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Inferring the timing and strength of natural selection and gene migration in the evolution of chicken from ancient DNA data
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  • Wenyang Lyu,
  • Xiaoyang Dai,
  • Mark Beaumont,
  • Feng Yu,
  • Zhangyi He
Wenyang Lyu
University of Bristol

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Xiaoyang Dai
University of Bristol
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Mark Beaumont
University of Bristol
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Feng Yu
University of Bristol
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Zhangyi He
University of Cambridge
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Abstract

With the rapid growth of the number of sequenced ancient genomes, there has been increasing interest in using this new information to study past and present adaptation. Such an additional temporal component has the promise of providing improved power for the estimation of natural selection. Over the last decade, statistical approaches for detection and quantification of natural selection from ancient DNA (aDNA) data have been developed. However, most of the existing methods do not allow us to estimate the timing of natural selection along with its strength, which is key to understanding the evolution and persistence of organismal diversity. Additionally, most methods ignore the fact that natural populations are almost always structured, which can result in overestimation of the effect of natural selection. To address these issues, we propose a novel Bayesian framework for the inference of natural selection and gene migration from aDNA data with Markov chain Monte Carlo techniques, co-estimating both timing and strength of natural selection and gene migration. Such an advance enables us to infer drivers of natural selection and gene migration by correlating genetic evolution with potential causes such as the changes in the ecological context in which an organism has evolved. The performance of our procedure is evaluated through extensive simulations, with its utility shown with an application to ancient chicken samples.
22 May 2021Submitted to Molecular Ecology Resources
08 Jun 2021Submission Checks Completed
08 Jun 2021Assigned to Editor
11 Jun 2021Reviewer(s) Assigned
06 Aug 2021Review(s) Completed, Editorial Evaluation Pending
12 Aug 2021Editorial Decision: Revise Minor
10 Sep 2021Review(s) Completed, Editorial Evaluation Pending
10 Sep 20211st Revision Received
28 Sep 2021Editorial Decision: Accept
May 2022Published in Molecular Ecology Resources volume 22 issue 4 on pages 1362-1379. 10.1111/1755-0998.13553