Biology subjects

Raynaud, M.

Publications and source records attributed to Raynaud, M..

2 recordsLinked to original sources

bioRxiv2024

PRDM9 drives the location and rapid evolution of recombination hotspots in salmonids

In many eukaryotes, meiotic recombination occurs preferentially at discrete sites, called recombination hotspots. In various lineages, recombination hotspots are located in regions with promoter-like features and are evolutionarily stable. Conversely, in some mammals, hotspots are driven by PRDM9 that targets recombination away from promoters. Paradoxically, PRDM9 induces the self-destruction of its targets and this triggers an ultra-fast evolution of mammalian hotspots. PRDM9 is ancestral to all animals, suggesting a critical importance for the meiotic program, but has been lost in many lineages with surprisingly little effect on meiosis success. However, it is unclear whether the function of PRDM9 described in mammals is shared by other species. To investigate this, we analyzed the recombination landscape of several salmonids, the genome of which harbors one full-length PRDM9 and several truncated paralogs. We identified recombination initiation sites in Oncorhynchus mykiss by mapping meiotic DNA double-strand breaks (DSBs). We found that DNA DSBs clustered at hotspots positioned away from promoters, enriched for the H3K4me3 and H3K4me36 marks and the location of which depended on the genotype of full-length Prdm9. We observed a high level of polymorphism in the zinc finger domain of full-length Prdm9, but not of the truncated paralogs. Moreover, population-scaled recombination maps in O. mykiss, Oncorhynchus kisutch and Salmo salar revealed a rapid turnover of recombination hotspots caused by PRDM9 target motif erosion. Our results imply that PRDM9 function is conserved across vertebrates and that the peculiar evolutionary runaway caused by PRDM9 has been active for several hundred million years.

evolutionary biology↗

bioRxiv2022

Performance and limitations of linkage-disequilibrium-basedmethods for inferring the genomic landscape of recombination anddetecting hotspots: a simulation study

Knowledge of recombination rate variation along the genome provides important insights into genome and phenotypic evolution. Population genomic approaches offer an attractive way to infer the population-scaled recombination rate {rho}=4Ner using the linkage disequilibrium information contained in DNA sequence polymorphism data. Such methods have been used in a broad range of plant and animal species to build genome-wide recombination maps. However, the reliability of these inferences has only been assessed under a restrictive set of conditions. Here, we evaluate the ability of one of the most widely used coalescent-based programs, LDhelmet, to infer a genomic landscape of recombination with the biological characteristics of a human-like landscape including hotspots. Using simulations, we specifically assessed the impact of methodological (sample size, phasing errors, block penalty) and evolutionary parameters (effective population size (Ne), demographic history, mutation to recombination rate ratio) on inferred map quality. We report reasonably good correlations between simulated and inferred landscapes, but point to limitations when it comes to detecting recombination hotspots. False positive and false negative hotspots considerably confound fine-scale patterns of inferred recombination under a wide range of conditions, particularly when Ne is small and the mutation/recombination rate ratio is low, to the extent that maps inferred from populations sharing the same recombination landscape appear uncorrelated. We thus address a message of caution for the users of these approaches, at least for genomes with complex recombination landscapes such as in humans.

genomics↗