A quantitative genetics and ecological model system: Understanding the. aliphatic glucosinolate biosynthetic network via QTLs

Transcription

1 A quantitative genetics and ecological model system: Understanding the aliphatic glucosinolate biosynthetic network via QTLs Daniel J. Kliebenstein 1 1 Department of Plant Sciences University of California, Davis One Shields Avenue Davis, CA USA Corresponding author: Kliebenstein, D.J. (kliebenstein@ucdavis.edu) The author has no conflict of interest to report with regards to this review. 1

2 Abstract Key Words: glucosinolate, quantitative trait, QTL, system biology, maintenance of diversity Abbreviations QTL Quantitative trait locus. GSL-() QTL for glucosinolates. GSL-OX QTL for conversion of methylthio to methylsulfinyl glucosinolate. GSL-Elong QTL for controlling side-chain length of glucosinolates. GSL-ALK QTL for production of alkenyl glucosinolates. GSL-OHP QTL for production of hydroxalkyl glucosinolates. GSL-AOP QTL for production of alkenyl or hydroxyalkyl glucosinolates. GSL-OH QTL for production of hydroxylalkenyl glucosinolates. FMO flavin monooxygenase BCAT branched chain amino transferase CYP cytochromes P450 PMSR peptide methionine sulfoxide reductase MAM methylthioalkylmalate synthase UGT UDP-glucosyl transferase ST Sulfotransferase 2

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4 Introduction Plants sessile nature forces them to directly cope with environmental changes rather than escape to more favorable sites. Secondary metabolites are a large and diverse set of small organic compounds that enable plants to respond to these environmental challenges, including insect herbivory, pathogen invasion, UV-B radiation, and drought. The currently known >100,000 secondary metabolites probably represents a minority of the total (Wink, 1988) with this large chemical diversity presumably arising from a vast set of biosynthetic enzymes. While numerous studies have biochemically investigated the enzymes and regulatory factors controlling biosynthesis of secondary metabolites, little is known about the genetics or ecology controlling quantitative and qualitative variation in secondary chemistry in wild plants. The easy detection of numerous secondary metabolites makes them an optimal model trait to investigate complex quantitative genetics and the pressures that maintain this variation. A model system for understanding complex quantitative traits with potential ecological importance are the glucosinolates, amino acid derived thioglucosides specific to the order Capparales (Bones and Rossiter, 1996). Plants utilize a three part biosynthetic pathway to produce glucosinolates from methionine, phenylalanine and other amino acids (Hogge et al., 1988; Halkier and Du, 1997). This involves carbon chain elongation of a protein amino acid, entrance of the amino acid into the core pathway and finally side chain modification (Kahn et al., 1999; de Quiros et al., 2000; Graser et al., 2000; Wittstock and Halkier, 2000; Kliebenstein et al., 2001a; Hansen et al., 2007; 4

5 Textor et al., 2007). Tryptophan derived glucosinolates do not go through the chain elongation component. The final glucosinolates form a bipartite defense system such that upon tissue disruption, a myrosinase enzyme cleaves the sugar from the glucosinolate, and a series of toxic compounds are released (Burow and Wittstock, This Issue). Glucosinolates and their breakdown products alter insect herbivory (Li et al., 2000; Lambrix et al., 2001; Barth and Jander, 2006; Zhang et al., 2006; Lankau, 2007), plant-plant interactions (Lankau and Strauss, 2007), nematode survival (Donkin et al., 1995), and fungal resistance (Mithen et al., 1986; Tierens et al., 2001). The diverse biological roles played by glucosinolates are controlled by variation in the final glucosinolate structure and the amount of glucosinolate. This variation is controlled by numerous qualitative and quantitative loci for both the type of glucosinolate produced (Magrath et al., 1994; Parkin et al., 1994b; Mithen et al., 1995; Giamoustaris and Mithen, 1996; Kliebenstein et al., 2001b; 2001c) and the amount of glucosinolate produced (Toroser et al., 1995; Kliebenstein et al., 2001b; Wentzell et al., 2007). This variation exists in multiple species and is frequently controlled by homologous genes in each species. More importantly, it is this natural genetic variation in the glucosinolate system that controls variation in plant/biotic interactions (Mauricio and Rausher, 1997; Li et al., 2000; Lambrix et al., 2001; Zhang et al., 2006; Lankau, 2007; Lankau and Strauss, 2007). This genetic diversity suggests that the glucosinolates are important for controlling variation in crucifer fitness. The recent identification of most biosynthetic pathway genes and numerous regulators makes the glucosinolate pathway an optimal 5

6 system for studying important quantitative genetics or ecological questions (Halkier and Gershenzon, 2006; Gigolashvili et al., 2007; Hirai et al., 2007; Sønderby et al., 2007; Wentzell et al., 2007). These questions include why does genetic variation in a trait exist, what genes control this variation and does variation at one locus impact variation at another locus (Mackay, 2001). This review article will discuss how these questions are being or can be addressed within the context of the glucosinolate biosynthetic pathway. Structural genetic variation in glucosinolates Variation in glucosinolate structure both within and between different species has long been a noted characteristic of this group of secondary metabolites. In contrast to phenylpropanoids and isoprenoids that have 10 s of thousands of structures, glucosinolate structural variation does not appear open ended. Plants within the order Capparales appear to resample the same set of glucosinolate structures (Rodman, 1980; Rodman et al., 1981; Daxenbichler et al., 1991). This resampling is capable of generating a significant level of secondary metabolite diversity within the crucifers without requiring glucosinolates to have as many different structures as other plant secondary metabolites. This biosynthetic diversity of the glucosinolate system is further expanded upon by structural modifications during glucosinolate activation (Burow and Wittstock, This Issue). Glucosinolate structural variation is under genetic control allowing the causes of this variation to be studied in the Brassica s using structured mapping 6

7 populations (Magrath et al., 1994; Parkin et al., 1994a; Mithen et al., 1995; Mithen and Toroser, 1995; Giamoustaris and Mithen, 1996). This generated a model whereby there are four major biosynthetic loci, GSL-AOP, -ELONG, -OH and -OX, controlling structural variation in methionine derived glucosinolates (Figure 1 and 2). These four loci function epistatically to generate a modular genetic system whereby the four loci allow the plant to generate 14 different structural profiles (Figure 1). Thus, a plant population can quickly shift between these profiles via mutation, migration or recombination allowing for rapid evolution in glucosinolate structural variation with a minimal amount of genetic polymorphism (Kliebenstein et al., 2001c). However, not all of the 14 different profiles appear equally fit as some occur more frequently than expected and others significantly less frequently (Figure 1). Of ecological and evolutionary importance, the presence and absence of these four structural loci explains a significant fraction of aliphatic glucosinolate variation in most major crucifer genera including Streptanthus, Cakile, Brassica and Arabidopsis (Rodman, 1980; Rodman et al., 1981; Magrath et al., 1993; Windsor et al., 2005). This raises the interesting question about how the same apparent biochemical polymorphisms can evolve and exist in widely divergent plant families. Additionally, why do crucifers frequently resample the same structural variation rather than generate new structural variation as occurs in other secondary metabolite pathways? Answering these questions requires the identification of the causal genes for each polymorphism in each species and 7

8 progress towards these ends will be discussed in the ensuing section of this review. GSL-AOP The GSL-AOP structural locus was first identified as the GSL-ALK locus controlling the presence or absence of alkenyl glucosinolates within Brassica mapping populations (Mithen et al., 1995; Mithen and Toroser, 1995; Giamoustaris and Mithen, 1996; Raybould and Moyes, 2001). Next, a GSL-OHP locus was identified that controlled the presence or absence of hydroxyalkyl glucosinolates within Brassica and shown to be an allele of GSL-ALK. As such, the GSL-AOP locus was defined as a single genetic locus potentially containing an OHP allele, ALK allele or a null allele whereby the plant accumulates methylsulfinyl glucosinolates (Kliebenstein et al., 2001b; 2001c). GSL-AOP was shown to control plant resistance to a number of biotic stresses including multiple herbivores (Mithen, 1992; Giamoustaris and Mithen, 1995; Kliebenstein et al., 2002b). GSL-AOP was cloned in Arabidopsis and shown to be two tandem genes, AOP2 and AOP3, which control all three GSL-AOP allelic states in both Arabidopsis and Brassica (Kliebenstein et al., 2001a; Li and Quiros, 2003)(Table 1). AOP2 is the enzyme for the production of alkenyl glucosinolates while AOP3 is the enzyme for the production of 3C hydroxyalkyl glucosinolates (Table 1)(Kliebenstein et al., 2001a). In the GSL-ALK allele, the AOP2 gene is expressed while the AOP3 gene is not expressed in rosette tissue. In contrast, within the GSL-OHP allele, the AOP3 gene is expressed while the AOP2 gene is 8

9 silent. For the null allele, neither AOP2 nor AOP3 is expressed or functional leading to the accumulation of the precursor methylsulfinyl glucosinolates (Figure 1)(Wentzell et al., 2007). While the cloned AOP2 and AOP3 enzymes remove the methylsulfinyl moiety during their reaction, some plants such as Raphanus sativa contain glucosinolates with both the alkenyl and methylsulfinyl moiety yet it remains to be determined if these glucosinolates are produced by AOP2/AOP3 homologues or other previously unidentified glucosinolate biosynthesis genes (Daxenbichler et al., 1991). One interesting facet of the GSL-AOP locus is that it acts as a single genetic locus with no published reports of any mapping population having functional AOP2 and AOP3 both on the same chromatid (Parkin et al., 1994b; Mithen et al., 1995; Giamoustaris and Mithen, 1996; Mithen and Campos, 1996; Kliebenstein et al., 2001b; 2002a; 2002b; Pfalz et al., 2007; Wentzell et al., 2007). The published and unpublished Arabidopsis mapping populations represent thousands of meiotic events that should have allowed for recombination between AOP2 and AOP3. This lack of recombination suggests that there may be a mechanism preventing recombination between these genes. Sequencing of the GSL-AOP locus in Arabidopsis has shown that the difference between the GSL-ALK and GSL-OHP alleles is a local inversion involving AOP2 and AOP3 such that the two genes have flipped and there is only one functional promoter within the locus. This local inversion likely causes a localized suppression of recombination preventing the two alleles from combining. Another possibility is that the two enzymes may interfere with each other and as such the 9

10 plant has evolved this complex genetic structure to separate them. However, heterozygous progeny containing the two alleles on opposite chromatids show no evidence of inhibition between the two enzymes (Daxenbichler et al., 1991; Mithen et al., 1995; Mithen and Campos, 1996; Kliebenstein et al., 2001b; Pfalz et al., 2007). Another fitness related possibility is that the presence of both alleles in one plant may diminish the defensive capacity of the plant. This agrees with the observation that no wild collected plants have both hydroxyalkyl and alkenyl glucosinolates in the same leaf (Daxenbichler et al., 1991). As such, the unique inversion structure of this locus may be of selective benefit to the plant by forcing the two genes to act as a single genetic locus. Fitness consequences of the different GSL-AOP alleles remain to be tested in the field. GSL-ELONG The GSL-ELONG locus is responsible for Arabidopsis and Brassica making either predominantly 3 or 4-Carbon aliphatic glucosinolates (Mithen et al., 1995). In Streptanthus, GSL-ELONG also appears to have evolved a 5-Carbon allele and other species have even longer chain glucosinolates that may be caused by evolution at this locus (Rodman et al., 1981; Daxenbichler et al., 1991). The causal basis of this locus is a family of methylthioalkylmalate (MAM) enzymes that are under positive selection potentially for new biochemical activities (Kroymann et al., 2003; Textor et al., 2004; Benderoth et al., 2006; Textor et al., 2007; Kroymann et al., This issue). The MAM family is also the source of polymorphism leading to the GSL-PRO locus that blocks aliphatic 10

11 glucosinolate synthesis in Brassica (Gao et al., 2007). The molecular basis of natural variation at GSL-ELONG within the Brassicaceae is distinct from the GSL-AOP in that GSL-AOP is controlled by the presence or absence of specific genes and GSL-ELONG uses both presence/absence and repeated evolution of new amino acid sequences and hence biochemical activities. It is possible that this difference in the molecular pattern of evolution at the two loci is that both GSL-ALK and GSL-OHP have only two potential states, on or off. In contrast, GSL-ELONG genes have at least 10 potential biochemical states, adding 0 to 9 different carbons to the entering methionine (Daxenbichler et al., 1991; Textor et al., 2007). It is possible that the different causal polymorphism patterns may allow the plants to efficiently sample the maximal potential variation at each locus. GSL-OX The GSL-OX locus is responsible for the oxygenation of a methylthioalkyl glucosinolate to its methylsulfinylalkyl structure (Figure 1 and Table 1)(Mithen et al., 1995; Giamoustaris and Mithen, 1996; Kliebenstein et al., 2001c). In some Arabidopsis populations, there are multiple QTLs controlling GSL-OX and a forward genetics screen of Arabidopsis mutants also identified multiple modifier loci complicating genetic approaches to identify the causal basis of this structural polymorphism (Kliebenstein et al., 2007; Wentzell et al., 2007). The majority of this appears to be due to regulatory polymorphisms controlling the expression of the actual GSL-OX enzyme allowing this to act as a single structural locus with 11

12 numerous modifiers (Hansen et al., 2007; Wentzell et al., 2007; West et al., 2007). Further biochemical identification of the enzyme controlling this reaction was also highly recalcitrant. The conclusive identification of the GSL-OX biosynthetic locus required a combination of genomics, enzymology and genetics (Hansen et al., 2007). In this analysis, fine scale-mapping of natural variation identified a subset of candidate genes that was further filtered by genomic analysis to find candidate genes co-expressed with the known aliphatic glucosinolate biosynthetic genes. This identified a crucifer specific family of flavin-monooxygenases that are the likely candidates for the GSL-OX QTLs and reaction (Hansen et al., 2007). One of these enzymes (FMO GS-OX1 ) was shown to control the enzymatic conversion of methylthioalkyl to methylsulfinylalkyl glucosinolate both in vitro and in planta. Similar to AOP2 and AOP3, this gene also showed naturally variable gene expression that appears to cause a GSL-OX QTL (Hansen et al., 2007; Wentzell et al., 2007). However, unlike GSL-AOP absolute loss of FMO GS-OX1 expression does not lead to a complete blockage of the GSL-OX reaction. This is likely due to the presence of the other FMO GS-OX1 gene homologues whose gene expression is also naturally variable and co-locate with other known GSL-OX loci (Kliebenstein et al., 2006; Hansen et al., 2007; Wentzell et al., 2007; West et al., 2007). The function of the flavinmonooxygenases homologous to FMO GS-OX1 remains to be proven but this system establishes a potential model whereby several QTL for the same enzymatic reaction may be caused by differential expression of gene family members. 12

13 Other biosynthetic loci The GSL-OH locus is polymorphic within a number of species and between species and controls the introduction of a hydroxyl into 4C or longer alkenyl glucosinolates. However, it is difficult to predict if inter- and intra-specific polymorphisms are due to new enzyme evolution as in GSL-ELONG or simple presence/absence polymorphisms as seen in GSL-AOP and GSL-OX. A presence/absence polymorphism is supported by the biochemical activity showing presence or absence variation within the Brassicas and Arabidopsis thaliana (Parkin et al., 1994a; Kliebenstein et al., 2001b; 2001c). However, the variation between species is more indicative of new enzyme evolution because the reactions stereochemistry of ranges from a mixture of R/S in Arabidopsis thaliana to mainly R in Brassica napus to mainly S in Crambe abyssinica (Daxenbichler et al., 1991; Parkin et al., 1994a; Daubos et al., 1998; Kliebenstein et al., 2001c). It is difficult to theorize how polymorphisms can cause a single enzyme to change its stereochemistry thus, suggesting that the different species may use different enzymes. However, the explanation of this sterochemical puzzle requires the identification of the underlying gene/s. The identity of the GSL-OH gene remains to be validated in part because of its dependency upon the allelic status at the other three structural loci limiting the potential germplasm within which this locus can be studied (Figure 1 and Table 1). While the epistatic network between the four major loci sets up a modular genetic system that may facilitate evolution, it also generates the potential to 13

14 miss significant QTLs that require specific allelic combinations at the four major biosynthetic loci (Figure 1 and Table 1). A detailed analysis of a large Arabidopsis population suggested that a biosynthetic enzyme was the basis of a QTL only when GSL-AOP and GSL-ELONG are in a single specific allelic combination (Wentzell et al., 2007). This enzyme, SGT74B1, catalyzes glycosylation of the characteristic glucosinolate backbone structure and has differential expression within Arabidopsis accessions likely due to a promoter polymorphism (Grubb et al., 2004; Wentzell et al., 2007). While we might predict that variation in the expression of SGT74B1 would influence production of multiple aliphatic glucosinolates, this locus only controlled one metabolic trait, the accumulation of but-3-enyl glucosinolate. The SGT74B1 enzyme is not specific to the synthesis of but-3-enyl glucosinolate, as previous work has demonstrated that it has broad glucosylation activity (Grubb et al., 2004). This QTL detection bias is likely because genotypes accumulating but-3-enyl glucosinolate also exhibit the highest level of total aliphatic glucosinolates (Figures 1 and 2 and Table 1)(Wentzell et al., 2007). Thus, the SGT74B1 expression polymorphism may only become limiting when flux across the biosynthetic pathway is above a certain high threshold. A similar relationship is observed for the SGT7471 enzyme in a different Arabidopsis population (Figure 2)(Gachon et al., 2005). This potential for interactions between the four major loci to limit the ability to detect additional biosynthetic QTLs raises the question of how many enzyme/qtl linkages exist in the aliphatic glucosinolate pathway. If we control for the effect of the four major structural polymorphisms we may find that the 14

15 majority of genes in the aliphatic glucosinolate pathway control quantitative variation in the accumulation of the metabolites. Very large populations would be required to test this hypothesis. Selection on structural diversity The repeated evolution of identical interspecific glucosinolate structural diversity between different crucifer species suggests that there may be selection pressures favoring the presence of structural diversity (Rodman et al., 1981; Daxenbichler et al., 1991). Supporting this concept is the observation that the frequency distribution of glucosinolate structural profiles is not random within Arabidopsis accessions (Kliebenstein et al., 2001c; Lambrix et al., 2001)(Figure 1). In Arabidopsis, some specific structural profiles are statistically overrepresented at the apparent cost of other structural profiles in comparison to an expectation of independent assortment. For instance 3-hydroxypropyl accessions appear to be favored over accession containing 3-methylsulfinyl glucosinolates (Figure 1). In accessions with the 4C GSL-Elong, this relationship is reversed such that the 4-methylsulfinyl profile is favored over the hydroxyalkyl profile (Figure 1). A potential alternative explanation for this distortion is population structure or migration history but this would have to ignore the differential impacts of these structural loci on insect herbivory (Kliebenstein et al., 2002b). Further supporting the concept that there is potential selection for diversity is the observation that glucosinolate gene expression amongst Arabidopsis accessions is under positive selection for diversity (Kliebenstein, 2008). In this study, the 15

16 glucosinolate biosynthetic genes were shown to have significantly elevated levels of gene expression polymorphisms in comparison to the average neutral gene as would be expected for genes under positive selection for diversity. This expression diversity shows the most extreme selection at the major structural loci (Kliebenstein, 2008). Thus, while the four structural loci establish a modular diversity system that can rapidly sample glucosinolate structural diversity, not all profiles appear equally fit. Now that nearly all the structural loci have or are nearly cloned, it will be possible to transgenically re-engineer these profiles and test their fitness in the field. Given that selection appears to act to maintain diversity, these field tests would have to be conducted in multiple years in multiple locations as it is likely fluctuating or balancing selection due to variable insect populations that is the major driver of glucosinolate variation (Hairston and Dillon, 1990; Ellner and Hairston, 1994; Tiffin and Rausher, 1999). Regulatory genetic variation in glucosinolates In addition to structural variation, there is significant natural genetic variation both within and between species that generates glucosinolate levels ranging across nearly two log orders within individual species. While the added complexity of measuring absolute accumulation has led to less focus on this topic, numerous QTLs have been identified that control glucosinolate accumulation both within the Brassicas (Toroser et al., 1995; Uzunova et al., 1995; Faulkner et al., 1998; Hill et al., 2003; Mithen et al., 2003; Lionneton et al., 2004) and Arabidopsis thaliana (Kliebenstein et al., 2001b; 2002a; 2002b; Pfalz 16

17 et al., 2007; Wentzell et al., 2007). Like the structural loci, these content QTL frequently overlap between the different species and within Arabidopsis these loci frequently overlap between populations (Figure 2). Recent work is beginning to identify the genes underlying the quantitative glucosinolate accumulation loci and this work is starting to explain long identified relationships between structure and content as well as illuminating the aliphatic glucosinolate regulatory genes regulating. These regulatory QTL will be the focus of the next section of this review. Structural QTLs and pathway regulation During the identification of the structural QTL, frequent observations identified a relationship between the glucosinolate structure and the level accumulation such that some structures accumulated to different levels (Toroser et al., 1995; Giamoustaris and Mithen, 1996; Kliebenstein et al., 2001b; Raybould and Moyes, 2001)(Figure 1). However the mechanism for how structure and accumulation were co-regulated was unknown. Recent global transcriptomics QTL approaches have begun to unravel mechanisms relating structure to potential accumulation. In these transcriptomics QTL experiments, microarrays are used to measure gene expression for all genes in a mapping population. This data is then used to map QTLs controlling gene expression for all genes, so called eqtls (Brem et al., 2002; Keurentjes et al., 2007; West et al., 2007; Hansen et al., 2008; Potokina et al., 2008). Given that most of the glucosinolate biosynthetic genes are known and there is an existing global eqtl analysis 17

18 within Arabidopsis, it became possible to compare eqtls controlling expression of the biosynthetic enzymes to the QTLs controlling the metabolites (Figure 2)(West et al., 2006; Wentzell et al., 2007; West et al., 2007). This comparison identified a number of eqtls controlling the expression of most if not all of the biosynthetic genes suggesting that these loci are regulatory eqtl controlling the aliphatic glucosinolate biosynthetic pathway (Wentzell et al., 2007). Unexpectedly, the GSL-AOP and GSL-ELONG QTL colocated with two regulatory eqtls controlling gene expression for the aliphatic glucosinolate biosynthetic pathway. This suggested that the structural loci may also be regulatory loci controlling pathway gene expression. This was further confirmed when introduction of AOP2 into a GSL-AOP null background increased transcript level for all genes in the aliphatic biosynthetic pathway. This suggests that in addition to controlling glucosinolate structure, some molecular property of the AOP2 gene controls glucosinolate accumulation by increasing gene expression and potentially flux through the aliphatic glucosinolate pathway (Wentzell et al., 2007). Similar variation in expression and possibly the presence of the MAM1 and MAM3 genes also associated with altered gene expression for the entire pathway. This suggests that the previously noted relationship between glucosinolate content and accumulation may occur because the structural QTL are also regulatory eqtl (Toroser et al., 1995; Giamoustaris and Mithen, 1996; Kliebenstein et al., 2001b; Raybould and Moyes, 2001; Wentzell et al., 2007). The mechanism by which these enzymatic genes may regulate gene expression for the aliphatic glucosinolate pathway is currently unknown. One 18

19 proposed explanation is that the AOP2 enzymatic reaction releases sulfur and this leads to increased sulfur availability and corresponding increases in aliphatic glucosinolate related transcripts under sulfur regulation (Kliebenstein et al., 2001a; Maruyama-Nakashita et al., 2006). This hypothesis predicts that because the AOP3 enzymatic reaction also releases sulfur, that AOP3 would also increase aliphatic glucosinolate related transcript accumulation. However, AOP2 s transcriptional effect is greater than AOP3 and AOP3 in the absence of AOP2 does not regulate glucosinolate accumulation (Kliebenstein et al., 2001a; 2001b; 2002a; 2002b). Further introduction of AOP2 does not alter levels of the sulfur regulatory gene EIL3/SLIM1 arguing against an involvement of sulfur in the AOP2 mechanism (Maruyama-Nakashita et al., 2006; Wentzell et al., 2007). A further argument against a sulfur availability explanation is that AOP2 releases one out of three sulfur molecules while doubling the aliphatic GLS content. As such, in the absence of AOP2, there is one unit of glucosinolate containing three sulfurs but in the presence of AOP2 there are two units of glucosinolate containing two sulfurs. Thus, AOP2 leads to increased sulfur demand and if sulfur deficiency was the explanation, AOP2 should inhibit gene expression, which is not the case. A final argument against a sulfur mechanism is that the GSL-ELONG reaction does not alter sulfur status in the plant but also controls gene expression. Future experiments are required to identify the molecular mechanism by which the structural loci control gene expression. MYBs and QTLs 19

20 In addition to structural enzymes, traditional transcription factors appear to be the basis of other regulatory eqtls that control glucosinolate accumulation. A set of three MYB transcription factors, MYB28, MYB29 and MYB76, have been found via numerous independent approaches to control aliphatic glucosinolate accumulation and gene expression for the biosynthetic enzymes (Gigolashvili et al., 2007; Hirai et al., 2007; Sønderby et al., 2007). The MYB28 gene co-localizes with one of three major QTLs for aliphatic glucosinolate content and gene expression within the Arabidopsis Bay Sha population (Figure 2 and Table 1)(Wentzell et al., 2007). Several lines of evidence strongly argue for MYB28 being the basis for this regulatory QTL. First, MYB28 has differential expression between the Bay and Sha parents that correlates with glucosinolate content such that the high glucosinolate Sha has higher MYB28 expression. Additionally, MYB28 underlies a QTL for both increased aliphatic glucosinolate content and increased gene expression for the majority of the biosynthetic pathway (Sønderby et al., 2007). Finally, transgenic manipulation of MYB28 s expression mimics the expression polymorphism between Bay and Sha for both aliphatic glucosinolate content and transcripts (Sønderby et al., 2007). Thus, it appears that variation in MYB28 controls this QTL within Arabidopsis and potentially a co-localized QTL in Brassica juncea (Lionneton et al., 2004). MYB29 and MYB76 are tandem MYB transcription factor genes that colocate with a QTL in the Ler Cvi population of Arabidopsis thaliana (Figure 2 and Table 1)(Kliebenstein et al., 2001b; 2002b). Of the two genes, only MYB76 20

21 shows an expression polymorphism within the Arabidopsis accessions and is likely the basis of this glucosinolate accumulation QTL (Kliebenstein et al., 2006). MYB76 has differential expression between Ler and Cvi and this differential expression is positively correlated with glucosinolate content. Further, there are no predicted functional polymorphisms in the MYB29 gene using genomic sequence from Ler and Cvi (Borevitz et al., 2007; Clark et al., 2007). Similar to the other glucosinolate loci, there is overlap in this genomic region with a QTL controlling aliphatic glucosinolate content in Brassica juncea (Lionneton et al., 2004). The identification of these MYBs as the likely cause of two regulatory QTLs within Arabidopsis and their association with similar QTLs in Brassica raises the possibility that like the structural diversity, the regulatory diversity of glucosinolates is also modular and utilizes similar genes in diverse species. Epistasis and gene regulation In addition to identifying structural and accumulation QTL, the previous research on quantitative glucosinolate variation also identified numerous epistatic interactions between these loci. The most obvious epistatic interactions were those between the four major structural loci that led to altered profiles of glucosinolates within the plant (Figure 1)(Magrath et al., 1994; Parkin et al., 1994a; Mithen et al., 1995; Giamoustaris and Mithen, 1996; Kliebenstein et al., 2001c). However, there were also numerous epistatic interactions identified that controlled aliphatic glucosinolate accumulation (Kliebenstein et al., 2001b; Pfalz et al., 2007; Wentzell et al., 2007). The identification of the causal genes for 21

22 these regulatory QTL and the fact that they control of gene expression is beginning to generate a regulatory model of how epistasis controls glucosinolate accumulation. In the Arabidopsis Ler x Cvi population, there is a three way epistasis between the GSL-ALK, GSL-ELONG and GSL-MYB2976 loci (Kliebenstein et al., 2001b). This is likely caused by the AOP2 gene within the GSL-ALK QTL inducing the MYB76 gene which is polymorphic within the GSL-MYB2976 QTL and can control the AOP2 gene expression (Sønderby et al., 2007; Wentzell et al., 2007). This sets up a feedback amplification loop whereby the two polymorphisms amplify each others phenotypic effect leading to a non-linear interaction of the two loci. Similarly, the measured MAM genes are induced by MYB76 and AOP2 and one of the MAM genes likely induces AOP2 and MYB76 (Wentzell et al., 2007). This sets up a network whereby the genes underlying all three QTL are regulating each other and amplifying each others phenotypic variation. Thus, the polymorphisms begin to generate an epistatic network due to their multiplicative effect. A similar situation exists in the Arabidopsis Bay x Sha population where there is a three way epistasis between the GSL-ALK, GSL-ELONG and GSL- MYB28 loci (Wentzell et al., 2007). In this situation, it is likely that crossregulation by AOP2, MYB28 and the MAMs is leading to the formation of a epistatic network based on expression (Hirai et al., 2007; Sønderby et al., 2007; Wentzell et al., 2007). This sets up a highly interconnected regulatory network whereby variation in gene expression for the transcript regulators MYB28, 22

23 MYB76, a MAM and AOP2 can generate an epistatic regulatory network and produce a wide range of aliphatic glucosinolate content, again with a minimal level of genetic polymorphism (Kliebenstein et al., 2001b; Wentzell et al., 2007). As the model Arabidopsis accession Col-0 does not have functional AOP2, it remains to be seen how these feedback amplification loops actually function within Arabidopsis (Kliebenstein et al., 2001a). Conclusion Genetic variation within the aliphatic glucosinolate pathway is rapidly becoming a model system for understanding the molecular basis of quantitative genetic traits. The cloning of numerous genes for individual QTLs is allowing studies into the molecular basis of epistatic interactions within quantitative traits. This will also greatly facilitate the study of how genotype and environment interact to control the resulting phenotypic value. Beyond quantitative genetics, the fact that these QTLs are also the basis of glucosinolate variation in wild species will allow glucosinolates to become a model system for studying ecological and evolutionary questions about the relationship between variation in specific genes/pathways and plant fitness. Acknowledgements Funding for metabolite QTL analysis was obtained by a National Science Foundation grants DBI to DJK. 23

24 Tables Table 1. Identification of glucosinolate QTLs Arabidopsis Locus Alleles Gene AGI Proof Brassica Elong C3 MAM2 NA Comp. Yes C4 MAM1 AT5G23010 Comp. AOP ALK AOP2 AT4G03060 Comp. Yes OHP AOP3 AT4G03050 Comp. Null Comp. OH Quant GSL-OH AT2G25450 Assoc. Yes OX Quant FMO AT1G62540 Assoc. Yes FMO AT1G62560 Assoc. FMO AT1G62570 Assoc. FMO AT1G65860 Comp. MYB28 Quant MYB28 AT5G61420 Comp. Yes MYB2976 Quant MYB29 AT5G07690 None Yes MYB76 AT5G07700 Assoc. UGT74B1 Quant UGT74B1 AT1G24100 Assoc.? UGT74C1 Quant UGT74C1 AT2G31790 Assoc.? Locus shows the GSL nomenclature. Allele shows which allele at the specific locus is being described. For Allele, quant shows that there are likely multiple alleles at the locus each with a different quantitative value. Gene and AGI provide gene name information on the cloned Arabidopsis genes. Proof shows that the QTL to gene linkage is validated at either the complementation or association level. Brassica shows if there is an overlapping QTL identified in Brassicas. 24

25 Figure Legends Figure 1. Genetic control of aliphatic glucosinolates. Shown is the impact of the four main structural QTL within Arabidopsis and Brassica upon the composition of glucosinolates within the plant. Glucosinolate content shows the average accumulation of total aliphatic glucosinolates in pmol per 100 µg of tissue in the leaves of Arabidopsis with the corresponding genotypes. Letters show those genotypes with different total aliphatic glucosinolate accumulation. Observed genotype frequency shows the number of Arabidopsis accessions out of 126 that had the given four locus genotype. Deviation from expected frequency shows the χ 2 value comparing the observed four locus genotype against the expected four locus frequency if the genetically unlinked loci admixed at random. Black bars show genotypes that occur more (positive) or less (negative) frequently than would be expected by random chance. White bars are genotypes occurring in a random fashion. All glucosinolates are shown with regards to the specific side-chain. Glucosinolate side-chain names are as follows (1) 3-hydroxypropyl, (2) 3-methylthiopropyl, (3) 3-methylsulfinylpropyl, (4) allyl, (5) 4-methylsulfinylbutyl, (6) 4-methylthiobutyl, (7) but-3-enyl, (8) 2-hydroxybut-3-enyl. In Arabidopsis, structure 8 occurs as both the R and S enantiomers and the non-sterospecific structure is shown for simplicity. Figure 2. Aliphatic glucosinolate QTL to gene linkage. 25

26 Shown are any QTL detected for any aliphatic glucosinolate in five different QTL mapping experiments within Arabidopsis. The most likely position of the QTL is shown for an Ler x Cvi population, (Kliebenstein et al., 2001b) using white boxes; two different analyses of the Ler x Col population, (Kliebenstein et al., 2002b) as grey boxes and (Kliebenstein et al., 2002a) as black boxes; a Bay- 0 x Sha population (Wentzell et al., 2007),as boxes with black circles and a Da(1)-12 x Ei-2 population (Pfalz et al., 2007),shown as boxes with crosshatches. All known or predicted glucosinolate related genes are shown with those genes having evidence for significant gene expression polymorphisms in Arabidopsis accessions shown in bold. 26

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