Investigation of the geographical scale of adaptive phenological variation and its underlying genetics in Arabidopsis thaliana

Authors

  • Benjamin Brachi,

    1. Laboratoire Génétique et Evolution des Populations Végétales, UMR CNRS 8198, Université des Sciences et Technologies de Lille – Lille 1, Villeneuve d'Ascq Cedex, France
    2. Department of Ecology and Evolution, University of Chicago, Chicago, IL, USA
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    • These authors contributed equally to this work.
  • Romain Villoutreix,

    1. Laboratoire Génétique et Evolution des Populations Végétales, UMR CNRS 8198, Université des Sciences et Technologies de Lille – Lille 1, Villeneuve d'Ascq Cedex, France
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    • These authors contributed equally to this work.
  • Nathalie Faure,

    1. Laboratoire Génétique et Evolution des Populations Végétales, UMR CNRS 8198, Université des Sciences et Technologies de Lille – Lille 1, Villeneuve d'Ascq Cedex, France
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  • Nina Hautekèete,

    1. Laboratoire Génétique et Evolution des Populations Végétales, UMR CNRS 8198, Université des Sciences et Technologies de Lille – Lille 1, Villeneuve d'Ascq Cedex, France
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  • Yves Piquot,

    1. Laboratoire Génétique et Evolution des Populations Végétales, UMR CNRS 8198, Université des Sciences et Technologies de Lille – Lille 1, Villeneuve d'Ascq Cedex, France
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  • Maxime Pauwels,

    1. Laboratoire Génétique et Evolution des Populations Végétales, UMR CNRS 8198, Université des Sciences et Technologies de Lille – Lille 1, Villeneuve d'Ascq Cedex, France
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  • Dominique Roby,

    1. INRA, Laboratoire des Interactions Plantes-Microorganismes (LIPM), UMR441, Castanet-Tolosan, France
    2. CNRS, Laboratoire des Interactions Plantes-Microorganismes (LIPM), UMR2594, Castanet-Tolosan, France
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  • Joël Cuguen,

    1. Laboratoire Génétique et Evolution des Populations Végétales, UMR CNRS 8198, Université des Sciences et Technologies de Lille – Lille 1, Villeneuve d'Ascq Cedex, France
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  • Joy Bergelson,

    1. Department of Ecology and Evolution, University of Chicago, Chicago, IL, USA
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  • Fabrice Roux

    Corresponding author
    • Laboratoire Génétique et Evolution des Populations Végétales, UMR CNRS 8198, Université des Sciences et Technologies de Lille – Lille 1, Villeneuve d'Ascq Cedex, France
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Correspondence: Fabrice Roux, Fax: +33 (0)3 20 43 69 79; E-mail: fabrice.roux@univ-lille1.fr

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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