The divergence history of European blue mussel species reconstructed from Approximate Bayesian Computation: the effects of sequencing techniques and sampling strategies
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 ac...
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PeerJ Inc.
2018-07-01
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| author | Christelle Fraïsse Camille Roux Pierre-Alexandre Gagnaire Jonathan Romiguier Nicolas Faivre John J. Welch Nicolas Bierne |
| author_facet | Christelle Fraïsse Camille Roux Pierre-Alexandre Gagnaire Jonathan Romiguier Nicolas Faivre John J. Welch Nicolas Bierne |
| author_sort | Christelle Fraïsse |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-09T06:53:41Z |
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| issn | 2167-8359 |
| language | English |
| last_indexed | 2024-03-09T06:53:41Z |
| publishDate | 2018-07-01 |
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| spelling | doaj.art-eddc7620bdc34c7cb7a30259e7bec5a62023-12-03T10:16:33ZengPeerJ Inc.PeerJ2167-83592018-07-016e519810.7717/peerj.5198The divergence history of European blue mussel species reconstructed from Approximate Bayesian Computation: the effects of sequencing techniques and sampling strategiesChristelle Fraïsse0Camille Roux1Pierre-Alexandre Gagnaire2Jonathan Romiguier3Nicolas Faivre4John J. Welch5Nicolas Bierne6Institut des Sciences de l’Evolution UMR5554, University Montpellier, CNRS, IRD, EPHE, Montpellier, FranceUniversité de Lille, Unité Evo-Eco-Paléo (EEP), UMR 8198, Villeneuve d’Ascq, FranceInstitut des Sciences de l’Evolution UMR5554, University Montpellier, CNRS, IRD, EPHE, Montpellier, FranceInstitut des Sciences de l’Evolution UMR5554, University Montpellier, CNRS, IRD, EPHE, Montpellier, FranceInstitut des Sciences de l’Evolution UMR5554, University Montpellier, CNRS, IRD, EPHE, Montpellier, FranceDepartment of Genetics, University of Cambridge, Cambridge, UKInstitut des Sciences de l’Evolution UMR5554, University Montpellier, CNRS, IRD, EPHE, Montpellier, FranceGenome-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.https://peerj.com/articles/5198.pdfDemographic inferencesJoint site frequency spectrumNext-generation sequencingApproximate Bayesian ComputationMytilus edulis |
| spellingShingle | Christelle Fraïsse Camille Roux Pierre-Alexandre Gagnaire Jonathan Romiguier Nicolas Faivre John J. Welch Nicolas Bierne The divergence history of European blue mussel species reconstructed from Approximate Bayesian Computation: the effects of sequencing techniques and sampling strategies PeerJ Demographic inferences Joint site frequency spectrum Next-generation sequencing Approximate Bayesian Computation Mytilus edulis |
| title | The divergence history of European blue mussel species reconstructed from Approximate Bayesian Computation: the effects of sequencing techniques and sampling strategies |
| title_full | The divergence history of European blue mussel species reconstructed from Approximate Bayesian Computation: the effects of sequencing techniques and sampling strategies |
| title_fullStr | The divergence history of European blue mussel species reconstructed from Approximate Bayesian Computation: the effects of sequencing techniques and sampling strategies |
| title_full_unstemmed | The divergence history of European blue mussel species reconstructed from Approximate Bayesian Computation: the effects of sequencing techniques and sampling strategies |
| title_short | The divergence history of European blue mussel species reconstructed from Approximate Bayesian Computation: the effects of sequencing techniques and sampling strategies |
| title_sort | divergence history of european blue mussel species reconstructed from approximate bayesian computation the effects of sequencing techniques and sampling strategies |
| topic | Demographic inferences Joint site frequency spectrum Next-generation sequencing Approximate Bayesian Computation Mytilus edulis |
| url | https://peerj.com/articles/5198.pdf |
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