loading page

Estimating temporally variable selection intensity from ancient DNA data with the flexibility of modelling linkage and epistasis
  • +2
  • Zhangyi He,
  • Xiaoyang Dai,
  • Wenyang Lyu,
  • Mark Beaumont,
  • Feng Yu
Zhangyi He
Cancer Research UK Beatson Institute

Corresponding Author:[email protected]

Author Profile
Xiaoyang Dai
Queen Mary University of London Barts and The London School of Medicine and Dentistry
Author Profile
Wenyang Lyu
University of Bristol
Author Profile
Mark Beaumont
University of Bristol
Author Profile
Feng Yu
University of Bristol
Author Profile


Innovations in ancient DNA (aDNA) preparation and sequencing technologies have exponentially increased the quality and quantity of aDNA data extracted from ancient biological materials. The additional temporal component from the incoming aDNA data can provide improved power to address fundamental evolutionary questions like characterising selection processes that shape the phenotypes and genotypes of contemporary populations or species. However, utilising aDNA to study past selection processes still involves considerable hurdles such as how to eliminate the confounding effect of genetic interactions in the inference of selection. To circumvent this challenge, in this work we extend the method introduced by He et al. (2022) to infer temporally variable selection from the data on aDNA sequences with the flexibility of modelling linkage and epistasis. Our posterior computation is carried out through a robust adaptive version of the particle marginal Metropolis-Hastings algorithm with a coerced acceptance rate. Moreover, our extension inherits their desirable features like modelling sample uncertainties resulting from the damage and fragmentation of aDNA molecules and reconstructing underlying gamete frequency trajectories of the population. We assess the performance and show the utility of our procedure with an application to ancient horse samples genotyped at the loci encoding base coat colours and pinto coat patterns.
16 Aug 2022Submitted to Molecular Ecology Resources
08 Sep 2022Submission Checks Completed
08 Sep 2022Assigned to Editor
16 Sep 2022Reviewer(s) Assigned
15 Oct 2022Review(s) Completed, Editorial Evaluation Pending
07 Dec 2022Editorial Decision: Revise Minor
20 Feb 20231st Revision Received
22 Feb 2023Submission Checks Completed
22 Feb 2023Assigned to Editor
22 Feb 2023Review(s) Completed, Editorial Evaluation Pending
27 Feb 2023Reviewer(s) Assigned
24 Mar 2023Editorial Decision: Accept