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Accounting for diverse evolutionary forces reveals mosaic patterns of selection on human preterm birth loci
Currently, there is no comprehensive framework to evaluate the evolutionary forces acting on genomic regions associated with human complex traits and contextualize the relationship between evolution and molecular function. Here, we develop an approach to test for signatures of diverse evolutionary f...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7382462/ https://www.ncbi.nlm.nih.gov/pubmed/32709900 http://dx.doi.org/10.1038/s41467-020-17258-6 |
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author | LaBella, Abigail L. Abraham, Abin Pichkar, Yakov Fong, Sarah L. Zhang, Ge Muglia, Louis J. Abbot, Patrick Rokas, Antonis Capra, John A. |
author_facet | LaBella, Abigail L. Abraham, Abin Pichkar, Yakov Fong, Sarah L. Zhang, Ge Muglia, Louis J. Abbot, Patrick Rokas, Antonis Capra, John A. |
author_sort | LaBella, Abigail L. |
collection | PubMed |
description | Currently, there is no comprehensive framework to evaluate the evolutionary forces acting on genomic regions associated with human complex traits and contextualize the relationship between evolution and molecular function. Here, we develop an approach to test for signatures of diverse evolutionary forces on trait-associated genomic regions. We apply our method to regions associated with spontaneous preterm birth (sPTB), a complex disorder of global health concern. We find that sPTB-associated regions harbor diverse evolutionary signatures including conservation, excess population differentiation, accelerated evolution, and balanced polymorphism. Furthermore, we integrate evolutionary context with molecular evidence to hypothesize how these regions contribute to sPTB risk. Finally, we observe enrichment in signatures of diverse evolutionary forces in sPTB-associated regions compared to genomic background. By quantifying multiple evolutionary forces acting on sPTB-associated regions, our approach improves understanding of both functional roles and the mosaic of evolutionary forces acting on loci. Our work provides a blueprint for investigating evolutionary pressures on complex traits. |
format | Online Article Text |
id | pubmed-7382462 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-73824622020-07-28 Accounting for diverse evolutionary forces reveals mosaic patterns of selection on human preterm birth loci LaBella, Abigail L. Abraham, Abin Pichkar, Yakov Fong, Sarah L. Zhang, Ge Muglia, Louis J. Abbot, Patrick Rokas, Antonis Capra, John A. Nat Commun Article Currently, there is no comprehensive framework to evaluate the evolutionary forces acting on genomic regions associated with human complex traits and contextualize the relationship between evolution and molecular function. Here, we develop an approach to test for signatures of diverse evolutionary forces on trait-associated genomic regions. We apply our method to regions associated with spontaneous preterm birth (sPTB), a complex disorder of global health concern. We find that sPTB-associated regions harbor diverse evolutionary signatures including conservation, excess population differentiation, accelerated evolution, and balanced polymorphism. Furthermore, we integrate evolutionary context with molecular evidence to hypothesize how these regions contribute to sPTB risk. Finally, we observe enrichment in signatures of diverse evolutionary forces in sPTB-associated regions compared to genomic background. By quantifying multiple evolutionary forces acting on sPTB-associated regions, our approach improves understanding of both functional roles and the mosaic of evolutionary forces acting on loci. Our work provides a blueprint for investigating evolutionary pressures on complex traits. Nature Publishing Group UK 2020-07-24 /pmc/articles/PMC7382462/ /pubmed/32709900 http://dx.doi.org/10.1038/s41467-020-17258-6 Text en © The Author(s) 2020 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 LaBella, Abigail L. Abraham, Abin Pichkar, Yakov Fong, Sarah L. Zhang, Ge Muglia, Louis J. Abbot, Patrick Rokas, Antonis Capra, John A. Accounting for diverse evolutionary forces reveals mosaic patterns of selection on human preterm birth loci |
title | Accounting for diverse evolutionary forces reveals mosaic patterns of selection on human preterm birth loci |
title_full | Accounting for diverse evolutionary forces reveals mosaic patterns of selection on human preterm birth loci |
title_fullStr | Accounting for diverse evolutionary forces reveals mosaic patterns of selection on human preterm birth loci |
title_full_unstemmed | Accounting for diverse evolutionary forces reveals mosaic patterns of selection on human preterm birth loci |
title_short | Accounting for diverse evolutionary forces reveals mosaic patterns of selection on human preterm birth loci |
title_sort | accounting for diverse evolutionary forces reveals mosaic patterns of selection on human preterm birth loci |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7382462/ https://www.ncbi.nlm.nih.gov/pubmed/32709900 http://dx.doi.org/10.1038/s41467-020-17258-6 |
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