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Quantifying the impact of changes in effective population size and expression level on the rate of coding sequence evolution

Author

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  • Latrille, T.
  • Lartillot, N.

Abstract

Molecular sequences are shaped by selection, where the strength of selection relative to drift is determined by effective population size (Ne). Populations with high Ne are expected to undergo stronger purifying selection, and consequently to show a lower substitution rate for selected mutations relative to the substitution rate for neutral mutations (ω). However, computational models based on biophysics of protein stability have suggested that ω can also be independent of Ne. Together, the response of ω to changes in Ne depends on the specific mapping from sequence to fitness. Importantly, an increase in protein expression level has been found empirically to result in decrease of ω, an observation predicted by theoretical models assuming selection for protein stability. Here, we derive a theoretical approximation for the response of ω to changes in Ne and expression level, under an explicit genotype-phenotype-fitness map. The method is generally valid for additive traits and log-concave fitness functions. We applied these results to protein undergoing selection for their conformational stability and corroborate out findings with simulations under more complex models. We predict a weak response of ω to changes in either Ne or expression level, which are interchangeable. Based on empirical data, we propose that fitness based on the conformational stability may not be a sufficient mechanism to explain the empirically observed variation in ω across species. Other aspects of protein biophysics might be explored, such as protein–protein interactions, which can lead to a stronger response of ω to changes in Ne.

Suggested Citation

  • Latrille, T. & Lartillot, N., 2021. "Quantifying the impact of changes in effective population size and expression level on the rate of coding sequence evolution," Theoretical Population Biology, Elsevier, vol. 142(C), pages 57-66.
  • Handle: RePEc:eee:thpobi:v:142:y:2021:i:c:p:57-66
    DOI: 10.1016/j.tpb.2021.09.005
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    References listed on IDEAS

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    1. Paul D Williams & David D Pollock & Benjamin P Blackburne & Richard A Goldstein, 2006. "Assessing the Accuracy of Ancestral Protein Reconstruction Methods," PLOS Computational Biology, Public Library of Science, vol. 2(6), pages 1-8, June.
    2. J. Romiguier & P. Gayral & M. Ballenghien & A. Bernard & V. Cahais & A. Chenuil & Y. Chiari & R. Dernat & L. Duret & N. Faivre & E. Loire & J. M. Lourenco & B. Nabholz & C. Roux & G. Tsagkogeorga & A., 2014. "Comparative population genomics in animals uncovers the determinants of genetic diversity," Nature, Nature, vol. 515(7526), pages 261-263, November.
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