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dc.contributor.authorFraïsse, Christelle
dc.contributor.authorRoux, Camille
dc.contributor.authorGagnaire, Pierre-Alexandre
dc.contributor.authorRomiguier, Jonathan
dc.contributor.authorFaivre, Nicolas
dc.contributor.authorWelch, John
dc.contributor.authorBierne, Nicolas
dc.date.accessioned2018-10-18T10:21:18Z
dc.date.available2018-10-18T10:21:18Z
dc.date.issued2018
dc.identifier.issn2167-8359
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/284121
dc.description.abstractGenome-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.
dc.format.mediumElectronic-eCollection
dc.languageeng
dc.publisherPeerJ
dc.rightsAttribution 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.titleThe divergence history of European blue mussel species reconstructed from Approximate Bayesian Computation: the effects of sequencing techniques and sampling strategies.
dc.typeArticle
prism.publicationDate2018
prism.publicationNamePeerJ
prism.startingPagee5198
prism.volume6
dc.identifier.doi10.17863/CAM.31492
dcterms.dateAccepted2018-06-19
rioxxterms.versionofrecord10.7717/peerj.5198
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserved
rioxxterms.licenseref.startdate2018-01
dc.contributor.orcidFraïsse, Christelle [0000-0001-8441-5075]
dc.contributor.orcidWelch, John [0000-0001-7049-7129]
dc.contributor.orcidBierne, Nicolas [0000-0003-1856-3197]
dc.identifier.eissn2167-8359
rioxxterms.typeJournal Article/Review
cam.issuedOnline2018-07-30


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Attribution 4.0 International
Except where otherwise noted, this item's licence is described as Attribution 4.0 International