Ecological, genetic and evolutionary drivers of regional genetic differentiation in Arabidopsis thaliana

Background: Disentangling the drivers of genetic differentiation is one of the cornerstones in evolution. This is because genetic diversity, and the way in which it is partitioned within and among populations across space, is an important asset for the ability of populations to adapt and persist in changing environments. We tested three major hypotheses accounting for genetic differentiation—isolation-by-distance (IBD), isolation-by-environment (IBE) and isolation-by-resistance (IBR)—in the annual plant Arabidopsis thaliana across the Iberian Peninsula, the region with the largest genomic diversity. To that end, we sampled, genotyped with genome-wide SNPs, and analyzed 1,772 individuals from 278 populations distributed across the Iberian Peninsula. Results: IBD, and to a lesser extent IBE, were the most important drivers of genetic differentiation in A. thaliana. In other words, dispersal limitation, genetic drift, and to a lesser extent local adaptation to environmental gradients, accounted for the within- and among-population distribution of genetic diversity. Analyses applied to the four Iberian genetic clusters, which represent the joint outcome of the long demographic and adaptive history of the species in the region, showed similar results except for one cluster, in which IBR (a function of landscape heterogeneity) was the most important driver of genetic differentiation. Using spatial hierarchical Bayesian models, we found that precipitation seasonality and topsoil pH chiefly accounted for the geographic distribution of genetic diversity in Iberian A. thaliana. Conclusions: Overall, the interplay between the influence of precipitation seasonality on genetic diversity and the effect of restricted dispersal and genetic drift on genetic differentiation emerges as the major forces underlying the evolutionary trajectory of Iberian A. thaliana.DATA: Genetic and environmental data of 278 Arabidopsis thaliana populations and 1772 individuals. The file has two sheets including the following information: 1. SNP data (240 polymorphic nuclear SNPs): 1st row: SNP name. 2nd row: chromosome in which SNPs are located. 3rd row: physical position of SNPs. 4th row: genetic position of SNPs. 5th row: collections of polymorphic SNPs (WHF: worldwide collection; CE: Central Europe; IP: Iberian Peninsula). 6th row: empty. 7th row: SNP name. 1st column: names of variables, including population-individual codes after the empty row. 2nd to 241st column: nucleotides (A, C, G or T). Notes: all loci are homozygous. Missing data = 9999. 2. Geographic and environmental data (29 variables): 1st row: Population and variable names. 1st column: population-individual codes. 2nd column: longitude (degrees). 3rd column: latitude (degrees). 4th column: altitude (masl). 5th to 23rd column: WordClim variables (code and self-explanatory name). 24th to 29th column: CORINE variables (self-explanatory name). 30th column: pH from The Soil Geographical Database from Eurasia. Funding provided by: Agencia Estatal de InvestigaciónCrossref Funder Registry ID: http://dx.doi.org/10.13039/501100011033Award Number: BIO2016‐75754‐PSee Methods section in the manuscript