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Genomic Determinants of Protein Evolution and Polymorphism in Arabidopsis

Recent results from Drosophila suggest that positive selection has a substantial impact on genomic patterns of polymorphism and divergence. However, species with smaller population sizes and/or stronger population structure may not be expected to exhibit Drosophila-like patterns of sequence variatio...

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Autores principales: Slotte, Tanja, Bataillon, Thomas, Hansen, Troels T., St. Onge, Kate, Wright, Stephen I., Schierup, Mikkel H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3296466/
https://www.ncbi.nlm.nih.gov/pubmed/21926095
http://dx.doi.org/10.1093/gbe/evr094
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author Slotte, Tanja
Bataillon, Thomas
Hansen, Troels T.
St. Onge, Kate
Wright, Stephen I.
Schierup, Mikkel H.
author_facet Slotte, Tanja
Bataillon, Thomas
Hansen, Troels T.
St. Onge, Kate
Wright, Stephen I.
Schierup, Mikkel H.
author_sort Slotte, Tanja
collection PubMed
description Recent results from Drosophila suggest that positive selection has a substantial impact on genomic patterns of polymorphism and divergence. However, species with smaller population sizes and/or stronger population structure may not be expected to exhibit Drosophila-like patterns of sequence variation. We test this prediction and identify determinants of levels of polymorphism and rates of protein evolution using genomic data from Arabidopsis thaliana and the recently sequenced Arabidopsis lyrata genome. We find that, in contrast to Drosophila, there is no negative relationship between nonsynonymous divergence and silent polymorphism at any spatial scale examined. Instead, synonymous divergence is a major predictor of silent polymorphism, which suggests variation in mutation rate as the main determinant of silent variation. Variation in rates of protein divergence is mainly correlated with gene expression level and breadth, consistent with results for a broad range of taxa, and map-based estimates of recombination rate are only weakly correlated with nonsynonymous divergence. Variation in mutation rates and the strength of purifying selection seem to be major drivers of patterns of polymorphism and divergence in Arabidopsis. Nevertheless, a model allowing for varying negative and positive selection by functional gene category explains the data better than a homogeneous model, implying the action of positive selection on a subset of genes. Genes involved in disease resistance and abiotic stress display high proportions of adaptive substitution. Our results are important for a general understanding of the determinants of rates of protein evolution and the impact of selection on patterns of polymorphism and divergence.
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spelling pubmed-32964662012-03-07 Genomic Determinants of Protein Evolution and Polymorphism in Arabidopsis Slotte, Tanja Bataillon, Thomas Hansen, Troels T. St. Onge, Kate Wright, Stephen I. Schierup, Mikkel H. Genome Biol Evol Research Articles Recent results from Drosophila suggest that positive selection has a substantial impact on genomic patterns of polymorphism and divergence. However, species with smaller population sizes and/or stronger population structure may not be expected to exhibit Drosophila-like patterns of sequence variation. We test this prediction and identify determinants of levels of polymorphism and rates of protein evolution using genomic data from Arabidopsis thaliana and the recently sequenced Arabidopsis lyrata genome. We find that, in contrast to Drosophila, there is no negative relationship between nonsynonymous divergence and silent polymorphism at any spatial scale examined. Instead, synonymous divergence is a major predictor of silent polymorphism, which suggests variation in mutation rate as the main determinant of silent variation. Variation in rates of protein divergence is mainly correlated with gene expression level and breadth, consistent with results for a broad range of taxa, and map-based estimates of recombination rate are only weakly correlated with nonsynonymous divergence. Variation in mutation rates and the strength of purifying selection seem to be major drivers of patterns of polymorphism and divergence in Arabidopsis. Nevertheless, a model allowing for varying negative and positive selection by functional gene category explains the data better than a homogeneous model, implying the action of positive selection on a subset of genes. Genes involved in disease resistance and abiotic stress display high proportions of adaptive substitution. Our results are important for a general understanding of the determinants of rates of protein evolution and the impact of selection on patterns of polymorphism and divergence. Oxford University Press 2011-09-16 /pmc/articles/PMC3296466/ /pubmed/21926095 http://dx.doi.org/10.1093/gbe/evr094 Text en © The Author(s) 2011. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. http://creativecommons.org/licenses/by-nc/3.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Articles
Slotte, Tanja
Bataillon, Thomas
Hansen, Troels T.
St. Onge, Kate
Wright, Stephen I.
Schierup, Mikkel H.
Genomic Determinants of Protein Evolution and Polymorphism in Arabidopsis
title Genomic Determinants of Protein Evolution and Polymorphism in Arabidopsis
title_full Genomic Determinants of Protein Evolution and Polymorphism in Arabidopsis
title_fullStr Genomic Determinants of Protein Evolution and Polymorphism in Arabidopsis
title_full_unstemmed Genomic Determinants of Protein Evolution and Polymorphism in Arabidopsis
title_short Genomic Determinants of Protein Evolution and Polymorphism in Arabidopsis
title_sort genomic determinants of protein evolution and polymorphism in arabidopsis
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3296466/
https://www.ncbi.nlm.nih.gov/pubmed/21926095
http://dx.doi.org/10.1093/gbe/evr094
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