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Is RAD-seq suitable for phylogenetic inference? An in silico assessment and optimization

Marie Cariou 1 Laurent Duret 2 Sylvain Charlat 1
1 Génétique et évolution des interactions hôtes-parasites
GINSENG - Département génétique, interactions et évolution des génomes [LBBE]
Abstract : Inferring phylogenetic relationships between closely related taxa can be hindered by three factors: (1) the lack of informative molecular variation at short evolutionary timescale; (2) the lack of established markers in poorly studied taxa; and (3) the potential phylogenetic conflicts among different genomic regions due to incomplete lineage sorting or introgression. In this context, Restriction site Associated DNA sequencing (RAD-seq) seems promising as this technique can generate sequence data from numerous DNA fragments scattered throughout the genome, from a large number of samples, and without preliminary knowledge on the taxa under study. However, divergence beyond the within-species level will necessarily reduce the number of conserved and non-duplicated restriction sites, and therefore the number of loci usable for phylogenetic inference. Here, we assess the suitability of RAD-seq for phylogeny using a simulated experiment on the 12 Drosophila genomes, with divergence times ranging from 5 to 63 million years. These simulations show that RAD-seq allows the recovery of the known Drosophila phylogeny with strong statistical support, even for relatively ancient nodes. Notably, this conclusion is robust to the potentially confounding effects of sequencing errors, heterozygosity, and low coverage. We further show that clustering RAD-seq data using the BLASTN and SiLiX programs significantly improves the recovery of orthologous RAD loci compared with previously proposed approaches, especially for distantly related species. This study therefore validates the view that RAD sequencing is a powerful tool for phylogenetic inference.
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Marie Cariou, Laurent Duret, Sylvain Charlat. Is RAD-seq suitable for phylogenetic inference? An in silico assessment and optimization. Ecology and Evolution, Wiley Open Access, 2013, 3 (4), pp.846-852. ⟨10.1002/ece3.512⟩. ⟨hal-02140475⟩

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