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      Polygenic adaptation: From sweeps to subtle frequency shifts

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          Abstract

          Evolutionary theory has produced two conflicting paradigms for the adaptation of a polygenic trait. While population genetics views adaptation as a sequence of selective sweeps at single loci underlying the trait, quantitative genetics posits a collective response, where phenotypic adaptation results from subtle allele frequency shifts at many loci. Yet, a synthesis of these views is largely missing and the population genetic factors that favor each scenario are not well understood. Here, we study the architecture of adaptation of a binary polygenic trait (such as resistance) with negative epistasis among the loci of its basis. The genetic structure of this trait allows for a full range of potential architectures of adaptation, ranging from sweeps to small frequency shifts. By combining computer simulations and a newly devised analytical framework based on Yule branching processes, we gain a detailed understanding of the adaptation dynamics for this trait. Our key analytical result is an expression for the joint distribution of mutant alleles at the end of the adaptive phase. This distribution characterizes the polygenic pattern of adaptation at the underlying genotype when phenotypic adaptation has been accomplished. We find that a single compound parameter, the population-scaled background mutation rate Θ bg , explains the main differences among these patterns. For a focal locus, Θ bg measures the mutation rate at all redundant loci in its genetic background that offer alternative ways for adaptation. For adaptation starting from mutation-selection-drift balance, we observe different patterns in three parameter regions. Adaptation proceeds by sweeps for small Θ bg ≲ 0.1, while small polygenic allele frequency shifts require large Θ bg ≳ 100. In the large intermediate regime, we observe a heterogeneous pattern of partial sweeps at several interacting loci.

          Author summary

          It is still an open question how complex traits adapt to new selection pressures. While population genetics champions the search for selective sweeps, quantitative genetics proclaims adaptation via small concerted frequency shifts. To date the empirical evidence of clear sweep signals is more scarce than expected, while subtle shifts remain notoriously hard to detect. In the current study we develop a theoretical framework to predict the expected adaptive architecture of a simple polygenic trait, depending on parameters such as mutation rate, effective population size, size of the trait basis, and the available genetic variability at the onset of selection. For a population in mutation-selection-drift balance we find that adaptation proceeds via complete or partial sweeps for a large set of parameter values. We predict adaptation by small frequency shifts for two main cases. First, for traits with a large mutational target size and high levels of genetic redundancy among loci, and second if the starting frequencies of mutant alleles are more homogeneous than expected in mutation-selection-drift equilibrium, e.g. due to population structure or balancing selection.

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          Most cited references44

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          The hitch-hiking effect of a favourable gene

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            Soft sweeps: molecular population genetics of adaptation from standing genetic variation.

            A population can adapt to a rapid environmental change or habitat expansion in two ways. It may adapt either through new beneficial mutations that subsequently sweep through the population or by using alleles from the standing genetic variation. We use diffusion theory to calculate the probabilities for selective adaptations and find a large increase in the fixation probability for weak substitutions, if alleles originate from the standing genetic variation. We then determine the parameter regions where each scenario-standing variation vs. new mutations-is more likely. Adaptations from the standing genetic variation are favored if either the selective advantage is weak or the selection coefficient and the mutation rate are both high. Finally, we analyze the probability of "soft sweeps," where multiple copies of the selected allele contribute to a substitution, and discuss the consequences for the footprint of selection on linked neutral variation. We find that soft sweeps with weaker selective footprints are likely under both scenarios if the mutation rate and/or the selection coefficient is high.
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              Genomic insights into the origin of farming in the ancient Near East

              We report genome-wide ancient DNA from 44 ancient Near Easterners ranging in time between ~12,000-1,400 BCE, from Natufian hunter-gatherers to Bronze Age farmers. We show that the earliest populations of the Near East derived around half their ancestry from a ‘Basal Eurasian’ lineage that had little if any Neanderthal admixture and that separated from other non-African lineages prior to their separation from each other. The first farmers of the southern Levant (Israel and Jordan) and Zagros Mountains (Iran) were strongly genetically differentiated, and each descended from local hunter-gatherers. By the time of the Bronze Age, these two populations and Anatolian-related farmers had mixed with each other and with the hunter-gatherers of Europe to drastically reduce genetic differentiation. The impact of the Near Eastern farmers extended beyond the Near East: farmers related to those of Anatolia spread westward into Europe; farmers related to those of the Levant spread southward into East Africa; farmers related to those from Iran spread northward into the Eurasian steppe; and people related to both the early farmers of Iran and to the pastoralists of the Eurasian steppe spread eastward into South Asia.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: InvestigationRole: SoftwareRole: ValidationRole: VisualizationRole: Writing – original draft
                Role: ConceptualizationRole: InvestigationRole: MethodologyRole: SoftwareRole: SupervisionRole: Writing – review & editing
                Role: ConceptualizationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: SupervisionRole: ValidationRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS Genet
                PLoS Genet
                plos
                plosgen
                PLoS Genetics
                Public Library of Science (San Francisco, CA USA )
                1553-7390
                1553-7404
                March 2019
                20 March 2019
                : 15
                : 3
                : e1008035
                Affiliations
                [1 ] Mathematics and BioSciences Group, Faculty of Mathematics and Max F. Perutz Laboratories, University of Vienna, Vienna, Austria
                [2 ] Vienna Graduate School of Population Genetics, University of Vienna, Vienna, Austria
                [3 ] Department of Biology, San Francisco State University, San Francisco, California, USA
                University of Rochester, UNITED STATES
                Author notes

                The authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0001-7780-2202
                http://orcid.org/0000-0001-7476-9283
                Article
                PGENETICS-D-18-02054
                10.1371/journal.pgen.1008035
                6443195
                30893299
                c37a3e19-511c-4bb6-8b3f-b564e3722eae
                © 2019 Höllinger et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 23 October 2018
                : 20 February 2019
                Page count
                Figures: 5, Tables: 1, Pages: 26
                Funding
                Funded by: Austrian Science Fund (AT)
                Award ID: DK W-1225-B20
                Award Recipient :
                IH was funded by the Austrian Science Fund (FWF): DK W-1225-B20, Vienna Graduate School of Population Genetics. https://www.popgen-vienna.at/ https://fwf.ac.at The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Genetics
                Genetic Loci
                Biology and Life Sciences
                Genetics
                Genetic Loci
                Quantitative Trait Loci
                Biology and Life Sciences
                Computational Biology
                Genome Analysis
                Trait Locus Analysis
                Biology and Life Sciences
                Genetics
                Genomics
                Genome Analysis
                Trait Locus Analysis
                Biology and Life Sciences
                Genetics
                Mutation
                Biology and Life Sciences
                Genetics
                Phenotypes
                Biology and Life Sciences
                Genetics
                Heredity
                Epistasis
                Biology and Life Sciences
                Evolutionary Biology
                Evolutionary Processes
                Natural Selection
                Research and Analysis Methods
                Crystallographic Techniques
                Phase Determination
                Custom metadata
                vor-update-to-uncorrected-proof
                2019-04-01
                We provide a comprehensive Wolfram Mathematica notebook, showing visualizations of the analytical predictions. The simulation code and data, and summary statistics underlying all figures are available via Dryad (Höllinger I, Pennings PS, Hermisson J. Data from: Polygenic adaptation: From sweeps to subtle frequency shifts. Dryad Digital Repository. DOI: https://doi.org/10.5061/dryad.7n6vg10).

                Genetics
                Genetics

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