Philosophical Transactions of the Royal Society B Biological Sciences · 2022 · 31 citations · 56 references
Life SciencesGeneticsPlant BiologyGenomicsPlant GeneticsPlant GenomicsFunctional GenomicsGene MappingGenome-wide Association StudiesMetabolite ProfilingPlant MetabolomicsQuantitative Trait Loci MappingBiochemical CharacterizationGenetic Architecture Of DefenseGenetic Architecture Of TraitsGenetic Heterogeneity AnalysisGenome-wide Association MappingMolecular Genetic ArchitecturePlant Metabolic ProfilingPlant Metabolite Profiling
Abstract A paradoxical finding from genome-wide association studies (GWAS) in plants is that variation in metabolite profiles typically maps to a small number of loci, despite the complexity of underlying biosynthetic pathways. This discrepancy may partially arise from limitations presented by geographically diverse mapping panels. Properties of metabolic pathways that impede GWAS by diluting the additive effect of a causal variant, such as allelic and genetic heterogeneity and epistasis, would be expected to increase in severity with the geographical range of the mapping panel. We hypothesized that a population from a single locality would reveal an expanded set of associated loci. We tested this in a French Arabidopsis thaliana population (less than 1 km transect) by profiling and conducting GWAS for glucosinolates, a suite of defensive metabolites that have been studied in depth through functional and genetic mapping approaches. For two distinct classes of glucosinolates, we discovered more associations at biosynthetic loci than the previous GWAS with continental-scale mapping panels. Candidate genes underlying novel associations were supported by concordance between their observed effects in the TOU-A population and previous functional genetic and biochemical characterization. Local populations complement geographically diverse mapping panels to reveal a more complete genetic architecture for metabolic traits. This article is part of the theme issue ‘Genetic basis of adaptation and speciation: from loci to causative mutations’.
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