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Data from: Investigation of the geographic scale of adaptive phenological variation and its underlying genetics in Arabidopsis thaliana

Citation

Brachi, Benjamin et al. (2013), Data from: Investigation of the geographic scale of adaptive phenological variation and its underlying genetics in Arabidopsis thaliana, Dryad, Dataset, https://doi.org/10.5061/dryad.07s25

Abstract

Despite the increasing number of genomic tools, identifying the genetics underlying adaptive complex traits remains challenging in the model species Arabidopsis thaliana. This is due, at least in part, to the lack of data on the geographical scale of adaptive phenotypic variation. The aims of this study were (i) to tease apart the historical roles of adaptive and nonselective processes in shaping phenological variation in A. thaliana in France and (ii) to gain insights into the spatial scale of adaptive variation by identifying the putative selective agents responsible for this selection. Forty-nine natural stands from four climatically contrasted French regions were characterized (i) phenologically for six traits, (ii) genetically using 135 SNP markers and (iii) ecologically for 42 variables. Up to 63% of phenological variation could be explained by neutral genetic diversity. The remaining phenological variation displayed stronger associations with ecological variation within regions than among regions, suggesting the importance of local selective agents in shaping adaptive phenological variation. Although climatic conditions have often been suggested as the main selective agents acting on phenology in A. thaliana, both edaphic conditions and interspecific competition appear to be strong selective agents in some regions. In a first attempt to identify the genetics of phenological variation at different geographical scales, we phenotyped worldwide accessions and local polymorphic populations from the French RegMap in a genome-wide association (GWA) mapping study. The genomic regions associated with phenological variation depended upon the geographical scale considered, stressing the need to account for the scale of adaptive phenotypic variation when choosing accession panels for GWAS.

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