The genetics of plant metabolism

Abstract

Variation for metabolite composition and content is often observed in plants. However, it is poorly understood to what extent this variation has a genetic basis. Here, we describe the genetic analysis of natural variation in the metabolite composition in Arabidopsis thaliana. Instead of focusing on specific metabolites, we have applied empirical untargeted metabolomics using liquid chromatography-time of flight mass spectrometry (LC-QTOF MS). This uncovered many qualitative and quantitative differences in metabolite accumulation between A. thaliana accessions. Only 13.4% of the mass peaks were detected in all 14 accessions analyzed. Quantitative trait locus (QTL) analysis of more than 2,000 mass peaks, detected in a recombinant inbred line (RIL) population derived from the two most divergent accessions, enabled the identification of QTLs for about 75% of the mass signals. More than one-third of the signals were not detected in either parent, indicating the large potential for modification of metabolic composition through classical breeding.Metabolites are critical in biology, and plants are especially rich in diverse biochemical compounds. It has been estimated that over 100,000 metabolites can be found in plants, and each species may contain its own chemotypic expression pattern 1 . Moreover, substantial quantitative and qualitative variation in metabolite composition is often observed within plant species 2 .Although knowledge on the regulation of metabolite formation is increasing, for thousands of metabolites, their function in the plant, their biosynthetic pathway and the regulation thereof is still unknown. QTL analysis of natural variation, which can affect metabolites 3 , in segregating populations can identify loci explaining the observed variation 4 . In recent years, a few studies have focused on identifying QTLs regulating a specific group of known metabolites using detection methods directed toward specific metabolite groups 5-9 . However, recent advances in mass spectrometry-based metabolomics and data processing techniques should now allow large-scale QTL analyses of untargeted metabolic profiles, which may uncover previously unknown regulatory functions of loci in metabolic pathways. Using dedicated alignment software, it is now possible to perform an unbiased comparison of large numbers of metabolite-derived masses detectable in large numbers of samples arising from inherently large sets of genotypes (which are required for accurate mapping of QTLs) in an RIL population 10,11 . QTL mapping will result in the localization of loci, and ultimately genes, causal for the observed variation and will allow the discovery of coregulated compounds. In this way, genomewide genetic correlative metabolic analysis now becomes feasible, as we demonstrate here. RESULTS Metabolite variation is abundant and genetically controlledTo assess the natural variation in metabolite content present in A. thaliana, we performed HPLC-QTOF MS-based untargeted metabolic fingerprinting of acidified aqueous methanol extracts fr...

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Editor’s Choice: Evaluating the Potential for Adverse Interactions within Genetically Engineered Breeding Stacks

“…However, the mechanisms underlying heterosis are far from understood and likely vary among hybrids. Recent studies have measured the molecular parameters that might be involved in heterosis (Auger et al, 2005;Keurentjes et al, 2006;SwansonWagner et al, 2006;Hochholdinger and Hoecker, 2007;Groszmann et al, 2011); these studies clearly indicate that thousands of nonadditive interactions are occurring when genomes are combined by breeding. Furthermore, these gene interactions have sometimes led to gene silencing, which has been unknowingly selected by plant breeders to obtain desirable traits (Parrott et al, 2010).…”

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