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A spatially aware likelihood test to detect sweeps from haplotype distributions
The inference of positive selection in genomes is a problem of great interest in evolutionary genomics. By identifying putative regions of the genome that contain adaptive mutations, we are able to learn about the biology of organisms and their evolutionary history. Here we introduce a composite lik...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9022890/ https://www.ncbi.nlm.nih.gov/pubmed/35404934 http://dx.doi.org/10.1371/journal.pgen.1010134 |
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author | DeGiorgio, Michael Szpiech, Zachary A. |
author_facet | DeGiorgio, Michael Szpiech, Zachary A. |
author_sort | DeGiorgio, Michael |
collection | PubMed |
description | The inference of positive selection in genomes is a problem of great interest in evolutionary genomics. By identifying putative regions of the genome that contain adaptive mutations, we are able to learn about the biology of organisms and their evolutionary history. Here we introduce a composite likelihood method that identifies recently completed or ongoing positive selection by searching for extreme distortions in the spatial distribution of the haplotype frequency spectrum along the genome relative to the genome-wide expectation taken as neutrality. Furthermore, the method simultaneously infers two parameters of the sweep: the number of sweeping haplotypes and the “width” of the sweep, which is related to the strength and timing of selection. We demonstrate that this method outperforms the leading haplotype-based selection statistics, though strong signals in low-recombination regions merit extra scrutiny. As a positive control, we apply it to two well-studied human populations from the 1000 Genomes Project and examine haplotype frequency spectrum patterns at the LCT and MHC loci. We also apply it to a data set of brown rats sampled in NYC and identify genes related to olfactory perception. To facilitate use of this method, we have implemented it in user-friendly open source software. |
format | Online Article Text |
id | pubmed-9022890 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-90228902022-04-22 A spatially aware likelihood test to detect sweeps from haplotype distributions DeGiorgio, Michael Szpiech, Zachary A. PLoS Genet Research Article The inference of positive selection in genomes is a problem of great interest in evolutionary genomics. By identifying putative regions of the genome that contain adaptive mutations, we are able to learn about the biology of organisms and their evolutionary history. Here we introduce a composite likelihood method that identifies recently completed or ongoing positive selection by searching for extreme distortions in the spatial distribution of the haplotype frequency spectrum along the genome relative to the genome-wide expectation taken as neutrality. Furthermore, the method simultaneously infers two parameters of the sweep: the number of sweeping haplotypes and the “width” of the sweep, which is related to the strength and timing of selection. We demonstrate that this method outperforms the leading haplotype-based selection statistics, though strong signals in low-recombination regions merit extra scrutiny. As a positive control, we apply it to two well-studied human populations from the 1000 Genomes Project and examine haplotype frequency spectrum patterns at the LCT and MHC loci. We also apply it to a data set of brown rats sampled in NYC and identify genes related to olfactory perception. To facilitate use of this method, we have implemented it in user-friendly open source software. Public Library of Science 2022-04-11 /pmc/articles/PMC9022890/ /pubmed/35404934 http://dx.doi.org/10.1371/journal.pgen.1010134 Text en © 2022 DeGiorgio, Szpiech https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://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 DeGiorgio, Michael Szpiech, Zachary A. A spatially aware likelihood test to detect sweeps from haplotype distributions |
title | A spatially aware likelihood test to detect sweeps from haplotype distributions |
title_full | A spatially aware likelihood test to detect sweeps from haplotype distributions |
title_fullStr | A spatially aware likelihood test to detect sweeps from haplotype distributions |
title_full_unstemmed | A spatially aware likelihood test to detect sweeps from haplotype distributions |
title_short | A spatially aware likelihood test to detect sweeps from haplotype distributions |
title_sort | spatially aware likelihood test to detect sweeps from haplotype distributions |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9022890/ https://www.ncbi.nlm.nih.gov/pubmed/35404934 http://dx.doi.org/10.1371/journal.pgen.1010134 |
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