Gene expression is the main driver of purifying selection in large penguin populationsuse asterix (*) to get italics

Emiliano Trucchi, Piergiorgio Massa, Francesco Giannelli, Thibault Latrille, Flavia A.N. Fernandes, Lorena Ancona, Nils Chr Stenseth, Joan Ferrer Obiol, Josephine Paris, Giorgio Bertorelle, Celine Le BohecPlease use the format "First name initials family name" as in "Marie S. Curie, Niels H. D. Bohr, Albert Einstein, John R. R. Tolkien, Donna T. Strickland"

2024

<p style="text-align: justify;">Purifying selection is the most pervasive type of selection, as it constantly removes deleterious mutations arising in populations, directly scaling with population size. Highly expressed genes appear to accumulate fewer deleterious mutations between divergent species' lineages (known as E-R anticorrelation), pointing towards gene expression as an additional driver of purifying selection. However, estimates of the effect of gene expression on segregating deleterious variants in natural populations are scarce, as is an understanding of the relative contribution of population size and gene expression to purifying selection. Here, we analyse genomic and transcriptomic data from two natural populations of closely related sister species with different demographic histories, the Emperor penguin (<em>Aptenodytes forsteri</em>) and the King penguin (<em>A. patagonicus</em>), and show that purifying selection at the population-level depends on gene expression rate, resulting in very high selection coefficients at highly expressed genes. Leveraging realistic forward simulations, we estimate that the top 10% of the most highly expressed genes in a genome experience a selection pressure corresponding to an average selection coefficient of -0.1, which decreases to a selection coefficient of -0.01 for the top 50%. Gene expression rate can be regarded as a fundamental parameter of protein evolution in natural populations, maintaining selection effective even at small population size. We suggest it could be used as a proxy for gene selection coefficients, which are notoriously difficult to derive in non-model species under real-world conditions.</p>

https://doi.org/10.6084/m9.figshare.23863503.v1You should fill this box only if you chose 'All or part of the results presented in this preprint are based on data'. URL must start with http:// or https://

https://github.com/emitruc/ExpressionLoadYou should fill this box only if you chose 'Scripts were used to obtain or analyze the results'. URL must start with http:// or https://

https://github.com/emitruc/ExpressionLoadYou should fill this box only if you chose 'Codes have been used in this study'. URL must start with http:// or https://

Keywords Purifying selection, gene expression, population size, E-R anticorrelation, forward simulations

NonePlease indicate the methods that may require specialised expertise during the peer review process (use a comma to separate various required expertises).

Bioinformatics & Computational Biology, Evolutionary Dynamics, Evolutionary Theory, Population Genetics / Genomics

Tanja Pyhäjärvi suggested: Emily Josephs, josep993@msu.edu

e.g. John Doe john@doe.com

No need for them to be recommenders of PCIEvolBiol. Please do not suggest reviewers for whom there might be a conflict of interest. Reviewers are not allowed to review preprints written by close colleagues (with whom they have published in the last four years, with whom they have received joint funding in the last four years, or with whom they are currently writing a manuscript, or submitting a grant proposal), or by family members, friends, or anyone for whom bias might affect the nature of the review - see the code of conduct

2023-08-09 17:53:03

Bruce Rannala