The main goal of this IEF proposal is to allow the fellow to acquire all the competencies to develop, carry out, and lead his own research group in plant population genomics integrating functional approaches, with a special emphasis on the use of next generation sequencing (NGS) data. The fellow will complement his skills in theoretical population genetics and evolutionary genomics by acquiring new skills in the analyses of population genomic data, gene expression, and association mapping. Thanks to NGS technologies, the combination of these approaches is becoming pivotal in the study of natural populations. This will be done through an innovative research project, which aim is to tackle the paradox of adaptation in selfing species, which can be successful on the short term, though selfing is expected to be a evolutionary dead-end strategy on the long term. Polyploidy and efficient local adaptation could be key issues to resolve this paradox. We propose to address this question by combining population genomics, gene expression and association mapping to analyse the genetic bases and the geographical scales of adaptation in Capsella bursa-pastoris, a polyploid selfing that has a large distribution and has adapted to contrasted environments, despite its low genetic diversity. Genomic data are increasingly available in the genus Capsella and the host’s lab has strongly contributed in establishing C. bursa-pastoris as a wild model species. The project will strengthen collaborations between European partners on plant population genomics, an important field in the context of the knowledge-based bio-economy. Importantly, as many crops and weeds are selfers and/or polyploids (eg. wheat, potato), the results should be easily transferable for the identification of genes of interest in plant breeding programs and for a better use of plant genetic resources for developing new crop varieties adapted to sustainable agriculture in the context of rapidly changing environments.