A Genomic Map of Climate Adaptation in Arabidopsis thaliana at a Micro-Geographic Scale

作者：Frachon, Lea; Bartoli, Claudia; Carrere, Sebastien; Bouchez, Olivier; Chaubet, Adeline; Gautier, Mathieu; Roby, Dominique; Roux, Fabrice^*

来源：Frontiers in Plant Science, 2018, 9: 967.

DOI：10.3389/fpls.2018.00967

• Arabidopsis thaliana
• Bayesian hierarchical model
• climate change
• genome-environment association analysis
• local adaptation
• Pool-Seq
• spatial grain

Understanding the genetic bases underlying climate adaptation is a key element to predict the potential of species to face climate warming. Although substantial climate variation is observed at a micro-geographic scale, most genomic maps of climate adaptation have been established at broader geographical scales. Here, by using a Pool-Seq approach combined with a Bayesian hierarchical model that control for confounding by population structure, we performed a genome-environment association (GEA) analysis to investigate the genetic basis of adaptation to six climate variables in 168 natural populations of Arabidopsis thaliana distributed in south-west of France. Climate variation among the 168 populations represented up to 24% of climate variation among 521 European locations where A. thaliana inhabits. We identified neat and strong peaks of association, with most of the associated SNPs being significantly enriched in likely functional variants and/or in the extreme tail of genetic differentiation among populations. Furthermore, genes involved in transcriptional mechanisms appear predominant in plant functions associated with local climate adaptation. Globally, our results suggest that climate adaptation is an important driver of genomic variation in A. thaliana at a small spatial scale and mainly involves genome-wide changes in fundamental mechanisms of gene regulation. The identification of climate-adaptive genetic loci at a micro-geographic scale also highlights the importance to include within-species genetic diversity in ecological niche models for projecting potential species distributional shifts over short geographic distances.

• 出版日期2018-7-10