Titre :

The divergence history of European blue mussel species reconstructed from Approximate Bayesian Computation: the effects of sequencing techniques and sampling strategies

Auteur(s) :

Fraisse, Christelle [Auteur]
Institute of Science and Technology [Klosterneuburg, Austria] [IST Austria]
Institut des Sciences de l'Evolution de Montpellier [UMR ISEM]
Roux, camille [Auteur]
Évolution, Écologie et Paléontologie (Evo-Eco-Paleo) - UMR 8198 [Evo-Eco-Paléo (EEP)]
Gagnaire, Pierre-Alexandre [Auteur]
Institut des Sciences de l'Evolution de Montpellier [UMR ISEM]
Romiguier, Jonathan [Auteur]
Institut des Sciences de l'Evolution de Montpellier [UMR ISEM]
Faivre, Nicolas [Auteur]
Institut des Sciences de l'Evolution de Montpellier [UMR ISEM]
Welch, John [Auteur]
Department of Genetics [Cambridge]
Bierne, Nicolas [Auteur]
Institut des Sciences de l'Evolution de Montpellier [UMR ISEM]

Titre de la revue :

PeerJ

Éditeur :

PeerJ

Date de publication :

2018

ISSN :

2167-8359

Mot(s)-clé(s) en anglais :

Approximate Bayesian Computation
Demographic inferences
Joint site frequency spectrum
Mytilus edulis
Next-generation sequencing

Discipline(s) HAL :

Sciences du Vivant [q-bio]/Génétique/Génétique des populations [q-bio.PE]

Résumé en anglais : [en]

Genome-scale diversity data are increasingly available in a variety of biological systems, and can be used to reconstruct the past evolutionary history of species divergence. However, extracting the full demographic ...
Lire la suite >Genome-scale diversity data are increasingly available in a variety of biological systems, and can be used to reconstruct the past evolutionary history of species divergence. However, extracting the full demographic information from these data is not trivial, and requires inferential methods that account for the diversity of coalescent histories throughout the genome. Here, we evaluate the potential and limitations of one such approach. We reexamine a well-known system of mussel sister species, using the joint site frequency spectrum (jSFS) of synonymous mutations computed either from exome capture or RNA-seq, in an Approximate Bayesian Computation (ABC) framework. We first assess the best sampling strategy (number of: individuals, loci, and bins in the jSFS), and show that model selection is robust to variation in the number of individuals and loci. In contrast, different binning choices when summarizing the jSFS, strongly affect the results: including classes of low and high frequency shared polymorphisms can more effectively reveal recent migration events. We then take advantage of the flexibility of ABC to compare more realistic models of speciation, including variation in migration rates through time (i.e., periodic connectivity) and across genes (i.e., genome-wide heterogeneity in migration rates). We show that these models were consistently selected as the most probable, suggesting that mussels have experienced a complex history of gene flow during divergence and that the species boundary is semi-permeable. Our work provides a comprehensive evaluation of ABC demographic inference in mussels based on the coding jSFS, and supplies guidelines for employing different sequencing techniques and sampling strategies. We emphasize, perhaps surprisingly, that inferences are less limited by the volume of data, than by the way in which they are analyzed.Lire moins >

Langue :

Anglais

Vulgarisation :

Non

Projet ANR :

Génomique Comparative de la Divergence pour relier la spéciation aux traits d'histoire de vie

Collections :

• Évolution, Écologie et Paléontologie (Evo Eco Paleo) - UMR 8198

Source :

Harvested from HAL