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Recombination in Adaptive Evolution (EvolRecombAdapt)
Date du début: 1 août 2014, Date de fin: 31 juil. 2019 PROJET  TERMINÉ 

Meiotic recombination is a key source of genetic diversity with considerable implications for the genomic landscape and evolutionary process. By shuffling parental alleles to produce novel haplotypes, recombination impacts the strength of selection on nearby polymorphisms, and can increase the rate of adaptation in natural populations. Recombination defects can have serious phenotypic consequences: inviable gametes, miscarriages and developmental abnormalities. Strikingly, recombination rate differs by orders of magnitude across the genome, among individuals, sexes, populations and species. Despite recent progress, we know little about how molecular constraints and evolutionary forces interact to shape recombination in natural populations. We will close this knowledge gap using threespine stickleback fish—an exceptional evolutionary model system that bridges molecular genetic studies and adaptive evolution in the wild. This research program combines next-generation genomics with cutting-edge molecular biology and transgenics. We will 1) create kilobase-scale maps of the recombination landscape in adaptively diverging populations; 2) genetically dissect factors cis- and trans-acting factors that cause recombination variation; 3) characterize molecular mechanisms of recombination modifiers using cutting-edge techniques; and 4) test evolutionary theory that predicts natural selection favours recombination suppression in hybrids. This will significantly improve our understanding of recombination and introduce sophisticated genetic engineering techniques that further cement sticklebacks as an evolutionary model organism. Our ultimate goal is to understand how molecular mechanisms and natural selection shape and constrain recombination during adaptive divergence. This research connects a fundamental biological process that underlies severe human diseases with the tempo of adaptation in natural populations

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