Phylogenetic patterns of GC-biased gene conversion in placental mammals and the evolutionary dynamics of recombination landscapes.
GC-biased gene conversion (gBGC) is a major evolutionary force shaping genomic nucleotide landscapes, distorting the estimation of the strength of selection, and having potentially deleterious effects on genome-wide fitness. Yet, a global quantitative picture, at large evolutionary scale, of the relative strength of gBGC compared with selection and random drift is still lacking. Furthermore, owing to its dependence on the local recombination rate, gBGC results in modulations of the substitution patterns along genomes and across time which, if correctly interpreted, may yield quantitative insights into the long-term evolutionary dynamics of recombination landscapes. Deriving a model of the substitution process at putatively neutral nucleotide positions from population-genetics arguments, and accounting for among-lineage and among-gene effects, we propose a reconstruction of the variation in gBGC intensity at the scale of placental mammals, and of its scaling with body-size and karyotypic traits. Our results are compatible with a simple population genetics model relating gBGC to effective population size and recombination rate. In addition, among-gene variation and phylogenetic patterns of exon-specific levels of gBGC reveal the presence of rugged recombination landscapes, and suggest that short-lived recombination hot-spots are a general feature of placentals. Across placental mammals, variation in gBGC strength spans two orders of magnitude, at its lowest in apes, strongest in lagomorphs, microbats or tenrecs, and near or above the nearly neutral threshold in most other lineages. Combined with among-gene variation, such high levels of biased gene conversion are likely to significantly impact midly selected positions, and to represent a substantial mutation load. Altogether, our analysis suggests a more important role of gBGC in placental genome evolution, compared with what could have been anticipated from studies conducted in anthropoid primates.
Centre Robert-Cedergren pour la Bioinformatique, Département de Biochimie, Université de Montréal, Québec, Canada. nicolas.lartillot@umontreal.ca
Nicolas
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Lartillot
D000465:Algorithms; D000818:Animals; D001482:Base Composition; D001499:Bayes Theorem; D003198:Computer Simulation; D018899:CpG Islands; D019143:Evolution, Molecular; D005785:Gene Conversion; D056426:Genetic Loci; D014644:Genetic Variation; D016678:Genome; D006801:Humans; D008322:Mammals / Q000235:genetics; D008390:Markov Chains; D008957:Models, Genetic; D009010:Monte Carlo Method; D010802:Phylogeny; D011323:Primates / Q000235:genetics; D011995:Recombination, Genetic