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Evidence of selection on splicing-associated loci in human populations and relevance to disease loci mapping

We performed a whole-genome scan of genetic variants in splicing regulatory elements (SREs) and evaluated the extent to which natural selection has shaped extant patterns of variation in SREs. We investigated the degree of differentiation of single nucleotide polymorphisms (SNPs) in SREs among human...

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Autores principales: Gamazon, Eric R., Konkashbaev, Anuar, Derks, Eske M., Cox, Nancy J., Lee, Younghee
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5519721/
https://www.ncbi.nlm.nih.gov/pubmed/28729732
http://dx.doi.org/10.1038/s41598-017-05744-9
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author Gamazon, Eric R.
Konkashbaev, Anuar
Derks, Eske M.
Cox, Nancy J.
Lee, Younghee
author_facet Gamazon, Eric R.
Konkashbaev, Anuar
Derks, Eske M.
Cox, Nancy J.
Lee, Younghee
author_sort Gamazon, Eric R.
collection PubMed
description We performed a whole-genome scan of genetic variants in splicing regulatory elements (SREs) and evaluated the extent to which natural selection has shaped extant patterns of variation in SREs. We investigated the degree of differentiation of single nucleotide polymorphisms (SNPs) in SREs among human populations and applied long-range haplotype- and multilocus allelic differentiation-based methods to detect selection signatures. We describe an approach, sampling a large number of loci across the genome from functional classes and using the consensus from multiple tests, for identifying candidates for selection signals. SRE SNPs in various SNP functional classes show different patterns of population differentiation compared with their non-SRE counterparts. Intronic regions display a greater enrichment for extreme population differentiation among the potentially tissue-dependent transcript ratio quantitative trait loci (trQTLs) than SRE SNPs in general and includ outlier trQTLs for cross-population composite likelihood ratio, suggesting that incorporation of context annotation for regulatory variation may lead to improved detection of signature of selection on these loci. The proportion of extremely rare SNPs disrupting SREs is significantly higher in European than in African samples. The approach developed here will be broadly useful for studies of function and disease-associated variation in the human genome.
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spelling pubmed-55197212017-07-26 Evidence of selection on splicing-associated loci in human populations and relevance to disease loci mapping Gamazon, Eric R. Konkashbaev, Anuar Derks, Eske M. Cox, Nancy J. Lee, Younghee Sci Rep Article We performed a whole-genome scan of genetic variants in splicing regulatory elements (SREs) and evaluated the extent to which natural selection has shaped extant patterns of variation in SREs. We investigated the degree of differentiation of single nucleotide polymorphisms (SNPs) in SREs among human populations and applied long-range haplotype- and multilocus allelic differentiation-based methods to detect selection signatures. We describe an approach, sampling a large number of loci across the genome from functional classes and using the consensus from multiple tests, for identifying candidates for selection signals. SRE SNPs in various SNP functional classes show different patterns of population differentiation compared with their non-SRE counterparts. Intronic regions display a greater enrichment for extreme population differentiation among the potentially tissue-dependent transcript ratio quantitative trait loci (trQTLs) than SRE SNPs in general and includ outlier trQTLs for cross-population composite likelihood ratio, suggesting that incorporation of context annotation for regulatory variation may lead to improved detection of signature of selection on these loci. The proportion of extremely rare SNPs disrupting SREs is significantly higher in European than in African samples. The approach developed here will be broadly useful for studies of function and disease-associated variation in the human genome. Nature Publishing Group UK 2017-07-20 /pmc/articles/PMC5519721/ /pubmed/28729732 http://dx.doi.org/10.1038/s41598-017-05744-9 Text en © The Author(s) 2017 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Gamazon, Eric R.
Konkashbaev, Anuar
Derks, Eske M.
Cox, Nancy J.
Lee, Younghee
Evidence of selection on splicing-associated loci in human populations and relevance to disease loci mapping
title Evidence of selection on splicing-associated loci in human populations and relevance to disease loci mapping
title_full Evidence of selection on splicing-associated loci in human populations and relevance to disease loci mapping
title_fullStr Evidence of selection on splicing-associated loci in human populations and relevance to disease loci mapping
title_full_unstemmed Evidence of selection on splicing-associated loci in human populations and relevance to disease loci mapping
title_short Evidence of selection on splicing-associated loci in human populations and relevance to disease loci mapping
title_sort evidence of selection on splicing-associated loci in human populations and relevance to disease loci mapping
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5519721/
https://www.ncbi.nlm.nih.gov/pubmed/28729732
http://dx.doi.org/10.1038/s41598-017-05744-9
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