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Identifying artificial selection signals in the chicken genome
Identifying the signals of artificial selection can contribute to further shaping economically important traits. Here, a chicken 600k SNP-array was employed to detect the signals of artificial selection using 331 individuals from 9 breeds, including Jingfen (JF), Jinghong (JH), Araucanas (AR), White...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5919632/ https://www.ncbi.nlm.nih.gov/pubmed/29698423 http://dx.doi.org/10.1371/journal.pone.0196215 |
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author | Ma, Yunlong Gu, Lantao Yang, Liubin Sun, Chenghao Xie, Shengsong Fang, Chengchi Gong, Yangzhang Li, Shijun |
author_facet | Ma, Yunlong Gu, Lantao Yang, Liubin Sun, Chenghao Xie, Shengsong Fang, Chengchi Gong, Yangzhang Li, Shijun |
author_sort | Ma, Yunlong |
collection | PubMed |
description | Identifying the signals of artificial selection can contribute to further shaping economically important traits. Here, a chicken 600k SNP-array was employed to detect the signals of artificial selection using 331 individuals from 9 breeds, including Jingfen (JF), Jinghong (JH), Araucanas (AR), White Leghorn (WL), Pekin-Bantam (PB), Shamo (SH), Gallus-Gallus-Spadiceus (GA), Rheinlander (RH) and Vorwerkhuhn (VO). Per the population genetic structure, 9 breeds were combined into 5 breed-pools, and a ‘two-step’ strategy was used to reveal the signals of artificial selection. GA, which has little artificial selection, was defined as the reference population, and a total of 204, 155, 305 and 323 potential artificial selection signals were identified in AR_VO, PB, RH_WL and JH_JF, respectively. We also found signals derived from standing and de-novo genetic variations have contributed to adaptive evolution during artificial selection. Further enrichment analysis suggests that the genomic regions of artificial selection signals harbour genes, including THSR, PTHLH and PMCH, responsible for economic traits, such as fertility, growth and immunization. Overall, this study found a series of genes that contribute to the improvement of chicken breeds and revealed the genetic mechanisms of adaptive evolution, which can be used as fundamental information in future chicken functional genomics study. |
format | Online Article Text |
id | pubmed-5919632 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-59196322018-05-11 Identifying artificial selection signals in the chicken genome Ma, Yunlong Gu, Lantao Yang, Liubin Sun, Chenghao Xie, Shengsong Fang, Chengchi Gong, Yangzhang Li, Shijun PLoS One Research Article Identifying the signals of artificial selection can contribute to further shaping economically important traits. Here, a chicken 600k SNP-array was employed to detect the signals of artificial selection using 331 individuals from 9 breeds, including Jingfen (JF), Jinghong (JH), Araucanas (AR), White Leghorn (WL), Pekin-Bantam (PB), Shamo (SH), Gallus-Gallus-Spadiceus (GA), Rheinlander (RH) and Vorwerkhuhn (VO). Per the population genetic structure, 9 breeds were combined into 5 breed-pools, and a ‘two-step’ strategy was used to reveal the signals of artificial selection. GA, which has little artificial selection, was defined as the reference population, and a total of 204, 155, 305 and 323 potential artificial selection signals were identified in AR_VO, PB, RH_WL and JH_JF, respectively. We also found signals derived from standing and de-novo genetic variations have contributed to adaptive evolution during artificial selection. Further enrichment analysis suggests that the genomic regions of artificial selection signals harbour genes, including THSR, PTHLH and PMCH, responsible for economic traits, such as fertility, growth and immunization. Overall, this study found a series of genes that contribute to the improvement of chicken breeds and revealed the genetic mechanisms of adaptive evolution, which can be used as fundamental information in future chicken functional genomics study. Public Library of Science 2018-04-26 /pmc/articles/PMC5919632/ /pubmed/29698423 http://dx.doi.org/10.1371/journal.pone.0196215 Text en © 2018 Ma 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 (http://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 Ma, Yunlong Gu, Lantao Yang, Liubin Sun, Chenghao Xie, Shengsong Fang, Chengchi Gong, Yangzhang Li, Shijun Identifying artificial selection signals in the chicken genome |
title | Identifying artificial selection signals in the chicken genome |
title_full | Identifying artificial selection signals in the chicken genome |
title_fullStr | Identifying artificial selection signals in the chicken genome |
title_full_unstemmed | Identifying artificial selection signals in the chicken genome |
title_short | Identifying artificial selection signals in the chicken genome |
title_sort | identifying artificial selection signals in the chicken genome |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5919632/ https://www.ncbi.nlm.nih.gov/pubmed/29698423 http://dx.doi.org/10.1371/journal.pone.0196215 |
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