Understanding population divergence that eventually leads to speciation is essential for evolutionary biology. High species diversity in the sea was regarded as a paradox when strict allopatry was considered necessary for most speciation events because geographical barriers seemed largely absent in the sea, and many marine species have high dispersal capacities. Combining genome-wide data with demographic modelling to infer the demographic history of divergence has introduced new ways to address this classical issue. These models assume an ancestral population that splits into two subpopulations diverging according to different scenarios that allow tests for periods of gene flow. Models can also test for heterogeneities in population sizes and migration rates along the genome to account, respectively, for background selection and selection against introgressed ancestry. To investigate how barriers to gene flow arise in the sea, we compiled studies modelling the demographic history of divergence in marine organisms and extracted preferred demographic scenarios together with estimates of demographic parameters. These studies show that geographical barriers to gene flow do exist in the sea but that divergence can also occur without strict isolation. Heterogeneity of gene flow was detected in most population pairs suggesting the predominance of semipermeable barriers during divergence. We found a weak positive relationship between the fraction of the genome experiencing reduced gene flow and levels of genome-wide differentiation. Furthermore, we found that the upper bound of the ‘grey zone of speciation’ for our dataset extended beyond that found before, implying that gene flow between diverging taxa is possible at higher levels of divergence than previously thought. Finally, we list recommendations for further strengthening the use of demographic modelling in speciation research. These include a more balanced representation of taxa, more consistent and comprehensive modelling, clear reporting of results and simulation studies to rule out nonbiological explanations for general results.
We greatly thank all the corresponding authors of the studies that were included in our synthesis for the sharing of additional data: Thomas Broquet, Dmitry Filatov, Quentin Rougemont, Paolo Momigliano, Pierre-Alexandre Gagnaire, Carlos Prada, Ahmed Souissi, Michael Møller Hansen, Sylvie Lapègue, Joseph Di Battista, Michael Hellberg and Carlos Prada. RKB and ADJ were supported by the European Research Council. MR was supported by the Swedish Research Council Vetenskapsrådet (grant number 2021-05243; to MR) and Formas (grant number 2019-00882; to KJ and MR), and by additional grants from the European Research Council (to RKB) and Vetenskapsrådet (to KJ) through the Centre for Marine Evolutionary Biology (https://www.gu.se/en/cemeb-marine-evolutionary-biology).
De Jode A, Le Moan A, Johannesson K, et al. Ten years of demographic modelling of divergence and speciation in the sea. Evolutionary Applications. 2022;00:1-18. doi:10.1111/eva.13428
De Jode, A., Le Moan, A., Johannesson, K., Faria, R., Stankowski, S., Westram, A. M., … Fraisse, C. (2022). Ten years of demographic modelling of divergence and speciation in the sea. Evolutionary Applications. https://doi.org/10.1111/eva.13428
De Jode, Aurélien, Alan Le Moan, Kerstin Johannesson, Rui Faria, Sean Stankowski, Anja M Westram, Roger K. Butlin, Marina Rafajlović, and Christelle Fraisse. “Ten Years of Demographic Modelling of Divergence and Speciation in the Sea.” Evolutionary Applications, 2022. https://doi.org/10.1111/eva.13428.
A. De Jode et al., “Ten years of demographic modelling of divergence and speciation in the sea,” Evolutionary Applications, vol. 00. pp. 1–18, 2022.
De Jode A, Le Moan A, Johannesson K, Faria R, Stankowski S, Westram AM, Butlin RK, Rafajlović M, Fraisse C. 2022. Ten years of demographic modelling of divergence and speciation in the sea. Evolutionary Applications. 00, 1–18.
De Jode, Aurélien, et al. “Ten Years of Demographic Modelling of Divergence and Speciation in the Sea.” Evolutionary Applications, vol. 00, 2022, pp. 1–18, doi:10.1111/eva.13428.
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