar ch, April and May) and summer (June, July and August). Early season shoots presented well developed buds with the procambium connected to the stem and prophyll growth. Late season shoots presented mostly blind nodes and anatomic observations showed that th ere were empty axils with partial development of stem procambium to the position of the aborted axillary buds In some cases an axillary meristem was observed but with very limited growth. A genetic disorder named noninfectious bud failure (NBF) has been d escribed in almond (Kester et al. 2004) ; the disorder is characterized by bud death, rough bark and erratic budbreak. Similar to peach, the incidence of NBF is associated with increased mean temperatures in June The predisposition of a branch to expres s the bud failure phenotype increases with the number of vegetative seasons A phenotype similar to blind nodes (Lanner, 1966). T he foxtail phenotype is characterized by the lack of or greatly reduced number of late ral branches and is typically associated with the growth of pine trees in exotic environments. Pine provenances vary in the expression of the foxtail phenotype and studies in Pinus caribaea var. hondurensis indicate that it has a heritability of 0.17 (Ledi g and Whitmore, 1981)

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48 L ittle is known about the genetics and i nheritance of this phenotype for peach although previous research indicates that highly branched Prunus kansuensis and to their respective progenies (Carrillo Mendoza et al., 2010). In this research we are testing that the phenotypic variation for branching and blind nodes is under genetic control. The objective of this research was to evaluate the branching intensity a nd blind node incidence and determine their inheritance in interspecific Prunus backcross families. Materials and Methods Plant Material Seven backcross (Table 3 1) families were generated in 2008 and planted in Gainesville, Florida. The parents were sele cted based upon their contrasting branching intensity and blind node incidence. F G ) x Prunus kansuensis A ( P. kan ) hybrids showed higher branch production and lower blind node incidence than FG x T brids. Two selections from P. kan F 1 (seedlings number 3 and 6) and one selection from TNP F 1 (seedling number 1260) were used as male parents. P. kansuensis hybrid was also selected for generating backcrosses as a male parent. The peach se AP00 30 and were used as backcross female parents. F G x P. kan and FG x TNP hybrids AP00 30 wbs are defined as specie s level backcrosses. UF 97 x P. kan s define d as a genotype backcross Plant Management backcross seeds were harvested at maturity and soaked in 0.4% Captan fungicide solution, placed in a bag of moist perlite, and on the same day

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49 of harvest placed into a co ld chamber at 7C Breeding selection 30 wbs fruit development period below 110 days and therefore require d in vitro culture to ensure a high germination frequency. Seeds were removed under as eptic conditions and cultured in a modified KNOPS germination media ( Lyrene, 1980). T he cultures were stratified in a fridge at 7C for approximately 8 weeks. S eed s showing radicle protrusion were planted into cone containers of sphagnum peat and perlite (1:1) containing 6kg/m 3 of 15 9 12 controlled release fertilizer. Seed lings were grown in a greenhouse at approximately 27C for 16 weeks and planted in the field in October 2008 in a complete randomized block design with a total of four blocks rootstocks were planted simultaneously with the backcross seedling s in each block and were budded in May 2009 with buds from each parent used to generate the backcrosses. Pruning consisted of removing basal suckers that might interfere with weed control Four fertiliz er applications were made during the growing season w ith 125 g of 10 10 10 fertilizer in 2009 and 200 g in 2010. Weeds were controlled by three applications of Roundup each growth season. Plants were irrigated in drought periods during the growing season at weekly intervals. Branching Index Data Collection Data for total number of first order branches and total number of second, third and fourth order branches from three randomly and representative selected first order branches located on the lower, intermediate and upper part of each tree were obtained duri ng the winters of 2010 and 2011. Branching index was calculated for each tree (Carrillo Mendoza et al. 2010) Trunk diameter was measured at the crown of the tree

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50 with a cal iper and tree height with a ruler in the winter of 2010 and 2011 to aid as covariat es for the branching index. Blind node data collection Blind node frequency was measured as the percentage of blind nodes from the total number of nodes in the uppermost 50 nodes of the main axis of the tree, and the percentage of blind nodes from three ra ndomly selected lateral branches that grew the previous season. These branches were chosen because they represent the genotype and genotype x environmental interaction from the previous growing season Identification of Selfs Six SSRs markers used for mapp ing were also utilized to distinguish and separate contaminating progeny originating from self pollination from true backcross progeny (Appendix, Table A 1). Genomic DNA was extracted from leaf tissue of all the individuals within each backcross family (Ta ble 3 1) using the CTAB method (Doyle, 1991), DNA isolation was con firmed by electrophoresis at 120 volts for 6 0 minutes on a 1% agarose gel stained with ethi dium bromide and TBE buffer (10.8 g Tris Base, 5.5g Boric acid, 4mL 0.5M EDTA (p H 8.0 ) ). Lambda DNA of 5, 25, 50, and 100ng/L was loaded ne xt to the samples to obtain a visual estimate of the concentration of isolated DNA. The gel was pho tographed on a transilluminator and afterwards DNA concentration was determined by spectrophotometry. Genomic DNA fr om the parents was amplified by polymerase chain re action (PCR) using six polymorphic SSR s (Table 3 2) and informative markers per family that differentiated selfs from true backcrosses. SSR markers that segregated for alleles that differed by less than 4 base pairs were amplified using labeled primers. PCR was carried out in a total volume of 10L containing 1 L 10X ThermoPol Reaction

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51 Buffer (10mM KCl, 10mM (NH 4 ) 2 SO 4 20mM Tris HCl, 2mM MgSO 4 0.1% Triton X 100, pH 8.8 @ 25C), 1 L 5 M forward primer, 1 L 5 M reverse primer, 0.8 L 2.5mM dN TP, 0.2 L Taq DNA Polymerase, 3 L DNA grade water, and 3 L approx. 10ng/L DNA. PCR reactions were done on an Eppendorf thermal cycler using the following cycling parameters: initial denaturation for 3 min. at 94C, follo wed by 40 cycles of 30 s. at 94 C, 30 s. at the primer specific annealin g temperature (Table 4 1), and 1 min. at 72 C; and a final extension of 7 min. at 72C. PC R products were separated on a 3.5 % electrophoresis agarose gel stained with ethydi um bromide at 220 volts and observed and photographed on a transilluminator to corroborate amplification and to determine the approximate size o f the amplified DNA fragments. Markers segregating for alle les that differed by more than 6 bp were visualized a nd genotyped by size separation after four hour electrophoresis. Markers segregating for alle les that differed by less than 6 bp were fluorescently labeled and detected by capillary electrophoresis. A 100x 400x dilution of PCR product was sent to the ICBR Genetics Analysis Laboratory at the University of Florida for fragment analysis on an ABI 3730 Automated Sequencer. Allelic segregation was visualized using the Soft Genetics analysis program GeneMarker (SoftGenetics, State College, United States) v ersio n 1. Statistical A nalysis square, correlation and regression tests were performed for branching index and blind node incidence using PROC MIX in SAS version 9.2. Branching index was anal yzed using blind node incidence, tree diameter and height as covariates to assess the effect of blind nodes and tree vigor on branching. Blind node incidence data were transformed using a logarithmic function.

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52 Results and Discussion Branching Index Branchi ng intensit ies among the parents used for developing the backcross families were not signific (Table 3 2). Significant differences were observed after the second growth season (Table 3 3 ) P. kansuensis hybrids had the highest value, the peach genotypes w ere intermediate and the TNP hybr id had the lowest mean branching index values The lack of significance in 2010 could be due to the short growing season the budded parental trees had in their first growth season. T he trees were budded in May 2009 and had only a 6 month growing season bu t there are similar tendencies to the significant results of 2011. The branching behavior of the parents was t ransmitted to the different backcross progenies for branching intensity in 2010 (Table 3 4 ). P. kan backcrosses presented the highest and TNP bac kcrosses had the lowest branching index. P. kan hybrids P. kan hybrids backcrossed to each ranked lower for branching. T hese results are si milar to those obtained by Gradziel (2002) where TNP and its progeny presented limited branching relative to other almond s crossed to peach and P. webbii progenies. The contrast test ( T able 3 5 ) confirms the previous result, where the effect for branching from P. kan hybrid offspring was highly significant progeny from different peach genotypes in 2010 ( T able 3 5) UF 97 progeny had a higher branching index t In this case families having

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53 TNP were not considered when compar ed crossed with TNP hybrids. Branching index values for the winter 2011 increased in all the backcross fami lies as a result of an increm ent in the number of first, second, third and four th order branches (Figure 3 1). Few individuals from the P. kan 6) backcross famil i es i n 2010 had generated fourth order branches and more P. kan backcross progeny presented third order br anches compared to TNP backcross progeny. B ranching complexity increased i n 2011 with a larger number of progeny having fourth order branching and some P. kan progeny expressing an even greater branching index compared to TNP values in this category. Trans gressive segregation was found for branching index in the different backcross families suggesting that peach and almond may have alleles with different phenotypic effects at many genes controlling branching (Figure 3 1). The differences found in 2010 were conserved among the different families in Table 3 6 ). The FG x P. kan and 97 47 x P. kan offspring branched more profusely than FG x TNP offspring. The orthogonal contrasts show that P. kan progeny had significantly higher branching (P Table 3 7 ), and that there were no differ ences among the peach genotypes even reduced branching in 2010 when compared to the other two selections. In general, P. kan progeny developed more profuse branching, and a lmond progeny developed less complex and lower branching These results imply the potential of TNP or similar almonds in breeding for less twiggy peach trees that can be easier to prune (Gradziel, 2002).

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54 The covariates blind node incidence and tree heigh t did not appear to have a significant effe owever tree trunk diameter was significant. In addition a positive and moderate relationship between tree diameter and branching (r=0.45 ) was found. C onversely tree height had no association with branching (r=0 .05 P > 0.05 ). These results demonstrate that there is an association between tree diameter and branching intensity. Additionally there were significant backcross families ( T ables 3 8 and 3 9 ), where the P. Kan ) backcross family had the greatest average diameter. However, no significant differences were detected for tree height, demonstrating that there is a contribution from genotype to trunk diameter as well as branching. Field ob servations indicated that some FG x TNP offspring had low branching even though they were taller than other trees and in some cases many FG x P. kan offspring that were profusely branching were not tall but had a large canopy and occupied a wide space. Bl ind nodes in the main axis and lateral branches had a negative but low relationship with branching index (r= 0.19 and 0.21 respectively). This indicates that presence or absence of vegetative buds is a component of branching but does not have th e greatest impact, since branching can be also a consequence of bud density, tree vigor and strength of apical dominance. Blocks did not have a significant effect on branching index, but there was 01 ) between the two years of evaluat ion. T he differences were a consequence of the increase in the number and complexity of branches but also suggest effects from different growing seasons as the two years data correlate

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55 moderately (r=0.58, ). A s a consequence additional growi ng seasons for evaluation for branching may be useful. Blind Nodes The parents chosen for originating the backcross progeny had significant in the incidence of blind nodes o n the main axis and lateral branches The peach P00 demonstrated the highest incidence in 2010 ( T able 3 2 ) and 2011 ( T able 3 3 ), whereas FG x TNP was intermediate and all P. kan hybrids had the lowest percentage of blind nodes The incidence of blind 97 47 was sim ilar to that of the FG x P. kan hybrids in 2010; however, in 2011 the frequency increased to a level similar to the FG x TNP hybrid s indicating a significant environmental effect Backcross families as well as the parents showed significant differences (P for blind nodes in the main axis and lateral branches in 2010 ( T able 3 4 ) and 2011 ( T able 3 6 ) x ( FG x TNP ) x ( FG x TNP ) backcross hybrids x (FG x P kan ) and x ( FG x P. kan ) backcross hybrids were intermediate x ( P. kan ) backcross hybrids had the lowest incidence of blind nodes Blind node presence in the main axis and branches are highly correlated (r=0.90 ) and ofte n the incidence is slightly higher in the main axis than lateral branches. The orthogonal contrasts between different parents used to generate the backcross progeny confirms the previous results D ifferences in the frequency of blind nodes between P. kan and TNP almond progeny in 2010 ( T able 3 5 ) and 2011 ( T able 3 7) 97 47 offspring had the

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56 varia bility for blind node propensity as indicated by Richards (1994). There was high variability for blind node frequency within the backcross families B lind node frequency in lateral shoots of FG x P. kan and FG x TNP progeny ranged from 0 90% in 2010 and 2 011 ( F igure 3 2 and F igure 3 3 respectively), showing a broad segregation for the trait in progeny derived from contrasting parents. Even though the range of blind nodes was similar for both families, the means were significantly different in both years, with TNP progeny having a higher mean incidence of blind nodes than P. kan progeny. The proportion of individuals that had low incidence, classified as having 0 30% of blind nodes, was around 0.70 in 2010 ( F igure 3 2) and 2011 ( F igure 3 3) in FG x P. kan b ackcross populations. In contrast the proportion of progeny with a low incidence of blind nodes in FG x TNP was approximately 0.30 in 2010 and 2011. A chi square test showed that these proportions are significantly different (P<0.001) between these two fa P. kan ) backcross had the narrowest range with 100% of individuals in the lower blind node categories in 2010 and 2011 In contrast to the two previous families, this family had less phenotypic variation ; both of the paren ts used to generate this backcross had low average blind node frequency ( T ables 3 3 and 3 4). These results suggest that blind node frequency is under genetic control and that use of parents with low blind node frequency such as P. kansuensis will produce offspring with fewer blind nodes. Similar to the branching trait, transgressive segregation was observed in the backcross progeny again suggesting that peach and P. kansuensis carry different alleles at multiple loci controlling the blind node trait.

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57 The re were no significant differences among blocks for blind node frequency. branches among the two years of evaluation, suggesting different responses during different grow ing seasons. The overall mean for 2010 in the main axis and lateral shoots was 28.4 and 23.0 percent and for 2011 there was an increase to 36.9 and 33.7 percent Nevertheless, there is a n association for the incidence of blind nodes between the two y ears of evaluation (r= 0.80 ). Variation was noticed in some trees, primarily in progeny with a blind nod e incidence between 10 to 50%. However, trees with an incidence of 70% or more were the most constant in both years. These results indicate that a genotype with high blind node presence will likely have the same behavior in the following seasons. On the other hand trees with an incidence of 10 to 70% may require additional time for accurate evaluation. Individuals with the lowest incidence, 0 to 10%, in 2010 or 2011 rarely had a blind node incidence above 25% in the other year, demonstrating that selection for the lowest or no incidence range is necessary. T here are no known threshold s for a maximum incidence of blind nodes that would risk a profitable yield, but selection f or fewer blind nodes is necessary in climate s with late spring freeze s (Richards et al., 1994). Heritability for Branching and Blind Nodes Narrow sense heritability was calculated by mid parent offspring regression for branching index and blind node inciden ce in main axis and lateral branches. Branching index narrow sense heritability was 0.37 and blind node heritabilities were 0.21 and 0.20 for main and lateral branches respectively. Branching index narrow sense heritability was moderate. Segura et al. (2 006) reported a broad sense heritability of 0.54 for number of sylleptic branches in one year

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58 old apples (2007); Segura et al. (2006) reported on one year old apricot broad sense heritabilities of 0.71 for trunk branching, 0.51 for long sylleptic shoot bra nching and 0.69 for the percentage of branching nodes. Branching and other growth trait s heritability estimates for apple and apricot appear to be very variable confirming the complexity of these traits (Liebhard et al., 2003; Segura et al. 2007). Differe nt factors such as density of lateral vegetative buds, percentage of buds that break and elongate shoots and plant vigor affect shoot branching. Besides different methods were used to evaluate branching Segura et al. (2006 and 2007) dissected the trait i n number of sylleptic branches originated in trunk and long sylleptic shoots, number of shoots per unit of length an d percentage of branching nodes. I n this study the branching index was used as a tool to evaluate the intensity and complexity of branching as an overall mean to depict tree branching in breeding populations, giving additional explanation for the differences in heritability estimates. An additional source of variation that affected heritability was year or the two different growth season s of e valuation where significant differences were found between 2010 and 2011 (P Despite the complex nature of branching the data supports that parents with low branching index will produce lower branching offspring, as almond hybrids produced significantly lower branching on average backcrosses compared to P. kansuensis hybr ids. Blind node heritabilities were in the low range, indicating that it is a complex trait Complex traits are influenced by many genes and t he environment Previous research has shown that summer temperatures impact the occurrence of blind nodes (Richard s et al., 1994; Boonprakob et al., 2003). The broad and transgressive segregation

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59 observed in the backcross families is also indicative of the complexity of this trait. There were also significant differences between the two years of evaluation 2010 and 20 11 (P that affected heritability. The peach genotypes AP00 30 and UFSharp had the highest frequency of blind nodes and contributed to the broad range of segregation in the different progenies On the other hand the male parent s relatively sm all differences contributed to the differences between the families. The narrowest range of segregation was detected in the P. kan ) backcross population (Figures 3 2 and 3 3) where both parents had the lowest blind node frequency among standard peaches and hybrids and produced the progeny having the lowest mean incidence of this disorder. These results suggest that breeding for fewer blind nodes is possible by using parents with lower frequencies of blind nodes, even though eradic ating or reducing greatly this disorder from the breeding program will take several generations and high selection intensity as indicated by the low heritability estimate. In conclusion the P. kansuensis and TNP almond parents and progeny contrasted in br anching and blind node propensity. P. kansuensis parents and progeny showed higher branching and lower blind node incidence compared to TNP parents and progeny, demonstrating that the traits are heritable. Low and moderate heritability estimates reveal tha t these are polygenic traits that are impacted by the environment. The data obtained will be used to identify QTLs and candidate genes that can be used to assist breeding for trees with low incidence of blind nodes and reduced branching.

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6 0 Table 3 1. Total number of progeny and number of contaminating self pollinated progeny in the interspecific backcross families used for studies in branching and blind nodes. FG= Flordaguard P. kan = Prunus kansuensis and TNP= Tardy Nonpareil Family Individua ls (#) Selfs (#) P. kan 3) 66 8 P. kan 6) 62 12 78 13 P. kan 3) 8 5 12 P. kan 6) 99 18 126 24 P. kan ) 8 8 9 Table 3 2 Mean b ranching index (BI) and blind node incidence values for the main axis (BNM) and lateral branches (BNL) of the parental genotypes ( winter of 2010 ) Parent BI BNM (%) BNL (%) Flordaguard x P. kansuensis 3 6.8 a z 6.8 b 7.4 b Flordaguard x P. kansuensis 6 5.5 a 1.7 b 3.4 b Flordaguard 3.8 a 13.3 ab 11.6 ab 6.1 a 60 .0 a 54.3 a 6.5 a 44.1 a 48.1 a 7.2 a 2.5 b 2.9 b P. kansuensis 7.8 a 3.3 b 1.7 b z Means followed by different letters are significantly different, Tukey Table 3 3 Mean b ranching index (BI) and blind node incidence values for the main axis (BNM) and lateral branches (BNL) of the parental genotypes ( winter of 2011) Parent BI BNM (%) BNL (%) Flordaguard x P. kansuensis 3 21.0 a z 2.2 b 4 0 b Flordaguard x P. kansuensis 6 17.8 ab 7.5 b 2.8 b Flordaguard 6.6 b 14.8 ab 19.8 ab 10.0 ab 53.3 ab 57.0 a 13.2 ab 77.5 a 71.4 a 10.5 ab 17.5 ab 16.3 ab P. kansuensis 17.8 a b 1.1 b 0 .0 b z Means followed by different letters are significantly different, Tukey (

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61 Table 3 4 Mean b ranching index (BI) and blind node incidence for the main axis (BNM) and lateral branches (BNL) in the interspecific backcross families (winter of 2010) FG= Flordaguard P. kan = Prunus kansuensis and TNP= Tardy Nonpar eil Parent BI BNM (%) BNL (%) P. kan 3) 5.7 ab z 20.5 b 18.4 b P. kan 6) 5.6 ab 24.9 b 21.3 ab 3.9 b 34.5 ab 32.1 a P. kan 3) 7.3 a 18.4 bc 14.5 bc P. kan 6) 8.2 a 23.2 b 18.4 b 5.2 b 44.4 a 34.4 a P. kan ) 8.3 a 10.7 c 11.5 c z Means followed by different letters are significantly different, Tukey ( Table 3 5 Orthagonal c ontrast s of backcross families by parent for branching index (BI) and blind node incidence in the main axis (B NM) and lateral branches (BNL) ( winter of 2010 ) Parent groups contrasted BI Group mean P value BNM Group mean P value BNL Group mean P value P. kansuensis 7.0 4.0 <0.001 z 19.5 39.4 <0.001 16.8 33.2 <0.001 5.0 6.9 0.0325 26.6 28.6 0.7838 23.9 22.4 0.2529 3 0 5.6 8.3 0.0119 22.7 10.7 0.0064 19.8 11.5 0.0212 7.7 8.3 0.0605 26.4 10.7 0.0021 16.4 11.5 0.0465 z Alpha = 0.05 Table 3 6 Mean b ranching index (BI) and blind node incidence values for the main axis (BNM) and lateral branches (BNL) in the interspecific backcross families ( winter of 2011 ) FG= Flordaguard P. kan = Prunus kansuensis TNP= Tardy Nonpareil Parent BI BNM (%) BNL (%) P. kan 3) 17.3 ab z 27.7 bc 24.4 b P. kan 6) 20.7 a 30.1 b 28.4 b x TNP) 9.5 b 46.1 ab 43.5 a S P. kan 3) 19.8 a 27.9 b 23.3 bc P. kan 6) 18.6 a 30.3 b 26.7 b 11.9 b 55.9 a 52.4 a P. kan ) 21.3 a 14.1 c 12.9 c z Means followed by diff erent letters are significantly different, Tukey

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62 Table 3 7 Orthagonal c ontrast s of backcross families by parent for branching index (BI) and blind node incidence in the main axis (BNM) and lateral branche s (BNL) (winter of 2011) Parent groups contrasted BI Group mean P value BNM Group mean P value BNL Group mean P value P. kansuensis 19.5 10.7 <0.001 z 26.0 51.0 <0.001 23.1 41. 8 <0.001 15.8 16.7 0.6902 34.6 38.1 0.6477 32.1 34.1 0.9537 30w 19.0 21.3 0.1769 28.9 14.1 <0.001 26.4 12.9 <0.001 19.2 21.3 0.1032 26.4 12.9 <0.001 25.0 12.9 <0.001 z Alpha = 0.05 Table 3 8 Covariates measured in the interspecific backcross families ( winter of 2010) FG= Flordag uard P. kan = Prunus kansuensis TNP= Tardy Nonpareil almond Parent Trunk diameter (mm) Tree height (m) P. kan 3) 35.3 ab 2.17 a P. kan 6) 35.5 ab 2.16 a 30.0 b 2.09 a P. kan 3) 45.6 a 2.40 a P. kan 6) 43.0 a 2.60 a 37.7 ab 2.69 a P. kan ) 39.4 ab 2.12 a z Means followed by different letters are significantly different, Tukey ( Table 3 9 Covariates measured in the interspecific backcross families ( winter of 2011) FG= Flordaguard P. kan = Prunus kansuensis TNP= Tardy Nonpareil almond Parent Trunk diameter (mm) Tree height (m) P. kan 3) 73.08 ab 5.04 a P. kan 6) 72.32 ab 4.84 a 62.00 b 4.60 a P. kan 3) 83.66 a 4.85 a P. kan 6) 80.70 a 5.32 a 73.20 ab 5.44 a 4 P. kan ) 70.07 b 4.76 a z Means followed by different letters are significantly different, Tukey (

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63 A B Figure 3 1. Branching index values of interspecific backcross progenies in A) 2010 and B) 2011. Vertical lines show borders between trees having different branching order s Arrows indicate blind node parental F 1 hybrid mean (F 1 ), back cross FG= Flordaguard P. kan = Prunus kansuensis and TNP= Tardy Nonpareil 1 st order 2 nd order 3 rd order 4 th order P. kan ) P. kan 6) F 1 F 1 F 1 BC BC BC P kan ) P. kan 6) 1 st order 2 nd order 3 rd order 4 th order F 1 F 1 F 1 BC BC BC

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64 Figure 3 2. Distribution of blind node incidence in lateral branches within inters pecific backcross families in 2010 Arrows indicate blind node parental F 1 hybrid mean (F 1 ), backcross family mean (BC) and parental peach selection mean FG= Flordaguard P. kan = Prunus kansuensis and TNP= Tardy Nonpareil almond x (FG x TNP ) UF97 P. kan ) Incidence of blind nodes (%) Individuals (%) UF x P. kan 6 ) F 1 BC F 1 BC BC F 1

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65 Individuals (%) Incidence of blind nodes (%) x (FG x P. kan 6 ) x (FG x TNP ) UF97 P. kan ) BC BC F 1 F 1 F 1 BC BC UFSharp Figure 3 3. Distribution of blind node incidence in lateral branches within interspecific backcross families in 2011. Arrows indicate blind node parental F 1 hybrid mean (F 1 ), backcross family mean (BC) and parental peach selection mean ( FG= Flordaguard P. kan = Prunus kansuensis and TNP= Tardy Nonpareil

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66 CHAPTER 4 MAPPING CANDIDATE GE NES AND QTL s ASSOCIATED WITH BRAN CING AND BLIND NODES IN P runus sp INTERSPECIFIC BACKCR OSS FAMILIE S Introduction Breeding for unconventional fruit tree architecture that would reduce production costs and increase yield potential has been very limited. Progress in this area has been hindered by a poor understanding of the genetic control of these traits (Segura et al 2007). There is genetic diversity for tree structure in closely related Prunus species that could be used to modify the architecture of peach trees (Scorza and Okie, 1990). For branches, is a sixth generation descendant from P. davidiana and peach (Sherman et al., 1991). P. kansuensis highly branched trees Almond ( P. dulcis ) develops lateral branches similar to peach and perennial spurs (Gradziel, 2001) although a great diversity of tree architecture can almond and its hybrids have limited branching in current and previous gr owth season. In addition to increasing phenotypic variability, interspecific hybridization in Prunus has been used to facilitate genetic studies by raising the percentage of informative markers (Scorza and Okie, 1990; Laurens et al., 2000; Martinez Gomez et al., 2003). Cultivated peach has been through several genetic bottlenecks and has low levels of genetic diversity (Mowrey et al., 1990; Dirlewanger et al., 2004a). The levels of polymorphism detected with different markers ranges from ~25 35% depending on the marker system used (Yamamoto et al., 2002). Formation of axillary lateral buds and consequent lateral bud outgrowth control the shoot branching pattern, an important factor for plant architecture (McSteen and Leyser,

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67 2005). Blind nodes are nodes la cking axillary flower and vegetative buds due to a failure in the formation of axillary meristems. Blind node incidence is another factor that affects peach tree architecture and productivity (Boonprakob et al 1996). There is genetic variability for blin d node incidence, and breeding against this disorder should be feasible if its mode of inheritance can be determined (Richards et al 1994). Genome mapping and quantitative trait analysis of architectural traits in peach can be the framework for understa nding the genetic basis of these and other complex traits (Tanksley et al., 1989). Previous genetic maps for Prunus serve as a source of markers and facilitate QTL detection (Chaparro et al., 1994; Dirlewanger et al., 2004a). Markers associated closely wi th advantageous traits can be used to select parents for crosses and cull undesirable progeny from crosses soon after germination, reducing time, expense and effort of maintaining and evaluating larger number of offspring (Bernardo, 2008; Bielenberg et al. 2009). QTL analysis for branching has been done in several species. Mapping of the branching locus (b1) in sunflower identified 15 associated RFLP markers and provided an opportunity for marker assisted selection for branching sunflower plants that can be used as restorer lines (Rojas Barros et al., 2008). Three significant QTLs were detected for the number of lateral branches in cucumber with additive variation for each QTL ranging from 1.6 to 29.5% (Li et al., 2008). Four QTLs for the total number of sylleptic branches were detected in apple, which explained 64% of the observed variability, suggesting a strong and complex genetic control for branching. An alternative approach for identifying the genes controlling a trait is the candidate gene approach where previous knowledge of biochemical and signaling pathways

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68 involved in detectable changes in the phenotype can supply a list of genes that can be mapped and tested for association with the trait (Kloosterman et al., 2010). In the past decade, branching mutants have been used to identify the genes responsible and elucidate metabolic pathways responsible for plant architecture differences in Arabidopsis and other species (Figure 4 1). An apical source of auxin as well as active polar auxin transport are r equired for apical dominance, AXR 1 (auxin resistant) protein is required for response to auxins in Arabidopsis ; axr 1 mutants display increased lateral branching and other pleiotropic effects such as defects in stem elongation and lateral root formation ( Stirnberg et al., 1999). The axr 1 mutants have a defect in auxin regulated transcription and do not respond to the application of exogenous auxin (McSteen and Leyser, 2005). In Arabidopsis there is a negative regulation of cytokinins mediated by AXR1 (Nor dstrom et al., 2004). Auxin regulation of the strigolactone and branching related genes MAX3 and MAX4 occurs by the intervention of AXR1 (Brewer et al., 2009). Auxin transported from the apex does not enter the bud directly, suggesting the existence of a s econd branching inhibitor messenger (Brewer et al., 2009). Candidate genes for the branching inhibitor came from profuse branching mutants with fewer pleiotropic effects, max (more axillary growth) in Arabidopsis rms (ramosus) in pea, dad (decreased apica l dominance) in petunia and htd (high tillering dwarf) in rice (Bennett et al., 2006). MAX1 encodes a cytochrome P450 family member and acts as an intermediary between MAX 3 4 and MAX2 in synthesizing a carotenoid derived hormone that inhibits branching (B ooker et al., 2004). Carotenoid cleaving dioxygenase 7 (CCD7) and carotenoid cleaving dioxygenase 8 (CCD8) are encoded by

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69 MAX3/RMS5/HTD1 ) (Johnson et al., 2006) and by MAX4/RMS1/DAD (Arite et al., 2007), respectively. MAX2 / RMS4 encodes a leucine rich repea t F box protein which is involved in the transduction of a branching inhibitor from MAX1 at the end of the MAX pathway and acts only in the shoot meristem ( Booker et al., 2004 ; Arite et al., 2007 ). Carotenoid cleavage enzymes are involved in biosynthesis of strigolactones (Matusova et al., 2005). Gomez Roldan (2008) et al. and Umehara et al. (2008) found that max3 and max4 in Arabidopsis rice and pea mutants were defective in strigolactone production and that exogenous application of strigolactones restored wild type reduced branching demonstrating the important role of strigolactones in branching regulation. In monocots, genes arresting bud development have been identified. Teosinte branched1 ( tb1 ) from maize (Doebley et al., 1997), is considered responsible for the differences in the suppression of axillary branches between maize and its wild ancestor teosinte. TB1 encodes transcription factors containing a TCP domain that regulates cell division (Cubas et al., 1999) and inhibits branching without pleiotropic effects. Branched1 ( BRC1 ) and Branched 2 ( BRC2 ) from Arabidopsis show sequence homology to TB1 and also control bud development. Expression patterns of B RC1 and BRC2 indicate that they are expressed primarily within the bud. Mutant and expression analyses show that BRC1 and BRC2 are downstream of the MAX pathway and transcription is affected by environmental stimuli, such as high density, where less branch ing corresponded to more than double BRC1 mRNA expression (Aguilar Martinez et al., 2007). In tomato two Arabidopsis BRC1 like paralogues have been

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70 identified, SlBRC1 and SlBRC2 which are expressed in arrested axillary buds (Martin Trillo et al., 2011). T he supershoot ( SPS ) gene from Arabidopsis encodes a cytochrome P450 involved in axillary meristem formation and development. SPS mutants show an over proliferation of branches and higher cytokinins levels (Tantikanjana et al., 2001). Mutants defective in t he formation of axillary meristems have been characterized (Figure 4 1) (Wang and Li, 2006). PIN1 (pin formed) is an auxin efflux carrier that develops auxin gradients in the shoot apical meristem and subsequent formation of axillary meristems (Benkova et al., 2003). The pin1 mutant is unable to form lateral organs but the mutant phenotype can be complemented by exogenous application of auxin in Arabidopsis and tomato (Reinhardt et al., 2000). Revoluta ( REV ) is required for initiation of floral and shoot l ateral meristems. REV encodes a homeodomain/leucine zipper transcription factor, and in rev mutants there is a complete absence of meristem activity in leaf axils (Otsuga et al., 2001). Tomato ( Ls ) and Arabidopsis ( LAS ) lateral suppressor and rice (MOC1) m onoculm1 are orthologous genes (Wang and Li, 2008), LAS is a member of the GRAS (giberellin insensitive ( GI ), repressor of GA 1 3 ( RGA ) and scare crow ( SCR )) transcription factor family and mutants for these genes fail to produce axillary meristems during v egetative development (Greb et al., 2003; Li et al., 2003). Expression analysis showed that LAS acts upstream of REV in axillary meristem development (Greb et al., 2003). CUC1 CUC2 and CUC3 (cup shaped cotyledons) and CUC3 orthologous CUP (cupuliformis) in Anthirrinium and NAM (no apical meristem) in petunia encode

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71 transcription factors within the transcription factor NAC gene family (no apical meristem) ( NAM ). Arabidopsis transcription activactor/factor ( ATAF ) and cup shaped cotyledon ( CUC ) have redundan t functions and are involved in the regulation of embryonic stem meristem formation in the axils of cotyledons and organ boundaries for the development of separated organs besides formation of axillary meristems (Souer et al., 1996; Hibara et al., 2006; Kw on et al., 2006; Hasson et al., 2011). CUC2 and CUC3 overlap in function but are upstream of LAS in Arabidopsis whereas the role of CUC1 has not been well elucidated in this process (Hibara et al., 2006). The hypothesis tested in this study is that the gen es involved in meristem formation and outgrowth in model systems are also involved in controlling branching and blind node development in Prunus The objective of the present study is to identify QTLs and candidate genes associated with branching and bli nd nodes in Prunus. The identification of associated markers will permit marker assisted selection for trees with better tree architecture and reduced incidence of blind nodes in peach. Materials and Methods Plant Material Seven backcross (Table 4 1) fa milies were generated and planted in Gainesville, Florida, in October 2008 in a complete randomized block design with a total of four blocks. Clonally propagated trees of the parents used to derive the backcrosses were planted in each block. The parents o f the backcrosses were selected based upon their contrasting Prunus kansuensis P. kan ) F 1 hybrids showed higher branch production and lower blind

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72 1 hybrids. Two selections from the P. kan F 1 hybrid population (seedlings number 3 and 6) and one selection from TNP F 1 hybrid population (seedling number 1260) were used as male parents. One P. kansuensis hybrid wa s also selected for generating backcrosses as a as backcross female parents. FG x P. kan and FG x TNP hybrids backcrossed to P. kan for the amplification and sequencing of candidate genes. The haploid sequences were used to determine peach haplotypes. DNA Extraction Genomic DNA was extracted from leaf tissue of P. kan TNP almond, FG peach, P. kan P. kan each backcross family (Table 4 1) using the CTAB method (Doyle, 1991). Successful DNA isolation was confirmed by electrophoresis of diluted DNA samples in a 1% agarose gel made using TBE buffer (10.8g Tris Base, 5.5g Boric acid, 4mL 0.5M EDTA (pH 8.0)) and run at 120 volts for 60 minutes before being stained with ethidium bromide. Lambda DNA standards of 5, 25, 50, and 100ng/L were loaded next to the samples to obtain a visual estimate of the concentration of isolate d DNA. The gel was photographed on a transilluminator and the DNA concentration was determined by spectrophotometry.

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73 Candidate Gene Primer Design A group of candidate genes associated with axillary meristem formation or blind nodes and shoot outgrowth or b ranching were selected (Appendix, Table A 2). Arabidopsis sequences were retrieved from the ICBR GenBank database and BLAST was carried out using the tblastx option in Phytozome 7.0 (Joint Genome Institute and Center for Integrative Genomics) with the Arab idopsis gene sequence as query and peach genome as target. The output peach sequence with the highest score and e value was selected. Exon and intron splicing from the peach gene sequence were determined by means of Phytozome 7.0 or tblastx using the peach sequence as query and mRNA database as target in the GenBank BLAST application. Once exon and intron boundaries were determined, Primer3 was used to select primers that amplified a target containing flanking exon sequence and a single intron (Appendix, Ta ble A 2). Branching Index Data Collection Data for the total number of first order branches; and total number of second, third and fourth order branches from three randomly selected first order branches located on the lower, intermediate and upper part o f each tree was obtained during the winters of 2010 and 2011. The branching index was calculated for each tree (Carrillo Mendoza et al. 2010). Blind Node Data Collection Blind node frequency was measured as the percentage of blind nodes from the total num ber of nodes in the uppermost 50 nodes of the main axis of the tree, and the percentage of blind nodes from three randomly selected lateral branches that grew the

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74 previous season. These branches were chosen because they represent the genotype and genotype x environmental interaction from the previous growing season. Candidate Gene Primer PCR Optimization The optimum annealing temperature (55 62 C ) for each primer pair was determined and the PCR reactions run using two haploids and all the genotypes used to generate the backcross populations. The haploids were included as controls to confirm the amplification of single loci and to generate reference haplotype sequence data (Appendix, Tables A 3 to A 16). PCR was carried out in a total volume of 50 L contain ing 5 L 10X ThermoPol Reaction Buffer (10mM KCl, 10mM (NH 4 ) 2 SO 4 20mM Tris HCl, 2mM MgSO 4 0.1% Triton X 100, pH 8.8 at 25C), 5 L 5 M forward primer, 5 L 5 M reverse primer, 4 L 2.5mM dNTP, 1 L Taq DNA Polymerase, 15 L DNA grade water, and 15 L o f approx. 10ng/L DNA. PCR reactions were done on an Eppendorf thermal cycler using the following cycling parameters: initial denaturation for 3 min. at 94C, followed by 40 cycles of 30 s. at 94C, 30 s. at the primer specific annealing temperature ( App endix, Table A 2 ), and 1 min. at 72C; and a final extension of 7 min. at 72C. PCR products were run on a 3.5% electrophoresis agarose gel stained with ethidium bromide at 220 volts and observed and photographed on a transilluminator to confirm amplifica tion, determine the approximate size of the amplified DNA fragment and determine if length polymorphisms were present. Candidate Gene Sequencing Bands of the PCR products were excised from the gel and the PCR products were purified with Qiagen MinElute Ge l Extraction Kit The purified PCR products and corresponding primers (10uM) were used for sequencing at the University of Florida ICBR Core Sequencing lab. The sequence identity was confirmed by comparison to

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75 reference sequences using the blastn option o f NCBI BLAST (National Library of Medicine). The parental sequences were aligned using Sequencher version 5.0 sequence analysis software (Gene Codes Corporation, Ann Arbor, MI USA). Sequence and fragment size polymorphisms were detected by comparison of parental sequences (Appendix, Tables A 3 to A 16). Genotyping SSR markers Genomic DNA from the backcross parents was amplified by polymerase chain peach (T x E) Prunus genomic reference map (Dirlewanger et al. 2004b). Polymorphic markers spaced at a map resolution of approximately 20cM were selected and PCR amplified in the backcross progeny ( Appendix, Table A 17 ). PCR was carried out in a total volume of 10 L containing 1 L 10X ThermoPol Reaction Buffer (10mM KCl, 10mM (NH 4 ) 2 SO 4 20mM Tris HCl, 2mM MgSO 4 0.1% Triton X 100, pH 8.8 @ 25C), 1 L 5 M forward primer, 1 L 5 M reverse primer, 0.8 L 2.5mM dNTP, 0.2 L Taq DNA Polymerase, 3 L DNA grade water, and 3 L 10ng/L D NA. PCR reactions were performed in an Eppendorf thermal cycler using the following cycling parameters: initial denaturation for 3 min. at 94C, followed by 40 cycles of 30 s. at 94C, 30 s. at the primer specific annealing temperature (Table 4 17), and 1 min. at 72C; and a final extension of 7 min. at 72C. PCR products were size separated on a 3.5% agarose gel stained with ethidium bromide at 220 volts and observed and photographed on a transilluminator to confirm amplification and to determine the appr oximate size of the amplified DNA fragments. Markers segregating for alleles that differed by more than 6

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76 bp were visualized and genotyped by size separation after electrophoresis for a period of 4 hours. Markers segregating for alleles that differed by le ss than 6 bp were fluorescently labeled and detected by capillary electrophoresis. A 100x 400x dilution of PCR product was sent to the ICBR Genetics Analysis Laboratory at the University of Florida for fragment analysis on an ABI 3730 Automated Sequencer. Allelic segregation was visualized using the Soft Genetics analysis program GeneMarker (SoftGenetics, State College, United States) version1. Data for leaf and flesh color was collected and used as additional markers for mapping and QTL analysis. Candidat e gene genotyping with restriction enzymes The candidate gene sequences were scanned for restriction site polymorphisms to allow the mapping candidate genes via CAPs (cleaved amplified polymorphic sequences) ( Appendix, Table A 18 ). DNAs representing the ba ckcross parents and the backcross progeny were included in each CAPs assay. PCRs were first carried out in a total volume of 10 L containing 1 L 10X ThermoPol Reaction Buffer (10mM KCl, 10mM (NH 4 ) 2 SO 4 20mM Tris HCl, 2mM MgSO 4 0.1% Triton X 100, pH 8.8 at 25C), 1L 5 M forward primer, 1 L 5 M reverse primer, 0.8 L 2.5mM dNTP, 0.2 L Taq DNA Polymerase, 3 L DNA grade water, and 3 L approx. 10ng/L DNA. PCR reactions were done on an Eppendorf thermal cycler using the following cycling parameters: initial denaturation for 3 min. at 94C, followed by 40 cycles of 30 s. at 94C, 30 s. at the primer specific annealing temperature ( Appendix, Table A 2 ), and 1 min. at 72C; and a final extension of 7 min. at 72C. PCR products were run on a 3.5% agarose gel stained with ethidium bromide at 220 volts and observed and photographed on a transilluminator to confirm amplification.

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77 PCR products were digested with restriction enzymes for 6 hours under the manufacturers recommended conditions ( Appendix, Table A 1 8 ). The samples were genotyped by running on a 2.0% agarose gel stained with ethidium bromide at 160 volts for four hours and photographed on a transilluminator. Candidate gene genotyping with high resolution melt analysis Sequences without informative re striction enzyme recognition sites were genotyped by high resolution melt analysis (HRMA) ( Appendix, Table A 19 ). Primer3 software was used to select primers to generate SNP containing amplicons less than 200 bp in size. PCR and HRMA were carried out using a Roche LightCycler 480 Real Time PCR system PCR reactions were prepared in a total volume of 10 L containing 5 L of Roche High Resolution Melting Master Mix 1 L 25 mM MgCL 2 0.5 L 4mM forward primer, 0.5 L 4mM reverse primer, 1 L DNA grade wate r and 2 L template DNA. The PCR cycling parameters were: one pre incubation cycle at 95 C for 10 minutes, followed by 55 amplification cycles of 10 s. at 95C, 15 s. at the appropriate annealing temperature ( Appendix, Table A 19 ), and 15 s. at 72C. The HRMA cycling parameters were: one minute at 95C, one minute at 40C and finally 65 to 95C raise step, followed by a cooling step at 40C. The experiment was analyzed using the LightCycler 480 software version 1.5 and LightCycler 480 Gene Scanning softwa re ; normalized melting curves were used to obtain the genotypes. The two parents were included in each HRMA run to ensure accurate genotyping and confirm the genotype of each backcross individual. Statistical Analysis Linkage maps were constructed with Ma pmaker/Exp 3.0 (Lander et al., 1987) using the SSRs, morphological and candidate gene markers. The Kosambi map

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78 function was used to convert recombination frequencies to genetic map distances (centiMorgan, cM). A minimum LOD of 3.0 and a maximum recombinati on fraction of 0.4 were used to declare linkage between markers. Linkage groups were formed by the mmand. After the first map was generated, the genotype data was checked for possible genotype errors using the Graphical Genotype (GGT) 2.0 software (Berloo, 2008). A final map was constructed using the corrected genotype. The genotype data was tested for 2 test. A homogeneity test based on 2 test was performed to determine if the marker segregation data from individual backcross families could be combined for QTL analysis. QTL analysis of branching index a nd blind nodes was performed with Windows QTL Cartographer version 2.5 (Wang et al., 2011) using the composite interval mapping function. Background markers, or cofactors, and intermarker positions were selected by the software program to reduce residual g enetic variation from unlinked QTL. Threshold LOD scores significant at 0.05 and 0.01 were chosen to detect putative QTL based on significance levels determined by a permutation test (1000 permutations, 0.05% level) (Churchill and Doerge, 1994). Results an d Discussion Phenotypic Differences within and among Backcross Families There were significant differences (P 0.05) among the different backcross populations for branching index and blind nodes in 2010 (Table 4 2) and 2011 (Table 4 3). FG x P. kan 97 P. kan hybrids backcrosses had more branching and less blind node incidence whereas FG x TNP backcrosses had fewer branches and

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79 more blind nodes. Despite the differences detected between FG x P. kan and FG x TNP backcrosses, there was a wide segre gation for branching and blind nodes within the families. Branching index values ranged from values of 2 to 25 and 2 to 47 in 2010 and 2011, respectively in FG x P. kan backcrosses while they varied from 2 to 15 and 2 to 47 in 2010 and 2011, respectively f or FG x TNP backcrosses. Blind nodes varied from 0 to 90% and 0 to 80% in 2010 and 2011 respectively for FG x P. kan backcrosses while the frequency varied from 0 to 90% both years for FG x TNP backcrosses. The proportion of individuals that had low incide nce, classified as having 0 30% of blind nodes, was around 0.70 in 2010 and 2011 for FG x P. kan backcross populations. The proportion of individuals with low incidence of blind nodes in FG x TNP was approximately 0.30 in 2010 and 2011. The backcross peach blind nodes among all the parents. These female parents contributed to the broad range of segregation in the different progenies. On the other hand, th e male parents contributed to the differences among families, where FG X TNP almond hybrids showed higher incidence of blind nodes compared to FG x P. kan P. kan ) presented the lowest average and narrowest variation in seg regation for blind nodes (0 30% in both years) among all the families. This same family had the highest branching frequency with variation of the branching index value ranging from 2 to 15 and 5 to 50 for 2010 and 2011, respectively. These results show tha t branching and blind nodes are complex quantitative traits, influenced by multiple genes. Polymorphism in Branching and Blind Node Candidate Genes Most candidate gene sequences contained polymorphisms in the regions amplified ( Appendix, Tables A 3 to A 16 ). Some exceptions for P. kansuensis hybrids were

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80 PpCUC1 ( Prunus persica CUC1) and PpCUC2 where no introns with SNPs could be rids SNPs were not detected for PpCUC3. Low levels of sequence polymorphism for branching candidate genes have also been reported in Arabidopsis where a panel of 24 accessions from different geographic regions had no polymorphism for the PINOID gene (Ehren reich et al., 2007), PpMAX1 primers produced two fragments when tested in the haploids, suggesting the existence of gene duplication. The two copies had similar sequences but there was an indel of 53 bp. The copy having the insertion was used for genotypin g in order to design primers that could amplify only with the presence of the insertion and map one copy. The sequences obtained from the different genotypes for branching and blind node candidate genes ( Appendix, Tables A 3 to A 16 ) made it possible to id entify P. kansuensis track the inheritance of these differences into the hybrids used to generate the backcrosses for the present study. There were differences among the different candida te genes for the frequency of SNPs (Table 4 4), PpMAX 2, 3, 4 and PpSPS genes had the highest frequency of SNPs. In most of the genes the SNP frequency within the intron regions was higher than in the exon regions as was expected. Exceptions to this includ ed PpMAX3, which had a higher high frequency of SNPs in exon regions. The rate of transitions was higher than transversions in most of the candidate genes, PpSPS and PpMAX4 had the

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81 highest frequency of transitions and PpAXR1 had the highest frequency of tr ansversions. From a genotype perspective, there are noticeable differences for the frequency of heterozygous positions within the branching and blind node candidate gene sequences (Table 4 had the P. davidiana in its peach selection containing only peach genotypes in its pedigree has a similar fr equency of heterozygocity (1/1000), which is high if compared to the average frequency of SNPs in the whole genome sequence of three peach genomes (1/40,000) (Ahmad et al., 2011). The low frequency of SNPs in peach selections and haploids is an indicator o f the low genetic variability within the UF peach breeding program, where most selections are hybrids and few self pollinated populations are generated. Therefore it is necessary to use interspecific crosses to increase variability and permit mapping of se gregating sequence fragments studied were found to be homozygous in P. kansuensis, a self p ollinated species (Cao et al., 2011). Almond and P. kansuensis had sequence haplotypes in 11 out of 14 loci and 12 out of 14 that were not present in the peach genotypes studied, respectively (Table 4 6). This is manifested in the high number of heterozygo P. kansuensis hybrid (FG x P. kan ) sequences. These results confirm the power of

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82 interspecific crosses for genetic studies in peach as they increase the polymorphism frequency. Genetic Maps The peach candidate genes and SSRs were positioned in linkage maps for each individual FG x P. kan and FG x TNP backcross family (Appendix, Figure A 1). The homogeneity test did not detect statistical differences (P 0.05) among the individual FG x P. ka n and FG x TNP backcross families. This permitted the generation of a combined map from the backcross families sharing the same hybrid male parent (Figures 4 2 and 4 3). From all the candidate genes that were segregating, it was not possible to map the PpM AX1 candidate gene with the linkage criteria used. BLAST analysis of the peach genome using Phytozome 7.0 (Joint Genome Institute and Center for Integrative Genomics) indicated the presence of two tandem open reading frames with high homology to the Arabid opsis thaliana MAX1 gene sequence. PpMAX1 sequences were physically located in LG1 around 34,892 kbp. FG x P. kan combined map (Figure 4 2) consisted of 28 SSRs, two morphological markers and 10 candidate genes. The map represents 87% coverage of the T x E markers ranged between 9.2 and the maximum distance was 31.2 cM between markers. FG x TNP combined map (Figure 4 3) consisted of 26 SSRs, two morphological markers and 12 cand idate genes, the selected SSRs represent 90.6% coverage of the maximum distance was 31.9 cM.

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83 P. kan ) backcross map (Figure 4 4) contained 21 SSRs, 1 morphological marker and 10 candidate genes, the SSRs represent 82% coverage of the T x E map, the map distance was 320.4 cM, the average distance between markers was 10.1 cM, and the maximum distance was 25.1 cM. Regions from the T x E reference map th at were not represented in the FG x P. kan backcross combined map due to the lack of polymorphic markers were at the top of LG1, the bottom of LG1 where PpMAX4 was located, the top of LG6 where the candidate gene PpLAS was positioned and the top of LG8. Re gions from the T x E reference map that were not represented by SSRs in the maps of the FG x TNP backcrosses were on the top of LG1; and the bottom of LG 4 where PpCUC1 and PpCUC2 were positioned, LG6 and LG8. Cao et al. (2011 ) reported low levels of polymorphism in some genomic regions in P. kansuensis peach backcrosses and used sequence related amplified polymorphisms (SRAPs) to improve genome coverage (Cao et al., 2011). Map maker was used to generate seven linkage groups in all the FG x P. kan and FG x TNP backcross families (Figures 4 2 and 4 3). Linkage groups 1 5 and 7 were homologous to the same LG from the T x E reference map. However, a chimeric 6/8 linkage group contai ning portions of LG6 and LG8 from the reference map was generated. This results from a reciprocal translocation between LG6 and L8 near the Gr leaf color locus (Jauregui et al., 2001; Yamamoto et al., 2001; Lambert and Pascal, 2011). This 6/8 translocation has been detected only in populations segregating for the dominant Gr allele for red leaf color (Yamamoto et al., 2001; Dirlewanger et al., 2007; Lambert and Pascal, 2011) similar to the FG x P. kan and FG x TNP families.

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84 P. kan ) population does not segregate for green vs. red leaf, only one polymorphic marker (udp98409) was identified in LG8 (Figure 4 4) and therefore the generated genome map consists of only 7 linkage groups. Similar difficulties in identifying pol ymorphic markers in linkage group 8 have been previously reported (Dirlewanger et al., 2007). 2 test was detected in FG x P. kan backcrosses (Figure 4 2). Markers on LG1 and LG4 showing segregation distortion favored homozygous individuals, while markers at LG3 and LG6/8 favored heterozygous individuals. All loci demonstrating distorted segregati on ratios in the FG x TNP backcrosses favored homozygous genotypes (Figure 4 3). P. kan ) population (Figure 4 4). The loci on LG1 favored heterozygous genotype while those on LG6/8 an d LG7 favored the homozygous genotype. The markers or regions where segregation distortion was present where similar in the FG x P. kan and FG x TNP backcross families, indicating similar causes for the occurrence of distorted ratios according to the cross Segregation distortion due to gametic selection or zygotic lethals resulting from chromosomal rearrangements is reported to be more frequent when the level of divergence between parents increases (Kianian and Quiros, 1992). This suggests selection acting against particular genetic combinations from distant parents (Paterson et al., 1990) or possible mistakes in the coupling of homologous chromosomes during meiosis I at specific chromosomal regions (Dirlewanger et al., 2004a). Segregation distortion can also result from selection at the

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85 post zygotic level in peach x almond F2 where the genetic differences between these two species results in hybrid weakness and hybrid breakdown (Foolad et al., 1995). The proportion of marker loci demonstrating segregati on distortion has been reported to range from 36% (Foolad et al., 1995) to 45% of loci (Joobeur et al., 1998; Bliss et al., 2002) in F 2 peach x almond crosses. In this study, 30, 37 and 12% of the markers respectively for FG x P. kan 47 P. kan backcrosses deviated from expected mendelian ratios, respectively. In the FG x TNP backcross maps, approximately 60% of the markers demonstrating segregation distortion where in LG6/8. However, the frequency for corresponding markers in FG x P. kan was 14 36%. The presence of the self incompatible allele from almond causes selection against almond alleles at the pre zygotic level around the self incompatible locus which is located at the bottom of LG6 in peach and almond (Joobeur et al., 1998; B liss et al., 2002). Similarly in the present experiment, the peach homozygotes (peach/peach) were favored over almond heterozygotes (peach/almond) in loci located at LG 6/8 in FG x TNP backcrosses, in contrast with FG x P. kan which in the same region the peach/ P. kan heterozygotes were favored over the peach/peach homozygotes. Additionally, chromosomal rearrangements are reported to lead to segregation distortion in Brassica sp. (Paterson et al., 1990). In Prunus, all loci surrounding the 6/8 translocation breakpoint presented segregation distortion (Jauregui et al., 2001; Lambert and Pascal, 2011). In this study segregation distortion was also detected in the LG6/8 translocation in the FG x P. kan and FG x TNP backcrosses.

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86 Branching Index QTLs Individual b ackcross family analysis for FG x P. kan backcrosses presented one QTL at LG2 in 2011 (Appendix, Figures A 2 to A 5). Combined FG x P. kan backcross families analysis (Table 4 7 and Figure 4 5) confirmed the QTL on LG2 in 2011 ( P P ( P P phenotypic variation for branching in 2010 and 2011, respectively. The difference between the i ndividual family and half sib combined analysis demonstrates the increased power from larger samples for identifying QTLs. For instance, the major QTL for 2011 in LG2 was more significant in the family with larger number of individuals P. kan 6) (Appendix, Figure A 5) and in the combined analysis of the families (Figure 4 5) where the LOD score increased noticeably to 9.9. In addition, QTLs for 2010 that were not previously detected in individual analysis were detected in the combined anal ysis. The differences between 2010 and 2011 in the QTLs discovered were due to ). This moderate correlation suggests possible differences in branching development among different growing seasons or during different stages of development of the tree. Therefore, a third year evaluation is needed to confirm the QTLs detected in the second year and evaluation during three growing seasons is recommended in future studies. Individual backcross family a nalysis for FG x TNP presented one QTL on LG7 (Appendix, Figures A 6 and A 7). Combined FG x TNP backcross family analysis (T able 4 8 and Figure 4 6) detected one QTL on LG7 ( P 2011, one in LG4 and one in LG7 ( P

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87 analysis explained 6 and 12% of the phenotypic variation in 2010 and 2011, respectively. Similar to the FG x P. kan backcrosses, the QTL identified i n LG4 in 2011 was not present in 2010 (Figure 4 6). The lack of correspondence for all the QTLs was also paralleled by a moderate correlation (r=0.54, P ) between the two years of data. P. kan ) b ackcross population (Table 4 9 and Figure 4 7) ( P in 2010. The first QTL was on LG2 close to a QTL detected in the FG x P. kan, but detected in 2011, and a second QTL on LG5. The QTL with the largest effect on branching in the FG x P. kan and F G x TNP backcross families were located in different regions (Figures 4 5 and 4 6). Previous studies show that different QTLs can be detected in populations with different genetic backgrounds. QTLs for floral and vegetative budbreak were situated in differ ent genomic regions in two different apple intraspecific F 1 populations, suggesting the influence of diverse genes on budbreak in different genetic backgrounds (Celton et al., 2011). A plum pox virus resistance QTL detected in F 1 and F 2 populations of P. davidiana P. davidiana F 1 population (Rubio et al., 2010), indicating strong QTL interactions with the susceptible peach and nectarine parents. In this study, the primary determinants were P. kansuensis Previous research shows inconsistency of QTLs in different crops resulting from small population sizes and sampling error (Tanksley and Hewitt, 1988; Beavis et al., 1991;

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88 Plomion and Durel, 1996). In many cases different loci can be segregating in different populations. If the locus is not segregating in a particular population, there is no segregat ion data to allow the detection of a QTL at that locus. More stable QTLs are required to be useful in marker assisted breeding (Celton et al., 2011). Faster progress in breeding commercial quality peaches would be made if we were able to detect and selec t for the branching and blind node QTL segregating within P. persica However, the low frequency of marker polymorphism will hinder the task. The QTL found in this study may be useful in cases where almond and P. kansuensis are being used to introgress no vel traits to peach. Additionally, our data indicates that both traits are under strong environmental influence and that QTL by environment interactions cannot be ignored. Therefore, additional research is needed to validate the QTL detected in the present study. Blind Node QTLs Individual backcross family analysis for FG x P. kan backcrosses presented one QTL on LG1 and LG2 (Appendix, Figures A 8 to A 11). Combined FG x P. kan backcross family analysis confirmed t he QTLs ( P hi ghest LOD scores ( Table 4 10, Figure 4 8 ) although the QTL on LG1 is only significant for blind nodes in lateral branches in 2010 and 2011, similar to another QTL detected on LG3. Other significant QTL s ( P LG6/8, but t hey were not consistent across years and traits. The detected QTL explained 25 and 19% of the variation for blind nodes in main axis and lateral branches respectively in 2010, and 15 and 33% in 2011. Individual backcross family analysis for FG x TNP backcr osses detected one QTL on LG1, two at LG3, one on LG6/8 and one on LG7, which presented the highest LOD

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89 score (Appendix, Figures A 12 and A 13). Combined FG x TNP backcross family analysis confirmed the QTL detected in the individual family analysis (Table 4 11, Figure 4 9) The QTL with the highest LOD score was detected at LG7 (Table 4 11). The QTL found explain 52 and 64% of the phenotypic variation for blind nodes in main axis and lateral branches respectively in 2010, and 54 and 53% in 2011. As observe d for branching, the largest effect QTL discovered for blind nodes in FG x P. kan and FG x TNP families were different. However, lower effect QTL observed on the top of LG1 and LG3 and in the middle of LG4 and LG6/8 are localized in similar regions in both groups of families (Figures 4 8 and 4 9). Blind node QTL s P. kan ) population (Figure 4 10). This could be due to the small population size of the backcross family or to the low phenotypic variability for b lind nodes in this family. The expression of blind nodes in this family was much more restricted with blind node frequency ranging from 0 to 30% whereas the frequency of blind nodes in FG x P. kan and FG x TNP backcross populations ranged from 0 90%. Alle lic effects from QTLs Using the markers most closely linked to the QTLs detected, it was possible to measure the average phenotypic effect of different alleles on branching and blind node expression in the backcross progeny. FG x P. kan combined analysis detected different QTLs for branching in 2010 and 2011. For the 2010 QTL, heterozygous peach/ P. kan individuals for the marker closest to the QTLs on LG5 (PpCUC3) presented reduced branching (branching index = 7.6) compared to the peach/peach homozygotes ( branching index = 10.5). When the QTL detected in 2011 on LG2 (bppct030) was used to separate the population into

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90 heterozygous peach/ P. kan versus homozygous peach/peach progeny, the heterozygotes had a higher branching index value (23) in comparison to t o the homozygotes (16). Different QTLs were detected in FG x TNP backcross families in both years. The QTL detected in 2010 on LG7 (cppct033) separated the population in peach/almond heterozygous individuals having a branching index value of 5 versus homo zygous peach/peach progeny which had an average of 6.2. In 2011, the QTLs on LG4 (PpCUC1) and LG7 (pms2) showed that peach/almond heterozygous individuals at both QTLs had a lower branching index value (6.6) compared to peach/peach homozygous (12.1). The data obtained from the QTLs and from the backcross family phenotypes demonstrates the effect from the P. kansuensis hybrid parent in increasing branching and of the almond hybrid parent in reducing branching relative to peach. These results confirm the pot ential of almond as a germplasm resource for breeding peach trees with less complicated branching that would reduce pruning. Allelic effects on blind node expression were considered using an average of blind nodes in the main axis and lateral shoots across the two years of evaluation, since the QTLs detected were consistent across traits and years. In the FG x P. kan backcross populations, progeny heterozygous for the peach/ P. kan alleles at LG1 ( Y ) and LG2 (udp96013) QTLs had fewer blind nodes (14.6%) comp ared to those homozygous for the peach alleles at both loci (41.6%). Here the contribution from P. kansuensis resulted in reduced blind node incidence in the offspring, which demonstrates the value of this species for breeding.

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91 In the FG x TNP families, th e three QTLs at LG1, LG3 and LG7 had different parent of origin effects. The QTL having the highest LOD on LG7 (cppct022) indicated that heterozygous peach/almond individuals had a higher frequency of blind nodes (53.7%) compared to the homozygous peach/pe ach progeny (31.3%). At the other two QTLs, progeny homozygous for peach allele presented a higher incidence of blind nodes than peach/almond heterozygotes. Based upon the genotypes at the three QTLs, the individuals that presented lower blind node frequen cy (18.2%) were heterozygous peach/almond alleles at the QTLs on LG1 (PpBRC2) and LG3 (cpdct027) and homozygous for peach/peach at the QTL at LG7 (cppct022). On the other hand, the average for individuals with all other possible genotypes at the three QTL had a blind node frequency of 67.9%. Indicating the contribution from both parents, peach and peach x almond hybrids to modulate blind nodes as observed in the phenotypic data Relationships between Branching and Blind Node QTLs Blind nodes and branching are associated since the formation of axillary meristems precedes and is necessary for the development of axillary shoots. In the present study, the blind node trait in the main axis and lateral shoots had a negative and relatively low relationship with br anching index (r= 0.19 and 0.21 respectively P 0.05), suggesting a negative influence from blind nodes on branching. However, other factors such as apical dominance that control bud dormancy or extension growth act as well. The largest effect QTLs detecte d for both branching and blind nodes were localized in different regions of the same linkage group (LG2) in the FG x P. kan backcross families (Figures 4 5 and 4 8). Similarly, the main QTLs for branching and blind nodes were in different regions of the sa me linkage group (LG7) in the FG x TNP backcross families (Figures 4 6 and 4 9). The only QTL region detected common to

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92 both blind nodes and branching was localized close to bppct008 on LG6/8 (Tables 4 8 and 4 11) in the FG x TNP population. QTLs Detection by Candidate Genes Candidate genes were found to be more commonly associated with small effect QTLs than large effect QTLs (Figures 4 5, 4 6, 4 8 and 4 9). PpCUC3 was the closest candidate gene marker to a minor branching QTL in the FG x P. kan backcrosses in 2010 (Table 4 7). In the FG x TNP backcrosses PpCUC1 was the closest marker to a small effect QTL for branching in 2011 (Table 4 8). The QTLs close to PpCUC3 and PpCUC1 had limited effects on the phenotypic v ariance (R 2= 0.06). CUC1 and CUC3, which are implicated in organ boundary formation and meristem identity, also play a role in axillary meristem formation in Arabidopsis (Hibara et al., 2006). These genes are not reported to play a role in shoot outgrowth after the axillary meristems have been successfully formed. Hence, PpCUC1 was expected to be associated with blind nodes. Conversely, two candidate genes associated with shoot outgrowth in Arabidopsis MAX2 and BRC2 were the closest markers to small effe ct blind node QTLs. PpMAX2 was detected in a lateral shoot blind node QTL for FG x P. kan and a main axis blind node QTL for FG X TNP blind node in 2010. PpBRC2 was closely associated with a main axis blind node QTL in 2011 and lateral shoot blind node QTL s in 2010 and 2011. The contribution of these QTLs to the total phenotypic variance was low, between R 2 =0.05 and 0.10. MAX2/RMS4 in Arabidopsis and pea act locally in the node to inhibit shoot growth from the axillary bud after a mobile signal is produced by the branching genes, MAX1 MAX3 and MAX4 (Stirnberg et al., 2007). There is no previous information of MAX2 being involved in axillary meristem formation. Arabidopsis brc1 mutants and in a weaker manner brc2 mutants showed accelerated formation of axil lary

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93 meristems and fewer leaf axils without buds, besides having profuse branching, indicating some role of this gene in axillary bud development in addition to shoot outgrowth (Aguilar Martinez et al., 2007). In a comparison between candidate gene associa tion and QTL mapping for branching genes in Arabidopsis (Ehrenreich et al., 2007), there were significant associations between MAX2 MAX3 and SPS and branching variation in a panel of 96 accessions. However, the location of these genes did not overlap addi tive but epistatic QTLs in two recombinant inbred line populations. Similarly in our study the major QTLs did not locate in the same regions as the candidate genes, although these were included in the QTL analysis as marker genes. There are additional bra nching and blind node associated genes identified in Arabidopsis and other species that might be used in future studies. For instance Arabidopsis regulator of axillary meristems ( RAX1 RAX2 and RAX3 ) are members of the MYB family of transcription factors, the three RAX genes have redundant functions and mutants fail to produce axillary meristems, RAX genes act early in establishing the axillary meristem niche and is required for the expression of CUC2 (Keller et al., 2006; Muller et al., 2006). BLAST analys is of the RAX gene sequences from Arabidopsis to the peach genome sequence yielded many sequences with low homology; hence, it was not possible to use this gene for candidate analysis in this study. Other branching genes have also been identified such as A XR2, AXR3 and AXR6 and terminal flower ( TF1) in Arabidopsis (Ehrenreich et al., 2007). The QTLs detected in this study require evaluation in additional environments and genetic backgrounds. Fine mapping and evaluation of additional candidate genes

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94 located in the validated QTL regions using the peach genome sequence could help to identify the genes responsible for branching and blind node incidence. By means of this and future studies, it will be possible to develop an understanding of blind node development and branching in peach making feasible the breeding of peach cultivars with reduced branching and without blind nodes.

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95 Table 4 1. Interspecific backcross families used for studies in tree architecture. FG= Flordaguard P. kan = Prunus kansuensis TN P= Tardy Nonpareil almond Family Individuals (#) P. kan 3) 66 P. kan 6) 62 AP00 78 P. kan 3) 8 5 P. kan 6) 99 126 P. kan ) 8 8 Table 4 2 Mean b ranching index (BI) and blind node incidence for the main axis (BNM) and lateral branches (BNL) in the interspecific backcross families (winter of 2010) FG= Flordaguard P. kan = Prunus kansu ensis and TNP= Tardy Nonpareil Parent BI BNM (%) BNL (%) P. kan 3) 5.7 ab z 20.5 b 18.4 b P. kan 6) 5.6 ab 24.9 b 21.3 ab 3.9 b 34.5 ab 32.1 a P. kan 3) 7 .3 a 18.4 bc 14.5 bc P. kan 6) 8.2 a 23.2 b 18.4 b 5.2 b 44.4 a 34.4 a P. kan ) 8.3 a 10.7 c 11.5 c z Means followed by different letters are significantly different, Tukey Table 4 3 Mean b ranching index (BI) and blind node incidence values for the main axis (BNM) and lateral branches (BNL) in the interspecific backcross families ( winter of 2011 ) FG= Flordaguard P. kan = Prunus kansuensis TNP= Tardy Nonpa reil Parent BI BNM (%) BNL (%) P. kan 3) 17.3 ab z 27.7 bc 24.4 b P. kan 6) 20.7 a 30.1 b 28.4 b 9.5 b 46.1 ab 43.5 a S P. kan 3) 19.8 a 27.9 b 23.3 bc P. kan 6) 18.6 a 30.3 b 26.7 b 11.9 b 55.9 a 52.4 a P. kan ) 21.3 a 14.1 c 12.9 c z Means followed by different letters are sig nificantly different, Tukey

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96 Table 4 4. Statistics for single nucleotide polymorphic positions (SNP) within each branching and blind node candidate gene for Prunus parents and hybrids used for obtaining backcross populations. Gene SNP frequency Exon SNP frequency Intron SNP freq uency Transition frequency Transversion freq uency Pp AXR1 z 0.017 0.020 0.017 0.004 0.013 Pp BRC1 0.009 0.000 0.012 0.003 0.006 Pp BRC2 0.003 0.000 0.006 0.002 0.001 Pp CUC1 0.008 0.008 0.009 0.007 0.001 Pp CUC2 0.008 0.000 0.012 0.008 0.000 Pp CUC 3 0.003 0.000 0.004 0.003 0.000 Pp LAS 0.008 0.007 0.008 0.003 0.005 Pp MAX1 0.007 0.000 0.012 0.004 0.003 Pp MAX2 0.024 0.016 0.027 0.011 0.013 Pp MAX3 0.021 0.025 0.019 0.011 0.010 Pp MAX4 0.027 0.015 0.036 0.024 0.003 Pp PIN 0.012 0.013 0.011 0.007 0.0 05 Pp REV 0.009 0.012 0.008 0.007 0.002 Pp SPS 0.021 0.012 0.025 0.012 0.009 z Prefixes (Pp) before Arabidopsis gene name stands for P persica

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97 Table 4 5 Number of heterozygous single nucleotide polymorphic positions (SNP) within different Prunus genotype sequences for each candidate gene and their total frequencies. FG= Flordaguard P. kan = Prunus kansuensis and TNP= Tardy Nonpareil Gene P. persica genotypes P. kan TNP FG 30 47 PpAXR1 0 0 0 0 0 0 PpBRC1 0 0 0 0 0 0 PpBRC2 0 0 0 0 0 0 PpCUC1 0 0 0 0 0 1 PpCUC2 0 0 0 0 0 1 PpCUC3 0 0 0 0 0 0 PpLAS 1 0 0 0 0 1 PpMAX1 0 0 0 0 0 0 PpMAX2 0 0 0 0 0 0 PpMAX3 0 0 0 0 0 2 PpMAX4 3 0 3 5 0 0 PpPIN 0 0 0 0 0 1 PpREV 0 0 0 0 0 0 PpSPS 2 0 1 1 0 0 SNP frequencies for all the sequences (5938 bp) 0.001 0 0.0006 0.00 1 0 0.001 z Prefixes (Pp) before Arabidopsis gene name stands for P persica

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98 Table 4 6 Haplotypes found in single nucleotide polymorphic posit ions in branching and blind nodes candidate genes and their frequencies in different Prunus genotypes. Gene Haplotype Peach z P. kansuensis Pp AXR1 y acctc ctagc accta 1 0 0 0 0 1 0 1 0 Pp BRC1 ccc tca cgc 1 0 0 0 1 0 0 0 1 Pp BRC2 tc cc cg 1 0 0 0 1 0 0 0 1 Pp CUC1 gctaa aacgg accgg 1 0 0 1 0 0 0 0.5 0.5 Pp CUC2 cta acg ccg 1 0 0 1 0 0 0 0.5 0.5 Pp CUC3 at ca 1 0 0 1 1 0 Pp LAS cgg cgt ctg tgg 0.9 0.1 0 0 0 0 1 0 0.5 0 0 0.5 Pp MAX1 at ac cc ct 1 0 0 0 0 0 0.5 0.5 0 1 0 0 Pp MAX2 gcaagtcgtc ggtgcthhtt agtggagcct 1 0 0 0 1 0 0 0 1 Pp MAX3 ctaaccc ctcaccc cccagct ccctgtc tcctgcc 0.9 0.1 0 0 0 0 0 1 0 0 0 0 0 0.5 0.5 Pp MAX4 ccgaaagta ccgaagggg tcgaagagg ccggagggg ctagcgggg 0.7 0.2 0.1 0 0 0 0 0 1 0 0 0 0 0 1

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99 Table 4 6. Continued Ge ne Haplotype Peach z P. kansuensis PpREV cctc tctc tgct 1 0 0 0 1 0 0 0 1 PpSPS aatgcggtga aatacggtgg aatgctgtga aatgcggtgg cccgtgacca 0.7 0.1 0.1 0.1 0 1 0 0 0 0 0 0 0 0 1 Pp PIN agtcc agcca gacaa ggcaa 1 0 0 0 0 1 0 0 0 0 0.5 0. 5 z Flordaguard 30 and y Prefixes (Pp) before Arabidopsis gene name stands for P persica Table 4 7. QTL s associated with branching index (BI) i n and UFSharp (FG x P. kan ) combined families Trait and year LG LOD peak position (cM) Nearest marker and distance (cM) Maximum LOD R 2 BI 2010 LG3 47.0 udp96008 (0) 2.9* z 0.04 BI 2010 LG4 34.0 pchgms5 (2) 2.7* 0.04 BI 2010 LG5 0.0 PpCUC3 (0) 4.1** 0.06 BI 2011 LG2 46.0 bppct030 (7) 9.9** 0.19 z *Significant at 0.05, **Significant at 0.01 Table 4 8. QTL s associated with branching index (BI) in and UFSharp (FG x TNP ) combined families Trait and year LG LOD peak p osition cM) Nearest marker and distance (cM) Maximum LOD R 2 BI 2010 LG7 23.3 cppct033 (2) 3.51** z 0.07 BI 2011 LG4 39.3 PpCUC1 (1) 3.19** 0.06 BI 2011 LG7 29.6 pms2 (1) 3.06** 0.06 z *Significant at 0.05, **Significant at 0.01 Table 4 9 QTL s associa ted with branching index (BI) in P. kan ) Trait and year LG LOD peak position (cM) Nearest marker and distance (cM) Maximum LOD R 2 BI 2010 LG2 32.1 bppct030 (3) 2.1* z 0.14 BI 2010 LG5 17.4 cpsct006 (5) 2.7* 0.21 z *Significant at 0.05, **Significant at 0.01

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100 Table 4 10 QTL s associated with blind nodes in main axis (BNM) and lateral branches (BNL) in and UFSharp P. kan ) combined families Trait and year LG LOD peak position (cM) Nearest marker and distance (cM) Maximum LOD R 2 BNM 2010 LG2 30.8 udp96013 (6) 7.9** z 0.16 BNM 2010 LG4 32.9 pchgms5 (1) 2.7* 0.04 BNM 2010 LG5 28.5 cpsct006 (2) 2.8* 0.05 BNL 2010 LG1 12.5 Y (7 cM) 4.7** 0.08 BNL 2010 LG2 24.7 udp96013 (1) 4.3** 0.07 BNL 2010 LG3 21.1 PpMAX 2 (1) 2.6* 0.04 BNM 2011 LG2 21.4 udp96013 (3) 6.8** 0.11 BNM 2011 LG5 29.0 cpsct006 (2) 2.8* 0.04 BNL 2011 LG1 19.4 Y (1) 5.1** 0.07 BNL 2011 LG2 29.3 udp96013 (5) 7.9** 0.12 BNL 2011 LG3 15.5 bppct039 (3) 3.5** 0.06 BNL 2011 LG4 32.3 pchgms5 (1) 2. 7* 0.04 BNL 2011 LG6/8 31.1 Gr (2) 2.8* 0.04 z *Significant at 0.05, **Significant at 0.01

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101 Table 4 11 QTLs associated with blind nodes in main axis (BNM) and lateral branches combined fami lies Trait and year LG LOD peak position (cM) Nearest marker and distance (cM) Maximum LOD R 2 BNM 2010 LG3 16.8 PpMAX2 (1) 4 .8** z 0.07 BNM 2010 LG3 54.2 cpdct027 (1) 6.3** 0.11 BNM 2010 LG6/8 32.0 bppct008 (2) 5.0** 0.09 BNM 2010 LG6/8 46.4 cppct0 23 (1) 4.8** 0.07 BNM 2010 LG6/8 56.7 eppcu5628 (2) 2.6* 0.05 BNM 2010 LG7 11.7 cppct033 (7) 6.5** 0.13 BNL 2010 LG1 16.0 PpBRC2 (1) 6.5** 0.10 BNL 2010 LG3 8.7 bppct039 (0) 3.2** 0.05 BNL 2010 LG3 51.2 udp96008 (3) 6.9** 0.13 BNL 2010 LG4 16. 9 udp98024 (4) 2.5* 0.07 BNL 2010 LG7 10.6 cppct033 (8) 14.4** 0.29 BNM 2011 LG1 16.0 PpBRC2 (1) 3.6** 0.05 BNM 2011 LG1 56.7 bppct028 (1) 2.6* 0.04 BNM 2011 LG3 8.9 bppct039 (1) 3.2* 0.05 BNM 2011 LG3 54.0 cpdct027 (1) 5.6** 0.11 BNM 2011 LG6/ 8 46.1 cppct023 (1) 2.6* 0.04 BNM 2011 LG7 7.6 cppct022 (7) 11.6** 0.25 BNL 2011 LG1 15.7 PpBRC2 (1) 5.1** 0.08 BNL 2011 LG3 8.9 bppct039 (1) 3.4** 0.05 BNL 2011 LG3 53.7 cpdct027 (1) 3.3** 0.06 BNL 2011 LG6 46.1 cppct023 (1) 2.2* 0.03 BNL 201 1 LG6 65.1 eppcu5628 (7) 2.6* 0.06 BNL 2011 LG7 7.0 cppct022 (7) 11.7** 0.25 z *Significant at 0.05, **Significant at 0.01

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102 Figure 4 1. Genes involved in axillary meristem formation and outgrowth and their interactions. Names in brown indicate genes that were not studied in the present research. FP, foliar primordia; AM, apical meristem; AXR1 auxin resistant1; BRC1 and BRC2 branched1 and 2; CUC1 CUC2 and CUC3 cup shaped cotyledon; LAS lateral suppressor; MAX1 MAX2 MAX3 and MAX4 more axillary growth1, 2, 3 and 4; PIN pinhead; REV revoluta; RAX1 RAX2 and RAX3 regulator of axillary growth1, 2 and 3; SPS supershoot. FP A M FP AM

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103 Figure 4 2. and x P. kansuensis ) backcross combined linkage map. z Loci followed by asterisk(s) indicates segregation distortion at P 0.05 (*), 0.01 (**) and 0.001 (***). ** *** ** ** ** / 8 z

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104 Figure 4 3. and x T a ) backcross combined linkage map. z Loci followed by asterisk(s) indicates segregation ** ** ** ** ** ** * ** ** ** ** ** ** / 8

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105 Figure 4 4. UF97 P. kansuensis ) backcross li nkage map. z Loci followed by asterisk(s) indicates segregation distortion at P 0.05 (*), 0.01 (**) and 0.001 (***). ** ** **

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106 Figure 4 amilies. Solid lines represent LOD threshold at 0.01, dashed lines represent LOD threshold at 0.05. Figure 4 lines represent LOD threshold at 0.01, dashed lines represent LOD threshold at 0.05.

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107 Figure 4 7 QTL s associated with branching index (BI) in F 97 P. kan suensis ) Solid lines represent LOD threshold at 0.01, dashed lines represent LOD threshold at 0.05.

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108 Figure 4 8 QTL s associated with blind nodes in main axis (BNM) and lateral branches (BNL) in and UFSharp x P. kan suensis ) combined families Solid lines represent LOD threshold at 0.0 1, dashed lines represent LOD threshold at 0.05. Figure 4 9 QTL s associated with blind nodes in main axis (BNM) and lateral branches (BNL) in and UFSharp ) combined families Solid lines represent LO D threshold at 0.01, dashed lines represent LOD threshold at 0.05.

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109 Figure 4 10 QTL s associated with blind nodes in main axis (BNM) and lateral branches (BNL) in P. kan ) BNM 2010 and BNM 2011 threshold at 0.01=3.2, BNL 2010 t hreshold at 0.01=3.0, BNL 20100 threshold at 0.01=2.8 (not shown in graph). BNM 2010, BNL 2010 and BNM 2011 threshold at 0.05=3.1, BNL 2010 threshold at 0.05=2.4 (not shown in graph).

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110 CHAPTER 5 CONCLUSIONS A branching index was deve loped as a tool to identify tree branching complexity and quantity in large breeding populations. This index is based on the number of first order branches in the tree plus the average number of second and further order branches within three first order br anches. F 1 hybrids from peach x P. kansuensis ( P. kan index. Two years of evaluation showed that the total number of branches per tree and its branching index had a fairly stro ng association with r 2 of 0.71 and 0.78. The branching index can be used in peach breeding programs to select trees with reduced branching that would not need much pruning and potentially produce better quality fruit. Branching index and blind node variabi lity was found among seven backcross P. kan P. kan and FG x TNP almond hybrids backcrossed to different peach selections. FG peach x P. kansuensis backcross families had on average a branching in dex value of 7 and 19 and a blind node incidence of 18 and 25% for 2010 and 2011, respectively. The FG x TNP backcross families had on average a branching index value of 4 and 11 and a blind node incidence of 36 and 46% for 2010 and 2011, respectively. Cl ones of the F 1 hybrids and peach selections used to generate the backcross populations were evaluated along with their progeny. Peach x P. kan hybrids had higher branching and fewer blind nodes when compared to peach x TNP, resembling the backcross progeny they generated. Even though differences were found among populations, there was broad variability within populations. The branching index varied from 2 25 and 4 50 in 2010 and 2011, respectively. The incidence of blind nodes ranged from 0 90% in the FG x P. kan

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111 backcross families, whereas branching index varied 2 12 and 4 38 in 2010 and 2011, respectively. Blind node frequency ranged from 0 95% in the FG x TNP backcross presented higher branching and low blind node incidence, contributing to the detected variability within families and indicating variability within peach. The transgressive segrega tion observed suggests that both traits are influenced by many genes. Narrow sense heritability estimates were 0.37 for branching index and 0.21 for blind nodes, indicating that both are quantitative traits affected by the environment. Nevertheless, select ion for low blind node incidence and reduced branching is feasible As shown by the P. kan ) backcross family which had a blind node incidence below 30% and its parents which also had the lowest incidence of blind nodes among all th e backcross parents Similarly, i n the case branching the almond hybrids and their backcross progeny showed reduced branching in comparison with the P. kan hybrids and backcross progeny again indicating that parental selection for reduced branching is p ossible Detection of QTL associated with branching and blind nodes was performed using a map generated by SSRs and a set of 14 candidate genes associated with axillary meristem formation and outgrowth in Arabidopsis SNPs were found within the candidate g ene sequences in the different Prunus sequences. P. kansuensis from peach, r esulting in a high number of heterozygous SNP positions in the sequences

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112 of the peach x P kansuensis 1 s. This confirms the value of interspecific crosses for genetic studies in peach as they increase the polymorphism frequency The genomic maps generated consisted of seven linkage groups (LG), LG1 5 and 7 were homologous to the same LG from the Prunus reference map, but a chimeric 6/8 linkage group containing portions of LG6 and LG8 from the reference map was generated as a re sult of a reciprocal translocation between LG6 and LG8 near the Gr leaf color locus which has been detected only in populations segregating for the dominant Gr allele for red leaf color Segregation distortion was detected mostly in loci at LG6/8 as a res ult of the translocation and to the proximity to the self incompatibility locus in TNP almond backcrosses. The branching QTL detected in 2010 and 2011 differed, and the moderate correlation between the two years data is potentially responsible for the lack of stability of the detected QTL. The QTL with the highest LOD values were detected in 2011, one in LG2 in the FG x P. kan backcrosses which explained 19% of the phenotypic variance; and two, one in LG4 and another in LG7 in the FG X TNP backcrosses that explained 12% of the phenotypic variance. The results suggest that more than two years of evaluation are necessary for analysis of branching. In the FG x P. kan backcrosses, progeny heterozygous for the major QTL in 2011 had higher branching index values ( 23) when compared to progeny homozygous for the peach alleles (16). In the FG x TNP backcross families, individuals carrying almond alleles at both of the QTLs detected in 2011 had lower branching index values (6.6) when compared to progeny homozygous for the peach alleles (12.1). These results demonstrate the impact of P.

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113 kansuensis and TNP almond QTL for increasing and decreasing branching, respectively. Blind node QTL were consistent in both 2010 and 2011. The QTL with the highest LOD score in the FG x P kan backcrosses was detected on LG2 and minor QTL were identified on LG1, LG3, LG4, LG5 and LG6/8. These QTL explained ~25% of the phenotypic variation observed. In the FG X TNP backcrosses, the QTL with the highest LOD was detected on LG7 and minor QTL s at LG1, LG3, and LG6/8, explaining ~56% of the phenotypic variation. In the FG x P. kan backcrosses, individuals heterozygous for the P. kan allele at the major QTL had fewer blind nodes (15.1%) compared to those homozygous for the peach (25.9%) allele. In the FG x TNP backcross families, individuals heterozygous for the almond allele at the major QTL had more blind nodes (53.7%) compared to progeny homozygous for the peach allele (31.3%). The major effect QTL in the FG x P. kan and FG X TNP backcrosses were different, indicating that multiple loci control both traits and that different loci may segregate in different populations. Suprisingly, t he major QTL detected for both branching and blind nodes were localized on LG2 in the FG x P. kan backcross fam ilies and on LG7 in the FG X TNP backcross families. Blind nodes and branching are related since the formation of axillary meristems is necessary for the development of axillary shoots. The correlation between b lind node frequency and the branching index w as 0.20, suggesting a limited negative influence from blind nodes in branching. Other factors such as auxin levels that control axillary bud dormancy may also have an impact.

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114 C andidate genes did not map to the location of large effect QTLs. However, PpCU C1 and PpCUC3 genes associated in Arabidopsi s with axillary meristem formation; and PpBRC2 and PpMAX2 associated in Arabidopsis with meristem outgrowth overlapped minor effect QTLs for branching and blind nodes, respectively. The detected QTLs need to be validated in different populations and environments. Further research on candidate genes and fine mapping may help to identify the genes responsible for differences in branching blind nodes in peach. This information could be used to develop markers for b reeding trees with reduced branching and low incidence of blind nodes in peach.

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115 APPENDIX COMPLEMENTARY TABLES AND FIGURES Table A 1. Microsatellite markers used to identify self pollinated in the interspecific backcross populatio ns studied. FG= Flordaguard P. kan = Prunus kansuensis and TNP= Tardy Nonpareil Family SSRs P 00 P. kan 3) bppct8, bppct26, bppct30, cpsct39, epdcu3382 and udp9825 P 00 P. kan 6) bppct8, bppct23, bppc t30, pmsg2, epdcu3382 and udp9825 bppct8, bppct26, bppct30, cpsct39, pmsg2 and udp9825 P. kan 3) bppct14, bppct26, epdcu3382, udp968, udp98412 and udp9825 P. kan 6) bppct14, bppct30, cppct33 pmsg2, udp9613 and udp9825 bppct14, bppct26, cppct29, epdcu3382, pmsg2 and udp9825 F 97 F 97 P. kan ) bppct8, bppct26, bppct30, cpsct39, epdcu3382 and udp9825

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116 Table A 2. Specific primers des igned to amplify candidate genes associated with axillary meristem formation (AMF) and outgrowth (AMO). Gene Trait F orward p rimer R everse p rimer AT z (C) Fragment size (bp) Pp AXR1 y AMO AGCAAGGACAGA CAGCCCTA CTTGGCCTTAAC AGCATCGT 59 419 Pp BRC1 AMO CACAAGCAC CAC CCCTTACT CCTGAATGAGCA ACCACTCA 57 342 Pp BRC2 AMO TCAAGCGGGAAT AAGGACAG GCTCCACTGGGA ATTGTTGT 57 692 Pp CUC1 AMF CTTGACAGCAGC TTCACTGG AGCTCTGCCACG GTAGAAAA 57 364 Pp CUC2 AMF GTTTTCTACCGT GGCAGAGC TTGCTCATTCGG GTCTTCTT 57 741 Pp CUC3 AMF GAGTGAGCTGAG TGGGGAAG TGGCCCTGTTGG TTCTTAAC 57 751 Pp LAS AMF ATGCGCCAATTG CTCATTAC AAAGTCGAGGAT GTGGATGG 57 402 Pp MAX1 AMO TTACGAGCATCT CCTTGCTG TTGCAACTAATG GGGAAACC 57 331 Pp MAX2 AMO AAAACTTGGATG CTGCTGCT TCCGAATCTCCT CCAGATTG 57 441 Pp MAX3 AMO TTGCTTCCTCGG TCTCCTAA GAGGTAGCGTCT T GCTTTGG 57 387 Pp MAX4 AMO CGGTCATTGCAG ATTGTTGT CAACCCTCTTCC ATGTTCGT 57 341 Pp PIN AMF ATTTCAGCTTTGG CAACAGG GCCAAGTCCTGC ATCAGATAG 57 447 Pp REV AMF CGCCAGTATGTT CGAAGTGT CCAAGGAATCAG GTCTCAGC 57 480 Pp SPS AMO ACTCAAAGACGC CAGTGGTC GCCCTTGGGGAT GAAGTAAT 57 485 z AT=Annealing temperature y Prefixes (Pp) before Arabidopsis gene name stands for P persica

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117 Table A 3. Single nucleotide polymorphisms detected in Pp AXR1 amplicon ( 296 bp). Flordaguard P. kan = Prunus kansuensis TNP= Tardy Nonpareil almond Genotype Position within the sequence (bp) 42 169 182 185 235 Haploid 1 A C C T C Haploid 2 A C C T C Flordaguard A C C T C P. kansuensis A C C T A C T A G C FG y x P. kan 3 A C C T M FG x P. kan 6 A C C T M FG x TNP M Y M K C A C C T C A C C T C A C C T C P. kan A C C T M Blue fill =Common nucleotide. Green fill = Heterozygous nucleotides. Yellow fill = Rare nucleotide. Table A 4. Single nucleotide polymorphisms detected in Pp BRC1 amplicon ( 325 bp). Flordaguard P. kan = Prunus kansuensis TNP= Tardy Nonpareil almond Genotype Position within the sequence (bp) 41 60 73 Haploid 1 C C C Haploid 2 C C C Flordaguard C C C P. kansuensis T C A C G C FG x P. kan 3 Y C M FG x P. kan 6 Y C M FG x TNP C S C C C C C C C UF97 C C C P. kan Y C M Blue fill =Common nucleotide. Green fill = Heterozygous nucleotides. Yellow fill = Rare nucleotide.

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118 Table A 5. Single nucleotide polymorphisms detected in Pp BRC2 amplicon (663bp). Flordaguard each P. kan = Prunus kansuensis TNP= Tardy Nonpareil almond Genotype Position within the sequence (bp) 334 503 Haploid 1 T C Haploid 2 T C Flordaguard T C P. kansuensis C C C G FG x P. kan 3 Y C FG x P. kan 6 Y C FG x TNP Y S T C T C T C P. kan Y C Blue fill =Common nucleotide. Green fill = Heterozygous nucleotides. Yell ow fill = Rare nucleotide. Table A 6. Single nucleotide polymorphisms detected in Pp CUC1 amplicon (598bp). Flordaguard P. kan = Prunus kansuensis TNP= Tardy Nonpareil almond Genotype Position within the sequence (bp) 111 222 355 399 516 Haploid 1 G C T A A Haploid 2 G C T A A Flordaguard G C T A A P. kansuensis G C T A A A M C G G FG x P. kan 3 G C T A A FG x P. kan 6 G C T A A FG x TNP R C Y R R G C T A A G C T A A G C T A A P. kan G C T A A Blue fill =Common nucleotide. Green fill = Heterozygous nucleotides. Yellow fill = Rare nucleotide.

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119 Table A 7. Single nucleotide polymorphisms detected in P p CUC2 amplicon (356 bp). Flordaguard P. kan = Prunus kansuensis TNP= Tardy Nonpareil almond Genotype Position within the sequence (bp) 104 237 282 Haploid 1 C T A Haploid 2 C T A Flordaguard C T A P. kansuen sis C T A M C G FG x P. kan 3 C T A FG x P. kan 6 C T A FG x TNP C Y R C T A C T A C T A P. kan C T A Blue fill =Comm on nucleotide. Green fill = Heterozygous nucleotides. Yellow fill = Rare nucleotide. Table A 8. Single nucleotide polymorphisms detected in PpCUC3 amplicon (599 bp). Flordaguard P. kan = Prunus kansuensis TNP= Tardy Nonpareil almond Genotype Position within the sequence (bp) 150 180 Haploid 1 A T Haploid 2 A T Flordaguard A T P. kansuensis C A A T FG x P. kan 3 M W FG x P. kan 6 M W FG x TNP A T A T A T A T P. kan M W Blue fill =Common nucleotide. Green fill = Heterozygous nucleotides. Yellow fill = Rare nucleotide.

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120 Table A 9. Single nucleotide polymorphisms detected in Pp LAS amplicon ( 389 bp). Flordaguard P. kan = Prunus kansuensis TNP= Tardy Nonpareil almond Genotype Position within the sequence (bp) 105 181 246 Haploid 1 C G G Haploid 2 C G G Flordaguard C G K P. kansuensis C T G Y G G FG x P. kan 3 C K G FG x P. kan 6 C K G FG x TNP Y G G C G G C G G C G G P. kan C K G Blu e fill =Common nucleotide. Green fill = Heterozygous nucleotides. Yellow fill = Rare nucleotide. Table A 10. Single nucleotide polymorphisms detected in PpMAX1 amplicon (280bp). Flordaguard P. kan = Prunus kansuensis TNP= Tardy Nonpareil almon d Genotype Position within the sequence (bp) 1 33 201 Haploid 1 A T Haploid 2 A T Flordaguard A T P. kansuensis C Y A C FG x P. kan 3 M Y FG x P. kan 6 M Y FG x TNP A Y A T A T A T P. kan M T Blue fill =Common nucleotide Green fill = Heterozygous nucleotides Yellow fill = Rare nucleotide

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121 Table A 11. Single nucleotide pol ymorphisms detected in Pp MAX2 amplicon (4 09 bp). Flordaguard P. kan = Prunus kansuensis TNP= Tardy Nonpareil almond Genotype Position within the sequence (bp) 84 127 129 132 145 168 179 195 247 381 Haploid 1 G C A A G T C G T C Haploid 2 G C A A G T C G T C Flordaguard G C A A G T C G T C P. kansuensis G G T G C T G G T T A G T G G A G C C T FG x P. kan 3 G S W R S T S G T Y FG x P. kan 6 G S W R S T S G T Y FG x TNP R S W R G W S S Y Y G C A A G T C G T C G C A A G T C G T C G C A A G T C G T C P. kan G S W R S T S G T Y Blue fill =Common nucleotide. Green fill = Heterozygous nucleotides. Yellow fill = Rare nucleotide. Table A 12. Single nucleotide polymorphisms detected in PpMAX3 amplicon ( 328 bp). Flordaguard P. kan = Prunus kansuensis TNP= Tardy Nonpareil almond Genotype Position within the sequence (bp) 94 98 113 152 174 191 250 Haploid 1 C T A A C C C Haploid 2 C T C A C C C Florda guard C T A A C C C P. kansuensis C C C A G C T Y C C T G Y C FG x P. kan 3 C Y M A S C Y FG x P. kan 6 C Y M A S C Y FG x TNP Y Y M W S C C C T A A C C C C T A A C C C C T A A C C C P. kan C Y M A S C Y Blue fill =Common nucleotide. Green fill = Heterozygous nucleotides. Yellow fill = Rare nucleotide.

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122 Table A 13. Single nucleotide polymorphisms detected in Pp MAX4 amplicon ( 332 bp). Flordaguard peach P. kan = Prunus kansuensis TNP= Tardy Nonpareil almond Genotype Position within the sequence (bp) 44 81 138 151 203 210 215 219 220 Haploid 1 C C G A A A G T A Haploid 2 C C G A A A G T A Flordaguard C C G A A R G K R P. kansuensis C C G G A G G G G C T A G C G G G G FG x P. kan 3 C C G R A G G G G FG x P. kan 6 C C G R A G G G G FG x TNP C Y R R M G G G G C C G A A A G T A C C G A A R G K R Y C G A A R R K R 47 P. kan Y C G R A G R G G Blue fill =Common nucleotide. Green fill = Heterozygous nucleotides. Yellow fill = Rare nucleotide. Table A 14. Single nucleotide polymorphisms detected in Pp PIN amplicon (429 bp). Flordaguard P. kan = Prunus kansu ensis TNP= Tardy Nonpareil almond Genotype Position within the sequence (bp) 44 62 201 272 286 Haploid 1 A G T C C Haploid 2 A G T C C Flordaguard A G T C C P. kansuensis A G C C A G R C A A FG x P. kan 3 A G Y C M FG x P. kan 6 A G Y C M FG x TNP R G Y M M A G T C C A G T C C A G T C C P. kan A G Y C M Blue fill =Common nucleotide. Green fill = Heterozygous nucleotides. Yellow fill = Rare nucleotide.

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123 Table A 15. Single nucleotide polymorphisms detected in Pp REV amplicon ( 465 bp). Flordaguard P. kan = Prunus kansuensis TNP= Tardy Nonpareil almond Genotype Position within the sequence (bp) 70 71 368 389 Haploid 1 C C T C Haploid 2 C C T C Flordaguard C C T C P. kansuensis T C T C T G C T FG x P. kan 3 Y C T C FG x P. kan 6 Y C T C FG x TNP Y S Y Y 30wbs C C T C C C T C C C T C P. kan Y C T C Blue fill = Common nucleotide. Green fill = Heterozygous nucleotides. Yellow fill = Rare nucleotide. Table A 16. Single nucleotide polymorphisms detected in Pp SPS amplicon (469 bp). Flordaguard P. kan = Prunus kansuensis TNP= Tardy Nonpareil almond Genotype Position within the sequence (bp) 17 65 78 104 114 131 140 149 192 278 Haploid 1 A A T G C G G T G A Haploid 2 A A T G C G G T G A Fl ordaguard A A T R C G G T G R P. kansuensis A A T G C G G T G A C C C G T G A C C A FG x P. kan 3 A A T G C G G T G R FG x P. kan 6 A A T G C G G T G R FG x TNP M M Y R Y G R Y S A A A T G C G G T G A A A T G C K G T G A A A T G C G G T G R P. kan A A T G C G G T G A Blue fill = Common nucleotide. Green fill = Heterozygous nucleotides. Yellow fill = Rare nucleotide.

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124 Table A 17. SSR and morphological markers selected to use in t he mapping of backcross populations. LG Marker z AT (C) y Locus (cM) B ackcross family x Reference 1 udp96005 57 29.2 1, 2, 4 and 5 Cipriani et al. 1999 1 Y w 35.0 All Dirlewanger et al., 2004b 1 bppct027 57 47.3 1, 2, 4, 5 and 7 Dirlewanger et al., 2002 1 bppct016 57 55.2 7 Dirlewanger et al. 2002 1 cppct029 55 65.1 3 and 6 Aranzana et al. 2002 1 bppct028 57 77.4 3 and 6 Dirlewanger et al., 2002 2 udp 98025 57 9.6 All Cipriani et al. 1999 2 udp 96013 57 27.8 All Cipriani et al. 1999 2 bppct030 57 38.0 All Dirlewanger et al. 2002 2 cpsct034 62 48.6 1, 2, 3, 4, 5 and 6 Mnejja et al. 2004 3 bppct007 57 11.2 1, 2, 3, 4, 5 and 6 Dirlewanger et al., 2002 3 bppct039 57 18 .0 All Dirlewanger et al., 2002 3 udp96008 57 36.4 All Cipriani et al. 1999 3 cpdct027 62 46.4 All Mnejja et al. 2005 4 cpsct039 62 1.8 1, 2, 4 and 5 Mnejja et al. 2004 4 udp98024 57 11.3 All Cipriani et al. 1999 4 pchgms5 57 24.1 1, 2, 4 an d 5 Sosinski et al., 2000 4 epdc3832 57 34.1 3 and 6 Cipriani et al. 1999 4 bppct023 57 45.4 1, 2, 4, 5 and 7 Dirlewanger et al., 2002 5 bppct026 57 5.2 All Dirlewanger et al., 2002 5 cpsct006 57 21.7 All Dirlewanger et al., 2002 5 bppct032 57 34.7 All Dirlewanger et al., 2002 5 bppct014 57 44 All Dirlewanger et al., 2002 6 eppcu1794 55 4.1 14.9 3 and 6 Howad et al. 2005 6 bppc t008 57 30.1 All Dirlewanger et al., 2002 6 Gr w 35.0 1, 2, 3, 4 and 5 Dirlewanger et al., 2004b 6 cppct023 55 41.5 All Aranzana et al. 2002 6 bppct025 57 56.4 1, 2, 3, 4 and 5 Dirlewanger et al., 2002 6 udp 98412 57 72.0 1, 2, 4, 5 and 7 Cipriani et al. 1999 7 cppct022 50 18.6 1, 2, 3, 4 and 5 Aranzana et al. 2002 7 cppct033 50 38.9 All Aranzana et al. 2002 7 pms 2 55 47.8 All Un published 7 epdcu3392 57 64.7 All Jung et al. 2008 8 eppcu5628 55 13.0 18.8 3 and 6 Howad et al. 2005 8 eppcu4726 60 30.1 40.9 3 and 6 Howad et al. 2005 8 cpdct023 62 42.6 1,2,4 and 5 Mnejja et al. 2004 8 udp 98409 57 44.5 1,2,4 and 5 Cipriani et al. 199 9 z y Annealing temperature.

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125 x Backcross families w h ere the markers w ere polymorphic and informative for use: x P. kan suensis 3) 2. x P. kan suensis 6) 3. x T ) 4. x P. kan suensis 3) 5. x P. kan suensis 6) 6. x T ) 7. P. ka n suensis ) w Morphological markers: Y =Flesh color (white/yellow), Gr =leaf color (red/green), Flesh color. Table A 18. Candidate genes genotyped with restriction enzymes Gene Restriction enzyme Family genotyped y Enzyme units Pp CUC3 z PacI 1,2,4,5,7 6 Pp MAX2 HphI All 5 Pp MAX3 TaqI All 8 Pp MAX4 HinfI All 7 Pp REV AccI 1,2,4,5,7 5 Pp REV BsmBI 3,6 5 Pp SPS HinfI 3,6 7 z Prefixes (Pp) before Arabidopsis gene name stands for P persica y x P. kan suensis 3) 2. x x P. kan suensis 6) 3. x T ) 4. x P. kan suensis 3) 5. x P. kan suensis 6) 6. x T ) 7. P. kan suensis )

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126 Table A 19. Candidate genes genotyped with high resolution melt analysis. Gene F orward p rimer R everse p rimer Annealing temperature (C) Fragment size (bp) Pp AXR1 z ATTGGGTGACC TTGGAAACA CTTGGCCTTAA CAGCATCGT 57 1 94 Pp BRC1 CACAAGCACCA CCCCTTACT CTTCTTCTCGG GATCTGTGG 57 181 Pp BRC2 GATGAATTCGT CCACTTCTGAG CTTGCCTCGAC CCTCGAT 57 150 Pp CUC1 TTGCAGACAAG GCAAAGATG TCATCCCAACA AGAGCACAA 57 171 Pp CUC2 GATGGGGGAG AAAGAGTGGT TCGGTAGCTCT AGCTCTTCCAC 57 197 Pp LAS TCCCAGCTTGA CTTCT CCTC AGTGCCTCCTC GTTGTTGTT 57 242 Pp MAX1 TCATTTCCCTCT TGTCTTCCA GTTGTCGTCCT CCTCTTCCA 57 191 Pp PIN ATTGGCCTCAC CTGGTCTCT GAATATTGTATT GCACCAATGCT 57 174 z Prefixes (Pp) before Arabidopsis gene name stands for P persica

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127 x P. kan suensis 3) x P. kansuensis 6) *** ** ** / 8 / 8 *** *** ** z

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128 x T ) x P. kansuensis 3) ** *** * ** ** / 8 *** *** ** *** ** ** *** ** * ** *** / 8

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129 x P. kansuensis 6) x T ) Figure A 1. Individual interspecific Prunus backcross genetic maps. z Loci followed by asterisk(s) indicates segregation distortion at P 0.05 (*), 0.01 (**) and 0.001 (***). * ** ** ** ** / 8 *** ** *** ** ** ** ** ** *** *** / 8

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130 Figure A 2. QTL s associated with branching index (BI) in P. kan 3) Solid lines represent LOD threshold at 0.01, dashed lines represent LOD threshold at 0.05. BI 2011 threshold at 0.01=3.1 (not shown in graph). Figure A 3. QTL s associated with branching index (BI) in P. kan 6 ) Solid lines represent LOD threshold at 0.01, dashed lines represent LOD threshold at 0.05.

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131 Figure A 4. QTL s associated with branching index (BI) in UFSharp P. kan 3) Solid lines represent LOD threshold at 0.01, dashed lines represent LOD threshold at 0.05. BI 2011 threshold at 0.01=3.0 (not shown in graph). Figure A 5. QTL s associated with branching index (BI) in UFSharp x P. kan 6 ) Solid lines represent LOD threshold at 0.01, dashed lines represent LOD threshold at 0.05

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132 Figure A 6. QTL s associated with branching index (BI) in x TNP ) Solid lines represent LOD threshold at 0.01, dashed lines repre sent LOD threshold at 0.05. BI 2010 threshold at 0.01=3.3, BI 2011 threshold at 0.01=3.1 (not shown in graph). Figure A 7. QTL s associated with branching index (BI) in UFSharp TNP ) Solid lines represent LOD threshold at 0.01, dashed lines re present LOD threshold at 0.05.

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133 Figure A 8. QTL s associated with blind nodes in main axis (BNM) and lateral branches (BNL) in P. kan 3) Solid lines represent LOD threshold at 0.01, dashed lines represent LOD threshold at 0.05. BNL 2010 and BNM 2011 threshold at 0.01=3.0, BNL 2011 threshold at 0.01=3.1 (not shown in graph). Figure A 9. QTL s associated with blind nodes in main axis (BNM) and lateral branches (BNL) in P. kan 6 ) Solid lines represent LOD thresh old at 0.01, dashed lines represent LOD threshold at 0.05. BNL 2010 and BNM 2011 threshold at 0.01=3.1, BNL 2010 and BNM 2011 threshold at 0.01=3.0 (not shown in graph).

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134 Figure A 10 QTL s associated with blind nodes in main axis (BNM) and lateral branche s (BNL) in UFSharp P. kan 3) Solid lines represent LOD threshold at 0.01, dashed lines represent LOD threshold at 0.05. Figure A 11. QTL s associated with blind nodes in main axis (BNM) and lateral branches (BNL) UFSharp P. kan 6 ) Solid lines represent LOD threshold at 0.01, dashed lines represent LOD threshold at 0.05.

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135 Figure A 12. QTL s associated with blind nodes in main axis (BNM) and lateral branches (BNL) x TNP ) Solid lines represent LOD threshold at 0.01, dashed lines represent LOD threshold at 0.05. Figure A 13. QTL s associated with blind nodes in main axis (BNM) and lateral branches (BNL) in UFSharp TNP ) Solid lines represent LOD threshold at 0.01, dashed lines represent LOD threshol d at 0.05.

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136 LIST OF REFERENCES Aguilar Martinez, J.A., Poza Carrion, C., Cubas, P., 2007. Arabidopsis BRANCHED1 acts as an integrator of branching signals within axillary buds. Plant Cell 19 458 472. Ahmad, R., Parfitt, D.E., Fass, J., Ogundiwin, E., Dh ingra, A., Gradziel, T.M., Lin, D. W., Joshi, N.A., Martinez Garcia, P.J., Crisosto, C.H., 2011. Whole genome sequencing of peach ( Prunus persica L.) for SNP identification and selection. BMC Genomics 12 569 Alvarez, N., Meeking, R.J., White, D.W.R., 200 6. The origin, initiation and development of axillary shoot meristems in Lotus japonicus. Ann Bot. 98 953 9 63. Aranzana, M.J., Garcia Mas, J., Carbo, J., Arus, P., 2002. Development and variability analysis of microsatellite markers in peach. Plant Breedi ng 121 87 92. Arite, T., Iwata, H., Ohshima, K., Maekawa, M., Nakajima, M., Kojima, M., Sakakibara, H., Kyozuka, J., 2007. DWARF10 an RMS1/MAX4/DAD1 ortholog, controls lateral bud outgrowth in rice. Plant Journal 51 1019 1029. Bahadori, F., Arzani, K., 2008. Study of short term effects of paclobutrazol on vegetative growth of J.H. Hale and Redskin peach trees. Journal of Science and Technology of Agriculture and Natural Resources 12 561 570. Barthelemy, D., Caraglio, Y., 2007. Plant architecture: A dyna mic, multilevel and comprehensive approach to plant form, structure and ontogeny. Annals of Botany 99 375 407. Bassi, D., Dima, A., Scorza, R., 1994. Tree structure and pruning response of 6 peach growth forms. Journal of the American Society for Horticul tural Science 119 378 382. Battaglia, M., Sands, P.J., 1998. Process based forest productivity models and their application in forest management. Forest Ecology and Management 102 13 32. Beavis, W.D., Grant, D., Albertsen, M., Fincher, R., 1991. Q uantita tive trait loci for plant height in 4 maize populations and their associations with qualitative genetic loci. Theoretical and Applied Genetics 83 141 145. Benkova, E., Michniewicz, M., Sauer, M., Teichmann, T., Seifertova, D., Jurgens, G., Friml, J., 2003 Local, efflux dependent auxin gradients as a common module for plant organ formation. Cell 115 591 602.

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137 Bennett, T., Sieberer T., Willett, B., Booker, J., Luschnig, C., Leyser, O., 2006. The Arabidopsis MAX pathway controls shoot branching by regulatin g auxin transport. Current Biology 16 553 563. Berloo, R. V ., 2008. GGT 2.0: versatile software for visualization and analysis of genetic data. Journal of Heredity 99 232 236. Bernardo, R., 2008. Molecular markers and selection for complex traits in plant s: Learning from the last 20 years. Crop Science 48 1649 1664. Bielenberg, D., Gasic, K., Chaparro, J.X., 2009. An Introduction to Peach ( Prunus persica ). Springer. New York. Birch, C.P.D., Hutchings, M.J., 1992. Stolon growth and branching in glechoma hed eracea l an application of a plastochron index. New Phytologist 122 545 551. Bliss, F.A., Arulsekar, S., Foolad, M.R., Becerra, V., Gillen, A.M., Warburton, M.L., Dandekar, A.M., Kocsisne, G.M., Mydin, K K., 2002. An expanded genetic linkage map of Prun us based on an interspecific cross between almond and peach. Genome 45 520 529. Booker, J., Auldridge, M., Wills, S., McCarty, D., Klee, H., Leyser, O., 2004. MAX3/CCD7 is a carotenoid cleavage dioxygenase required for the synthesis of a novel plant signa ling molecule. Current Biology 14 1232 1238. Booker, J., Chatfield, S., Leyser, O., 2003. Auxin acts in xylem associated or medullary cells to mediate apical dominance. Plant Cell 15 495 507. Boonprakob, U., Byrne, D.H., 2003. Temperature influences blin d node development in peach. Environmental Stress and Horticulture Crops 463 467. Boonprakob, U., Byrne, D.H., Mueller, D.M.J., 1996. Anatomical differences of axillary bud development in blind nodes and normal nodes in peach. Hortscience 31 798 801. Bou wmeester, H.J., Roux, C., Lopez Raez, J.A., Becard, G., 2007. Rhizosphere communication of plants, parasitic plants and AM fungi. Trends in Plant Science 12 224 230. Brewer, P.B., Dun, E.A., Ferguson, B.J., Rameau, C., Beveridge, C A., 2009. Strigolactone acts downstream of auxin to regulate bud outgrowth in pea and Arabidopsis Plant Physiology. 150 482 493. Byrne, D.H., Sherman, W.B., Bacon, T.A., Stone fruit breeding genetic pool an d its exploitation for growing under warm winter conditions. In: A. Ere z, (Ed.), Temperate fruit crops in warm climates. Kluwer Academic Publishers, Norwell, 2000, 1 57 230.

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138 Cao, K., Wang, L., Zhu, G., Fang, W., Chen, C., Zhao, P., 2011. Construction of a linkage map and identification of resistance gene analog markers for roo t knot nematodes in wild peach, Prunus kansuensis. Journal of the American So ciety for Horticultural Science 136 190 197. Carrillo Mendoza, O., Sherman, W.B., Chaparro, J.X., 2010. Development of a Branching Index for Evaluation of Peach Seedlings Using I nterspecific Hybrids. Hortscience 45 852 856. Celton, J.M., Martinez, S., Jammes, M.J., Bechti, A., Salvi, S., Legave, J. M., Costes, E., 2011. Deciphering the genetic determinism of bud phenology in apple progenies: a new insight into chilling and heat r equirement effects on flowering dates and positional candidate genes. New Phytologist 192 378 392. Chalmers, D.J., Mitchell, P D., Vanheek, L., 1981. Control of peach tree growth and productivity by regulated water supply, tree density, and summer pruning Journal of the American Society for Horticultural Science 106 307 312. Chaparro, J.X., Werner, D.J., Omal ley, D., Sederoff, R.R., 1994. T argeted mapping and linkage analysis of morphological isozyme, and rapd markers in peach. Theoretical and Applied Ge netics 87 805 815. Cheng, Z.L., Zhang, X.P., Chen, B.Q., 2007. Simple reconstruction of tree branches from a single range image. Journal of Computer Science and Technology 22 846 858. Churchill, G.A., Doerge, R.W., 1994. Empirical threshold values for qu antitative trait mapping. Genetics 138 963 971. Cipriani, G., Lot, G., Huang, W.G., Marrazzo, M. T., Peterlunger, E., Testolin, R., 1999. AC/GT and AG/CT microsatellite repeats in peach Prunus persica (L) Batsch : isolation, characterisation and cross spe cies amplification in Prunus Theoretical and Applied Genetics 99 65 72. Cline, M.G., 1997. Concepts and terminology of apical dominanc e. American Journal of Botany 84 1064 1069. Cook, N. ., Rabe, E., Jacobs, G., 1999. Early expression of apical control regulates length and crotch angle of sylleptic shoots in peach and nectarine. Hortscience 34 604 606. Costes, E., Lauri, P E., Regnard, J.L., 2006. Analyzing fruit tree architecture: implications for tree management and fruit production. Horticultural Rev iews 32 1 61.

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139 Cubas, P., Lauter, N., Doebley, J., Coen, E., 1999. The TCP domain: a motif found in proteins regulating plant growth and development. Plant Journal 18 215 222. DeJong, T.M., Johnson, R.S., Doyle, J.F., Ramming, D., 2005 Labor costs may be reduced. Research yields size controlling rootstocks for peach production. California Agriculture 59 80 83. DeJong, T.M., Weibel, A., Tsuji, W., Doyle, J.F., Johnson, R.S., Ramming, D., 2001. Evaluation of size controlling rootstocks for California peach production. Proceedings of the Seventh International Symposium on Orchard and Plantation Systems 103 110. Dirlewanger, E., Cosson, P., Boudehri, K., Renaud, C., Capdeville, G., Tauzin, Y., Laigret, F., Moing, A., 2007. Development of a second generation genetic linkage map for peach Prunus persica (L.) Batsch and characterization of morphological traits affecting flower and fruit. Tree Genetics and Genomes 3 1 13. Dirlewanger, E., Cosson, P., Tavaud, M., Aranzana, M.J., Poizat, C., Zanetto, A., Arus, P., Laigret, F., 2002. Development of microsatellite markers in peach Prunus persica (L.) Batsch and their use in genetic diversity analysis in peach and sweet cherry ( Prunus avium L.). Theoretical and Applied Genetics 105 127 138. Dirlewanger, E., Cosson, P ., Howad, W., Capdeville, G., Bosselut, N., Claverie, M., Voisin, R., Poizat, C., Lafargue, B., Baron, O., Laigret, F., Kleinhentz, M., Arus, P., Esmenjaud, D., 2004a. Microsatellite genetic linkage maps of myrobalan plum and an almond peach hybrid locat ion of root knot nematode resistance genes. Theoretical and Applied Genetics 109 827 838. Dirlewanger, E., Graziano, E., Joobeur, T., Garriga Caldere, F., Cosson, P., Howad, W., Arus, P., 2004b. Comparative mapping and marker assisted selection in Rosacea e fruit crops. Proceedings of the National Academy of Sciences of the United States of America 101 9891 9896. Doebley, J., Stec, A., Hubbard, L., 1997. The evolution of apical dominance in maize. Nature 386 485 488. Doyle, J. J., 1991. DNA protocols for plants. CABI. New York. Dun, E A., Ferguson, B.J., Beveridge, C.A., 2006. Apical Dominance and Shoot Branching. Divergent Opinions or Divergent Mechanisms? Plant Physiology 142 812 819.

PAGE 140

140 Ehrenreich, I.M., Stafford, P.A., Purugganan, M.D., 2007. The geneti c architecture of shoot branching in Arabidopsis thaliana : a comparative assessment of candidate gene associations vs. quantitative trait locus mapping. Genetics 176 1223 1236. Erez, A., 1986. Growth control with paclobutrazol of peaches grown in a meadow orchard system. Acta Horticulturae 217 224. Fideghelli, C., Sartori, A., Grassi, F., 2003. Fruit tree size and architecture. Genetics and Breeding of Tree Fruits and Nuts 279 293. Fleming, A.J., 2005. Formation of primordia and phyllotaxy. Current Opinion in Plant Biology 8 53 58. Foolad, M.R., Arulsekar, S., Becerra, V., Bliss, F.A., 1995. A genetic map of Prunus based on an interspecific cross between peach and almond. Theoretical and Applied Genetics 91 262 269. Fourcaud, T., Zhang, X., Stokes, A., La mbers, H., Korner, C., 2008. Plant growth modelling and applications: The increasing importance of plant architecture in growth models. Annals of Botany 101 1053 1063. Genard, M., Pages, L., Kervella, J., 1994. Relationship between sylleptic branching and components of parent shoot development in the peach tree Annals of Botany 74 465 470. Giovannini, D., Liverani, A., 2005. Suitability of the dwarf ( dw / dw ) habit for the peach industry Journal of Hortic ultural Science and Biotechnology 80 605 610. Godi n, C., Costes, E., Sinoquet, H., 1999. A method for describing plant architecture which integrates topology and geometry. Annals of Botany 84 343 357. Gomez Roldan, V., Fermas, S., Brewer, P B., Puech Pages, V., Dun, E.A., Pillot, J.P., Letisse, F., Matus ova, R., Danoun, S., Portais, J.C., Bouwmeester, H., Becard, G., Beveridge, C.A., Rameau, C., Rochange, S F., 2008. Strigolactone inhibition of shoot branching. Nature. 455 189 194 Gradziel, T.M., Almond species as sources of new genes for peach improvem ent. Proceedings of the 5th International Peach Symposium, Davis, California, USA, 8 11 July, 2001. Volume 1. International Society for Horticultural Science (ISHS), 2002, 81 88. Gradziel, T.M., Kester, D.E., Martinez Gomez, P., 2002. A development based c lassification for branch architecture in almond. Journ al American Pomological Society 56 106 112.

PAGE 141

141 Grassell, C ., 1974. Study of possibilities of producing intraoperative and interspecific F1 hybrids in sub genus amygdalus. Annales d e Amelioration d es Plant es 24 307 315. Greb, T., Clarenz, O., Schafer, E., Muller, D., Herrero, R., Schmitz, G., Theres, K., 2003. Molecular analysis of the LATERAL SUPPRESSOR gene in Arabidopsis reveals a conserved control mechanism for axillary meristem formation. Genes and De velopment 17 1175 1187. Guillaumin, J.J., Pierson, J., Grassely, C., 1991. The susceptibility to armillaria mellea of different prunus species used as stone fruit rootstocks. Scientia Horticulturae 46 43 54. Halle, F., Oldeman, R.A.A., Tomlinson, P.B., 1 978. Tropical trees and forests: an architectural analysis. Springer Verlag., Berlin. Hansche, P.E., 1989. 3 brachytic dwarf peach cultivars valley gem, valley red, and valley sun. Hortscience 24 707 709. Hartig, K., Beck, E., 2006. Crosstalk between au xin, cytokinins, and sugars in the plant cell cycle. Plant Biology 8 389 396. Hasson, A., Plessis, A., Blein, T., Adroher, B., Grigg, S., Tsiantis, M., Boudaoud, A., Damerval, C., Laufs, P., 2011. Evolution and diverse roles of the CUP SHAPED COTYLEDON ge nes in Arabidopsis leaf development. Plant Cell 23 54 68. Howad, W., Yamamoto, T., Dirlewanger, E., Testolin, R., Cosson, P., Cipriani, G., Monforte, A. J., Georgi, L., Abbott, A. G., Arus, P., 2005. Mapping with a few plants: Using selective mapping for microsatellite saturation of the Prunus reference map. Genetics 171 1305 1309. Hibara, K., Karim, M.R., Takada, S., Taoka, K., Furutani, M., Aida, M., Tasaka, M., 2006. Arabidopsis CUP SHAPED COTYLEDON3 regulates postembryonic shoot meristem and organ bou ndary formation. Plant Cell 18 2946 2957. Hu, D.Y., Scorza, R., 2009. Analysis of the 'A72' peach tree growth habit and its inheritance in progeny obtained from crosses of 'A72' with columnar peach trees. Journal of the American Society for Horticultural Science 134 236 243. Jauregui, B., Vicente, M. C. Messeguer, R., Felipe, A., Bonnet, A., Salesses, G., Arus, P., 2001. A reciprocal translocation between 'Garfi' almond and 'Nemared' peach. Theoretical and Applied Genetics 102 1169 1176. Johnson, E.C., F ischer, K.S., Edmeades, G.O., Palmer, A.F.E., 1986. Recurrent selection for reduced plant height in lowland tropical maize. Crop Science 26 253 260.

PAGE 142

142 Johnson, R.S., Handley, D.F., Dejong, T.M., 1992. Long term response of early maturing peach trees to post harvest water deficits. Journal of the American Society for Horticultural Science 117 881 886. Johnson, X., Brcich, T., Dun, E. A., Goussot, M., Haurogne, K., Beveridge, C.A., Rameau, C., 2006. Branching genes are conserved across species. Genes controlli ng a novel signal in pea are coregulated by other long distance signals. Plant Physiology 142 1014 1026. Joobeur, T., Viruel, M.A., de Vicente, M.C., Jauregui, B., Ballester, J., Dettori, M.T., Verde, I., Truco, M.J., Messeguer, R., Batlle, I., Quarta, R. Dirlewanger, E., Arus, P., 1998. Construction of a saturated linkage map for Prunus using an almond x peach F2 progeny. Theoretical and Applied Genetics 97 1034 1041. Jordan, M.O., Wendler, R., Millard, P., 2009. The effect of autumn N supply on the arc hitecture of young peach ( Prunus persica L.) trees. Trees: Structure and Function 23 235 245. Jung, S., Jiwan, D., Cho, I.H., Lee, T.I., Abbott, A., Sosinski, B., Main, D., 2009. Synteny of Prunus and other model plant species. BMC Genomics 10. Keller, T. Abbott, J., Moritz, T., Doerner, P., 2006. Arabidopsis REGULATOR OF AXILLARY MERISTEMS1 controls a leaf axil stem cell niche and modulates vegetative development. Plant Cell 18 598 611. Kelsey, D. ., Brown, S.K., 1992. 'McIntosh Wijcik': a columnar muta tion of 'McIntosh' apple proving useful in physiology and breeding research. Fruit Varieties Journal 46 83 87. Kester, D.E., Gradziel, T., 1990. Growth habit trait nomenclature in almond and peach phenotypes. Hortscience 25 1072. Kester, D.E., Shackel, K .A., Micke, W.C., Viveros, M., Gradziel, M., 2004. Noninfectious bud failure in 'Carmel' almond: I. Pattern of development in vegetative progeny trees. Journal of the American Society for Horticultural Science 129 244 249. Keyes, G., Sorrells, M.E., 1989. Rht1 and rht2 semidwarf genes effect on hybrid vigor and agronomic traits of wheat. Crop Science 29 1442 1447. Khush, G.S., 2001. Green revolution: the way forward. Nature Reviews Genetics 2 815 822. Kianian, S.F., Quiros, C.F., 1992. Generation of a Br assica oleracea composite RFLP map: linkage arrangements among various populations and evolutionary implications. Theoretical and Applied Genetics. 84 544 554.

PAGE 143

143 King, D.A., Maindonald, J.H., 1999. Tree architecture in relation to leaf dimensions and tree s tature in temperate and tropical rain forests. Journal of Ecology 87 1012 1024. Kloosterman, B., Oortwijn, M., Willigen, J., America, T., Vos, R., Visser, R.G F., Bachem, C.W.B., 2010. From QTL to candidate gene: genetical genomics of simple and complex t raits in potato using a po oling strategy. BMC Genomics 11 Kwon, C.S., Hibara, K., Pfluger, J., Bezhani, S., Metha, H., Aida, M., Tasaka, M., Wagner, D., 2006. A role for chromatin remodeling in regulation of CUC gene expression in the Arabidopsis cotyledo n boundary. Development 133 3223 3230. Lambert, P., Pascal, T., 2011. Mapping Rm2 gene conferring resistance to the green peach aphid ( Myzus persicae Sulzer) in the peach cultivar "Rubira". Tree Genetics and Genomes 7 1057 1068. Lander, E.S., Green, P., Abrahamson, J., Barlow, A., Daly, M.J., Lincoln, S.E., Newburg, L., 1987. MAPMAKER: an interactive computer package for constructing primary genetic linkage maps of experimental and natural populations. Genomics 1 174 181. Lang, G.A., Early, J.D., Arroyav e, N.J., Darnell, R.L., Martin, G.C., Stutte, G.W., 1985. Dormancy toward a reduced, universal terminology. Hortscience 20 809 812. Lanner, R.M., 1966. The phenology and growth habits of Pines in Hawaii. U.S. For. Serv. Res. Pap. Pacif. Sthwest. For. Ra nge Exp. Sta. 25. Laurens, F., Audergon, J.M., Claverie, J., Duval, H., Germain, E., Kervella, J., Lezec, M. l., Lauri, P.E., Lespinasse, J.M., 2000. Integration of architectural types in French programmes of ligneous fruit species genetic improvement. Fr uits 55 141 152. Ledbetter, C.A., Sisterson, M.S., 2008. Advanced generation peach almond hybrids as seedling rootstocks for almond: first year growth and potential pollenizers for hybrid seed production. Euphytica 160 259 266. Ledig, F.T., Whitmore, J.L ., 1981. Heritability and genetic correlations for volume, foxtails, and other characteristics of caribbean pine in puerto rico. Silvae Genetica 30 88 92. Legave, J.M., Segura, V., Fournier, D., Costes, E., 2006. The effect of genotype, location and their interaction on early growth and branching in apricot trees. Journal of Horticultural Science and Biotechnology 81 189 198.

PAGE 144

144 Li, X., Qian, Q., Fu, Z., Wang, Y., Xiong, G., Zeng, D., Wang, X., Liu, X., Teng, S., Hiroshi, F., Yuan, M., Luo, D., Han, B., Li, J., 2003. Control of tillering in rice. Nature 422 618 621. Li, X.Z., Yuan, X.J., Jiang, S., Pan, J.S., Deng, S.L., Wang, G., Le He, H., Wu, A.Z., Zhu, L.H., Koba, T., Cai, R., 2008. Detecting QTLs for plant architecture traits in cucumber ( Cucumis sativ us L.). Breeding Science.58 453 460. Liebhard, R., Kellerhals, M., Pfammatter, W., Jertmini, M., Gessler, C., 2003. Mapping quantitative physiological traits in apple ( Malus domestica Borkh.). Plant Molecular Biology 52 511 526. Lockard, R.G., Schneide r, G.W., 1981. Stock and scion growth relationships and the dwarfing mechanism in apple. Horticultural Reviews 3 315 375. Loreti, F. and Massai, R. (2002). The high density peach planting system: Present status and perspectives. Proceedings of the 5th In ternational Peach Symposium, Vols 1 and 2 377 390. Lyrene, P.M., 1980. Micropropagation of rabbiteye blueberries. Hortscience 15 80 81. Marini, R.P., Barden, J.A., 1987. Summer pruning of apple and peach trees. Janick, J. (Ed.). Horticultural Reviews, V ol. 9. Van Nostrand Reinhold Co. Inc. New York, 351 376. Marini, R P., Corelli Grappadelli, L., 2006. Peach orchard systems. Horticultural Reviews 32 63 109. Martin Trillo, M., Grandio, E.G., Serra, F., Marcel, F., Rodriguez Buey, M.L., Schmitz, G., There s, K., Bendahmane, A., Dopazo, H., Cubas, P., 2011. Role of tomato BRANCHED1 like genes in the control of shoot branching. Plant Journal 67 701 714. Martinez Gomez, P., Arulsekar, S., Potter, D., Gradziel, T.M., 2003. An extended interspecific gene pool a vailable to peach and almond breeding as characterized using simple sequence repeat (SSR) markers. Euphytica 131 313 322. Masabni, J., Andersen, R., Azarenko, A., Brown, G., Freer, J., Hayden, R., 2007. Performance of plum rootstocks with 'Stanley', 'Valo r', and 'Veeblue'as the scion in the 1990 NC 140 multi site plum trial. Journal of the American Pomological Society 61 196 207. Matusova, R., Kumkum, R., Verstappen, F. W.A., Franssen, M.C.R., Beale, M.H., Bouwmeester, H.J., 2005. The strigolactone germina tion stimulants of the plant parasitic Striga and Orobanche spp. are derived from the carotenoid pathway. Plant Physiology 139 920 934.

PAGE 145

145 McSteen, P., Leyser, O., 2005. Shoot branching. Annual Review of Plant Biology 56 353 374. Mnejja, M., Garcia Mas, J., Howad, W., Arus, P., 2005. Development and transportability across Prunus species of 42 polymorphic almond microsatellites. Molecular Ecology Notes 5 531 535. Mnejja, M., Garcia Mas, M., Howad, W., Badenes, M. L., Arus, P., 2004. Simple sequence repeat ( SSR) markers of Japanese plum ( Prunus salicina Lindl.) are highly polymorphic and transferable to peach and almond. Molecular Ecology Notes 4 163 166. Morita, S., Collins, H.P., 1990. A method to describe root branching. Japanese Journal of Crop Science 5 9 580 581. Morita, S., Thongpae, S., Abe, J., Nakamoto, T., Yamazaki, K., 1992. Root branching in maize .1. Branching index and methods for measuring root length. Japanese Journal of Crop Science 61 101 106. Mowrey, B.D., Werner, D.J., Byrne, D.H., 1990. Isozyme survey of various species of prunus in the subgenus amygdalus Scientia Horticulturae 44 251 260. Muller, D., Schmitz, G., Theres, K., 2006. Blind homologous R2R3 Myb genes control the pattern of lateral meristem initiation in Arabidopsis. Plant Cell 18 586 597. Nordstrom, A., Tarkowski, P., Tarkowska, D., Norbaek, R., Astot, C., Dolezal, K., Sandberg, G., 2004. Auxin regulation of cytokinin biosynthesis in Arabidopsis thaliana : A factor of potential importance for auxin cytokinin regulated devel opment. Proceedings of the National Academy of Sciences of the United States of America 101 8039 8044. Niu, L., Wang, Z., Liu, S., Song, Y., Zong, X., 2004. Advances in research on growth habits of peach tree ( Prunus persica ). Journal of Fruit Science 21 354 359. Otsuga, D., DeGuzman, B., Prigge, M.J., Drews, G.N., Clark, S.E., 2001. REVOLUTA regulates meristem initiation at lateral positions. Plant Journal 25 223 236. Paterson, A.H., Verna, J. W., Lanini, B., Tanksley, S.D., 1990. Fine mapping of quanti tative trait loci using selected overlapping recombinant chromosomes, in an interspecies cross of tomato. Genetics 124 735 742. Plomion, C., Durel, C.E., 1996. Estimation of the average effects of specific alleles detected by the pseudo testcross QTL mapp ing strategy. Genetics, Selection, Evolution 28 223 235.

PAGE 146

146 Porter, G.W., Sherman, W.B., Beckman, T.G., Krewer, G.W., 2002. Fruit weight and shoot diameter relationship in early ripening peaches. Journal American Pomological Society 56 30 33. Prassinos, C., Ko, J.H., Lang, G., Iezzoni, A.F., Han, K.H., 2009. Rootstock induced dwarfing in cherries is caused by differential cessation of terminal meristem growth and is triggered by rootstock specific gene regulation. Tree Physiology 29 927 936. Prusinkiewicz, P., 2004. Modeling plant growth development. Current Opinion in Plant Biology 7 79 83. Reinhardt, D., Mandel, T., Kuhlemeier, C., 2000. Auxin regulates the initiation and radial position of plant lateral organs. Plant Cell 12 507 518. Reinhardt, D., Pesc e, E.R., Stieger, P., Mandel, T., Baltensperger, K., Bennett, M., Traas, J., Friml, J., Kuhlemeier, C., 2003. Regulation of phyllotaxis by polar auxin transport. Nature 426 255 260. Richards, G.D., Porter, G.W., Rodriguez, J., Sherman, W.B., 1994. Inciden ce of blind nodes in low chill peach and nectarine germplasm. Fruit Varieties Journal 48 199 202. Rojas Barros, P., Hu, J.G., Jan, C.C., 2008. Molecular mapping of an apical branching gene of cultivated sunflower ( Helianthus annuus L.). T heoretical and Ap plied Genetics 117 19 28. Rubio, M., Pascal, T., Bachellez, A., Lambert, P., 2010. Quantitative trait loci analysis of Plum pox virus resistance in Prunus davidiana P1908: new insights on the organization of genomic resistance regions. Tree Genetics and G enomes 6 291 304. Schmidt, H., Gruppe, W., 1988. Breeding dwarfing rootstocks for sweet cherries Hortscience 23 112 114. Scorza, R., 1984. Characterization of 4 distinct peach tree growth types. Journal of the American Society for Horticultural Science 109 455 457. Scorza, R., 1987. Identification and analysis of spur growth in peach ( P runus persica L B atsch). Journal of Horticultural Science 62 449 455. Scorza, R., Bassi, D., Liverani, A., 2002. Genetic interactions of pillar (columnar), compact, and dwarf peach tree genotypes. Journal of the American Society for Horticultural Science 127 254 261.

PAGE 147

147 Scorza, R., Li, Z.L., Lightner, G.W., Gilreath, L.E., 1986. Dry matter distribution and responses to pruning within a population of standard, semidwarf, com pact, and dwarf peach seedlings. Journal of the American Society for Horticultural Science 111 541 545. Scorza, R., Miller, S., Glenn, D.M., Okie, W.R., Tworkoski, T., 2006. Developing peach cultivars with novel tree growth habits. Proceedings of the VIth International Peach Symposium 61 64. Scorza, R., Okie, W.R., 1990. Peaches ( Prunus ). Acta Horticulturae 290, 175 231. Segura, V., Cilas, C., Laurens, F., Costes, E., 2006. Phenotyping progenies for complex architectural traits: a strategy for 1 year old apple trees ( Malus x domestica Borkh.). Tree Genetics and Genomes 2 140 151. Segura, V., Denance, C., Durel, C. E., Costes, E., 2007. Wide range QTL analysis for complex architectural traits in a 1 year old apple progeny. Genome 50 159 171. Segura, V., O uangraoua, A., Ferraro, P., Costes, E., 2008. Comparison of tree architecture using tree edit distances: application to 2 year old apple hybrids. Euphytica 161 155 164. Shen, X., Li, Y., Kang, L., Zou, Y., Shu, H., 2008. Relationship between morphology an d hormones during weeping peach ( Prunus persica var. pendula) shoot development. Acta Horticulturae Sinica 35 395 402. Sherman, W.B., Lyrene, P.M., Sharpe, R.H., 1991. Flordaguard peach rootstock Hortscience. 26 427 428. Slafer, G.A., Araus, J.L., Richa rds, R.A., 1999. Physiological traits that increase the yield potential of wheat. Haworth Press Inc., New York. Sosinski, B., Gannavarapu, M., Hager, L. D., Beck, L. E., King, G. J., Ryder, C. D., Rajapakse, S., Baird, W. V., Ballard, R. E., Abbott, A. G., 2000. Characterization of microsatellite markers in peach Prunus persica (L.) Batsch. Theoretical and Applied Genetics 101 421 428. Souer, E., Houwelingen, A., Kloos, D., Mol, J., Koes, R., 1996. The no apical meristem gene of petunia is required for pat tern formation in embryos and flowers and is expressed at meristem and primordia boundaries. Cell 85 159 170. Stephan, J., Lauri, P.E., Dones, N., Haddad, N., Talhouk, S., Sinoquet, H., 2007. Architecture of the pruned tree: Impact of contrasted pruning p rocedures over 2 years on shoot demography and spatial distribution of leaf area in apple ( Malus domestica ). Annals of Botany 99 1055 1065.

PAGE 148

148 Stirnberg, P., Chatfield, S. P., Leyser, H. M. O., 1999. AXR1 acts after lateral bud formation to inhibit lateral b ud growth in Arabidopsis. Plant Physiology. 121 839 847. Stirnberg, P., Furner, I.J., Leyser, H.M.O., 2007. MAX2 participates in an SCF complex which acts locally at the node to suppress shoot branching. Plant Journal 50 80 94. Stirnberg, P., van de Sand e, K., Leyser, H.M.O., 2002. MAX1 and MAX2 control shoot lateral branching in Arabidopsis Development 129 1131 1141. Tanksley, S.D., Hewitt, J., 1988. U se of molecular markers in breeding for soluble solids content in tomato a re examination Theoretical and Applied Genetics 75 811 823. Tanksley, S.D., Young, N.D., Paterson, A.H., Bonierbale, M.W., 1989. RFLP mapping in plant breeding new tools for an old science. BioTechnology 7 257 264. Tantikanjana, T., Yong, J.W.H., Letham, D.S., Griffith, M., Hussa in, M., Ljung, K., Sandberg, G., Sundaresan, V., 2001. Control of axillary bud initiation and shoot architecture in Arabidopsis through the SUPERSHOOT gene. Genes and Development 15 1577 1588. Tomlinson, P. B., 1978. Branching and axis differentiation in t ropical trees. Tworkoski, T., Miller, S., Scorza, R., 2006. Relationship of pruning and growth morphology with hormone ratios in shoots of pillar and standard peach trees. Journal of Plant Growth Regulation 25 145 155. Umehara, M., Hanada, A., Yoshida, S. Akiyama, K., Arite, T., Takeda Kamiya, N., Magome, H., Kamiya, Y., Shirasu, K., Yoneyama, K., Kyozuka, J., Yamaguchi, S., 2008. Inhibition of shoot branching by new terpenoid plant hormones. Nature 455 195 200 Wang S., C.J. Basten, Z.B. Zeng, 2011. Win dows QTL Cartographer 2.5. Department of Statistics, North Carolina State University, Raleigh, NC. ( http://statgen.ncsu.edu/qtlcart/WQTLCart.htm ) Wang, Y.H., Li, J. Y., 2006. Genes controlling plant architecture. Current Opinion in Biotechnology 17 123 1 29. Wang, Y. H., Li, J. Y., 2008. Molecular basis of plant architecture. Annual Review of Plant Biology 59 253 279. Webster, A. D., Wertheim, S. J., Ferree, D.C., 2003. Apple rootstocks. Apples: Botany, production and uses New York.

PAGE 149

149 Weinbaum, S. A., Johnso n, R. S., DeJong, T. M., 1992. Causes and consequences of overfertilization in orchards. Hortechnology 2 112 121 Wert, T. W., Williamson, J. G., Chaparro, J.X., Miller, E.P., 2007. Node type development of four low chill peach cultivars at three locations i n Florida. Hortscience 42 1592 1595. Wu, R.L., Hinckley, T.M., 2001. Phenotypic plasticity of sylleptic branching: Genetic design of tree architecture. Critical Reviews in Plant Sciences 20 467 485. Yamamoto, T., Shimada, T., Imai, T., Yaegaki, H., Haji, T., Matsuta, N., Yamaguchi, M., Hayashi, T., 2001. Characterization of morphological traits based on a genetic linkage map in peach. Breeding Science 51 271 278. Yamamoto, T., Mochida, K., Imai, T., Shi, Y. Z., Ogiwara, I., Hayashi, T., 2002. Microsatell ite markers in peach Prunus persica (L.) Batsch derived from an enriched genomic and cDNA libraries. Molecular Ecology Notes 2 298 301. Y ang, X.C., Hwa, C.M., 2008. Genetic modification of plant architecture and variety improvement in rice. Heredity 101 396 404.

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150 BIOGRAPHICAL SKETCH Omar Carrillo Mendoza was born on 1977. He received his primary education in the public educational system of D.F. and Hidalgo State in Mexico. He got his Bachelo r degree in Agronomy from Universidad Autonoma Chapingo, Mexico; and a Master of Science degree in fruit science from Colegio de Postgraduados, Mexico. He worked as an assistant breeder and researcher in temperate fruit trees, small fruits and cactus pear at Colegio de Postgraduados from 2001 to 2006 He was a collaborator in the subtropical Mexico strawberry breeding program, breeding and releasing four strawberry varieties. In 2007 he got a scholarship from the National Council of Science from Mexico (CO NACyT) to study a doctorate at the University of Florida. He began working in 2008 with Dr. Jose Chaparro in the stone fruit breeding program of the Horticultural Sciences Department as a PhD student and graduate research assistant.