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A Model-Based Approach for Identifying Signatures of Ancient Balancing Selection in Genetic Data
While much effort has focused on detecting positive and negative directional selection in the human genome, relatively little work has been devoted to balancing selection. This lack of attention is likely due to the paucity of sophisticated methods for identifying sites under balancing selection. He...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4140648/ https://www.ncbi.nlm.nih.gov/pubmed/25144706 http://dx.doi.org/10.1371/journal.pgen.1004561 |
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author | DeGiorgio, Michael Lohmueller, Kirk E. Nielsen, Rasmus |
author_facet | DeGiorgio, Michael Lohmueller, Kirk E. Nielsen, Rasmus |
author_sort | DeGiorgio, Michael |
collection | PubMed |
description | While much effort has focused on detecting positive and negative directional selection in the human genome, relatively little work has been devoted to balancing selection. This lack of attention is likely due to the paucity of sophisticated methods for identifying sites under balancing selection. Here we develop two composite likelihood ratio tests for detecting balancing selection. Using simulations, we show that these methods outperform competing methods under a variety of assumptions and demographic models. We apply the new methods to whole-genome human data, and find a number of previously-identified loci with strong evidence of balancing selection, including several HLA genes. Additionally, we find evidence for many novel candidates, the strongest of which is FANK1, an imprinted gene that suppresses apoptosis, is expressed during meiosis in males, and displays marginal signs of segregation distortion. We hypothesize that balancing selection acts on this locus to stabilize the segregation distortion and negative fitness effects of the distorter allele. Thus, our methods are able to reproduce many previously-hypothesized signals of balancing selection, as well as discover novel interesting candidates. |
format | Online Article Text |
id | pubmed-4140648 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-41406482014-08-25 A Model-Based Approach for Identifying Signatures of Ancient Balancing Selection in Genetic Data DeGiorgio, Michael Lohmueller, Kirk E. Nielsen, Rasmus PLoS Genet Research Article While much effort has focused on detecting positive and negative directional selection in the human genome, relatively little work has been devoted to balancing selection. This lack of attention is likely due to the paucity of sophisticated methods for identifying sites under balancing selection. Here we develop two composite likelihood ratio tests for detecting balancing selection. Using simulations, we show that these methods outperform competing methods under a variety of assumptions and demographic models. We apply the new methods to whole-genome human data, and find a number of previously-identified loci with strong evidence of balancing selection, including several HLA genes. Additionally, we find evidence for many novel candidates, the strongest of which is FANK1, an imprinted gene that suppresses apoptosis, is expressed during meiosis in males, and displays marginal signs of segregation distortion. We hypothesize that balancing selection acts on this locus to stabilize the segregation distortion and negative fitness effects of the distorter allele. Thus, our methods are able to reproduce many previously-hypothesized signals of balancing selection, as well as discover novel interesting candidates. Public Library of Science 2014-08-21 /pmc/articles/PMC4140648/ /pubmed/25144706 http://dx.doi.org/10.1371/journal.pgen.1004561 Text en © 2014 DeGiorgio 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, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article DeGiorgio, Michael Lohmueller, Kirk E. Nielsen, Rasmus A Model-Based Approach for Identifying Signatures of Ancient Balancing Selection in Genetic Data |
title | A Model-Based Approach for Identifying Signatures of Ancient Balancing Selection in Genetic Data |
title_full | A Model-Based Approach for Identifying Signatures of Ancient Balancing Selection in Genetic Data |
title_fullStr | A Model-Based Approach for Identifying Signatures of Ancient Balancing Selection in Genetic Data |
title_full_unstemmed | A Model-Based Approach for Identifying Signatures of Ancient Balancing Selection in Genetic Data |
title_short | A Model-Based Approach for Identifying Signatures of Ancient Balancing Selection in Genetic Data |
title_sort | model-based approach for identifying signatures of ancient balancing selection in genetic data |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4140648/ https://www.ncbi.nlm.nih.gov/pubmed/25144706 http://dx.doi.org/10.1371/journal.pgen.1004561 |
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