Title: Estimation and analysis of the adaptive substitution rate in animals

Abstract: Understanding the determinants of the adaptive substitution rate is a central question in molecular evolution. In particular, the influence of the effective population size N_e on positive selection as well as the nature of amino acid changes that lead to adaptation are still debated. The DFE-α method, which was derived from the seminal McDonald & Kreitman test, is a powerful tool for estimating the adaptive substitution rate. However, it is sensitive to various sources of bias. In this thesis, we identified two major sources of bias of this test, long-term fluctuations of the selective-drift regime through demographic fluctuations, and GC-biased gene conversion (gBGC). Using simulations, we showed that under plausible scenarios of fluctuating demography, the DFE-α method can lead to a severe over-estimation of the adaptive substitution rate. We also showed that polymorphism data reflect a transient selective-drift regime which is unlikely to correspond to the average regime experienced by genes and genomes during the long-term divergence between species. This violates an important assumption of the DFE-α method. Our results also indicate that gBGC leads to an over-estimation of the adaptive substitution rate in primates and birds. Using a dataset of nine metazoan taxa for a total of 40 species, we started an analysis aiming at identifying the type of amino acid changes that are more prone to adaptation, and evaluated the link between N_e and the adaptive substitution rate while accounting for the two sources of bias previously explored. We reveal for the first time a negative relationship between the adaptive substitution rate and life-history traits representative of long-term N_e. This result is in contradiction with the widespread hypothesis that adaptation is more efficient in large populations.