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Sweepstakes reproductive success via pervasive and recurrent selective sweeps
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Árnason, Einar, Koskela, Jere, Halldórsdóttir, Katrin and Eldon, Bjarki (2023) Sweepstakes reproductive success via pervasive and recurrent selective sweeps. eLife, 12 . e80781. doi:10.7554/eLife.80781 ISSN 2050-084X.
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Official URL: https://doi.org/10.7554/eLife.80781
Abstract
Highly fecund natural populations characterized by high early mortality abound, yet our knowledge about their recruitment dynamics is somewhat rudimentary. This knowledge gap has implications for our understanding of genetic variation, population connectivity, local adaptation, and the resilience of highly fecund populations. The concept of sweepstakes reproductive success, which posits a considerable variance and skew in individual reproductive output, is key to understanding the distribution of individual reproductive success. However, it still needs to be determined whether highly fecund organisms reproduce through sweepstakes and, if they do, the relative roles of neutral and selective sweepstakes. Here we use coalescent-based statistical analysis of population genomic data to show that selective sweepstakes likely explain recruitment dynamics in the highly fecund Atlantic cod. We show that the Kingman coalescent
(modeling no sweepstakes) and the Xi-Beta coalescent (modeling random sweepstakes), including complex demography and background selection, do not provide an adequate fit for the data. The Durrett-Schweinsberg coalescent, in which selective sweepstakes result from recurrent and pervasive selective sweeps of new mutations, offers greater explanatory power. Our results show that models of sweepstakes reproduction and multiple-merger coalescents are relevant and necessary for understanding genetic diversity in highly fecund natural populations. These findings have fundamental implications for understanding the recruitment variation of fish stocks and general evolutionary genomics of high-fecundity organisms.
Item Type: | Journal Article | ||||||
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Divisions: | Faculty of Science, Engineering and Medicine > Science > Statistics | ||||||
Journal or Publication Title: | eLife | ||||||
Publisher: | eLife Sciences Publications Ltd. | ||||||
ISSN: | 2050-084X | ||||||
Official Date: | 20 February 2023 | ||||||
Dates: |
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Volume: | 12 | ||||||
Article Number: | e80781 | ||||||
DOI: | 10.7554/eLife.80781 | ||||||
Status: | Peer Reviewed | ||||||
Publication Status: | Published | ||||||
Access rights to Published version: | Open Access (Creative Commons) | ||||||
Copyright Holders: | © 2023, Árnason et al. | ||||||
Date of first compliant deposit: | 9 January 2023 | ||||||
Date of first compliant Open Access: | 8 March 2023 | ||||||
Funder: | Icelandic Research Fund, German Research Fundation, UKRI Engineering and Physical Sciences Research Council | ||||||
Grant number: | EP/R044732/1 and EP/V049208/1 | ||||||
Related URLs: | |||||||
Open Access Version: |
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