Genetic load: Genomic estimates and applications in non-model animals

Bertorelle, Giorgio, Raffini, Francesca, Bosse, Mirte, Bortoluzzi, Chiara, Iannucci, Alessio, Trucchi, Emiliano, Morales, Hernán E. and van Oosterhout, Cock ORCID: https://orcid.org/0000-0002-5653-738X (2022) Genetic load: Genomic estimates and applications in non-model animals. Nature Reviews Genetics, 23 (8). 492–503. ISSN 1471-0056

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Abstract

Genetic variation, which is generated by mutation, recombination and gene flow, can reduce the mean fitness of a population, both now and in the future. This ‘genetic load’ has been estimated in a wide range of animal taxa using various approaches. Advances in genome sequencing and computational techniques now enable us to estimate the genetic load in populations and individuals without direct fitness estimates. Here, we review the classic and contemporary literature of genetic load. We describe approaches to quantify the genetic load in whole-genome sequence data based on evolutionary conservation and annotations. We show that splitting the load into its two components — the realized load (or expressed load) and the masked load (or inbreeding load) — can improve our understanding of the population genetics of deleterious mutations.

Item Type: Article
Additional Information: Acknowledgements: The authors thank D. Charlesworth and A. Caballero for helpful comments on a previous version of the manuscript. C.v.O. was supported by the Royal Society International Collaborations Award (ICA\R1\201194) and the Earth and Life Systems Alliance (ELSA). G.B. and F.R. were supported by the University of Ferrara (Italy). G.B., F.R., A.I. and E.T. were funded by the MIUR PRIN 2017 grant 201794ZXTL to G.B. M.B. was financially supported by the Dutch NWO Veni grant n. 016.Veni.181.050. H.E.M. was funded by an EMBO long-term fellowship (grant 1111-2018) and the European Union’s Horizon 2020 research and innovation programme under a Marie Sklodowska-Curie grant (840519). C.B. is funded by the Wellcome grant WT207492.
Uncontrolled Keywords: molecular biology,genetics,genetics(clinical) ,/dk/atira/pure/subjectarea/asjc/1300/1312
Faculty \ School: Faculty of Science > School of Environmental Sciences
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Depositing User: LivePure Connector
Date Deposited: 14 Mar 2022 11:30
Last Modified: 22 Oct 2022 17:36
URI: https://ueaeprints.uea.ac.uk/id/eprint/84029
DOI: 10.1038/s41576-022-00448-x

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