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

Giorgio Bertorelle*, Francesca Raffini, Mirte Bosse, Chiara Bortoluzzi, Alessio Iannucci, Emiliano Trucchi, Hernán E. Morales, Cock van Oosterhout

*Corresponding author for this work

    Research output: Contribution to JournalReview articleAcademicpeer-review

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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.

    Original languageEnglish
    Pages (from-to)492-503
    Number of pages12
    JournalNature Reviews Genetics
    Volume23
    Issue number8
    Early online date8 Feb 2022
    DOIs
    Publication statusPublished - Aug 2022

    Bibliographical note

    Funding Information:
    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.

    Publisher Copyright:
    © 2022, Springer Nature Limited.

    Funding

    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.

    FundersFunder number
    Università degli Studi di Ferrara
    Nederlandse Organisatie voor Wetenschappelijk Onderzoek
    Horizon 2020 Framework Programme
    Earth and Life Systems Alliance
    H2020 Marie Skłodowska-Curie Actions840519
    Wellcome TrustWT207492, 207492
    Ministero dell’Istruzione, dell’Università e della Ricerca201794ZXTL
    Royal SocietyICA\R1\201194
    European Molecular Biology Organization1111-2018

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