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Lanore, V.

Publications and source records attributed to Lanore, V..

2 recordsLinked to original sources

Inferring long-term effective population size with Mutation-Selection models

Mutation-selection phylogenetic codon models are grounded on population genetics first principles and represent a principled approach for investigating the intricate interplay between mutation, selection and drift. In their current form, mutation-selection codon models are entirely characterized by the collection of site-specific amino-acid fitness profiles. However, thus far, they have relied on the assumption of a constant genetic drift, translating into a unique effective population size (Ne) across the phylogeny, clearly an unreasonable hypothesis. This assumption can be alleviated by introducing variation in Ne between lineages. In addition to Ne, the mutation rate () is susceptible to vary between lineages, and both should co-vary with life-history traits (LHTs). This suggests that the model should more globally account for the joint evolutionary process followed by all of these lineage-specific variables (Ne, , and LHTs). In this direction, we introduce an extended mutation-selection model jointly reconstructing in a Bayesian Monte Carlo framework the fitness landscape across sites and long-term trends in Ne, and LHTs along the phylogeny, from an alignment of DNA coding sequences and a matrix of observed LHTs in extant species. The model was tested against simulated data and applied to empirical data in mammals, isopods and primates. The reconstructed history of Ne in these groups appears to correlate with LHTs or ecological variables in a way that suggests that the reconstruction is reasonable, at least in its global trends. On the other hand, the range of variation in Ne inferred across species is surprisingly narrow. This last point suggests that some of the assumptions of the model, in particular concerning the assumed absence of epistatic interactions between sites, are potentially problematic.

evolutionary biology↗

Detecting convergent adaptive amino acid evolution

In evolutionary genomics, researchers have taken an interest in identifying in the genomes substitutions that subtend convergent phenotypic adaptations. This is a difficult question to address, because genomes contain billions of sites, many of which have substituted in the lineages where the adaptations took place, and yet are not linked to them. Those extra substitutions may be linked to other adaptations, may be neutral, or may be linked to mutational biases. Furthermore, one can think of various ways of defining substitutions of interest, and various methods that match those definitions have been used, resulting in different sets of candidate substitutions. In this manuscript we first clarify how adaptation to convergent phenotypic evolution can manifest itself in coding sequences. Second, we review methods that have been proposed to detect convergent adaptive evolution in coding sequences and expose the assumptions that underlie them. Finally, we examine their power on simulations of convergent changes, including in the presence of a confounding factor.

bioinformatics↗