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Characterization of a Novel Maize Brown Midrib Mutant

Permanent Link: http://ufdc.ufl.edu/UFE0022165/00001

Material Information

Title: Characterization of a Novel Maize Brown Midrib Mutant
Physical Description: 1 online resource (108 p.)
Language: english
Creator: Tayengwa, Reuben
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2008

Subjects

Subjects / Keywords: Agronomy -- Dissertations, Academic -- UF
Genre: Agronomy thesis, M.S.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: As part of the National Science Foundation (NSF) Plant Genome project ?Identification and characterization of cell wall mutants in maize and Arabidopsis using novel spectroscopies,? 2,200 F2 families of Mutator-tagged maize lines from the UniformMu population developed at the University of Florida were planted at Purdue University in the summer of 2002-2004. The UniformMu population has a high mutagenic rate caused by Mutator (Mu) transposons that have the capacity to move from one locus to another in the genome. If a Mu transposon inserts in a gene, it has the potential to disrupt the function of that gene. Among the mutants identified in the UniformMu population, was a novel brown midrib (bm) mutant that displayed a subtle orange-brown midrib. Currently, there are four bm mutants known in maize. These mutants, bm1, bm2, bm3, and bm4, are Mendelian recessives and are recognized by reddish-brown vascular tissue in the leaves and stems resulting from changes in lignin content and/or composition. This coloration has been observed in the stem, root, leaf, tassel and cob of the plant in several of the four bm mutants. The objective of this research was to characterize the novel brown midrib mutant and to identify the genetic basis of this mutation. Several chemical analyses were performed to compare the new bm mutant to the other characterized bm mutants and to wild-type plants. Stover from the bm mutant has similar biomass conversion efficiency as wild-type stover, and pyrolysis gas-chromatography-mass-spectrometry analysis of wild-type and bm midribs showed that the bm mutant has identical lignin sub-unit composition to the wild-type. Collectively, these data suggested that the bm phenotype is not due to a mutation in the lignin biosynthetic pathway. Pigment analyses have not provided evidence in favor of carotenoids and flavonoids as the pigments that accumulate in the midrib of the bm mutant. Work is in progress to identify the pigment responsible for the orange-brown color in the midribs. Since the assumption was that this mutation was caused by a Mu transposon insertion, obtaining all sequences flanking Mu transposons allowed a test of which element caused the mutant phenotype. A total of 192 flanking sequences were obtained using a PCR-based protocol. The sequences were subsequently filtered through a sequence database with Mu-flanking DNA from the progenitor and siblings of the bm mutant. This analysis resulted in 42 unique candidate sequences. Each of these were tested to see if they co-segregated with the bm mutant phenotype. None of the candidate genes co-segregated with the phenotype.
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 Reuben Tayengwa.
Thesis: Thesis (M.S.)--University of Florida, 2008.
Local: Adviser: Vermerris, Willem Wilfred.
Electronic Access: RESTRICTED TO UF STUDENTS, STAFF, FACULTY, AND ON-CAMPUS USE UNTIL 2009-08-31

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2008
System ID: UFE0022165:00001

Permanent Link: http://ufdc.ufl.edu/UFE0022165/00001

Material Information

Title: Characterization of a Novel Maize Brown Midrib Mutant
Physical Description: 1 online resource (108 p.)
Language: english
Creator: Tayengwa, Reuben
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2008

Subjects

Subjects / Keywords: Agronomy -- Dissertations, Academic -- UF
Genre: Agronomy thesis, M.S.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: As part of the National Science Foundation (NSF) Plant Genome project ?Identification and characterization of cell wall mutants in maize and Arabidopsis using novel spectroscopies,? 2,200 F2 families of Mutator-tagged maize lines from the UniformMu population developed at the University of Florida were planted at Purdue University in the summer of 2002-2004. The UniformMu population has a high mutagenic rate caused by Mutator (Mu) transposons that have the capacity to move from one locus to another in the genome. If a Mu transposon inserts in a gene, it has the potential to disrupt the function of that gene. Among the mutants identified in the UniformMu population, was a novel brown midrib (bm) mutant that displayed a subtle orange-brown midrib. Currently, there are four bm mutants known in maize. These mutants, bm1, bm2, bm3, and bm4, are Mendelian recessives and are recognized by reddish-brown vascular tissue in the leaves and stems resulting from changes in lignin content and/or composition. This coloration has been observed in the stem, root, leaf, tassel and cob of the plant in several of the four bm mutants. The objective of this research was to characterize the novel brown midrib mutant and to identify the genetic basis of this mutation. Several chemical analyses were performed to compare the new bm mutant to the other characterized bm mutants and to wild-type plants. Stover from the bm mutant has similar biomass conversion efficiency as wild-type stover, and pyrolysis gas-chromatography-mass-spectrometry analysis of wild-type and bm midribs showed that the bm mutant has identical lignin sub-unit composition to the wild-type. Collectively, these data suggested that the bm phenotype is not due to a mutation in the lignin biosynthetic pathway. Pigment analyses have not provided evidence in favor of carotenoids and flavonoids as the pigments that accumulate in the midrib of the bm mutant. Work is in progress to identify the pigment responsible for the orange-brown color in the midribs. Since the assumption was that this mutation was caused by a Mu transposon insertion, obtaining all sequences flanking Mu transposons allowed a test of which element caused the mutant phenotype. A total of 192 flanking sequences were obtained using a PCR-based protocol. The sequences were subsequently filtered through a sequence database with Mu-flanking DNA from the progenitor and siblings of the bm mutant. This analysis resulted in 42 unique candidate sequences. Each of these were tested to see if they co-segregated with the bm mutant phenotype. None of the candidate genes co-segregated with the phenotype.
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 Reuben Tayengwa.
Thesis: Thesis (M.S.)--University of Florida, 2008.
Local: Adviser: Vermerris, Willem Wilfred.
Electronic Access: RESTRICTED TO UF STUDENTS, STAFF, FACULTY, AND ON-CAMPUS USE UNTIL 2009-08-31

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2008
System ID: UFE0022165:00001


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1 CHARACTERIZATION OF A NOVEL MAIZE BROWN MIDRIB MUTANT By REUBEN TAYENGWA A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE UNIVERSITY OF FLORIDA 2008

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2 2008 Reuben Tayengwa

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3 To my family, teachers and friends.

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4 ACKNOWLEDGMENTS I thank m y supervisory committee for their wise guidance and advice, all current and past members of the Vermerris lab and current members of the Koch lab for their friendship and help during my research. I am also very grateful to the National Scie nce Foundation for their generous support.

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5 TABLE OF CONTENTS page ACKNOWLEDGMENTS ............................................................................................................... 4LIST OF TABLES ...........................................................................................................................8LIST OF FIGURES .........................................................................................................................9ABSTRACT ...................................................................................................................... .............10CHAPTER 1 LITERATURE REVIEW .......................................................................................................12Cell Walls .................................................................................................................... ...........12Cell Wall Polys accharides ..................................................................................................... .12Cellulose ..................................................................................................................... .....12Hemicellulose ................................................................................................................. .13Pectin ...............................................................................................................................14Type I vs. Type II Walls ...................................................................................................... ...14Lignin ........................................................................................................................ ..............15Lignin Biosynthetic Enzymes ................................................................................................. 16Phenylalanine Ammonia-Lyase .......................................................................................16Cinnamate 4-Hydroxylase ............................................................................................... 174-Coumarate: Coenzyme A Ligase ................................................................................. 18Hydroxycinnamoyl-Coenzyme A Shikimate/Qu inate Hydroxycinnamoyltransferase ... 18Coumarate 3-Hydroxylase ............................................................................................... 19Caffeoyl-Coenzyme A O -Methyltransferase ................................................................... 20Cinnamoyl-Coenzyme A Reductase ................................................................................ 20Caffeate O -Methyltransferase ......................................................................................... 20Ferulate 5-Hydroxylase ...................................................................................................21Cinnamyl Alcohol Dehydrogenase .................................................................................. 22Sinapyl Alcohol Dehydrogenase .....................................................................................22Lignin Polymerization ............................................................................................................23Lignin Mutants ................................................................................................................ ........24Arabidopsis Ref Mutants ................................................................................................. 25Maize Brown Midrib Mutants ......................................................................................... 26Sorghum Brown Midrib Mutants ..................................................................................... 28Pearl Millet Brown Midrib Mutants ................................................................................ 28Lignin Modification via Transgenic Approaches ...................................................................29Agro-Industrial Processes Affected by Cell Wall Composition ............................................. 32Ethanol Production ..........................................................................................................33Paper Production .............................................................................................................34Forage ........................................................................................................................ ......35Plant Pigmentation ............................................................................................................ ......36

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6 Carotenoids ................................................................................................................... ...36Flavonoids .......................................................................................................................38Pyrosequencing ................................................................................................................ .......392 SCREENING FOR ALTERED CELL W ALL COMPOSITION USING NIR SPECTROSCOPY .................................................................................................................. 43Background .................................................................................................................... .........43Introduction .................................................................................................................. ...........43Data Compression ...........................................................................................................45Principal Component Analysis ........................................................................................46Partial Least Squares ....................................................................................................... 46Materials and Methods ...........................................................................................................47Uniform Mu Population ....................................................................................................47Novel Brown Midrib Mutant ........................................................................................... 48Class Modelling ...............................................................................................................49Results .....................................................................................................................................493 AGRONOMIC AND CHEMICAL ANALYSES OF THE NOVEL BM MAIZE MUTANT ........................................................................................................................ .......53Introduction .................................................................................................................. ...........53Agronomic Traits .............................................................................................................53Chemical Analysis ...........................................................................................................53Materials and Methods ...........................................................................................................54Plant Material ..................................................................................................................54Flowering Time ...............................................................................................................54Klason Lignin Content ....................................................................................................54Lignin Sub-unit Composition .......................................................................................... 55Wiesner Reaction .............................................................................................................56Enzymatic Saccharification .............................................................................................57Cellulase Assays ..............................................................................................................57Carotenoid Extraction ...................................................................................................... 60Thin Layer Chromatography ........................................................................................... 61Flavonoid Extraction .......................................................................................................61Results .....................................................................................................................................62Agronomic Traits ....................................................................................................................62Chemical Analysis ..................................................................................................................63Wiesner Staining .............................................................................................................63Enzymatic Saccharification .............................................................................................63Carotenoid Extraction ...................................................................................................... 63Klason Lignin .........................................................................................................................64Pyrolysis-Gas Chromatography-Mass Spectrometry .............................................................64Near Infrared Reflectance Spectroscopy ................................................................................64Efforts to Clone the Bm Gene .................................................................................................64

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7 4 EFFORTS TO CLONE THE BM GENE ...............................................................................72Introduction .................................................................................................................. ...........72DNA Extraction ................................................................................................................ ......72Mu -TAIL PCR ........................................................................................................................72Sequencing .................................................................................................................... ..........73TOPO Cloning Reaction ......................................................................................................... 74Transformation ................................................................................................................ .......74In Silico Subtraction ............................................................................................................... 75Co-segregation Analysis .........................................................................................................755 DISCUSSION .................................................................................................................... .....846 FUTURE WORK ................................................................................................................... .90LIST OF REFERENCES ...............................................................................................................93BIOGRAPHICAL SKETCH .......................................................................................................108

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8 LIST OF TABLES Table page 3-1 Py-GC-MS program used to analyze midrib samples ........................................................ 663-2 Py-GC-MS oven program used to analyze midrib samples ............................................... 663-3 Cellulase enzyme cocktail ................................................................................................. .663-4 GC-MS program used to an alyze carotenoid samples ....................................................... 663-5 GC-MS oven program used to analyze carotenoid samples .............................................. 663-6 Spectrophotometer absorbance readings of carotenoids extracted from wild-type and bm mutant midrib samples ................................................................................................. 704-1 Thermal cycler programs used for Mu-TAIL PCR ............................................................764-2 Nested MuTIR primers used to amplify Muadjacent se quences ..................................... 774-3 Arbitrary primers used in combination with MuTIR nested primers in Mu-TAIL PCR ....................................................................................................................................784-4 Unique MuTAIL sequence types of the bm mutant obtained from in silico subtraction ................................................................................................................... .......784-5 Co-segregation primers .................................................................................................... ..79

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9 LIST OF FIGURES Figure page 1-1 Schematic representation of the lignified secondary wall ................................................. 411-2 Three monolignols that are incor porated into the lignin polymer. ....................................411-3 The lignin biosynthetic pathway. ....................................................................................... 422-1 Partial Least Squares plot showing separation between bm mutant and wild-type leaf samples. ...................................................................................................................... ........512-2 Based on NIR data, the mutant appears to have an abundance of proteins (1528 nm, 2061 nm) carbohydrates (1702 nm, 2379 nm). .................................................................. 512-3 Results confirming variation in cell wa ll composition between putative mutant and wild-type plants following NIR analysis. ..........................................................................522-4 Results confirming variation in cell wa ll composition between putative mutant and wild-type plants. Results were obtaine d after NIR and Py-MB-MS analyses. .................. 523-1 Differences in plant height between the bm mutant and wild-type ................................... 673-2 Time to flowering, measured as days af ter planting (averaged acr oss 4 replications), for the wild-type and mutant plants ................................................................................... 673-3 Time to silking, measured as days afte r planting (averaged acr oss 4 replications) ...........683-4 Maize stem sections after staining with the Wiesner reagent. ........................................... 683-5 Glucose yields (mg glucose /g DW stove r) following hydrolysis of wild-type and bm mutant stover samples (p-value = 0.85). ............................................................................ 693-6 Klason lignin content comparison between wild-type and mutant plants averaged across six replications (p-value = 0.57). ............................................................................ 693-7 The residue of the bm and wild-type samples after 24 hours of flavonoid extraction ....... 703-8 Midrib sections from 60 day old maize plants grown in a greenhouse. ............................ 703-9 Midrib stem section C) stained with Wiesner reagent and then viewed under a compound microscope (magnification 40). D) Dark staining surrounding the vascular tissue and the sclerenchyma confirms the presence of lignin in these tissues. .... 714-1 Agarose gel image of Mu -TAIL PCR products amplified using Mu -TIR6 and nested TIR8 primer and 12 arbitrary primers. ............................................................................... 77

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10 Abstract of thesis presente d to the graduate school of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science CHARACTERIZATION OF A NOVEL MAIZE BROWN MIDRIB MUTANT By Reuben Tayengwa August 2008 Chair: Dr. Wilfred Vermerris Major: Agronomy As part of the National Science Foundation (NSF) Plant Genome project Identification and characterization of cell wall mutants in ma ize and Arabidopsis using novel spectroscopies, 2,200 F2 families of Mutator-tagged maize lines from the Uniform Mu population developed at the University of Florida were planted at Pu rdue University in the summer of 2002-2004. The Uniform Mu population has a high mutagenic rate caused by Mutator (Mu) transposons that have the capacity to move from one locu s to another in the genome. If a Mu transposon inserts in a gene, it has the potential to disrupt the function of that gene. Among the mutants identified in the Uniform Mu population, was a novel brown midrib (bm) mutant that displayed a subtle orangebrown midrib. Currently, there are four bm mutants known in maize. These mutants, bm1, bm2, bm3 and bm4, are Mendelian recessives and are recogn ized by reddish-brown vascular tissue in the leaves and stems resulting from changes in lignin content and/or composition. This coloration has been observed in the stem, root, leaf tassel and cob of the pl ant in several of the four bm mutants. The objective of this rese arch was to characterize the novel brown midrib mutant and to identify the genetic basis of this mutation. Several chemical analyses were performed to compare the new bm mutant to the other characterized bm mutants and to wild-type plants. Stover from the bm mutant has similar

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11 biomass conversion efficiency as wild-type st over, and pyrolysis gas-chromatography-massspectrometry analysis of wild-type and bm midribs showed that the bm mutant has identical lignin sub-unit composition to the wild-type. Collectively, these data suggested that the bm phenotype is not due to a mutation in the lignin biosynthetic pathway. Pigment analyses have not provided evidence in favor of carotenoi ds and flavonoids as the pigments that accumulate in the midrib of the bm mutant. Work is in progress to identify the pigment responsible for the orange-brown color in the midribs. Since the assumption was that this mutation was caused by a Mu transposon insertion, obtaining all sequences flanking Mu transposons allowed a test of which element caused the mutant phenotype. A total of 192 flanking sequences were obtained using a PCR-based protocol. The sequences were subsequently filter ed through a sequence database with Mu -flanking DNA from the progenitor and siblings of the bm mutant. This analysis resu lted in 42 unique candidate sequences. Each of these were tested to see if they co-segregated with the bm mutant phenotype. None of the candidate genes co -segregated with the phenotype.

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12 CHAPTER 1 LITERATURE REVIEW Cell Walls Plant ce ll walls contribute to the functiona l specialization of ce ll types (Carpita and McCann, 2000). They are a highly organized co mposite of many different polysaccharides, proteins, and aromatic substances. The cell wall is composed of a middle lamella, primary cell wall, and in specialized tissues a secondary cell wall. Primar y cell walls are composed of polysaccharides, smaller proportions of glycoproteins and, in some specialized cell types, various non-carbohydrate substances such as lignin, suberin, cutin or silica (Fry, 2003). In contrast to primary cell walls, plant secondary cell walls are deposited once the cell has stopped expanding. Secondary cell walls offer several advantages fo r genetic analysis of plant cell walls: it is possible to recover severe mutants because the pl ants usually remain viable (Turner, 2001). The molecular composition and arrangement of the wall polymers differ among species, among individual cells, within a sp ecies and even among the regions of the wall around a single protoplast. Cell Wall Polysaccharides Polysaccharides are the m ain components of the cell wall and form its main structural framework (Carpita and McCann, 2000). There are th ree different classes of polysaccharides in the cell wall: cellulose, hemicellulose and pectin. Cellulose Cellulose is the principal scaffolding com ponent of all plant cell walls (Carpita and McCann, 2000) (Figure 1-1). It is an essential part of the plant cel l wall, where it is vital within the load-bearing network and an importan t determinant of the orientation of cell expansion (Taylor et al., 2004). It exists in the form of microfibrils, para -crystalline assemblies of several

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13 dozen (1-4)-D-glucan chains hydrogen bonded to one a nother along their length. Cellulose is the most abundant component of plant secondary walls and makes up a large proportion of the dry weight of these secondary cell walls (Taylo r et al., 2004). Turner and Sommerville (1997) isolated a series of mutants following a scre en of a chemically mutagenized population of Arabidopsis plants that had collapse d xylem cells and that were termed irregular xylem (irx) mutants The collapse of the xylem vessels was attr ibuted to a weakness in the secondary cell wall of the xylem cells which resulted in them being unable to withstand the negative pressure generated during water transport up the stem. Analysis of the cell wall composition of the mutants revealed that they had a severe decrease in the amount of cellulose in the stems. Turner and Sommerville (1997) reported that each mutant contains about a third the amount of cellulose found in the wild-type. Callose which consists of (1-3)-D-glucan chains, is made by a few cell types at specific stages of wall development that include growing pollen tu bes and cell plates of dividing cells. Hemicellulose Cross-linkin g glycans are a class of polysacch arides that can hydrogen bond to cellulose microfibrils (Carpita and McCann, 2000). They eith er coat microfibrils or are long enough to span the distance between microfibrils (Figure 11), and link them together to form a network (Carpita and McCann, 2000). Major hemicelluloses are the xylans (including arabinoxylans, glucuronoarabinoxylans [GAXs]), xy loglucans (XyGs) (composed mainly of glucose, xylose [Xyl], galactose, fucose, and mixed linkage -[1-3]), (1-4)-D-glucans only found in the Gramineae and a few related families (Fry, 2003). Xyloglucans consist of linear chains of (1-4)-D-glucan with numerous alpha-D-Xyl units linked at regular sites to the O -6 position of the glucose unit.

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14 Pectin Pectins are a m ixture of heterogeneous branch ed and highly hydrated polysaccharides that are rich in d-galacturonic acid (Carpita and McCann, 2000). They determine wall porosity, provide charged surfaces that modulate wall pH a nd ion balance, regulate cell-cell adhesion at the middle lamella, provide an environment fo r the deposition, slippage and extension of the cellulosic-glycan network and serv e as recognition molecules that alert the plant cells to the presence of symbiotic organisms, pathogens, and insects. Changes in the structures of these polysaccharides are associated with different de velopmental stages of plant cells and tissues (ONeill et al., 2003). There are two main components of pectins, homogalacturonan (HGA) and rhamnogalacturonan I (RG I). Homogalacturon ans are structurally modified into xylogalacturonan and rhamnogalacturonan II (RG II). These three pectic polysaccharides are covalently linked to one another to form a pectic macromolecule. Further covalent and noncovalent cross-linking of some gl ycosyl residues in this macromolecule form a three-dimensional pectic network (ONeill et al., 2003). RG I is composed of d-galactosyluronic acid, l-rhamnosyl, d-galactosyl, l-arabinosyl, and small amount s of l-fucosyl residues (McNeil, 1982). The backbone of RG I is composed of altern ating 2-linked l-rhamnosyl and 4-linked dgalactosyluronic acid residues. Overall, the modula tion of pectic structure can be viewed as the fine-tuning of conditions and capacities within the cell wall matrix, providing both mechanical properties and an operating environment for the activities of cell-wall modifying enzymes and other factors (ONeill et al., 2003). Type I vs. Type II Walls There are tw o distinct types of cell walls that differ in chemical composition. Type I cells are found in the walls of most dicots and nonc ommelinoid monocots and are composed of equal amounts of xyloglucans and cellulo se (Carpita and McCann, 2000). Xyloglucans bind to the

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15 cellulose microfibrils locking them into proper spatial arrangements. The cross-linking glycans span the distance between two microfibrils and bind to both of them. The XyG cellulose framework is embedded in a pectin matrix. In contrast, Type II walls of commelinoid monocots contain cellulose microfibrils that are interlocked together by GAXs even though small amounts of XyGs are also present. In addition, Type II cells are pectin-poor comp ared to Type I walls. There is also little structural pr otein compared to dico ts and other monocots, but they accumulate extensive interconnecting netw orks of phenylpropanoids as the cells stop expanding. Lignin Lignin is a m ajor constituent of secondary cell walls in all vascular plants, and it plays several important roles including the strength ening and impermeabilization of cell walls and providing a mechanical and chemical barrier against pat hogens (Baucher et al ., 1999). Lignin is a heterogeneous aromatic polymer that is com posed of different phenypropanoids mainly the monolignols pcoumaryl, coniferyl and sinapyl alcohols (Figure 1-2). Upon incorporation into lignin, these monolignols are called phydroxyphenyl (H), guaiacyl (G ) and syringyl (S) units (Raes et al., 2003) In addition to these three units, there are othe r phenylpropanoids that can be incorporated in lignin, including hydroxycinnamyl aldehyd es, hydroxycinnamyl acetates, hydroxycinnamyl phydroxybenzoates, hydroxycinnamyl pcoumarates and hydroxycinnamate esters (Ralph et al., 2001; Boerjan et al., 2003). The lignin structur e is complex, incorporating ether and carboncarbon linkages between monomers with extens ive cross-links, probably via hydroxycinnamic acid bridges, to other cell wall polymers. The monolignols are linked by way of ester, ether, or carbon-carbon bonds. The phenylpropanoid pathway is responsible for the biosynthesis of a variety of products that include lignin, flavonoids and hydroxycinnamic acids conjugates (Humphreys and Chapple,

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16 2002), (Figure 1-3). Most intermediates and end pr oducts of this pathway play vital roles in plants as phytoalexins, antiherbivory compounds, antioxidants, UV protectants, pigments and aromatic compounds (Humphreys and Chapple, 2002). Monolignols and hydroxycinnamic acids are the products of the phenylpropanoid pathwa y, which also supplies intermediates for the synthesis of phytoalexins, fla vonoids and tannins (Halpin et al., 1998). Of the many enzymes on this pathway only cinnamoyl coenzyme A-reduc tase (CCR) and cinnamy l alcohol dehydrogenase (CAD) are dedicated solely to monoli gnol synthesis (Halpin et al., 1998). Lignin Biosynthetic Enzymes Phenylalanine Ammonia-Lyase Phenylalan ine ammonia-lyase (PAL) catalyz es the deamination of phenylalanine to cinnamate the committed step in phenylpropanoid metabolism (Whetten and Sederoff, 1995). Considered as the entry point enzyme to the phenylpropanoid pathway, it was hypothesized that PAL served as a rate-determining step. As a re sult, it was assumed that PAL plays a regulatory role in controlling biosynthesis of all phenyl propanoid compounds, including lignin. However, Anterola et al. (2002) indicated that during the profiling of loblolly pine ( P. taeda L.) PAL does not serve as a rate-limiting step. They further ar gued that there may be distinct phenylalanine pools that exist for specific purposes. That is there may be a coordinated and specific upregulation of upstream pathways [leading to phe nylalanine] for phenylpropanoid metabolism. If correct, this assumption would remove PAL as be ing the entry step, due to the existence of distinct and coordinated metabolic networks be ginning from, for example, the pentose phosphate and glycolysis pathways and e nding with the monolignols/lignins directly (Anterola and Lewis, 2002). In most plant species, PAL is encoded by a multigene family (Baucher et al., 1998) and it has been speculated that individu al genes have distinct metabolic roles such as flavonoids and lignins.

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17 Transgenic plants with modifi ed levels of PAL activity have provided opportunities to test hypotheses about the role of PAL in metabolism and plant development. Bate et al. (1994) analyzed phenylpropanoid metabolites in transgenic tobacco plants with decreasing amounts PAL activity and reported that lignin content is not greatly affected until PAL activity is reduced to 20% of wild-type levels. Anterola and Lewi s (2002) agreed with the previous result and concluded that transgenic plants with modified PAL levels result in reductions in lignin, but only if PAL levels have been reduced belo w half that of the control plants. Cinnamate 4-Hydroxylase Cinnam ate 4-hydroxylase (C4H) is a cyto chrome P-450-linked monooxygenase that catalyzes the hydroxylation of cinnamic acid to paracoumaric acid (Whetten and Sederoff, 1995). C4H is expressed in all tissues and upon exposure to light, wounding, and fungal infection (Bell-Lelong et al., 1997). However, expression only increases during the later stages of stem development (Raes et al., 2003). C4H exists in at least two forms depending upon the species, C4H-1 and C4H-1/C4H-2 (Anterol a and Lewis, 2002). C4H-1 is correlated with lignification (Lewis et al., 1999) and ot her phenylpropanoid pathway branch points, whereas the physiological role of C4H-2 still needs to be fully established. C4H cataly zes the addition of an oxygen atom obtained from molecular oxygen, with one oxygen atom added to the aromatic ring and the other reduced to water. C4H has been purified and characterized from several plant species (Fahrendorf and Dixon, 1993). C4H cDNAs have been expressed in yeast and the active enzyme has been recovered. Fahrendorf and Dixon (1993) reported that C4 H is able to couple effectively with yeast NADPH-cytochrome P-450 reductase and catalyze with high efficiency and capacity, the hydroxylation of cinnamate in microsomes from transformed yeast.

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18 4-Coumarate: Coenzyme A Ligase 4-Coum arate: coenzyme A ligase (4CL) catalyzes the formation of coenzyme A thioesters of cinnamic acids, p-coumaric aci d, caffeic acid, ferulic acid, 5hydroxyferulic acid, and sinapic acid, in the biosynthesis of a va riety of phenolic derivatives in cluding benzoic acids, condensed tannins, flavonoids and the cinnamyl alcohols (G ross, 1985). The high number of substrates could explain why there are many 4CL isoenzymes in most plants (Raes et al., 2003, Lewis et al., 1999). The isoforms typically have different substrate specificities and spatial/temporal expression patterns, which have suggested dist inct physiological roles (Anterola and Lewis, 2002). In Arabidopsis, At4CL1 and At4CL2 are belie ved to be involved in lignification, whereas At4CL3 is considered to function in flavonoid biosynthesis (Ehlting et al., 1999). Similarly, in aspen it was proposed that PtCL1 was specifica lly involved in lignin biosynthesis, whereas PtCL2 participated in flavonoid formation (Hu et al., 1998). Expression an alysis showed that 4CL genes are expressed in almo st all tissues investigated. 4CL down-regulation has been carried out only w ith isoforms considered to be involved in lignin biosynthesis using three different species: tobacco, Arabidopsis and aspen. Responses ranged from no visible phenotypic differences in Arabidopsis, to dwarfing in tobacco and enhanced growth in aspen (Anterola and Le wis, 2002). However, the effect of 4CL downregulation on overall lignin content was consis tent in all three speci es; 4CL down-regulation resulted in significant reductions in lignin content, but only af ter more than 60% reduction in 4CL activity (Anterola and Lewis, 2002). Hydroxycinnamoyl-Coenzyme A Shikimate/ Quinate Hyd roxycinnamoyltransferase Hoffman et al. (2003) showed that hydr oxycinnamoyl-coenzyme A shikimate/quinate hydroxycinnamoyltransferase (HCT) is an acyltransferase that uses pcoumaroyl-coenzyme A as

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19 an acyl donor and shikimic acid or quinic acid as acceptor, yielding the shikimate or quinate ester, respectively. The enzyme acts both upstrea m and downstream of the 3-hydroxylation step. HCT also catalyzes the reverse reaction whereby it forms caffeoyl-Co A from chlorogenate (5Ocaffeoyl quinate ester). When the HCT gene was silenced in Arab idopsis, it resulted in dwarf plants that showed a decrease in syringyl units and an increase in phydroxyphenyl units (Hoffmann, 2004). Expression analysis in Arabidopsis also showed that HCT is expressed in all tissues, but the strongest expression is in the inflorescence stem. Coumarate 3-Hydroxylase Coum arate 3-hydroxylase (C3H) is a cyto chrome P450-dependent monooxygenase (Franke et al., 2002, Schoch et al., 2001). Franke et al. (2002), showed that the Arabidopsis mutant reduced epidermal fluorescence (ref8) which has a defective C3H gene, accumulates pcoumarate esters in place of th e sinapoylmalate found in wild-type plants and has an extremely dwarf phenotype. In addition, the ref8 mutant also deposits a lignin primarily from pcoumaryl alcohol (H units), the lignin subuni t which is a minor component in the lignin of normal plants. Furthermore, the ref8 mutant deposits only minor amounts of G and S units (Franke et al., 2002). These data indicate that both the G and S pathways are blocked in the ref8 mutant. Therefore, the ref8 mutant demonstrates that elimination of C3H activity restricts car bon flow into the monolignol pathway, as well as growth and develo pmental processes. In addition, transcriptional profiling of P. taeda also showed that this enzyme was directly correlated with induction of monolignol biosynthesis in a rate-determi ning capacity (Anterola et al., 2002) Contrary to earlier repor ts which suggested that pcoumaric acid was the main substrate for C3H, Schoch et al. (2001) showed that the C3H enzyme is highly active towards pcoumaroyl quinate and pcoumaroyl shikimate. Thus, the name coumarate 3-hydroxylase is now a

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20 misnomer. Expression analysis sh owed that C3H is expressed in all tissues with the highest expression being detected in vascular tissu es of stems and roots (Raes et al., 2003). Caffeoyl-Coenzyme A O -Methyltransferase Caffeoyl-coenzym e A O -methyltransferase (CCoA-OMT) is distinct from caffeate O methyltransferase (COMT) and ha s been identified in connection with the defense response in several dicot plant species (Ku hnl et al., 1989). Ye et al. (199 4) reported that CCoA-OMT plays a role in methylation of both caffeoyl-coe nzyme A and 5-hydroxyferuloyl-coenzyme A during monolignol biosynthesis. CCoA-COMT is expressed in all tissues of Arabidopsis (Raes et al., 2003). Cinnamoyl-Coenzyme A Reductase Reduction of hydroxycinnam oyl-coenzyme A thioes ters to the corres ponding aldehydes is catalyzed by cinnamoyl-coenzyme A reductase (CCR) (Whetten and Sederoff, 1995). CCR plays a key role in lignin biosynthesis as the firs t committed step in th e production of monolignols from phenylpropanoid metabolites. Down-regulation of the AtCCR1 gene in Arabidopsis led to plants with a 50% decrease in li gnin content, shorter than wild-t ype plants, and with changes in lignin composition, with ferulic acid being depos ited in the cell wall (Goujon et al., 2003). Caffeate O -Methyltransferase Caffeate O-m ethyltransferase (COMT) has the predominant role of methylating 5hydroxyconiferaldehyde and 5-hydroxyconiferyl to sinapaldehyde and sinapyl alcohol, respectively (Humphreys et al., 1999). The meth ylation step limits th e reactivity of the 3hydroxyl group, thereby reducing the number of sites on the aromatic ring that can form bonds to other monolignol molecules during polymerization. Vignols et al. (1995) s howed that the maize bm 3 mutant was a result of two independent mutati ons that resulted in stru ctural changes in the COMT gene. Down regulation of COMT in maize using the anti-sense method led to a decrease

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21 in lignin content, decrease in syringyl units, lowe r p-coumaric acid content and the occurrence of unusual 5-hydroxyguaiacyl units (Pi quemal et al., 2002). The same method in tall fescue grass, Festuca arundinacea, resulted in almost similar resu lts to those in maize except that there was no reduction in p-coumaryl acid content and the in corporation of 5-hydroxyguaiacyl units (Chen et al., 2004). Furthermore, it was shown that the prefe rred substrates for the tall fescue recombinant COMT are 5-hydroxyferulic acid and caffeoyl al dehyde in contrast to maize COMT, which preferred 5-hydroxyconiferaldehyde and 5-hydroxyconiferyl (Piquemal et al., 2002). In general, however, it has been observed that down-regulation of COMT results in reduced S/G ratio mainly due to inhibition of S ligni n biosynthesis (Guo et al., 2001a). Ferulate 5-Hydroxylase Ferulate 5-ydroxylase (F 5H), correctly name d coniferaldehyde 5-hydroxylase (Cald 5-H) is a cytochrome P-450-linked monooxygenase that catalyzes the hydroxylati on of ferulate to 5hydroxyferulate. A mutation in the Ar abidopsis gene encoding F5H ( fah-1) was identified, and mutant plants were shown to lack sinapate-d erived residues in lignin (Chapple et al., 1992). Consequently the lignin in fah-1 mutant Arabidopsis resembles a gymnosperm type of lignin composed of guaiacyl units derived from conifery l alcohol. Isolation of the gene encoding F5H and expression of the protein product in a heterelogous system will provide material for more intensive characteriza tion of this little studied enzyme. In addition, F5H has been implicated in the differences in lignin composition between an giosperms and gymnosperms. Its activity is necessary for the hydroxylation of coniferaldehyde, an essential st ep in the formation of sinapyl alcohol. Whetten and Sederoff ( 1995) hypothesized that F5H is pr esent in all plants except gymnosperms (Baucher et al., 1998) at varying le vels and that low levels of F5H activity are sufficient to allow synthesis of significant le vels of sinapyl alcohol and siringyl lignin.

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22 Cinnamyl Alcohol Dehydrogenase Cinnam yl alcohol dehydrogenase (C AD) catalyzes the reduction of hydroxycinnamaldehydes (cinnamyl aldehydes) to hydroxycinnamyl alcohols, the last stage in monolignol biosynthesis (Whetten and Sederoff, 1995). CAD has been considered to be an indicator of lignin biosynthesis because of its speci fic role at the end of the monolignol biosynthetic pathway. The maize bm1 mutant has reduced CAD tran script and protein levels (Halpin et al., 1998). The mutation results in redu ced lignin content and altered structure of the lignin polymer. Reduction of CAD activity in bm1 plants causes incorporation of cinnamyl aldehydes in the growing li gnin polymer (Halpin et al ., 1998). The gene encoding CAD has been a target for modification of lignin content in plants through ge netic engineering. Transformed tobacco plants with an antisense CAD constr uct show varying degrees of reduction in CAD activity and modification of phe nolic products (Halpin et al., 1994). Two lines of transgenic plants were investigated: one w ith 75% of wild-type CAD and the other with 20% of wild type CAD activity. The former had changes in mono lignol composition while the latter did not. The compositional changes included increases in the ratio of aldehyde -to-alcohol-derived products, with a preferential effect on syringyl subunits. Sinapyl Alcohol Dehydrogenase Sinapyl alcohol dehydrogenase (SA D) is a member of the NADP(H)-dependent dehydrogenase family that catalyzes the last reductive step in the formation of monolignols (Bomati et al., 2005). Although SAD and classical cinnamyl alcohol dehydrogenases (CADs) catalyze the same reaction and share some sequence identity, th e active site topology of SAD is strikingly different from that pr edicted for classical CADs (Li et al., 2001).

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23 Lignin Polymerization The process by which the structure of lignin is determ ined is not clea rly understood. There are two competing hypotheses to describe this pro cess. The traditional hypot hesis is that lignin is a polymer built from the more-or-less random co upling of the three monolignol units into the growing polymer (Hatfield and Ralph, 1997). Under this hypothesis lignin a ssembly occurs after passage of monolignol monomers into the cell wall, with polymer formation only requiring oxidative enzymes, namely peroxidase and lacca se, to generate the co rresponding free radicals, which will then undergo random coupling (Adler, 1977). Lewis and Davin (1998) put forward an alternative hypothesis based on th e discovery of dirigent protei ns. Dirigent proteins (Latin: dirigere to align or guide) are protei ns which bind and orientate the coniferyl alcohol-derived free radicals which then undergo stereoselectiv e coupling to lignans. Davin and Lewis (1998) question the random coupling model based on a prem ise that the formation of approximately 20 30% of all plant organic matter should not be left to chance. They go further and point out that the random coupling does not explain many bi ological aspects of li gnification, including targeting of specific monolignols into discrete regions within the lignifying cell wall and the observed regiospecificity in coupling resulti ng in approximately 50 -7 0% of all inter-unit linkages being O -4-bonded. Therefore, Davin and Lewis (1998) concluded that some coupling specificity was being exercised in planta which the dirigent protein model could help explain. This conclusion is based on severa l reports on the discovery of di rigent proteins (Ralph et al., 2006) as well as reports claiming evidence for the control of O -4 coupling (Lourith et al., 2005). Davin and Lewis (2005) also cited unpublished results whic h reportedly show that over expressing dirigent pr oteins resulted in significant increased levels of lignin constituents. Despite a steady increase in reports of di rigent proteins discovery in a number of species (Chen and Sarkanen, 2003), there has been no evidence which ch aracterizes at the molecular level, the basis

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24 of the various (dirigent) monomer-binding sites for both ligni n and lignin formation and on obtaining the primary sequences of the lignins being generated (Davin and Lewis, 2005). If lignin biosynthesis was under the control of the dirigent proteins, there has been, however, no explanation on the flexibility shown by plants under different conditions to allow monomer substitution and significant variat ion in final lignin structure. For example, COMT-deficient maize mutants do not produce syringyl lignin and instead, they incorporat e a novel structure (5hydroxyguaiacyl units) into the growing lig nin polymer (Piquemal et al., 2002). Lignin Mutants Analysis of mutants has been em ployed successf ully to uncover some of the mechanisms involved in the regulation of lignification (Rogers and Campbell, 2004). Many of the lignin mutants that were initially identified were impair ed in their ability to synthesize normal lignin, rather than in the control of its deposition. Rece ntly, mutant analysis has begun to reveal the genes that are necessary and sufficient to contro l the timing and localization of lignin deposition (Rogers and Campbell, 2004). Such genes show a more direct link between the control of cell differentiation and lignin biosynthesis. Lignin mutants are also importa nt for studying the effects that plants with altered lignin content and/or subunit composition have on the e nvironment. To reduce the concentration of CO2 in the atmosphere, soil carbon (C) sequestration is one of the methods that can be used. This is because plants with modified lignin s ub-unit composition and lignin content may have modified decomposition processes that will aff ect carbon cycling. White et al. (2007) compared C mineralization rates between sorghum brown midrib mutant (bmr) plants and their normal counterparts. They concluded that the bmr mutants had a faster rate of C mineralization compared to the normal isolines. Webster et al (2005) also compared tr ansgenic tobacco plants with antisense CAD, COMT and CCR genes and reached the same conclusion. This shows that

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25 alterations in lignin content and sub-unit compos ition leads to changes in the decomposition rates of plant residues. However, more field studie s are required to evaluate how widespread production of plants with altered lignin content af fects the ecology. Arabidopsis Ref Muta nts Arabidopsis and other members of the Brassicaceae accumulate hydroxycinnamic acid esters that are fluorescent when exposed to UV light (Ruegger and Chapple, 2001). These compounds include sinapoylmalate, a leaf-specific ester, sinapoylcholine, a seed-specific ester and a common intermediate ester si napoylglucose. Therefore, mutant s that are defective in leaf sinapate ester biosynthesis can be readily id entified since the fluorescent nature of the compounds can be visualized in vivo (Chapple et al., 1992). As a resu lt, mutations that lead to quantitative or qualitative changes in sinapate este r content in Arabidopsis either decrease the fluorescence, or reveal the chlorophyll fluoresce nce that makes the sinapate ester in other mutants appear under a partic ular color under UV light. Representatives of one class of mutants, reduced epidermal fluorescence (ref), display reductions in the blue-green fluorescence of their cotyledons and/or leaves suggesting the accumulation of lower levels of sinapoylmalate than the wild type (Ruegger and Chapple, 2001). All the ref mutants display a UV phenotype that is inte rmediate between the wild type and the fah1-2 null mutant. Bright trichomes (brt), a second class of mutants, also show less fluorescence when compared to the wild type, but have tr ichomes that are hyper-fl uorescent under UV light. Analysis of three week old Arabidopsis rose ttes by high performance liquid chromatography (HPLC) showed that all ref mutants contained less sinapoylmalate than wild type plants. When compared to the ref mutations, the brt1 mutations led to modest reductions in sinapoylmalate content.

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26 Maize Brown Midrib Mut ants Variation in lignin characteristics was first observed in maize brown midrib (bm) mutants by Kuc and Nelson (1964). The brown midrib mutants of maize show a reddish-brown pigmentation of the leaf midrib and stalk pith. Th is pigment is associated with tissues that are typically lignified and may result from accumu lation of an unknown phenolic derivative where normal lignin biosynthesis is bloc ked (Vignols et al., 1995). In mai ze, four spontaneous mutants ( bm1, bm2, bm3 and bm4 ) corresponding to independent genetic loci have been identified (Jorgensen, 1931; Kuc and Nelson, 1964; Kuc et al., 1968). These mutants have low lignin content (Kuc et al., 1968). The bm1 mutant gene is closely associated w ith, and possibly iden tical to, the gene encoding cinnamyl alcohol dehydrogenase (CAD). Halpin et al. (1998) determined CAD activity in stem tissue (second internode) of wild-type and bm1 plants at two-week intervals throughout development in three different inbred backgrounds. They showed that in all bm1 genotypes, CAD activity was significantly reduced at every developmental stage and in all lignified tissues. Guillaumie et al (2007) performed an in-depth transcriptome analysis of the gene families encoding enzymes of the lignin biosynthetic pathway. They not only confirmed that the bm1 mutant has reduced CAD expression, but when compared to other known bm mutants, it had the highest number of differentially expressed genes. The bm1 mutant had the following under expressed genes: CAD/SAD and several regulato ry genes including MYB, ARGONAUTE (ortholog of Arabidopsis ARGONAUTE) and HDZip (Guillaumie et al., 2007). Using acid phloroglucinol, a reagent used to de tect cinnamyl aldehydes and lignin, sections of midribs and stems were stained. Wild-type stems showed little staining, whereas bm1 stems showed strong staining (Halpin et al., 1998). The results sugg est an increased content of

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27 cinnamyl aldehydes in bm1 lignin. Moreover, Klason lignin analysis of bm1 plants showed a 20% reduction in total lignin content. The profile of under expressed genes in bm2 seedlings is nearly similar to that of bm1 (Guillaumie et al., 2007). The genes fall unde r several functional categories including phenylpropanoid metabolism, transport and traffi cking, transcription factors and regulatory genes. In addition, bm2 has a 15-25% reduction in lignin cont ent and its mature plants have a 60% decrease in ferulic acid (FA) levels (Barriere et al., 2004). On the other hand, Marita et al. (2003) reported a different conclusion when their study showed that younger bm2 plants had elevated levels of etherified FA than mature plants. There is, however, no information on the genes that are affected in the bm2 and bm4 mutants. Maize bm3 is severely deficient in COMT activit y, with only 10% of the activity found in normal plants (Halpin et al., 1998) and a lignin co ntent that is reduced by 25-40% (Barriere et al., 2004). Vignols et al. (1995) characterized the first gene encoding a lignin-related OMT in maize. Their results showed that the bm3 gene encodes a bi-functional enzyme that is able to methylate both caffeoyl coenzyme A and 5-hydr oxyconiferaldehyde to produce feruloyl coenzyme A and sinapaldehyde, respectively. Gu illaumie et al. (2007) performed differential expression studies in young bm3 mutant plants and their normal counterparts that confirmed the under-expression of the COMT gene. To compensate for the modified expression of COMT the differential expression st udies showed that two OMT s and two cytochrome P450 genes were significantly over-express ed. The lignin-related COMT gene is expressed in tissues that are undergoing lignification and these include elongating roots and va scular bundles in leaves (Collazo et al., 1992).

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28 Sorghum Brown Midrib Mutants In sorghum ( Sorghum bicolor (L.) Moench), 19 independently occurring bmr mutants were identified in segregating progenies of chemically treated seeds of two lines after treatment with diethyl sulfate (DES) (Porter et al., 1978). The resultant brown midrib plants were identified by the characteristic brown pigmentation (by the 4-6 leaf stage) present in the mid leaf of the stem as well as in the stem, pith, and immature panicle branches of mutant plants. There was variation among mutants in terms of lignin concentration, but there was no consistent reduction among the collection of mutants. This suggested the presence of several different bmr genes. Of the 19 mutants, genotypes designated bmr6, bmr12 and bmr18 were selected for further evaluation. In the bmr6 mutant, the CAD and COMT activities we re shown to be depressed (Bucholtz et al., 1980). However, the struct ural modifications of the lignin corresponded only to a reduction in CAD activity with a higher amount of cinnamaldehydes. The bmr6 mutant is thus, quite similar to that of bm1 although no cinnamaldehydes were detected in the latter. Using a candidate-gene-approach, Verme rris and Bout (2003), proved that the bmr12, bmr18 and bmr26 mutations are mutant alleles of the ge ne encoding COMT. In all three mutants there was a reduction in syri ngyl residues and cell wall bound pcoumaric acid. The point mutations in the three cases resulted in a premature stop codon, which resulted in reduced expression levels and reduced COMT activity. Thes e data indicate that these mutants are similar to the bm3 mutants. An increase in feru lic acid was observed in both bmr12 and bmr18. Allelism tests by Bittinger et al (1981) indicated that bmr12 and bmr18 are allelic and different from bmr6. Pearl Millet Brown Midrib Mutants Pearl millet ( Pennisetum glaucum (L.) R.Br.) is used extensiv ely as forage for livestock. Based on the negative relationship between ligni n and digestibility, redu cing lignin content is

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29 one way of increasing digestibility of pearl mille t. Cherney et al. (1988) chemically induced a brown midrib mutation in pearl millet from two inbred lines using ethyl methyl sulfonate (EMS) or diethyl sulfate (DES). A naturally occurring brown midrib mutant in pearl millet was also identified at the Coastal Plain Experiment Station in Tifton Georgia (Degenhart, 1991). This bmr was originally called orange node and was similar to the brown midrib mutant developed by Cherney et al. (1988) using EMS. Lignin Modification via Transgenic Approaches Transgenic plants show gross alterations in lignin am ount, composition, primary structure and on phenotypic effects caused by altering the expression of a si ngle gene (Boerjan et al., 2003). The cell wall has a major impact on th e utilization of plants by mankind, and has therefore, become a major targ et for genetic engineering (Gri ma-Pettenati and Goffner, 1999). Lignin genetic engineering has become an activ e area of research which has been stimulated within recent years by the characterization of important genes controlling lignification. A significant number of transformed plants exhibiting quantitative cha nges in their lignins, but also qualitative changes have been obtained using pa rtial sense or antisense constructs corresponding to several enzymes. However, there are drawba cks that are associated with this route. An important aspect of lignin manipulation lies in the potential di sturbance of plant development such that reduction or modification of the ligni n content of plant cell wa lls may potentially exert pleiotropic effects on plant func tions through changes in the st rength of plant organs, sap conduction through the phloem, or permeability of cell wall barriers (Boudet, 2000). Ralph et al. (2005) reported that the down-regulation of C3H gene in alfalfa resulted in an increase of p-hydroxyphenyl (H) units in the plants by up to 65% compared to wild-type levels of 1%, and a decrease of G units. C3H lines with 5% residual activity showed delayed flowering activity by 10-20 days and the plants were genera lly smaller, and grew more slowly than wild-

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30 type controls. The most severely down-regulated C3H line was G-and-S depleted, but was still viable, albeit with stunted growth, suggesting that plants without access to the two primary monolignols could be viable (R alph et al., 2006). On the othe r hand, lines with 20% residual activity were of almost normal size and showed delayed flowering by 1-2 days. In contrast, Franke et al. (2002) sh owed that Arabidopsis ref8 mutant lacking C3H activity produces lignin at 100% H level and is totally devoid of S and G units. Even though the ref8 mutant is viable, it has a dwarf phenotype, has collapsed xylem vessel elemen ts is susceptible to fungal attack, and does not flower, compared to the wild-type control. In transgenic Arabidopsis (fah1) mutant plants that over expressed F5H ectopically under the control of the C4H promoter, a novel lignin wa s generated, composed almost completely of S units (Meyer et al., 1996). This result impli cates F5H in determining the lignin monomer composition. Therefore, modifying F5H (Cald5H) a nd altering the relative amount of S units may offer opportunities for engineering lignin qu ality in hardwoods and softwoods (Baucher, 2003). A combinatorial down-regulation of 4CL along with an over expression of Cald5H has been achieved by co-transformation of two Agrobacterium strains in aspen (Li et al., 2003). This resulted in an additive indepe ndent transformation, particularly a 52% reduction in lignin content associated with an increase in cellulose and a hi gher S/G ratio. The result suggests that transgene stacking allows several beneficial traits to be improved in a single transformation (Li et al., 2003). For functional analysis in Arabidopsis, acyltransferase (HCT) was silenced by RNAmediated posttranscriptional gene silencing (Hoffmann et al., 2004). The silenced plant was severely dwarfed, had inhibited root growth, and had a 15% decrease in lignin accumulation. Results on down regulation of CCR in tobacco in dicate that the transgenic plants have lower

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31 lignin content and a modified lignin composition. In fact, the transgenic pl ants with the lowest CCR activity showed the strongest reduction in lignin content indicating that CCR is a rate limiting step in lignin biosynthesis (Lee, 1997). Piquemal (1998) obtained transgenic tobacco plants down-regulated in CCR ac tivity via ectopic expression of homologous antisense genes which resulted in a 53% decrease in lignin content and S and G units. The line with the most severely depressed CCR activity ex hibited altered development in the form of reduced size, abnormal morphology of the leaves and collapse d vessels. Similarly, Goujon et al. (2003) reported that down regulation of the AtCCR1 gene in Arabidopsis thaliana resulted in a 50% decrease in lignin accompanied by changes in lignin composition a nd structure. The transgenic plants also exhibited phenotypic alterations consisting of limited height and collapsing of the xylem vessels. These phenotypic modifications are likely direct consequences of the dramatic lignin depletion in the cell walls. Lignin is es sential for maintenance of xylem vessel integrity and it is, therefore, likely that the collapse of the xylem vessels may result in the dysfunction of xylem sap transport. These perturbations may affect water supply and consequently normal growth and plant morphology (Piquemal et al., 1998). Decreases in lignin content through the mani pulation of different lignin biosynthetic pathway genes, do not always lead to developm ental oddities. For exampl e, down regulation of one of the major enzymes involved in lignin bi osynthesis, 4-coumarate: coenzyme A ligase ( Pt CL1) in transgenic aspen ( Populus tremuloides), resulted in a 45% decrease in lignin with a compensation of 15% increase in cellulose, doubli ng the plant cellulose: lignin ratio without any change in lignin composition and without any harm to plant growth, devel opment, or structural integrity (Dean, 2005). This result indicates that lignin and cellulose deposition are regulated in a compensatory fashion and that a reduced car bon flow toward phenylpropanoid biosynthesis

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32 increases the availability of carbon for cellulose biosynthesis (Li et al., 2003). Similarly, COMT down regulation in alfalfa only ha d a moderate effect on overall es timated Klason lignin contents even at highly repressed levels (Guo et al., 2001 ). In the study, transformants were generated by expressing the full-length alfalfa COMT gene in the antisense orient ation. There was no report of any developmental abnormalities in the tran sgenic lines even though they had a low COMT activity of about 3 5 % of the wild-type and almost undetectable COMT transcripts and proteins. These results show that genetic engineering has yielded new insights into how the lignin biosynthetic pathway operates and demo nstrates that lignin can be improved. As shown by the previous examples, the data obtained by genetic engineering or by the analysis of mutants in the lignin biosynthesis pathwa y are very promising as they show that it is possible to engineer this pathway. However, more re search is still needed to improve the stability of sense/antisense constructs. Baucher et al. ( 1998) suggest large scale experiments to assess the effects of an alteration in the lignin content a nd lignin composition on the digestibility of forage crops and on pulping. Other characteristics such as calorific value, overall growth and the resistance against diseases have to be examined. Agro-Industrial Processes Affected by Cell Wall Composition The com position and structure of the cell wall has a dramatic impact on the technological value of raw materials. As a re sult, numerous strategies have been, and are being, developed to optimize the composition of plant cell walls for improved agro-industrial uses (Boudet, 2003). In addition to their critical role in normal plant health and develo pment, high lignin levels are problematic in the agro-industrial exploitation of various plant species. Lignin is considered an undesirable component in paper manufacture, and it has a negative impact on forage crop digestibility (Baucher et al., 1998) On the other hand, the high caloric values of lignin are an important source of energy if the mate rial is to be used for combustion.

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33 Ethanol Production Currently, most ethanol produced in the United States is deriv ed from maize kernels at a level of seven billion gallons per year (Sticklen, 2006). Although the fermentation technologies for such sugar and starch sources are well deve loped, they have a number of limits (Hamelinck, 2005). Maize kernels have a high value for food app lications, and the sugar yield of kernels per hectare is low when compared to the most abundant forms of sugar in nature: cellulose and hemicellulose. Lignocellulosic biomass holds tremendous promise as a feedstock for ethanol production due to its widespread availability and potential for high fuel yields (Brekke, 2005). Furthermore, lignocellulosic biomass is renewable and inexpensive. Severa l potential sources for cellulosic ethanol include corn stover, cereal st raws, sugarcane bagasse, sawdust, paper pulp, and switch grass (an energy crop). A ll these characteristics help make the case for the USA to develop alternate energy sources reduce the nations dependency on foreign oil, and increase the use of excess agricultural feedstock for biofuel. However, converting cellulosic biomass to et hanol requires first hydrolyzing the biomass into its constitutive sugars. One of the factors contributing to this bottleneck is the presence of lignin and hemicellulose. The combination of hemicellulose and lignin provides a protective sheath around the cellulose (Figur e 1-1), which must be modified or removed before efficient hydrolysis of cellulose can occur (Hamelinck, 2005). Thus, to economically hydrolyze cellulose, more advanced technologies are re quired more than for the proce ssing of sugar or starch crops. Hydrolysis is most efficiently done enzymati cally. However, enzymes are very expensive and the ones currently available have low activity. Over the past few years, the cost of cellulose enzymes to convert cellulose to glucose has been the greatest technical ba rrier to cost-effective production of cellulosic ethanol. Therefore, the challenge for adoption of stover as a source of ethanol remains that of converti ng lignocellulosic biomass to ethanol on a commercial scale. In

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34 addition, researchers have expresse d disappointment at the lack of specially tailored crops or the slow breeding programs for such crops. Recently, however, several companies have identified a range of new enzymes with enhanced activities to boost suga r yields, thus reducing the cost of enzymes for making ethanol from corn stover 30-fold, from $5 per gall on in 2001 to 10 cents per gallon in 2005 (Biotechnology Industry Organization, 2006). More importantly, recent genetic engineering advances could reduce biomass conversion cost s by developing crop vari eties with less lignin (Sticklen, 2006). As an illustration, down-regulati on of COMT in maize and alfalfa led to lower and modified lignin and consequently enhanced digestibility (Piquemal, 2002; Guo, 2001). Chen and Dixon (2007) also reported that transgenic alfalfa lines in dependently down regulated in each of the six lignin biosynthetic enzymes yielded more sugar compared to wild-type plants. Paper Production Pulp and paper production require the use of costly, energy consum ing, and often polluting treatments to separate lignins from cellulo se (Boudet, 2000). Mechan ical production gives a particularly high pulp yield (90 to 95%) but conserves all wood components (Reid, 1991). However, paper made via mechanical pulping has a low strength and turns yellow on exposure to sunlight due to photochemical oxidation of ligni n (Baucher et al., 1998). Chemical pulping on the other hand involves the chemical hydrolysis and solubilization of lignin using acid or alkaline in which lignin is degraded at high temperatures and extreme pH Alkaline pulping (kraft) is the most commonly utilized method worldwide, but it results in a lower pulp yield (40 50 %) compared with mechanical pulping. In addition, kraft pulping releases volatile and toxic mercaptans which pollute the atmosphere. Moreover a subsequent bleaching step with chlorine causes the formation of highly toxic and chlo rinated organic compounds Genetic engineering can thus play an important role in reducing the use of chemicals for pulping and bleaching by

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35 decreasing the lignin amount or by modifying th e lignin composition in trees to substantial industrial and envir onmental benefits. Forage Plant ce ll walls are the majo r source of dietary fiber fo r animals (Buxton and Redfearn, 1997). However, several chemical and structural features have been id entified that may limit fiber digestibility in most forage crops. Ligni n has been prominently mentioned and interferes with microbial degradation of fiber polysaccharid es by acting as a physical barrier. In addition, the cross-linking of lignin to polysaccharides by ferulate bridges al so contributes to the inhibition of grass fiber digesti on (Buxton and Redfearn, 1997). Lignin is necessary to provide mechanical support for the plant and to impart strength and rigidity to plant cell walls. Als o, lignin provides resistance to di seases, insects, pathogens and other biotic and abiotic stress es. The brown midrib plants w ith reduced lignin produce reduced forage yield, compared with the normal phenot ype, by an average of 15% for the first harvest and 30% for the second harvest (Cas ler et al., 2003). It is suggeste d that the reduced forage yield was due partly to reduced ground cover resulting from reduced tillering capability of the brown midrib lines. However, despite the agronomic performance limitations of the brown midrib plants, Casler et al. (2003) repo rted that brown midrib plants increas ed relative feed value by seven to 23% and raised predicted milk production by 19 to 50%. The brown midrib plants are more palatable than wild-type plants ba sed on a higher dry matter intake for bmr silage (Stallings et al., 1982). Higher intake may have been related to increased digestibility of dry matter and the sweet taste of the bmr plants. In conclusion, since the bmr genotypes have lower fiber and lignin values, intake and digestibility by animals are higher, leading to better animal performance (Cherney et al., 1991).

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36 Plant Pigmentation Pigm ents are chemical compounds that abso rb light in the visible region of the electromagnetic spectrum (Delgado-Valgas, 2000). Plant pigmentation is generated by the electronic structure of the pigmen t interacting with sunlight to alter the wavelengths that are either transmitted or reflected by the plant tissue (Davies, 2004). Pigments are classified based on their structural characteristics. Carotenoids Carotenoids are com pounds comprised of eight isoprenoid units (i p) (Delgado-Valgas, 2000). They can be considered as lycopene (C40H56) derivatives that involve: (i) hydrogenation, (ii) dehydrogenation, (iii) cyclization, (iv) oxygen insertion, (v) doubl e bond migration, (vi) methyl migration, (vii) chain el ongation, (viii) chain shortening. In general, carotenoids are classified by their chemical structures as: carotenes that are consti tuted by carbon and hydrogen; oxycarotenoids or xanthophylls that have carbon, hydrogen, and, additionally oxygen. Carotenoids main functions are to provide photoprotection during photosynthesis and to serve as precursors for the biosynthesis of the phytohormone abscisic ac id (ABA) and vitamin A biosynthesis (Grotewold, 2006). Biosynthesis takes place in plastids where isopentynyl diphosphate provides the five-carbon building block for carotenoids. As a result of the various important functions that carotenoids play, most of the enzymes in the carotenoid biosynthe tic pathway have been identified. Because of the identification of biosynthetic genes for several plant pigment pathways, it has been possible for genetic modification approaches to be used to alter pigmen t production in transgenic plants. Such metabolic engineering experiment s have resulted in stable tran sgenic plants with improved nutritional quality, increased abil ity to synthesize high value carotenoids and improved tolerance to abiotic stresses. Phytoene synthase is the first committed step in the carotenoid biosynthetic

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37 pathway and is, thus, considered to be a regulatory point. As a result, several constitutive over expression approaches have been targeted at th is gene. Perhaps the best known achievement to date is golden rice (Datta et al ., 2003). By using the rice-seed glutein promoter (Gt-1 P) to overexpress the phytoene synthase gene and the cauliflower mosaic virus 35S promoter (CaMV35S) to control the expression of the lycopene -cyclase ( lcy ) and phytoene desaturase ( crtl) genes. Datta et al. (2003) generated yellow-colored ri ce grains that contai ned high levels of -carotene. Shewmaker et al. (1999) ove r-expressed a bacterial phytoene synthase gene in rapeseed ( Brassica napus) resulting in orange embryos and mature seed that contained 50-fold increase in carotenoids. Similarly, constitutive expression of th e same enzyme in tomato led to 1.5 2-fold increase in carotenoids in tomatoes (Fray et al., 1995). However, over expression of phytoene synthase in other species did not always lead to dramatic increases in carotenoid level. These differences may be due to the source of the phytoene synthase (plant or bacterial), the tissue where expression is targeted (embryo versus endosperm versus vegetative), and/or the photosynthetic capability of the tissue, i.e green versus white (Shewmaker et al., 1999). In contrast, tomato plants transformed with a copy of the fruit-expressed phytoene synthase cDNA under the control of the CaMV 35S promoter showed ectopic pr oduction of carotenoids and stunted growth (Fray et al., 1995). The dwarf plants also showed a 30-fold reduction in levels of gibberellins A1 (GA1) but normal growth was restored by exogenous application of GA3. This can be explained by the fact that geranyl geranyl diphosphate (GGDP), a substrate for phytoene synthase, is a precursor to three diffe rent major pathways of plant growth regulator s: cytokinins, GAs and abscisic acid (ABA). Thus, the dwarf phe notypes are a result of altered flux through the isoprenoid pathway, with the high levels of phytoene being generate d at the expense of ent kaurene synthesis, therefore resulting in reduced levels of GAs (Fray et al., 1995).

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38 Mutant analysis has also provided much in formation regarding plant pigment biology. One interesting mutation is the cauliflower ( Brassica oleracea L. var botrytis ) Or gene. A spontaneous single-locus Or gene mutation causes a high level accumulation of -carotene in tissues where it is normally repressed. As a result of the mutation, the white edible curd is turned orange (Crisp et al., 1975). Flavonoids Flavonoids have a 15-carbon base structure that is m ade up of two phenyl rings (A and B rings) connected to a three carbon bridge that usually forms a third phenyl ring (C-ring) (Schwinn and Davies, 2004). There are more than 4500 different representatives of flavonoids known with various classes determined by the degr ee of oxidation of the C-ring (Buchanan et al., 2002; Schwinn and Davies, 2004). Despite the similar ity in structure, only some flavonoids have the ability to absorb light in the visible re gion of the spectrum and are thus pigments. Flavonoids have been demonstrated to perform a variety of functions in plants: attracting pollinators, conferring resistance to natural enem ies, facilitating interaction with symbionts, protection from ultra-vi olet light (Bieza and Lois, 2001), re gulating hormones, mediation of pollen-stigma interactions, am eliorating drought stress and ame lioration of adverse effects of heat stress on fertilization and early seed ma turation (Coberly and Rausher, 2003; Shirley, 1996; Warren and McKenzie, 2001). Even though carotenoids play the predominan t role in yellow pigmentation, flavonoids are responsible for this color in some instances (Schwinn and Da vies, 2004). The yellow pigments are the chalcones, aurones and some flavonol s. Chopra et al. (2003) characterized an Unstable factor for orange1 (Ufo1), a dominant allele-specific modifier of expression of the maize pericarp color1 (p1) gene. The p1 gene encodes a Myb-homologous transcriptional activator of genes required for biosynthesis of red phlobaphene s. The plants have red pigmented pericarp and

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39 an intense cob color caused by accumulation of phlobaphenes. Phlobaphenes are one of two major groups of flavonoid pigments, the other bei ng anthocyanins. The latter are water soluble compounds that occur in almost all vascul ar plants (Stobiecki and Kachlicki, 2006). Anthocyanins are the major cause of orange, red, purple and blue co lors of flowers. Most of the currently known flavonoids can be modified at one or several positions by methylation, acylation or glycosylation. These m odifications are believed to provide flavonoids with unique properties. For example flavonoids found on the surface of le aves or flowers are often methylated (Onyila gha and Grotewold, 2004). Pyrosequencing Pyrosequencing, also known as 454 sequenc ing, is a relatively new DNA sequencing technique that is based on the detection of a released pyrophosphate (PPi) during DNA synthesis (Ronaghi, 2001). Margulies et al. (2005) described a novel and high-throughput m ethod to sequence DNA. The entire genome is isolated, fragmented, ligated to adapters and then separated into single strands. The individual fr agments are attached to small beads under conditions that promote one fragment per bead before the beads are captured in an emulsion of PCR-reaction-mixture. PCR amplification occurs within each droplet cl onally amplifying the individual fragment resulting in beads carrying millions of co pies of a unique DNA template. This is a significant divergence from the Sanger-based sequencing technology which requires sub-cloning of fragments into vectors. The emulsion is broken, releasing the bead-attached fragments which will be subse quently denatured, and beads ca rrying single-stranded DNA clones are deposited into wells of a fibe r-optic slide. A mixture of smaller beads that carry immobilized ATP sulfurylase, luciferin and luciferase necessary to generate light from free pyrophosphate are also loaded into the wells. It is in these wells that sequencing-by-synthesis takes place. Each well has an opening through which sequencing reagents fl ow while the base of the well is in optical

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40 contact with a fiber optic cab le connected to a charge-coup led device (CCD) camera sensor. Each time a particular nucleotide is added ont o the growing chain, a pyrophosphate is released, which in turn reacts with ATP sulfurylase to fo rm ATP. The ATP then combines with luciferin and luciferase enzyme giving off a flash of light. In a cascade of enzymatic reactions visible light that is proportional to the number of incorporated nucleotides is generate d and is recorded by the CCD sensor. Pyrosequencing is high-throughput, has high sequen cing accuracy, and is fast and sensitive when dealing with small and microbial genomes (Wicker et al., 2006). Cheung et al. (2006) showed that 454 has the power of deep sequenc ing because it resulted in sequences that generated more gene hits, and revealed rare and novel transcripts. In addition, 454 sequencing can sequence large genomes 10 times faster comp ared to Sanger sequencing (Wicker et al., 2006). However, it has limitations of read length and capacity to sequence complex genomes that contain high amounts of repeti tive DNA. As a result, a whole-genome shotgun approach by 454 sequencing does not seem practical for multi-gigabase plant genomes. Instead, a bacterial artificial chromosome (BACby-BAC) approach still remains the best option for genomic sequencing in large and complex genomes.

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41 Figure 1-1. Schematic representation of the ligni fied secondary wall. In addition to cellulose, lignins and hemicelluloses, other cell wall constituents of minor abundance, including proteins and low-molecular weight phenolics, are not indicated on the figure. [Adapted from Boudet, A.M., Kajita, S ., Grima-Pettenati, J., Goffner, D., 2003. Lignins and lignocellulosics: a better control of synthesi s for new and improved uses. Trends Plant Sci. 8, 576-581]. Figure 1-2. Three monolignols that are incorporated into the li gnin polymer. [Adapted from Boudet, A.M., Kajita, S., Grima-Pettena ti, J., Goffner, D., 2003. Lignins and lignocellulosics: a bett er control of synthesis for new and improved uses. Trends Plant Sci. 8, 576-581].

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42 Figure 1-3. The lignin biosynthetic pathway. [Adapted from Boude t, A.M., Kajita, S., GrimaPettenati, J., Goffner, D., 2003. Lignins and lignocellulosics: a better control of synthesis for new and improved uses Trends Plant Sci. 8, 576-581].

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43 CHAPTER 2 SCREENING FOR ALTERED CELL WALL CO MPOSITION USING NIR SPEC TROSCOPY Background One of the goals of the NSF Plant Genom e pr oject Identification and characterization of cell wall mutants in maize and Arab idopsis using novel spectroscopies (http://cellwall.genomics.purdue.edu; Yong et al., 2005) is the generation of a large mutant population followed by identification of novel maize mutants with altered cell wall composition. The former was generated by the Uniform Mu population and the latter by the use of NIR spectroscopy (Yong et al., 2005). Identification of cell wall mutants will help in the understanding of roles played by various cell wall structural elements. Cell walls contribute to human and animal nutrition in several ways. Pr oducts of cell walls prov ide dietary fiber and calories that influence taste and texture of fruits and vegetables and they provide human clothing and shelter in the forms of fiber products. Ce ll walls of plants in the form of wood, lignocellulosic plant material provide fuel for cooking, transp ortation and electric power. Therefore, identification of muta nts is essential in understanding the roles of each structural element in cell walls. Introduction In an effort to create m utations in cell -wall-related genes, 2,200 F2 families (~ 40,000 plants) of Mu -tagged maize lines from the Uniform Mu population developed at the University of Florida, Gainesville, FL were planted at Purdue Universit y, West Lafayette, IN between 2002 and 2004. In order to screen a ll 40,000 plants, a method that enab led rapid screening of large numbers of plants was needed. Near infrared reflectance spec troscopy (NIRS), a high-throughput screening method, was an ideal option. Besides being high-throughput, NIRS requires little or no sample preparation, is non-destructive, has no ch emical usage and, therefore, does not generate

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44 chemical waste, is portable (can be used in the field), and operators do not require extensive training. NIRS is a vibrational spectrosc opic technique in which the re flectance (R) of light in the near-infrared range of the spectrum (800 2500 nm) is quantified (Seisler et al., 2002). Absorbance, which is defined as the logarithm of the inverse of R of light of a given wavelength confers information on the chemical composition of the sample. However, NIR only deals with organic molecules with water as an exception (Analytical Spectral Devices, 2005). Consequently, the types of materi als that can be analyzed with NIR are limited. Thus, metals such as silver, lead, and most inorganics, cannot absorb NIR light because they have electron transitions incapable of absorbing NIR wavele ngths. Various molecular arrangements in a sample will give that particular sample its ch aracteristics, the ability to absorb different wavelengths of light. So when a sample is an alyzed by NIR spectroscopy, what the instrument will be measuring is the number of photons at a particular wavelength (Analytical Spectral Devices, 2005). The number of photons that are ab sorbed is proportional to the abundance of a particular functional group present in the sample. The screening process, as mentioned above, generates large quantities of data, as is common for many techniques of modern analytical chemistry. For example, infrared, nuclear magnetic resonance (NMR), atomic absorption and UV/vis spectroscopies, chromatography and mass spectrometry, all generate la rge quantities of data (Kemsley, 1998). As a result, special processing and analytical methods are required to handle these complex data. What may appear as a single and simple spectrum can be composed of a large number of discrete values, from several hundred in a low resolution infrared spectrum to as ma ny as several hundred thousand in

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45 a high resolution NMR spectrum (Kemsley, 1998). There are, however, several statistical techniques that can deal w ith this kind of data, known collectively as chemometrics. The statistical software package Windows Di scriminant Analysis Software (Win-DAS) (Kemsley, 1998) was used in this study. Tw o common chemometric techniques were used: principal component analysis (P CA) and partial least squares (PLS) (Kemsley, 1998). For the study described in this report a FieldSpec Pro NIR spectrometer (Analytical Spectral Devices, Inc. Boulder, CO; www.asdi.com) was used to ac quire spectra from dried maize leaf samples. The resultant spectra were comprised of a larg e number of discrete data values, which are measurements of a series of spectral properties of each leaf sample. By definition, a spectrum reflects the absorbance at multiple frequencies or wavelengths, which makes the observations multivariate. Win-DAS will only handle spectral data that is ordered sequentially and equally spaced. That is variate values must be plotted sequentially and against a variate number (i.e. an integer 1, 2, 3, d). Data Compression As m entioned previously, data sets obtained from modern instruments like the FieldSpec Pro NIR spectrometer have a very large number of variates (d) that far exceed the number of observations (samples, n) and as a result such data sets are classified as hi gh-dimensional. High dimensional data are complex and c ontain inter-correlated variates. The n observations, which are continuous sets of variates that are closel y adjacent to each other, can be arranged into a matrix. These can be visualized as n points plotted on a set of d mutually perpendicular axes. Data compression techniques are used to transfor m these data into a new set of variates of manageable size. The transformed variates ar e known as scores. For example, data compression can reduce a set of 20 pairs of bi variate observations (a total 40 observations) plotted as spectral traces (value versus vari ate name) into 20 points which can be located on a

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46 plot of two axes in a two-dimensional coordinate system. Further reduction in complexity is obtained by rearranging the axes (rotation) until the 20 points are arranged in a manner that results in the maximum spread or variability (var iance). This reduction in complexity is helpful in data exploration, as it unmask s patterns or groups of observations which were not apparent in the original complex data set. The data co mpression methods used in Win-DAS are PCA and PLS with the latter specifically adapted for dealing with grouped data. Principal Component Analysis Principal component analysis (PCA) sim plif ies a data set by re ducing the number of variates needed to express releva nt information. It is a way of identifying patterns in data, and expressing the data in such a wa y as to highlight their similar ities and differences (Smith, 2002). This is achieved by rearranging the information in a data set by ordering th e scores in terms of decreasing variance. This means that PCA takes a cloud of data from, for example, hundred samples, each with about 1,000 variates, and rota te it such that maximum variability between different classes is clearly visible. Partial Least Squares PCA can effect a reduction in the complexity of a data set (K emsley, 1998). In addition, PCA is unable to produce scores which conform to a predetermined structure, i.e. it is not a modelling method. Therefore, in cases when there is an idea about the way in which the data might be structured, partial least square (PLS) is preferable. PLS is, how ever, solely used to analyze data sets that are believed to be stru ctured in groups. Therefore, in cases where PCA transformation does not yield info rmation that is efficiently compressed in the first few PC scores, PLS can be used.

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47 Materials and Methods Uniform Mu Population The Uniform Mu population carries active Robertsons Mutator transpo sons that can move from one locus to another within the genome to cause mutations. It was created by introgression of active Mutator and the bronze1 Mu -induced mutable9 (bz1-mum9) gene (Brown and Sundaresan, 1992) to a standard color-convert ed W22 inbred line which simplifies the identification of parental transposon in sertions (McCarty et al., 2005). This Mu population was designed to address specific cons traints associated with high-c opy transposons. These include (i) high mutagenic activity in a homogenous inbred; (ii) gene tic control of Mu activity for suppression of Mu transposition prior to molecular analysis; (iii) screening and removal of parental seed mutations to maximize independence of seed mutation; and (iv) ability to implement high-throughput molecular analyses of high-copy transposon insertions based on Mu TAIL (Settles et al., 2004; McCarty et al., 2005). Approximately 40,000 plants were grown at Purdue University, West Lafayette, IN between the summers of 2002 and 2004. To accommoda te variation in the field as well as variation related to the time of day, W22 controls were plante d along the edges and through the middle of the field. Leaf samples were collected from a field of maize plan ts that were bar-coded when they were eight weeks old. An eight centimeter section of the central part of the fifth leaf blade from the bottom was harvested. The leaf sa mples along with the barcode were collected in a glassine envelope (#5) and dried at 50 C in a drier for a week and subsequently stored at room temperature. One day before spectral acquis ition, leaf samples were re-dried overnight to remove any moisture absorbed during storage. Spectral acquisition was a two-pe rson job: one person arranged the leaves on a tray while the other acquired the spectra in a custom-made structure

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48 covered by a dark cloth to prevent light pe netration. A FieldSpec Pro NIR spectrometer (Analytical Spectral Devi ces, Inc. Boulder, CO; www.asdi.com ) was used to acquire spectra. From a handheld probe, light was emitted and directed through a leaf sample sandwiched between a piece of glass and a GoreTex disk ( www.gore-tex.com ). The GoreTex disk is a white disk that serv es as the white reference (100 % reflectance). The gla ss, disk and probe were kept clean by periodically clean ing them with methanol. The RS3 (Analytical Spectral Devices, Inc. Boulder, CO; www.asdi.com) program was used for acquisition. Following acquisition, the ViewSpec program (Analytical Spectr al Devices, Inc. Boulder, CO; www.asdi.com ) was used to export the data into one JCAMPDX file (Analytical Spectral Devices, Inc. Boulder, CO; www.asdi.com). Analysis of the data was ulti mately performed using the WinDAS program (Kemsley, 1988) after the .dx files were converted to .txt format using custom-designed software (Kemsley, 1988 and Vermerris et al., 2008). After the NIR data were imported into Wi nDAS they were visually inspected, and aberrant-looking spectra were deleted. The spect ra were then truncated to the 1000 2400 nm range, excluding variation in reflectance of visi ble light. The spectra were baseline-corrected (reflectance at 1000 and 2400 nm set to zero) and then the spectra were area normalized. Baseline correction removes linear shifts in the baseline that could be caused, for example, by instrumental drift during the course of data acquisition (Kemsley, 1998). Normalization corrects for variation in signal strength due to physical effects, such as variation in leaf size and light leaks between the glass surface a nd contact probe. After data fo rmatting, the spectra were saved in WinDAS format (.wdd file extension) and subjected to statistical analysis. Novel Brown Midrib Mutant A novel brown midrib mutant was co mpared to the wild -type control using NIR (Figure 21 and Figure 2-2). Sixty-seven bm mutant leaf samples and 39 w ild-type samples were compared

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49 for analysis. Spectra were analyzed as describe d above. Any contrasts in their spectra can help identify potential chemical differences leading to the chemical basis of the mutation, since specific functional group(s) are associated w ith each particular change in absorbance. Class Modelling Spectra of putative m utants (putants) were compared to spectra of W22 controls that were grown in the same area of the field. The W22 spectra were used to define a class. The spectra of the putants were tested for fit within the cl ass, and outliers were reported. Based on the assumption that the majority of the mutations would be segregating in a Mendelian recessive manner, we expected at least tw o out of 15-20 spectra to be diff erent from the W22 controls but similar to each other. Ideally, outlier spectra would consistently and tightly cluster together. The first spectral acquisition was pe rformed by a team of people taki ng turns. However, since the spectral acquisition process turned out to be sensitive to individual operators, two individuals then independently re-acquired the spectra from all the rows that had putative mutants. Data analysis was then redone on the new set of spect ra. Only the samples that were consistently being detected by the two individuals as outlier s were selected for the generation of homozygous mutants. Results A total of 39 cell wall mutants were identified. Seeds from these mutants were planted and the plants were selfed to gene rate homozygous plants. Once at le ast five individuals representing a mutant were identified, their spectra were comp ared to those of the W 22 controls to identify the chemical basis of the altered spectral properties. Part of the raw data that was generated was further analyzed by Dr. Vermerris and the resu lts are accessible to the public on Purdue Universitys cell wall genomics website ( http://cellwall.genomics.purdue.edu/families/7.html ). Two of the 39 putative mutants have been furt her evaluated in the field and by pyrolysis

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50 molecular-beam mass-spectrometry (Py-MB-MS) an alysis. Figures 2-3 and 2-4 show examples of how the two putative mutants differ in thei r chemical composition as well as in their performance under field conditions from their wild-type counterparts. Further characterizations of the remaining putative mutants are underway.

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51 Figure 2-1. Partial Least Squares plot showing separation between bm mutant and wild-type leaf samples. Figure 2-2. Based on NIR data, the mutant appear s to have an abundance of proteins (1528 nm, 2061 nm) carbohydrates (1702 nm, 2379 nm). -0.06 -0.04 -0.02 0 0.02 0.04 0.06 0.08 1000 1500 2000 2500coefficientwavelength (nm)

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52 Figure 2-3. Results confirming variation in cel l wall composition between putative mutant and wild-type plants following NIR analysis. Obse rvations made in the field also show differences in growth and development. Figure 2-4. Results confirming variation in cel l wall composition between putative mutant and wild-type plants. Results were obtaine d after NIR and Py-MB-MS analyses.

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53 CHAPTER 3 AGRONOMIC AND CHEMICAL ANALYSES OF THE NOVEL BM MAIZE MUTANT Introduction Agronomic Traits Functional genom ics using mutants of maize en ables the identificati on and manipulation of genes to gain understanding of the genetic contro l of plant genes, including those for quality and plant performance traits. This approach can, ther efore, be used to develop and assess novel maize for applications such as enhanced forage feed or as raw materials for biofuel processing (Donnison and Morris, 2003). The bm mutations have been shown to affect yield, plant height, flowering dynamics and biomass conversion efficiencies (Vermerris et al ., 2007). Vermerris et al. (2002) showed that bmr sorghum and bm maize have different flowering dynami cs compared to their wild-type counterparts. Oliver et al. (2005) concluded that the bmr phenotype is generally associated with reduced vigor and yield. Previous resear ch in maize has also demonstrated that bm mutants have reduced grain and stover yield (Lee and Brew baker, 1984). In a comprehensive study on the effect of the bm mutation on bm sudan grass, Casler et al (2003) showed that the bm phenotype reduced forage yield by 15 30 %. Reduction in forage yield was partly due to reduced ground cover as a result of reduced tillering capability of the bm lines. Chemical Analysis To investigate the chem ical basis of the muta tion, chemical analytical methods were used that enabled the extraction and analysis of the pigment in the midrib, high-throughput leaf screening with NIR spectroscopy, tissue staini ng experiments and to look for differences between wild-type and bm mutant plants. The ob jective of this study wa s to determine if the bm

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54 mutation had an effect on agronomic developmental traits. We also want ed to investigate any cell wall related chemical differe nces between the wild-type and bm mutant plants. Materials and Methods Plant Material The novel bm m utant sources 05-06 PRWN 301S, 05-06 PRWN 302ST1, 05-06PRWN 303ST3, 05-06 PRWN 299ST1 and their wild -type counterparts NSF04 360S1, NSF04 324S1, NSF04 309S1, NSF04 309S2 were grown in the field at the University of Floridas Plant Science Research and Education Unit (PSREU ) in Citra, FL in the fall of 2006 and again in the spring of 2007. Four replicates of 18 seeds of each genotype were planted in rows. Seeds were planted 30 cm apart. Flowering Time After six weeks, the plants were observed dail y for anthesis. F lowering time (emergence of pollen-shedding anthers from the tassel) and silk ing time (emergence of first silks from the ear) were recorded daily at midday. At physiological maturity, each pl ants height was measured and recorded. Klason Lignin Content Because of the heterogeneity of lign in structure, and also because lignins are covalently linked with cell wall carbohydrat es, proteins, phenolics, or other compounds, all lignin concentrations are purely empirical. The avai lable analytical procedure for the quantitative determination of lignin fall in two basic categories: those that remove all cell wall constituents except for lignin and quantify it gravimetrically, and those that oxidize the lignin polymer and quantify it spectrophotometrically. In this study, the former was used. Six bm and six wild-type plant stalks were coll ected at physiological maturity and placed in a 50 C drier for one week. The bottom three internodes were ground into a powder to pass

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55 through a 1-mm screen and collected in plastic 50-ml Falcon tubes. All samples were then cleaned in 80% (v/v) ethanol recovered by filtr ation through a Glass Micr ofiber Filter GF/A 55mm filter paper (Whatman, England, UK) and dried at 50 C for 48 hours. Klason lignin content was quantified gravim etrically as the as h-corrected residue remaining after total hydrolysis of cell wall polysaccharides (H atfield et al., 1994). One hundred mg of the cleaned and dried sample was we ighed into a 20 125 mm Pyrex glass tube containing five glass beads. The tube was cappe d with a Teflon-coated screw cap. The samples underwent primary hydrolysis in 1.5 ml 12M H2SO4 on ice for 30 minutes. The samples were then incubated in a shaker at 30 C for two hours, diluted with 9.75 ml of ddH2O and autoclaved at 120 C for one hour for secondary hydrolysis. Sa mples were cooled and filtered through a glass filter disc placed on a Bu chner funnel. The Pyrex glass tube was rinsed three times with 5ml 60 C warm distilled water to make sure that all small pieces of residue were collected on the filter disc. The filter discs where then oven dried at 50 C for 48 hours, weighed and then ashed in an Isotemp Muffle Furnace (Fisher Scientific, Pittsburgh, PA) at 500 C for five hours before being carefully reweighed. Klason lignin was calculated as the weight before ashing corrected for the weight after ashing. T-te st analysis was performed using Excel. Lignin Sub-unit Composition Pyrolysis-gas chrom atography-mass spectro metry (Py-GC-MS) has been used to characterize the composition in the cell wall of the bm mutants in corn (Vermerris and Boon, 2001). Lignins can be pyrolized reproducibly to produce a mixture of relatively simple phenols that result from the cleavage of the ethe r and carbon-carbon (C-C ) bonds (Ralph, 1991). Pyrolysis of the samples results in the forma tion of a vapor containi ng fragments that are separated by gas chromatography and identifi ed with mass spectrometry. For lignin, the

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56 substitution pattern of the phenolic ring is typically retained, but only limited information about the inter-unit bonds is obtained. Midribs from wild-type and bm mutant leaf samples were dissected from fully expanded leaves and cut into 3-mm pieces. The fresh pieces were soaked in deionized water for 30 minutes twice, to remove water sol uble compounds, then in acetone for one hour twice to remove unbound phenolics (Vermerris and Boon, 2001). Acetone was discarded and the samples rinsed and left to dry in the hood. Dried samples were analyzed with Py-GC-MS. One milligram midrib samples were placed in a small cup and injected into the Py-GC-MS (Varian 3800 GC, 1200 MS). The samples were separated on a capillary column which was inserted in the pyrolysis outlet set at 325 C. Helium gas (1.2ml/min) was used as the carrier ga s. For the analysis of midrib samples the GC program is shown in Table 3-1 and Table 3-2. Pyrograms were acquired and analyzed using Varian workstation software (Varian Inc., CA). Qualitative analysis of pyrograms from mutants and their wild-type plants were made by looking for differences in the peaks. Wiesner Reaction The W iesner reagent is a 1% (w/v) solution of phloroglucinol dissolved in a 3:1 mixture of ethanol and concentrated HCl (Vermerris and Nicholson, 2006). This reagent reacts with cinnamaldehyde end groups in the lignin, formin g a red cationic chromophore. This procedure, which is commonly known as the Wiesner reaction, is also used as a general stain for lignin. Phloroglucinol staining is probabl y the most common stain used because of its ease of use. The Wiesner reaction has also been used to compare lignin content and composition. Wild-type and bm mutant plants were grown in the fi eld and the stalks were harvested at the tassel emergency (VE) stage. The stalks were cut off from the base and placed in a bucket with water. The sixth internode of each plant was selected for analysis. The stem was sectioned

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57 with a razor blade and th e sections were incubated in five drops of 1% (w/v) phloroglucinol in ethanol: concentrated HCl (3:1). After five mi nutes, the drops were removed and the section was rinsed with distilled water. The sections were viewed on a Leica MZ12.5 stereomicroscope (Leica Microsystems, IL) with a camera attached. Enzymatic Saccharification In order to evaluate if the colorati on of the m idrib phenotype of the novel bm mutant had an impact on the extent of hydrolysis of cellulo se in maize stover, enzymatic saccharification experiments were performed. The term cellulase refers to a mix of thr ee classes of enzymes th at together hydrolyze cellulose to glucose. The cellula ses produced by the wit-rot fungus Trichoderrna reesei consist of endoglucanase (E.C. 3.2.1.4), cellobiohydrolase (E.C.3.2.1.91), and -glucosidase (E.C.3.2.1.21) (Gum et al., 1976). The combined syne rgistic actions of these three enzymes in the cellulase preparation comp letely hydrolyze cellulose to D-glucose. Lignin interferes with the access of the enzyme complex to the cellulose, pr obably due to their coating of the cellulose fibers (Boudet, 2003). Furthermore, lignin itself can bind cellul ase enzymes thereby rendering them inactive or less effective for di gesting cellulose (Berlin et al., 2006). Cellulase Assays Cellulases are a m ixture of enzymes that ac t synergistically (Mandels et al., 1976). The rates of enzyme reaction are affected by type of substrate. This includes chain length and crystallinity of the cellulose as well as by physical or chemical pret reatments. In order to be able to measure enzyme productivity there was need for an enzyme unit that would be used to predict sugar output. In addition, the enzyme unit woul d allow comparison of cellulase activities from different sources as well as allow comparison between various systems used in different laboratories. Mandels et al. ( 1976) proposed a unit of cellulase activity based on the hydrolysis

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58 of a Whatman No. 1 filter paper. They recognized that for quan titative results, the enzyme unit must be based on a fixed percent conversion: a f our percent conversion of 50 mg of filter paper unit, which required hydrolysis of some of the crystalline ce llulose and not only the loose amorphous portions of the substrate that are easily and quickly hydrolyzed. Cellulase was assayed using a 50-mg Whatman No. 1 filter paper following the National Renewable Energy Laboratory (NREL) in Go lden CO analytical procedure LAP 006 ( http://www.nrel.gov/biomass/analytical_procedures.htm l#LAP-006) This method describes a procedure for measurement of cellulase activity using International Union of Pure and Applied Chemistry (IUPAC) guidelines. The procedure has b een designed to measure cellulase activity in terms of "filter-paper units" (FPU ) per milliliter of original ( undiluted) enzyme solution. For quantitative results the enzyme preparations mu st be compared on the basis of significant and equal conversion. The value of 2.0 mg of reducing sugar as glucose from 50 mg of filter paper (4% conversion) in 60 minutes has been designated as the inter cept for calculating filter paper cellulase units (FPU) by IUPAC (Ghose, 1987). An enzyme mix (Table 3-3) containing the tw o cellulase enzymes was prepared into six different dilutions resulting in different enzyme concentrations which were then used to hydrolyze the Whatman filter paper. After 60-mi nute incubation, glucose readings from the hydrolysis of the Whatman paper in tubes contai ning the different enzyme concentrations were recorded. A calibration standard curve was constr ucted using the actual glucose readings and the measured glucose readings. The standard curve was used to de termine the amount of glucose released from each sample tube after subtraction of enzyme bla nk. Corrected or calculated values were acquired by substituting the measured glucose readings into the equation from the standard curve. The corrected value was converted from mg/dl to mg (glucose yield) by multiplying by

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59 1.5 (1.5 ml total volume) and dividing by 100. From these data, the enzyme dilution is plotted along the y-axis on a logarithmic scale and the gl ucose yield along x-axis on a regular scale. The two point reflecting readings clos est to 2-mg are connected and the enzyme concentration that would yield 2-mg is recorded. Using the filter paper activity formula, the enzyme concentration that yielded 2-mg glucose was used to calcula te the filter paper units (Mandels et al., 1987; Ghose, 1987). Six stalks from wild-type plants and six from bm mutant plants were harvested at grain harvesting stage. The stalks were placed into a 50 C drier for one week before the bottom three internodes were collected and ground into a fine powder. The ground tissue was cleaned with 80% warm ethanol to remove salts, soluble suga rs, small molecules such as hormones and other metabolites before being air-dried in a 50 C oven. A 300-mg stover sample was weighed into a 50-ml polypropylene tube. Forty six filter paper units (FPU) of an enzyme cocktail consisting of sodium citrate buffer, distilled water, cellula se enzymes sodium azide were added to each sample and the tubes were vortexed and placed on ice (Table 3-3). Celluclast 1.5L (Sigma, St Louis, MO), is a cellulase preparation obtained from Trichoderma reesei. Novozyme 188 (Sigma, St Louis, MO ) is a cellobiase preparation obtained from the fungus Aspergillus niger. A 0.5 ml aliquot was taken immediately after the enzyme cocktail was added to the stover samples labeled t0, boiled for 5 minutes in a waterbath, and stored at -20 C. The tubes containing the remainder of the samples were incubated in a shaker operating at 200 rpm at 50 C. After exactly 24 hours, the sa mples were placed on ice, and a 1ml aliquot was collected labeled t24 and boiled in a waterbath. In random order the glucose concentration of the samples was measured using the OneTouch Ultrasmart blood glucose

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60 meter. Each sample had three measurements taken before they were averaged. T-test analysis was done using Excel. Carotenoid Extraction Using a m ortar and pestle, fr ozen midrib tissue from six bm plants and six wild-type plants was ground into a fine powder and 0.8 1.2 g were weighed into screw-capped 15 ml polypropylene tubes. The tubes and th eir contents were kept frozen in a container with liquid N2 at all times. Working under low light throughout the whole experiment, the weighed sample was suspended in 10 ml of methanol, vortexed and centrifuged at 5,000 g for 15 minutes at 4 C in a 15 ml Polypropylene tube. The supernatant was tr ansferred to a clean 50-ml Polypropylene tube to which 1 ml 60 % (w/v) KOH was added. The mixture was heated at 65 C for 20 minutes in a water-bath. Carotenoids were extr acted by vortexing the mixture thr ee times in 10% (v/v) diethyl ether in hexane. The organic phase was evaporated under nitrogen to leave an oily residue at the bottom of the tubes which was dissolved in 700 l methanol. The extracted carotenoids were stored in the dark in -20 C freezer. For analysis, 100 l from the si x replicates of each genotype ( bm and wild type) were aliquoted randomly into individual wells in a 96well plate. A third row was filled with methanol as the control. Carotenoid absorbance readings were measured at 450 nm using a Spectra Max M5 (Molecular Devices, CA) plate reader. Data acquisition and analysis were performed using the Soft Max Pro software v5 (Mol ecular Devices, CA). Carotenoid samples were also analyzed using the GC-MS. Three micro liters of a carotenoid sample were injected into the GC-MS where separation of carotenoid compounds is base d on retention on the column (Table 3-4 and 3-5).

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61 Thin Layer Chromatography Carotenoid sam ples (100 l) were applied to silica gel 60-, 20 20 cm TLC plates (Whatman, Scheicher & Schuell, England, UK) using a pasteur pipette. The application was done in a way that left sharp concentrated sp ots evenly separated from each other and 1.5-cm from the bottom of the TLC plate. A distance of 1-cm was left between the plates edge and the first sample spot. Three bm and three wild-type samples were analyzed, with one bm mutant sample lined up next to a wild-type sample. The TLC plate was run in a 250 ml mixture of 40:10:10 (v/v/v) petroleum ether (PE), diethyl et her (DE) and acetone for 4-5 cm in about 5 minutes. Flavonoid Extraction Flavonoid biosynthesis has a num ber of branch pathways that result in nine major subgroups: chalcones, aurones, isoflavonoids, fla vones, flavonols, flavondiols, anthocyanins, condensed tannins and phlobaphenes pigments (Winkel-Shirley, 2001). A number of these subgroups are yellow, orange, red or brown. In order to investigate if the orangish-brown pigment in the bm mutant is a flavonoid, we used a fla vonoid extraction protocol on the ground-midrib samples. One gram of the ground powder from three mi drib samples from wild-type and three samples from mutant leaves was washed in 10 ml of acetone by vortexing before removing the supernatant. The residue was then washed in 10 ml 95% (w/v) ethanol as in the previous step. Five ml 0.1 N HCl in methanol was added to the remaining residue and left to soak overnight. After 24 hours the color of the pe llet and the solution were observe d to see if any pigments had been extracted (Figure 3-7).

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62 Results When viewed under a com pound m icroscope, the novel bm mutant is characterized by the accumulation of an orange pigment in the sclerenchyma cells (Figure 3-8). Sclerenchyma cells are thick, often lignified secondary walls. Func tionally, sclerenchyma is the strengthening and supporting element in plant parts. They are lo cated adjacent to the vascular bundle and spongy parenchyma. The orange coloration is restricted on ly to the sclerenchyma tissue. In contrast, the wild-type sclerenchyma is cream in color (Figure 38) and the cells are clearly distinct from the vascular tissue cells as well as the spongy parenchyma cells. Agronomic Traits W ild-type and bm mutant plants were grown in fall 2006 and summer 2007. In both seasons, the bm plants were shorter than the wild-type co ntrols. Figures 3-1A and 3-1B show that the mean height of the bm mutant is statistically different fr om the wild-type control. In fall 2006 the average height of the wild-type and bm mutant plants was 133 SE and 108 SE cm respectively. The differences were also observe d in summer 2007 when the average height for the wild-type was 154 SE cm while th at of the mutant was 142 SE cm. Figure 3-2 shows that time to flowering (as m easured by the time to anthesis) between the bm mutant and the wild-type was si gnificantly different in fall 2006. The mutant flowered earlier by four days. However, in summer 2007 there we re no significant differences in time to flowering between the wi ld-type controls and bm mutant. This sugge sts a seasonal effect on time to flowering. There were no differences in time to silking in both seasons for the two genotypes (Figure 3-3). This suggests that the mutation of the bm gene has no effect on time to silking.

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63 Chemical Analysis Wiesner Staining Following incubation of the stem section sample s with the Wiesner reagent, the wild-type and bm samples were stained with the same intensity in the vascular tissues. The results indicate equal levels of total lignin content and levels of coniferaldehyde end groups in the two genotypes (Figure 3-4). This result also confirms the pyrolysis-gas chromat ography mass-spectrometry outcome, which detects no differences in sub-unit composition. Enzymatic Saccharification Stover sam ples that were collected from wild -type and mutant plan ts at physiological maturity were hydrolyzed with a cocktail of cellu lase enzymes (Table 3-3). Glucose levels were measured using a OneTouch Ultrasmart (Lif eScan, Inc. Milpitas, CA) blood glucose meter and both stover samples yielded equa l amounts of glucose (Figure 3-5). Carotenoid Extraction Midrib samples from both the wild-type a nd mutant samples were collected and ground with a mortar and pestle into a powder using liquid nitrogen. Carote noids were extracted following a protocol by Wurtzel et al. (2001). The optical density (OD) of the carotenoid samples was measured (Table 3-6) using a sp ectrophotometer and there were no significant differences between the carotenoid samples from the wild-type and mutant samples. Carotenoids were extracted on three different occasions but the outcome remained the same (Table 3-1). Three microliters of the carotenoid sample s were also injected into a GC-MS and separation of the compounds was based on the retention on the column. Comparison of the chromatograms from wild-type and mutant carot enoid samples did not show any differences. Thin layer chromatography (TLC) is a techni que used to separate chemical compounds into individual components based on their solub ility in the solvent and their affinity for the

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64 matrix. In order to investigate if the carotenoids extracted from the bm mutant and wild-type midribs were different in composition, TLC was performed. One hundred microliter carotenoid samples from both genotypes were separated on a 60-, 20 cm2 silica gel TLC plate. Following separation samples from the two ge notypes did not show any differences in composition or intensity. Klason Lignin Klason lignin analysis is a gravim etric proced ure that dissolves all cell wall components except lignin. The procedures outcome revealed th at the stover samples from the wild-type and mutant plants did not have signi ficant differences in the total li gnin content (Figure 3-6). This suggests that the bm mutation does not have an effect on the Klason lignin content. The results further confirm the outcome from the stem section staining with the Wiesner reagent. Pyrolysis-Gas Chromatography-Mass Spectrometry W ild-type and mutant dissected midribs that are three to five millimeters in length were injected into the Py-GC-MS. Pyrograms obtained from the wild-type and mutant samples were compared and showed no apparent differences in the composition of the midrib samples. Near Infrared Reflectance Spectroscopy Near infrared reflectance spectra we re acquired f rom dried wild-type and bm mutant leaf samples. The data were analyzed with WinDAS software. Based on NIR data, the mutant appears to have an abundance of protei ns (1528 nm, 2061 nm) and carbohydrates (1702 nm, 2379 nm). Efforts to Clone the Bm Gene Mu -TAIL PCR products were cloned into a p CR4-TOPO vector and 192 colonies were selected for sequencing at th e UF-ICBR genome core facility. One hundred and ninety two single-pass sequence reads from randomly selected Mu -TAIL clones in the bm library were

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65 obtained. Candidate clones were identified by performing in silico subtraction against a large collection of Mu -TAIL sequences by assembling all sequences in the data set into contigs using the PHRAP program (Ewing and Green, 1998; Ewing et al., 1998). Out of the 192 bm Mu -TAIL clones, a total of 19 contigs were obtained. Of these, only six contigs were unique to the bm library. In addition, 15 unique singletons were identified giving a total of 21 unique candidates for the causative insertion in the bm gene. The 21 unique Mu -TAIL clones were analyzed by BLAS TN search (Altschul et al., 1990) to extract all available maize sequences that matched the Mu -TAIL clone sequences. Cosegregation analysis of a segregating set of plan ts was performed using Mu -TAIL clone-specific primers and a Mu terminal inverted repeat (TIR)-specific primer. P CR products were expected from DNA of heterezygotes as well as the homozygous bm mutant individuals. None of the 21 bm candidate gene sequences co-segregated with the bm phenotype. In a second round of trying to clone the Bm gene, the 192 Mu -TAIL PCR singlepass sequence reads were filtered through a large collection of private and public Mu -TAIL databases. Forty-two unique candidates were identified and these were analyzed by BLASTN search to extract all available maize sequences that matched the Mu -TAIL clone sequences, as before. These sequences were used to design Mu -TAIL clone-specific primers which were used together with TIR-specific primers to perform co-segregation analysis as described before. None of the 42 candidates co-segregated with the bm phenotype

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66 Table 3-1. Py-GC-MS program used to analyze midrib samples Rate ( C/min) Hold (min) Total (min) 0.25 0.25 200 0.5 2.6 Table 3-2. Py-GC-MS oven program used to analyze midrib samples Rate ( C/min) Hold (min) Total (min) 3.5 3.5 5 0 15.5 4 0 43 20 1.75 50 Table 3-3. Cellulase enzyme cocktail Reagent Volume (ml) per tube Sodium citrate (pH 4.5) 5 50mM final conc. ddH20 4.47 Novozyme 188 0.065 46 FPU Celluclast 1.5L 0.065 Sodium azide (NaN3) 0.1 10% Table 3-4. GC-MS program used to analyze carotenoid samples Rate ( C/min) Hold (min) Total (min) 0.5 0.5 100 1 1.7 200 0.5 3.04 Table 3-5. GC-MS oven program used to analyze carotenoid samples Temperature Rate ( C/min) Hold (min) Total (min) 4 4 180 40 0 7.25 250 5 0 21.25 300 20 0.25 24

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67 Figure 3-1. Differences in plant height between the bm mutant and wild-type in A) Fall 2006 (pvalue 0.002) and B) Summer 2007 (p-value = 0.008). Wild-type and mutant plant heights were measured at physiological maturity and averaged. Figure 3-2. Time to flowering, measured as days after planting (averaged across 4 replications), for the wild-type and mutant plants in A) Fall 2006 (p-value = 0.002) and B) summer 2007 (p-value = 0.08). 0 20 40 60 80 100 120 140 160 wildtypemutantheight (cm) 0 20 40 60 80 100 120 140 160 wildtypemutantheight ( cm) 0 20 40 60 80 wildtypemutanttime (days after planting) 0 20 40 60 80 wildtypemutanttime (days after planting)A A B A B

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68 Figure 3-3. Time to silking, measured as days af ter planting (averaged acro ss 4 replications), for the wild-type and mutant plants in A) Fall 2006 and B) Summer 2007. A B Figure 3-4. Maize stem sections after st aining with the Wiesner reagent. A) bm mutant plant B) wild-type. 0 10 20 30 40 50 60 70 80 wildtypemutanttime (days after planting) 0 20 40 60 80 wildtypemutanttime (days after planting) B A

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69 Figure 3-5. Glucose yields (mg glucose /g DW stover) following hydrolysis of wild-type and bm mutant stover samples (p-value = 0.85). Figure 3-6. Klason lignin content comparison between wild-type a nd mutant plants averaged across six replications (p-value = 0.57). 0 2 4 6 8 10 12 14 16 18 wildtype mutantmg/dL 0 50 100 150 200 250 300 wildtypemutantlignin content mg/g

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70 Table 3-6. Spectrophotometer absorb ance readings of carotenoids extracted from wild-type and bm mutant midrib samples wild-type mutant Mean 1.2 1.1 Standard deviation 0.3 0.4 A B Figure 3-7. The residue of the bm and wild-type samples after 24 hours of flavonoid extraction. The bm samples B) still retain their orangish -brown pigment compared to wild-type samples A). A B Figure 3-8. Midrib sections from 60 day old maize plants grown in a greenhouse. The sections were viewed under a compound micros cope (20 ) showing that the bm mutant A) accumulates the orange-brown pigment in th e sclerenchyma. B) Wild-type sections show only faint cream coloration in the sclerenchyma cells.

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71 C D Figure 3-9. Midrib stem secti on C) stained with Wiesner reagent and then viewed under a compound microscope (magnification 40). D) Dark staining surrounding the vascular tissue and the sclerenchyma confir ms the presence of lignin in these tissues.

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72 CHAPTER 4 EFFORTS TO CLONE THE BM GENE Introduction Since our brown midrib mutant was isolated from a transposon-active, m utagenic population, there is a high probability that a Mutator (Mu) element is inserted in the causal gene. Such an insertion will enable identification of the brown midrib gene using Mu -TAIL PCR (TAIL stands for T hermal A symmetric I nterL aced). Mu -TAIL PCR (Table 4-1), produces a population of fragments, each with one end anchored in the terminally inverted repeat (TIR) of the element and the other end at an ar bitrary site in the flanking DNA. The Mu -Tail PCR products can either be di rectly sequenced using a Mu -anchored 454 protocol, or cloned into a TOPO vector (Invitrogen, Carl sbad, CA) and the resulting microlibrary sequenced. DNA Extraction Mu -TAIL PCR am plifies genomic D NA flanking maize Robertsons Mutator insertions. DNA was extracted from 100-mg frozen leaf tissues of a bm mutant plant using the DNeasy Plant Mini kit (Qiagen, Carlsbad, CA) DNA extr action protocol. The eluted DNA (200 l) was collected in a 1.5 ml Epperndor f tube and stored at 20 C. Mu -TAIL PCR A m utant bm DNA sample was used undiluted in th e first of two PCR reactions. One microliter of ~50ng/l DNA was added to a 20 l primary Mu -TAIL PCR reaction. The primary reaction was composed of 1 U native Taq polymerase, (Invitrogen, Carlsbad, CA), 10 PCR buffer consisting of 20 mM Tris-H Cl pH 8.4, 50 mM KCl, 2 mM MgCl2, 200M dNTPs, 100 nM primer TIR6, 1 M arbitrary primer. Twelve ar bitrary primers (AP) were used. Water-only negative controls from the primary reaction were diluted and processed id entically to reactions containing DNA templates. During the set up of the P CR, all samples were kept cold at all times.

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73 The following order worked efficiently: water (n egative control) no-tem plate (NT) PCR tubes placed in a PCR tube cooler. Mast er mix was prepared then DNA te mplate added to template (T) PCR tubes followed by arbitrary pr imer (AP) (Table 4-3) additi on to NT and T tubes. Tubes were capped, vortexed and spun down while pre-hea ting the thermal cycler block (Table 4-1). After the primary reaction, all samples were kept cold (4 C). It was imperative to proceed to the secondary reaction on the sa me day. The secondary Mu -TAIL reaction was identical to the primary except that the TIR8 nested primer was used instead of the TIR6 (Table 4-2). MuTAIL thermocycling conditions were also different (Table 4-1). TIR8 primer is composed of TIR8.1, TIR8.2, TIR8.3 and TIR8.4 primers mixed in a 2:4: 4:1 ratio, respectively, to adjust for the degeneracy of each primer synthesis (Settles et al., 2004). PCR products from the primary reaction were used as the templates for the seco ndary reaction, but after they had been diluted 100 times in double distilled water. PCR products were run on a 1.2% agarose gel in 0.5 TBE for 70 minutes at 100 volts (Figure 4-1). Sequencing The products from the twelve reactions were divided into two groups of six, based on the strength of their intensity on the gel. From each of the AP products, 15 l were pooled to make a total of 90 l. The products were size-selecte d using a Sephacryl-400 (Promega, Madison, WI) spin column following manufacturers instructio ns. Size selection was done to limit sequencing reactions to products above 500 bp. Twenty microlit ers of the pooled sample were added to the center of the column and spun in a centrifuge at 2800 rpm. The size-selected product was collected in the eluate. The tw o pooled groups resulted in two-si ze-selected products which were labeled size-selected-1 and -2 (SS1 and SS2).

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74 TOPO Cloning Reaction Following size selection, 8-l of the eluate was run on a gel to conf irm if the size selection had succeeded (reduction in products less than 5 00 bp). After confirmation, the size selected products were mixed with a TOPO cloning reaction shown in the table below. The vector used was pCR2.1 (Invitrogen, Carlsbad, CA). After mi xing, the reaction was mixed gently by stirring with a pipette tip. The reaction was incubated in a PCR machine at 23 C for 30 minutes and then placed on ice. Transformation After incubation on ice 3-l of the T OPO cl oning reaction was added to a vial of One Shot Electrocompetent E. coli (Invitrogen, Carlsbad, CA) and mixed gently with a pipette tip. The mixture was incubated on ice fo r 10 minutes, heat shocked at 42 C for 30 seconds and immediately transferred to ice. This was follo wed by addition of 250 l of room temperature S.O.C medium (Invitrogen, Carlsbad, CA). The vial was tightly capped and placed in a shaker at 37 C, 200 rpm for 30 minutes. The cells were spr ead on LB agar medium containing 35 l 50mg/ml X-gal, 20 l 100mM IPTG and 20 l ampi cilin. Eight sterile glass beads were used to spread the cells on three 100mm petri dishes each containing 10, 50 and 200 l of the reaction respectively. Petri dishes we re incubated overnight at 37 C. White colonies were used to inoculate liquid LB (50 g/ml) with ampicillin in two 96-well plates which were incubated at 37 C before being sent for sequencing. Sequencing r eactions were performed at the University of Floridas Interdisciplinary Center for Bi otechnology Research (ICBR) using a Applied Biosystems Model 3130 Genetic analyzer. The T7 primer was used for all sequencing reactions.

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75 In Silico Subtraction The sequencing exerci se returned 192 Mu -TAIL sequences from the Mu -T AIL clone library. In order to identify candidate clones for the bm mutant, in silico subtraction was performed against a large collect ion of parental and sibling Mu -TAIL sequences. In silico selection compared the bm mutant Mu -TAIL sequences against a co llection of known parental sequences to identify unique Mu -TAIL sequences and discard the parental sequences which are presumably not the cause of the mutation (Table 4-4). In a second stag e of analysis, the 42 unique Mu -TAIL clones were analyzed by BLASTN sear ch of public and private databases to extract all available maize genome sequence and EST that matched the Mu -TAIL sequences. Co-segregation Analysis Prim ers were designed from the maize genom ic sequences extracted from the BLASTN (Altschul, 1997) searches of public and privat e databases (Table 4-5). Depending on genomic sequence length, upper and lowe r primers that flank the Mu insertion site were designed and these were tested on DNA extracted fr om a segregating population. Twenty one bm DNA samples and 19 wild-type DNA samples were tested. To confirm the presence of a Mu insertion in a gene that is causing the bm phenotype, PCR products were expected from 21 bm mutant individuals and wild-t ype heterozygotes but not from homozygote wildtypes if we use a TIR8 primer and an upper/lower primer.

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76 Table 4-1. Thermal cycler programs used for Mu-TAIL PCR TAIL 1 TAIL 2 Cycle # Temp ( Celsius) Time Cycle # Temp ( Celsius) Time 1 95 2 min 1 95 2 min 2 94 30 sec 2 94 10 sec 3 67 1 min 3 64 1 min 4 72 2:30 4 72 2:30 5 Go to 2 4 times 5 94 10 sec 6 94 30 sec 6 64 1 min 7 25 3 min 7 72 2:30 8 72 2:30 8 94 10 sec 9 25-72 (Ramp to 72) @ 0.3 degree/sec 9 44 1 min 10 94 10 sec 10 72 2:30 11 67 1 min 11 Go to 2 11 times 12 72 2:30 12 72 5 min 13 94 10 sec 13 4 forever 14 67 1 min 15 72 2:30 16 94 10 sec 17 44 1 min 18 72 2:30 19 Go to 9 14 times 20 72 5 min 21 4 Forever

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77 AP1 AP2 AP3 AP4 AP5 AP6 AP7 AP8 AP9 AP10 AP11 AP12 Figure 4-1. Agarose gel image of Mu -TAIL PCR products amplified using Mu -TIR6 and nested TIR8 primer and 12 arbitrary primers. Table 4-2. Nested Mu-TIR primers used to amplify Muadjacent sequences Primer Sequence (5 3) TIR6 AGAGAAGCCAACGCCAWCGCCTCYATTTCGTC TIR8.1 CGCCTCCATT TCGTCGAATCCCCTS TIR8.2 CGCCTCCATT TCGTCGAATCCSCTT TIR8.3 SGCCTCCATTTCGTCGAATCCCKT TIR8.4 CGCCTCCATTTCGTCGAATCACCTC

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78 Table 4-3. Arbitrary primers used in combination with MuTIR nested primers in Mu-TAIL PCR Primer Sequence (5 3) cggc1 GVCTYCGWSSGC SAD11 NTCAGSTWTSGWGWT SW41 AGWGHAGSAHCADAAS BAD5 WTCCASNTGSNACG DRM-CG2 GCNGNWCGWCGWG CST1 GTANTCGWAWNCST CTG1 GWWGGTSCWASWCTG AMS2-GAG3 GWSIDRAMSCTGCTC geeky1 GKYKGCKGCNGC DRM-AG1 GNGWSASTNGAGC BAD8 GTGASNTGSWATGG DRM-NC1 GSCNCSGWNCC Table 4-4. Unique MuTAIL sequence types of the bm mutant obtained from in silico subtraction Type of sequence Quantity Representative read with TIR 8 Representative read with no TIR 12 Unplaced with TIR 22 Total 42

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79 Table 4-5. Co-segregation primers Name Sequence CONTIG16_U346 CAACCTTGTGCAGAAGTACAAGTTCCA CONTIG16_U700 GCACCCCTT AAGTACGCATTAGTGTGT CONTIG3_U168 CTACAAGTATACAGCAGACTCCAAG CONTIG3_U363 GCATAATACCTGCTGGGCACCA CONTIG4_U2189 TGATACGGCGGAGGTGAAGACTTC CONTIG5_U155 GCAGACCTGGGTAACATGATCC CONTIG5_U230 GCTCTGGGCTACTCCATACCAA CONTIG5_U823 CTGATTCTGCTAACTGCCGCTT CONTIG6_L1294 TCAAGTGCCCAGTACCA GAAGAAG CONTIG6_U862 AGGACGCCGACCATTTGGTTAGTG SS1_A06-U1-22 GTGTCAGTTGAGCAAGTTTAGGAC SS1_A09-U1-23 GGGTCAGTTGAGCAAGTTTAGGA SS1_A12-L789 TCCGCCACTGATTTCAGGTTCT SS1_A12-L789 TCCGCCACTGATTTCAGGTTCT SS1_A12-U330 TCGCCTCCGCATTCTAGGGTTT SS1_A12-U330 TCGCCTCCGCATTCTAGGGTTT SS1_B02-L1167 GCGGCTGCGAGCTGAGGTTA SS1_B02-U583 GGGCCA AAATTGCTCAGCCCA SS1_C05-U1-24 GTGACACTTGAGCACATTGGATTC SS1_C05-U693-22 AAGTGGCGACAGCACGAGTGAT SS1_C08-U1-22 GTGCTC CATTTCCTCTAATCCC SS1_C08-U37-26 CATAATGGCAATGATCTCGTTCATGC SS1_C12-L645 CGGCCTAATCAAGTCAAGGTACTCC SS1_C12-U1-22 GACGGA ACCCTGCTCAATGACA SS1_C12-U222-23 TACGCTTGTAACTGTGCCAGATC SS1_C12-U381 GGGGCGAGCATACCTGCTGGG SS1_D01-U580 TTGCGTAAGAGTGATGAGACATAAAT SS1_D02-U182-22 GCTCTGGGCTACTCCATACCAA SS1_D06-U13-24 CGCATCAATGGGTTCTCAGAAGCT SS1_D06-U176-24 TGCTGCCGTAGCTGGTATGTAATG SS1_D08-U290 GCACGGGCACTTAGCTAGTTAAGG SS1_DO2-U618-23 TTCGGATGTAGTTGAGCGGGATA SS1_E07-U347-24 GGAATTGTTCGTGACACCAAGGAC SS1_E07-U588-24 TAGGAAAGATGTGTAGATCGGTGG SS1_E08-L570 GCGGGAGGGCACCTTGTCAAAGG SS1_E08-U229 GCCGGACACAGTAGCACGGAGGT SS1_E08-U229 GCCGGACACAGTAGCACGGAGGT SS1_E10-U1-22 GAGTCAGTTGAGCGGGATAAGG SS1_E10-U54-24 TGTCCTGTTGCCAGTGTCACACTAG SS1_F03-U1-24 GTGTCAGTTGAGCAAGTTTAGGAC

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80 Table 4-5. Continued Name Sequence SS1_F03-U75-22 ATTATGGACGAAGAGGGAAGCG SS1_F06-L849-26 AATGACGTGGCTCTACGGAATCACAG SS1_F06-U191-23 GTGTTGGATGTGGTGATTTGCTG SS1_F06-U225-25 GCATGTAAGTGTACTGAGTTCCTTC SS1_F06-U447-28 AGTACGCATTAGTGTGTACATACGGTAG SS1_F06-U849-25 CTGTGA TTCCGTAGAGCCACGTCAT SS1_F07_FB GGAAGCGGCGGGTAGGTTCTTAGTAC SS1_F07_RB CCGATTGAAGGGCACCGCCTATCAATTA SS1_F07_U71 TGCGTATCCATAACGGAGAAACC SS1_F07-L1171-23 TTCGGGTGCTCTAATTGATAGGC SS1_F07-L1344-24 GGAATCAAGAACCGTCTGCTGGAA SS1_F07-L143-24 TAGCGGTCTTGTTCAACGTGGTCT SS1_F07-U187 TCAAAGGGACCGAGATTCATGGG SS1_F07-U206-24 CAAGAAGCCTAACGGTCGAGTAAG SS1_F07-U284-22 AGTGATGGGATAGCCACATGGA SS1_F07-U558-24 AGATCC TGAGCCCTATGAACAACT SS1_F08-U200-23 CCAAGTCAAGTGAGGATTCACCG SS1_F08-U674-22 TTGTCCTGTTGCCAGTGTCACA SS1_F11-U GGAAGCGGATTCGACGAAATGGAG SS1_F11-U4-23 TCAGTTGAGCGGGATAAGGAGAA SS1_F12-U11-28 GCATTAGTACCAATTGTTGACTCTAGCC SS1_F12-U1-25 GGGTCAGTCGAGCATTAGTACCAAT SS1_G03-L926 CTTGCCCAGCATGTCAGAGAGA SS1_G03-L926 CTTGCCCAGCATGTCAGAGAGA SS1_G03-U475 ATGACGGCAGTCCTACAATCAG SS1_G03-U475 ATGACGGCAGTCCTACAATCAG SS1_G03-U66 TACGAGCGGAGCAAGAACCAC SS1_G03-U87 CCACTACCAGGAACAGCACAT SS1_G04-U29-22 GTTGCGTTGTGGAGCCCAACTA SS1_G04-U66-25 AGACCGTCGGGTTCCACTAGTTTTA SS1_G05-U177-25 GCTGCCGTAGCTGGTATGTAATGAC SS1_G05-U91-27 GGGAATACACAAAGGCTCCTTGAATTG SS1_G09_FA CTGCAGA GAAGCAGCAGGCATCGG SS1_G09_FB GTCGCGTTTCCAAACACTCCGACGACTAGG SS1_G09_RA CTAGTCACAATCCGAAGTGCTGTGCTGTGC SS1_G09_RB ATCGGAACCTGTCCTAGAGCAAGTAGCAGC SS1_G09_RC GTGTAGTAGGTC AGACGCCTGCTAATGCC SS1_G09-L1175 TGGATCGGAACCTGTCCTAGAG SS1_G09-L1175 TGGATCGGAACCTGTCCTAGAG SS1_G09-L175 CCGACTG ATCCATCCGCACAAG

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81 Table 4-5. Continued Name Sequence SS1_G09-L291 CCAATCTAGAGGAGGATTAGAGAGG SS1_G09-L416 TCTAGTCACAATCCGAAGTGCTGT SS1_G09-L425 CATGTCATGTCTAGTCACAATCCG SS1_G09-L565 GAGTACAGTGTAGTAGGTCAGAC SS1_G09-U491 GAACGGGGAAACACACCTTTATTG SS1_G09-U491 GAACGGGGAAACACACCTTTATTG SS1_G09-U60 GAGATAGATAGTTAGGTTTAGCCC SS1_G12-U1-22 GGGTCAGTTGAGCAAGTTTAGG SS1_G12-U39-24 TGGGTTCACATTCCTGTTTCAAGG SS1_H11-U377 TCTTCTTGGGGTTGGCAGCCAG SS1_H12-U231-22 AGGATTATCACCCCAGGTTCTC SS1_H12-U311-24 CAGCAAGTCGAGCTCTAGCATGAG SS2_A06-L1564 AGGTGGTGGTGGAGATGGAGT SS2_A06-L1564 AGGTGGTGGTGGAGATGGAGT SS2_A06-U952 GGCACCGCAAGCAGTAAAAACA SS2_A06-U952 GGCACCGCAAGCAGTAAAAACA SS2_A08-L2045 CCCCTTAGC ATTGAGACTACAAA SS2_A08-L2045 CCCCTTAGC ATTGAGACTACAAA SS2_A08-U1251 ATCGCAACATCACAAGGCTAACC SS2_A08-U1251 ATCGCAACATCACAAGGCTAACC SS2_A09 _FA TACGGTGGCACGGTGCGTATGT SS2_A09_RA CACAGCTGGCGAACCAAACACCT SS2_A09-L1267-22 CTGATGAGTTAGACATGAGTGC SS2_A09-L1322-24 TTGGACCTAGTAGCAGCAGTCATG SS2_A09-L1355-24 AGAGTGCTCTACACGATAGAGACT SS2_A09-U1 GAGCAGCAACATAACCACAAAAAACTA SS2_A09-U119 ACTGCCTATCTCATCGAGCACCTC SS2_A09-U1-24 CAATGTTGATGTGGGACTTCTCTT SS2_A09-U25 CTAAGAGAATGGAGACGCAGTAG SS2_A09-U659-23 ACAGAAGACCGAATCACTTCAGG SS2_A09-U693-26 AACAGAGCACAGCTTTGAACCACTGC SS2_A11-U130 AATACCAGTTTCCCCTTTTACGATGC SS2_B02-L1457-23 CTGGCTACTGGAGCAAATACCTC SS2_B02-U173-23 TTGTTGGTGGATGATCTGAGCAG SS2_B02-U385-22 CCGTACAGTCCTCAGCAGAATG SS2_B02-U526-22 AGGTGCCCAACCAAGAGTGTAG SS2_B02-U64 ACACGTCCAGAGGTAGAAGAGGCT SS2_B04-L581 GGCGATCTTAACTCTTCACTAGAA SS2_B04-L581 GGCGATCTTAACTCTTCACTAGAA SS2_B04-U170 TCGGCATATCTATACTCTCGTG

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82 Table 4-5. Continued Name Sequence SS2_B06-L435-22 ATCACTCGTGCTGTCGCTACTT SS2_B06-U1-22 GAGCAGCACCATAACCAACTTAATG SS2_B06-U162-22 ATAGATGACCCTCCACAGACCT SS2_B06-U520 CGGGCTGCTGGACTGGACCAAATT SS2_B09-U1925 CGCCGAGCTGCGTCTGTAAAATC SS2_B09-U482 ATTGCCCGCTTCACCTCCATACG SS2_C07-L218 CTAACTGTACCGTGCGGATGAGAG SS2_C07-U1 GCTGCTGCTGAGGTCGATCAC SS2_C11-L4339 GCTCAGGCATCACCTAATGTGTA SS2_C11-L4339 GCTCAGGCATCACCTAATGTGTA SS2_C11-U3448 GACTTCTCCATCCTTGAAATCC SS2_C11-U3448 GACTTCTCCATCCTTGAAATCC SS2_C12-U765 CGGGGTATTTTCTCGATATTTTCTTG SS2_D01-U266 CCACGTTTATTTACTTTCACTTTCAC SS2_D01-U470 TATTGCGGTGTTGGTTCTACAATGTC SS2_D02-L536-24 GTGAAGGACCATAAGGCAGATAAG SS2_D02-U186-23 TGGCAGGGGCATCCATTTCATCT SS2_D02-U368-26 TTTGCAGGCTCCCTATCCTACATAGC SS2_D02-U426-24 CTTATAACGTACTGCCGAGAGCGC SS2_D02-U477-25 CAGCTTCACTACAGCCATGCTCTTC SS2_D09-L1463-24 CTAGTACCAGCTTATCGCCAACCG SS2_D09-U1094-23 CACAATCGGTCCAACAAGTCAAC SS2_D09-U205 ACAATCGGTCCAACAAGTCAACTG SS2_D09-U514-23 GACCAGTGGCTCTATACAGATTG SS2_E01-L752 CGCCTCG TCCTTCTCGTCCAGG SS2_E01-U223 TGGCAAGCCGGACACAGTAGCACG SS2_F02-L1270-23 CCAACCTACCACGAGCATACTTC SS2_F02-U540-24 GCATTGATCACGAGGTGAGGTCTC SS2_F02-U691-22 ATGGGCTCCAACACGATACACG SS2_G06-L4344 TGGGCAGGGGGTCAACCTATAT SS2_G06-L4620 ATCATAAGACAGGGCAACGATAAAAA SS2_G06-U3976 CTGACGCTGCGGTTGTTTCTTG SS2_G06-U4120 CTCT CTTCCCCGTTCCTCTGTA SS2_G12-L1310-25 AACATCTTCCTCGCACCAATAACTC SS2_G12-U646-23 CAAACCGATGAACGACGACACTG SS2_H05-L1234-23 GGGTACTAGGCTAGAAAGAGTTG SS2_H05-U637-23 GAGGAAGTGATCCCACCATGTTC SS2_H05-U747-24 CCACTCTGAGCCATACGTCAGCAT SS2_H06-U318-23 CCTAA CCATACAGGTGACCTTGC SS2_H06-U757-23 AGGGCTGTTCAACAACATGATCG

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83 Table 4-5. Continued Name Sequence SS2_H06-U815-23 TCGTTGGTGCCTTTGAGATTGAC SS2_H09-U131-23 AAACC AGCAGTTCACCACCTCAA SS2_H09-U278-23 CCCATC ACTGAGCGTGTTCATAT SS2_H09-U508-23 TACAGGGCATGTTTCGGAAGAGG SS2-B02_FA ACTGTTGTAGCAGCAGCAAGGAGCATGCT SS2-B02_FB GACGTTCGGCTGCATCGTCTACGT SS2-B02_RA TCTGAGCACCTTGTGCTCTCTGCCAGTG SS2-B02_RB GGAAGATCTGCAAGTGTCCAGGTCTGG T SS2-D09_FA TAGACTTGTGCGTGCTCTGCCGCT SS2-D09_FB GGAATCGTCGAGTTCACTGGGAAGAATGGCG SS2-D09_RA AACTGCTGCCTCTACTCCGCCTACTTC SS2-D09_RB GCGACAGCTCAACCGAATGAGACATCTC SS2-F02_FA ATCCGGAGGCACGACCAGACCATCT SS2-F02_RA AGCTGGCGGCTGAGGTCATCATTCC SS2-G12_FA TAGAATGGCGAGGCCCGATCTTCC SS2-G12_RA GACAACACGAGCACGTGCACGACAGCTAA SS2-H05_FA TGCCGGCTAGTATGTGATGTCCTCTGAATG SS2-H05_FA AACAATGGCGACTGAGTGCTGAGGAAC SS2-H05_FA TGCCGGCTAGTATGTGATGTCCTCTGAATG SS2-H05_RA_ AAGGAGCCGATGAGGATGTCGACATCGA SS2-H05_RB TGGTAGACCTGTCCACCGAATTGGTGG SS2-H06_FA GTGCGTTGCATGTGGTCTGGTGGTAAC SS2-H06_FB CAGACGCGACATCCAGGAGCAGATGT SS2-H06_RA ATGCACACTGGAGGTCTAGAAGCGCTCAT SS2-H06_RB CATAGCTGGAGCAGCAGCAGGCTT SS2-H09_FA CAAGACGTTCGGCTGCATTGTCTATGTCC SS2-H09_FB TCATCTTCGACGAACAGGCTCAGTGGG SS2-H09_RA TATCCCTTCACTACCAGCCGTGCC SS2-H09_RB GAGGAAGATCCACAAGAGTCCAGGTCTGG

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84 CHAPTER 5 DISCUSSION Results from several experim ents have shown that the novel brown midrib mutant phenotype is different from the other known mai ze and sorghum brown midrib mutants. They show that the novel bm mutant does not have altered lignin content or modified lignin sub-unit composition compared to the wild-type controls. However, chemical tests, NIR spectroscopy and thermal analyses have been unable to identify the compound that is causing the orange-brown coloration. The brown coloration is, however, located in the sc lerenchyma tissue (Figure 3-9). The most distinctive feature of sclerenchyma cells is their thickened and lignified primary cell walls (Raven et al., 1999). Enzymatic saccharification experiments show that the bm mutant and the wild-type plants yield similar glucose amounts. The result suggests that the bm mutation does not impact the yield of glucose obtained after enzymatic sacch arification. In contrast the data from NIR analysis suggest that the mu tant has an abundance of carbohydr ates. Since cellulase enzymes were used in this experiment, the glucose yield was as a result of the hydrolysis of cellulose microfibrils. These data are, however, not conc lusive because cellulase enzymes used in the enzymatic saccharification experiments only hydrolyze cellulose fibers and do not act on hemicelluloses and other carbohydrate sources. In order to get a comp lete picture, there is need to include hemicellulases in the enzyme cock tail to make sure that all carbohydrates are hydrolyzed to their individual monosaccharides. Field trials revealed variation in plant height between controls and bm mutants, which provides evidence for a relationship between th e mutated gene and plant development. The bm mutant plants were shorter than their wild-type counterparts when grown in field trials in two consecutive seasons: fall 2006 and summer 2007. Vermerris et al. (1999) showed that bm1 and

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85 bm2 not only have an effect on lignin biosynthesis, but also on flowering dynamics and plant height. The height differen ces between wild-type and bm mutant plants suggest that the bm mutation has an effect on plant height. However, there were also signific ant height differences between the wild-type plants grown in fall 2006 and the wild-type plants grown in summer 2007. Fall 2006 wild-type plants were on average 21 cm shorter, across four re plications, than the summer grown wild-type plants. Similarly, the fall 2006 bm mutant plants were on average 34 cm shorter, across four replications than the summer 2007 bm plants. The differences in heights among same genotypes between the seasons could be due to changes in photoperiod or field management. In fall the day le ngth is shorter and, therefore, it is possible that both bm mutant and wild-type plants will be shorter compared to the summer crop. On the other hand, time to silking was not statistically different for the same genotypes between seasons, i.e. between fall 2006 and summer 2007. Since maize is a day-neutral pl ant, the day length di fferences in fall and summer were not expected to have any effect. The re sults from this study indicate that there is no effect from the bm on silking dynamics. However, while th ere were no differences in time to flowering in summer 2007, the plants that were grown in fall 2006 showed significant differences. It is possible that the mutant is sensitive to short days in the fall. However, more evidence would be required before drawi ng any conclusions based on these data. It can be hypothesized that the reduced height of the bm mutant is due to the accumulation of the orange-brown compound in the sclerenc hyma tissue in the midrib. Thus, the overproduction of the orange-brown compound could be diverting crucial intermediates from a pathway that is vital for producing phytohormone s (possibly gibberellin s) involved in plant development. Fray et al. (1995) showed that constitutive expression of phytoene synthase in tomato resulted in the overproduction of phyt oene synthase, which converts geranylgeranyl

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86 diphosphate to phytoene and, thereb y, diverts this intermediate away from the gibberellin and phytol biosynthetic pathways. As a re sult the tomato plants were dwarfs. However, it is possible that the bm phenotype is caused by over-expression of the mutated gene, thereby causing the overpr oduction of the orange-brown pigment in the sclerenchyma cells. Careful examination of the wild-type interc ellular space in the sclerenchyma shows that it is pink in color. We could, ther efore, hypothesize that the wild-type gene codes for a protein that represses the production and accumulation of the or ange-brown pigment in the sclerenchyma. It is also possible that bm is a dominant modifier of expres sion. Chopra et al. (2003) described a dominant factor named Ufo1 (Styles et al., 1987) which modifi es the organ-specific expression patterns of the P1-wr allele. Ufo1 was originally identified becau se of its ability to induce orange-red pigmentation (phlobaphe nes) in vegetative and floral tissues of maize plants, which normally do not accumulate significant amounts of phlobaphenes. Along the same lines, the phenotype of the bm mutant could also be due to a gain-of-function mutation whose gene product becomes constitutively active or gains a novel function normally not found in the wildtype protein. Lu et al (2006) characterized the orange ( or) gene mutation in cauliflower ( Brassica oleracea var. botrytis ) that confers the accumula tion of high levels of -carotene in various tissues normally de void of carotenoids. The or gene mutation is due to the insertion of a long terminal repeat retrotransposon in the Or allele. Since the bm mutant was identified from a trans poson-active, mutagenic population, there is a high probability that a Mu element is inserted in the causal gene. Therefore, the assumption is that the insertion of the Mu element disrupts the normal tran scription and expression of the gene.

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87 While co-segregation analysis showed that none of the candidate genes segregate with the phenotype, there are several reasons to believe that Mu -TAIL PCR did not faithfully amplify all the Mu -flanking genomic sequences. Acco rding to Settles et al. (2004), Mu -TAIL PCR only samples 67-86% of the Mu insertion sites in the genomes they tested. This leaves a significant number of inserts potentially unsequenced. The major reason is due to the failure of the 12 arbitrary primers to amplify all maize genic sequences robustly (Settle s et al., 2004). Studies showed that the 12 optimized arbi trary primers amplify 95.6% of the Mu insertion sites within a genome. These 12 arbitrary primers were de signed from the 100 most over-represented sequences found in the maize genome. This potentially excludes 4.4% part of the genome in which Mu -adjacent sequences are not amplified. There has been more evidence that has since been accumulated that points to the bias of the arbitrary primers in Mu -TAIL PCR (Koch, personal communication). It is therefore, likely that Mu -TAIL PCR might not have amplified all the Mu flanking genomic sequences in the bm mutant genome. In addition, Settles et al. (2004) reported that there is a subset of maize gene sequences that appears to be resistant to Mu -TAIL analysis. For example, even though in this study they tested a large number of lines that contained the bz1-mum9 locus, they did not identify the locus in the Mu -TAIL sequence libraries. This limitation is not only unique to Mu -TAIL analysis, but to all other flanking PCR methods. These include adap ter-mediated PCR and inverse PCR methods. Despite the afore-mentioned limitations, Suz uki et al. (2006) and Porch et al. (2006) successfully cloned the mo lybdenum cofactor biosynt hetic protein gene ( Cnx1) and the maize viviparous15 gene ( Vp15) using the Mu -TAIL PCR method. These result s show that despite its limitations, Mu -TAIL PCR can be successfully used to clone genes where Mu has inserted.

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88 Another explanation for the inability to identify a PCR product representing a Mu -flanking DNA fragment that co-segregated with the bm phenotype is that the mutation is a Mutator suppressible phenotype. Martiensse n et al. (1990) showed that the phenotypic effects of Mu element insertion sometimes depend on transpos on activity. They described a maize mutant, high chlorophyll fluorescence106 (hcf106), which conditions a pale; non-photosynthetic phenotype caused by the insertion of a Mu1 element in the 5 untranslated region (UTR). The hcf106 phenotype is only expressed when the Mu transposon system is active, where the insertion interferes with the accumulation of Hcf106 mRNA. When the Mu is inactive, the mutant phenotype is suppressed, and plants homozygous for the hcf106 mutation exhibit a normal phenotype. This is because when Mu becomes inactive, the promoter near the end of Mu1 is activated and it directs transcription outward, into the adjacent hcf106 gene (Barkan and Martienssen, 1991). They go on to suggest that hcf106 is a prototype for wh at may be a frequent class of Mu -induced mutations whose phenotypes are modulated by the phase of Mu activity. In fact, several Mutator-suppressible phenotypes have been described and include maize knotted1 gene (Greene et al. 1994), rough sheath1 and liguleless3 (Girard and Freeling, 2000) and les28 (Martienssen and Baron, 1994). The mechanism by which phase of Mu activity regulates the hcf106::Mu promoter is not known. Bark an and Martienssen (1991) hypothesize that there is a factor that is only expressed when Mu is active that binds to the Mu termini and represses transcription. Since the bm mutant phenotype has never been recovered from plants grown from bronze kernels (which are presumed to be Mu -inactive) after the bm mutant was backcrossed to a color-converted purple W22, it can be hypothesized that orange-brown ph enotype is dependent on Mu -activity. Consequently, co-segregation analysis would be affected. It will be hard to identify a co-segregating fragment, because a plant homozygous for a Mu inser tion in the Bm

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89 gene would have a wild-type phenotype if Mu became inactive, but would also generate a PCR product indicative of the mutation.

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90 CHAPTER 6 FUTURE WORK In order to circum vent the limitations associated with Mu -TAIL PCR and other PCR methods that are designed to amplify flanking DNA for that matter, a new method, 454Mu direct, has been suggested. Mu -direct is a highly efficient prot ocol for sequencing large numbers of germinal Mu insertion sites in the Uniform Mu population based on the massively-parallel 454 DNA sequencing platform developed by 454 Corp (Margulies et al., 2005) ( http://currant.hos.ufl.edu/mutail/454/454_summary.htm ). This m ethod is currently being tested and the details are still to be released. It is e xpected that this new protocol will be able to significantly increase the chances of amplifying all Mu -flanking genomic sequences. Enzymatic saccharification experiments showed th at stover material from wild-type plants and bm mutant plants yielded equal glucose levels. This process onl y used a cocktail of cellulase enzymes that hydrolyzed cellulose microfibrils. However, NIR anal ysis results suggest that the mutant has an abundance of car bohydrates. It is, therefore, a worthy idea to carry out an experiment that hydrolyzes all types of carbohydrates from the w ild-type and mutant samples. Saha and Cotta (2007) described an enzymatic hydr olysis protocol that contains cellulases, hemicellulases and xylanases. Such a protocol for maize would be able to give a detailed composition of stover material than the protocol used in our study. There is a possibility th at the mutation causing the bm phenotype was a spontaneous event. In that case map-based/positional cloning can be us ed to identify the causal gene. This method is, however, time consuming. Microarray analysis can be used to id entify up and down-regulated genes that can potentially explain the biological basis of the bm mutation. However, Shulze and Downward (2001) concluded that using microarray analysis to try and iden tify individual genes that are

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91 differentially expressed has not been the most successful use of microa rray technology. This is because a given stimulus or phenotypic differences could potentially lead to changes in the mRNA levels of hundreds of genes. However, these limitations can be minimized by careful experimental design. Nonetheless, changes in mRNA levels of hundreds of genes could provide some valuable information that if used in conj unction with information that is now known could provide important clues. As hypothesized earlier, the bm mutant could be a Mu -suppressible mutant, whereby, the mutant phenotype is dependent on Mu -activity. In this case, the bm mutant phenotype will only show when Mu is active. However, when Mu is inactive, the mutant phenotype is suppressed and the plants homozygous for the bm mutation will exhibit a normal phenotype. To test if this is the case, co-segregation analysis results have to be analyzed and identify primers that resulted in amplification in all 21 bm individual plants. By selfing th e normal plants, which could be homozygous (wild-type or mutant with inactive Mu ) or heterozygotes, the color of the kernels will reveal whether the bm is a Mu -suppressible mutant or not. In addition, methylation experiments will have to be done to find out the methylation status of the gene in question. To change the phase of the Mu element the bm mutant will have to be back-crossed to a Mu -off line. If the bm mutant is a Mu -suppressible mutant phenotype, then it is expected that after backcrossing to a Mu -off line, it will no longer show the bm phenotype. It is possible that there is a Mu -insertion in or near the bronze (Bz) locus that is causing the ectopic accumulation of the brown pigment in the sclerenchyma tissue. This hypothesis is based on an observation made by Rhoades (1952) that in Bz plants, no brown pigments are present and the anthocyanin is confined to the vacuoles. However, bz plants have deeply-colored, brown cell walls and greatly reduced amounts of anthocyanin in the vacuole. The bm mutant came out of a

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92 Uniform Mu population that used the bronze1 mutation as the marker gene and it ectopically accumulates a brown pigment in the cell walls of sclerenchyma cells. To test this hypothesis, upper and lower primers that flank the hypothetical Mu -element have to be designed. These will be used in combination with the Mu -TIR primer to test if the 21 individual bm mutant plants from a segregating population carry a Mu -insertion in the Bz1 gene. PCR products will be expected from all the 21 bm mutant individuals if there is a Mu -insertion in or near the bronze locus but not from homoz ygous wild-type individuals.

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108 BIOGRAPHICAL SKETCH Reuben Tayengwa was born on February 2, 1977 in Harare, Zim babwe. The fifth child of seven children, he grew up mostly in Harare, graduating from an Anglican High School in 1994. After graduation he was offered a scholarship to attend an international United World College institution in Norway. He earned an Internati onal Baccalaureate Diploma in 1997 at the college before returning to Zimbabwe in 1997. He took a year off and travelled to England, Denmark, and Germany to visit friends and relatives. In 1999 he enrolled at the University of Zimbabwe in the capital Harare. Upon graduating in August 2002 with a BSc. in Crop Science, Reuben joined a private company that specialized in developing and distributing elite plant cu ltivars to poor rural farmers. Reuben worked in a lab as well as th e field, developing disease free sweet potato, Irish potato and cassava planting material using tissue culture methods. Mo st of the planting material was distributed to families that had members suffering from HIV AIDS. Reuben was involved in instructing the families on the best agronomic methods to grow the crops as well as how to market the yield to their neighbors. In 2004, Reuben joined a Swedish NGO, Swed ish Co-operative Center, to continue working on the same project, but at a national level. He was responsib le for a large district in the rural southern part of Zimbabwe. In early 2005, Reuben decided to go back to sc hool and joined Dr. W ilfred Vermerris lab at Purdue University to pursue a masters de gree. When Dr. Vermerri ss was offered a new position at the University of Fl orida, Reuben followed him to Florida where he completed his studies. In fall 2008, Reuben will join the Mole cular Plant Sciences program at Washington State University as a PhD research assistant.