Consequences of Single-Locus and Tightly Linked Genomic Architectures for Evolutionary Responses to Environmental Change

Author:

Oomen Rebekah A12ORCID,Kuparinen Anna3,Hutchings Jeffrey A245

Affiliation:

1. Centre for Ecological and Evolutionary Synthesis, University of Oslo, Oslo, Norway

2. Centre for Coastal Research, University of Agder, Kristiansand, Norway

3. Department of Biological and Environmental Sciences, University of Jyväskylä, Jyväskylä, Finland

4. Department of Biology, Dalhousie University, Halifax, NS, Canada

5. Institute of Marine Research, Flødevigen Marine Research Station, His, Norway

Abstract

Abstract Genetic and genomic architectures of traits under selection are key factors influencing evolutionary responses. Yet, knowledge of their impacts has been limited by a widespread assumption that most traits are controlled by unlinked polygenic architectures. Recent advances in genome sequencing and eco-evolutionary modeling are unlocking the potential for integrating genomic information into predictions of population responses to environmental change. Using eco-evolutionary simulations, we demonstrate that hypothetical single-locus control of a life history trait produces highly variable and unpredictable harvesting-induced evolution relative to the classically applied multilocus model. Single-locus control of complex traits is thought to be uncommon, yet blocks of linked genes, such as those associated with some types of structural genomic variation, have emerged as taxonomically widespread phenomena. Inheritance of linked architectures resembles that of single loci, thus enabling single-locus-like modeling of polygenic adaptation. Yet, the number of loci, their effect sizes, and the degree of linkage among them all occur along a continuum. We review how linked architectures are often associated, directly or indirectly, with traits expected to be under selection from anthropogenic stressors and are likely to play a large role in adaptation to environmental disturbance. We suggest using single-locus models to explore evolutionary extremes and uncertainties when the trait architecture is unknown, refining parameters as genomic information becomes available, and explicitly incorporating linkage among loci when possible. By overestimating the complexity (e.g., number of independent loci) of the genomic architecture of traits under selection, we risk underestimating the complexity (e.g., nonlinearity) of their evolutionary dynamics.

Funder

James S. McDonnell Foundation

Academy of Finland

European Research Council

Natural Sciences and Engineering Research Council of Canada

Killam Trusts

Loblaw Companies Limited

Publisher

Oxford University Press (OUP)

Subject

Genetics(clinical),Genetics,Molecular Biology,Biotechnology

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