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

C. Fraisse, C. Roux, P. Gagnaire, J. Romiguier, N. Faivre, J. Welch, N. Bierne, PeerJ 2018 (2018).

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Abstract
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 synonymousmutations computed either fromexome 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.
Publishing Year
Date Published
2018-07-30
Journal Title
PeerJ
Volume
2018
Issue
7
Article Number
30083438
IST-REx-ID

Cite this

Fraisse C, Roux C, Gagnaire P, et al. The divergence history of European blue mussel species reconstructed from Approximate Bayesian Computation: The effects of sequencing techniques and sampling strategies. PeerJ. 2018;2018(7). doi:10.7717/peerj.5198
Fraisse, C., Roux, C., Gagnaire, P., Romiguier, J., Faivre, N., Welch, J., & Bierne, N. (2018). The divergence history of European blue mussel species reconstructed from Approximate Bayesian Computation: The effects of sequencing techniques and sampling strategies. PeerJ, 2018(7). https://doi.org/10.7717/peerj.5198
Fraisse, Christelle, Camille Roux, Pierre Gagnaire, Jonathan Romiguier, Nicolas Faivre, John Welch, and Nicolas Bierne. “The Divergence History of European Blue Mussel Species Reconstructed from Approximate Bayesian Computation: The Effects of Sequencing Techniques and Sampling Strategies.” PeerJ 2018, no. 7 (2018). https://doi.org/10.7717/peerj.5198.
C. Fraisse et al., “The divergence history of European blue mussel species reconstructed from Approximate Bayesian Computation: The effects of sequencing techniques and sampling strategies,” PeerJ, vol. 2018, no. 7, 2018.
Fraisse C, Roux C, Gagnaire P, Romiguier J, Faivre N, Welch J, Bierne N. 2018. The divergence history of European blue mussel species reconstructed from Approximate Bayesian Computation: The effects of sequencing techniques and sampling strategies. PeerJ. 2018(7).
Fraisse, Christelle, et al. “The Divergence History of European Blue Mussel Species Reconstructed from Approximate Bayesian Computation: The Effects of Sequencing Techniques and Sampling Strategies.” PeerJ, vol. 2018, no. 7, 30083438, PeerJ Inc , 2018, doi:10.7717/peerj.5198.
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