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Genetic redundancy fuels polygenic adaptation in Drosophila

The genetic architecture of adaptive traits is of key importance to predict evolutionary responses. Most adaptive traits are polygenic—i.e., result from selection on a large number of genetic loci—but most molecularly characterized traits have a simple genetic basis. This discrepancy is best explain...

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Autores principales: Barghi, Neda, Tobler, Raymond, Nolte, Viola, Jakšić, Ana Marija, Mallard, François, Otte, Kathrin Anna, Dolezal, Marlies, Taus, Thomas, Kofler, Robert, Schlötterer, Christian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6375663/
https://www.ncbi.nlm.nih.gov/pubmed/30716062
http://dx.doi.org/10.1371/journal.pbio.3000128
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author Barghi, Neda
Tobler, Raymond
Nolte, Viola
Jakšić, Ana Marija
Mallard, François
Otte, Kathrin Anna
Dolezal, Marlies
Taus, Thomas
Kofler, Robert
Schlötterer, Christian
author_facet Barghi, Neda
Tobler, Raymond
Nolte, Viola
Jakšić, Ana Marija
Mallard, François
Otte, Kathrin Anna
Dolezal, Marlies
Taus, Thomas
Kofler, Robert
Schlötterer, Christian
author_sort Barghi, Neda
collection PubMed
description The genetic architecture of adaptive traits is of key importance to predict evolutionary responses. Most adaptive traits are polygenic—i.e., result from selection on a large number of genetic loci—but most molecularly characterized traits have a simple genetic basis. This discrepancy is best explained by the difficulty in detecting small allele frequency changes (AFCs) across many contributing loci. To resolve this, we use laboratory natural selection to detect signatures for selective sweeps and polygenic adaptation. We exposed 10 replicates of a Drosophila simulans population to a new temperature regime and uncovered a polygenic architecture of an adaptive trait with high genetic redundancy among beneficial alleles. We observed convergent responses for several phenotypes—e.g., fitness, metabolic rate, and fat content—and a strong polygenic response (99 selected alleles; mean s = 0.059). However, each of these selected alleles increased in frequency only in a subset of the evolving replicates. We discerned different evolutionary paradigms based on the heterogeneous genomic patterns among replicates. Redundancy and quantitative trait (QT) paradigms fitted the experimental data better than simulations assuming independent selective sweeps. Our results show that natural D. simulans populations harbor a vast reservoir of adaptive variation facilitating rapid evolutionary responses using multiple alternative genetic pathways converging at a new phenotypic optimum. This key property of beneficial alleles requires the modification of testing strategies in natural populations beyond the search for convergence on the molecular level.
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spelling pubmed-63756632019-03-01 Genetic redundancy fuels polygenic adaptation in Drosophila Barghi, Neda Tobler, Raymond Nolte, Viola Jakšić, Ana Marija Mallard, François Otte, Kathrin Anna Dolezal, Marlies Taus, Thomas Kofler, Robert Schlötterer, Christian PLoS Biol Research Article The genetic architecture of adaptive traits is of key importance to predict evolutionary responses. Most adaptive traits are polygenic—i.e., result from selection on a large number of genetic loci—but most molecularly characterized traits have a simple genetic basis. This discrepancy is best explained by the difficulty in detecting small allele frequency changes (AFCs) across many contributing loci. To resolve this, we use laboratory natural selection to detect signatures for selective sweeps and polygenic adaptation. We exposed 10 replicates of a Drosophila simulans population to a new temperature regime and uncovered a polygenic architecture of an adaptive trait with high genetic redundancy among beneficial alleles. We observed convergent responses for several phenotypes—e.g., fitness, metabolic rate, and fat content—and a strong polygenic response (99 selected alleles; mean s = 0.059). However, each of these selected alleles increased in frequency only in a subset of the evolving replicates. We discerned different evolutionary paradigms based on the heterogeneous genomic patterns among replicates. Redundancy and quantitative trait (QT) paradigms fitted the experimental data better than simulations assuming independent selective sweeps. Our results show that natural D. simulans populations harbor a vast reservoir of adaptive variation facilitating rapid evolutionary responses using multiple alternative genetic pathways converging at a new phenotypic optimum. This key property of beneficial alleles requires the modification of testing strategies in natural populations beyond the search for convergence on the molecular level. Public Library of Science 2019-02-04 /pmc/articles/PMC6375663/ /pubmed/30716062 http://dx.doi.org/10.1371/journal.pbio.3000128 Text en © 2019 Barghi et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Barghi, Neda
Tobler, Raymond
Nolte, Viola
Jakšić, Ana Marija
Mallard, François
Otte, Kathrin Anna
Dolezal, Marlies
Taus, Thomas
Kofler, Robert
Schlötterer, Christian
Genetic redundancy fuels polygenic adaptation in Drosophila
title Genetic redundancy fuels polygenic adaptation in Drosophila
title_full Genetic redundancy fuels polygenic adaptation in Drosophila
title_fullStr Genetic redundancy fuels polygenic adaptation in Drosophila
title_full_unstemmed Genetic redundancy fuels polygenic adaptation in Drosophila
title_short Genetic redundancy fuels polygenic adaptation in Drosophila
title_sort genetic redundancy fuels polygenic adaptation in drosophila
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6375663/
https://www.ncbi.nlm.nih.gov/pubmed/30716062
http://dx.doi.org/10.1371/journal.pbio.3000128
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