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Theses

Analyse de la différenciation génétique à l'ère des nouvelles technologies de séquençage

Abstract : The advent of high throughput sequencing and genotyping technologies allows the comparison of patterns of polymorphisms at a very large number of genetic markers. The analysis of genetic differentiation between populations at a whole-genome scale makes it possible to characterize genomic regions involved in the local adaptation of organisms to their environment. In this thesis, we followed two complementary approaches to characterize differentiation from high-throughput genotyping data. First, we developed an unbiased estimator of the parameter FST for individuals sequenced in pools (Pool-seq). Deriving this estimator, in an analysis-of-variance framework, required to properly account for the different sampling steps: individual genes from the pool, and sequence reads from these genes. We show that it outperforms previously proposed estimators. Second, we developed a method to analyze genetic differentiation at a whole-genome scale in a hierarchical bayesian framework, in order to untangle the effect of demography from that of selection. To this end, we implemented different extensions to the SelEstim model, aimed at leveraging the information from linkage disequilibrium between markers. A first approach consisted in analyzing multiallelic data derived from the local clustering of SNPs into haplotype blocks. An alternative strategy consisted in including a smoothing model, which accounts for the spatial dependency between neighboring markers. This strategy relies on the analysis of biallelic data, and can be used both with individual genotype data or Pool-seq data. We discuss the relative benefits of these different approaches, based on the analysis of simulated data sets.
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Valentin Hivert. Analyse de la différenciation génétique à l'ère des nouvelles technologies de séquençage. Sciences agricoles. Montpellier SupAgro, 2018. Français. ⟨NNT : 2018NSAM0061⟩. ⟨tel-02542640⟩

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