Combining population genomics and fitness QTLs to identify the genetics of local adaptation in Arabidopsis thaliana.
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SUBMITTER: Price N
PROVIDER: S-EPMC5948977 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Organisms inhabiting different environments are often locally adapted, and yet despite a considerable body of theory, the genetic basis of local adaptation is poorly understood. Unanswered questions include the number and effect sizes of adaptive loci, whether locally favored loci reduce fitness elsewhere (i.e., fitness tradeoffs), and whether a lack of genetic variation limits adaptation. To address these questions, we mapped quantitative trait loci (QTL) for total fitness in 398 recombinant inbred lines derived from a cross between locally adapted populations of the highly selfing plant Arabidopsis thaliana from Sweden and Italy and grown for 3 consecutive years at the parental sites (>40,000 plants monitored). We show that local adaptation is controlled by relatively few genomic regions of small to modest effect. A third of the 15 fitness QTL we detected showed evidence of tradeoffs, which contrasts with the minimal evidence for fitness tradeoffs found in previous studies. This difference may reflect the power of our multiyear study to distinguish conditionally neutral QTL from those that reflect fitness tradeoffs. In Sweden, but not in Italy, the local genotype underlying fitness QTL was often maladaptive, suggesting that adaptation there is constrained by a lack of adaptive genetic variation, attributable perhaps to genetic bottlenecks during postglacial colonization of Scandinavia or to recent changes in selection regime caused by climate change. Our results suggest that adaptation to markedly different environments can be achieved through changes in relatively few genomic regions, that fitness tradeoffs are common, and that lack of genetic variation can limit adaptation.
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Project description:BackgroundGenome-wide association (GWA) is gaining popularity as a means to study the architecture of complex quantitative traits, partially due to the improvement of high-throughput low-cost genotyping and phenotyping technologies. Glucosinolate (GSL) secondary metabolites within Arabidopsis spp. can serve as a model system to understand the genomic architecture of adaptive quantitative traits. GSL are key anti-herbivory defenses that impart adaptive advantages within field trials. While little is known about how variation in the external or internal environment of an organism may influence the efficiency of GWA, GSL variation is known to be highly dependent upon the external stresses and developmental processes of the plant lending it to be an excellent model for studying conditional GWA.Methodology/principal findingsTo understand how development and environment can influence GWA, we conducted a study using 96 Arabidopsis thaliana accessions, >40 GSL phenotypes across three conditions (one developmental comparison and one environmental comparison) and ∼230,000 SNPs. Developmental stage had dramatic effects on the outcome of GWA, with each stage identifying different loci associated with GSL traits. Further, while the molecular bases of numerous quantitative trait loci (QTL) controlling GSL traits have been identified, there is currently no estimate of how many additional genes may control natural variation in these traits. We developed a novel co-expression network approach to prioritize the thousands of GWA candidates and successfully validated a large number of these genes as influencing GSL accumulation within A. thaliana using single gene isogenic lines.Conclusions/significanceTogether, these results suggest that complex traits imparting environmentally contingent adaptive advantages are likely influenced by up to thousands of loci that are sensitive to fluctuations in the environment or developmental state of the organism. Additionally, while GWA is highly conditional upon genetics, the use of additional genomic information can rapidly identify causal loci en masse.
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