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Whole-genome sequencing reveals selection signatures associated with important traits in six goat breeds

Comparative population genomics analysis is an effective approach to identify selection signatures in farm animals. In this study, we systematically investigated the selection signatures in six phenotypically diverse goat breeds using SNPs obtained from pooled whole-genome resequencing data. More th...

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Autores principales: Guo, Jiazhong, Tao, Haixi, Li, Pengfei, Li, Li, Zhong, Tao, Wang, Linjie, Ma, Jinying, Chen, Xiaoying, Song, Tianzeng, Zhang, Hongping
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6039503/
https://www.ncbi.nlm.nih.gov/pubmed/29991772
http://dx.doi.org/10.1038/s41598-018-28719-w
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author Guo, Jiazhong
Tao, Haixi
Li, Pengfei
Li, Li
Zhong, Tao
Wang, Linjie
Ma, Jinying
Chen, Xiaoying
Song, Tianzeng
Zhang, Hongping
author_facet Guo, Jiazhong
Tao, Haixi
Li, Pengfei
Li, Li
Zhong, Tao
Wang, Linjie
Ma, Jinying
Chen, Xiaoying
Song, Tianzeng
Zhang, Hongping
author_sort Guo, Jiazhong
collection PubMed
description Comparative population genomics analysis is an effective approach to identify selection signatures in farm animals. In this study, we systematically investigated the selection signatures in six phenotypically diverse goat breeds using SNPs obtained from pooled whole-genome resequencing data. More than 95.5% of 446–642 million clean reads were mapped to the latest reference goat genome, which generated a sequencing depth ranging from 22.30 to 31.75-fold for each breed. A total of 5,802,307, 6,794,020, 7,562,312, 5,325,119, 8,764,136, and 9,488,057 putative SNPs were detected in Boer, Meigu, Jintang Black, Nanjiang Yellow, Tibetan, and Tibetan cashmere goats, respectively. Based on the genome-wide F(ST) and expected heterozygosity scores along 100-kb sliding windows, 68, 89, 44, 44, 19, and 35 outlier windows were deemed as the selection signatures in the six goat breeds. After genome annotation, several genes within the selection signals were found to be possibly associated with important traits in goats, such as coat color (IRF4, EXOC2, RALY, EIF2S2, and KITLG), high-altitude adaptation (EPAS1), growth (LDB2), and reproduction traits (KHDRBS2). In summary, we provide an improved understanding of the genetic diversity and the genomic footprints under positive selection or the adaptations to the local environments in the domestic goat genome.
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spelling pubmed-60395032018-07-12 Whole-genome sequencing reveals selection signatures associated with important traits in six goat breeds Guo, Jiazhong Tao, Haixi Li, Pengfei Li, Li Zhong, Tao Wang, Linjie Ma, Jinying Chen, Xiaoying Song, Tianzeng Zhang, Hongping Sci Rep Article Comparative population genomics analysis is an effective approach to identify selection signatures in farm animals. In this study, we systematically investigated the selection signatures in six phenotypically diverse goat breeds using SNPs obtained from pooled whole-genome resequencing data. More than 95.5% of 446–642 million clean reads were mapped to the latest reference goat genome, which generated a sequencing depth ranging from 22.30 to 31.75-fold for each breed. A total of 5,802,307, 6,794,020, 7,562,312, 5,325,119, 8,764,136, and 9,488,057 putative SNPs were detected in Boer, Meigu, Jintang Black, Nanjiang Yellow, Tibetan, and Tibetan cashmere goats, respectively. Based on the genome-wide F(ST) and expected heterozygosity scores along 100-kb sliding windows, 68, 89, 44, 44, 19, and 35 outlier windows were deemed as the selection signatures in the six goat breeds. After genome annotation, several genes within the selection signals were found to be possibly associated with important traits in goats, such as coat color (IRF4, EXOC2, RALY, EIF2S2, and KITLG), high-altitude adaptation (EPAS1), growth (LDB2), and reproduction traits (KHDRBS2). In summary, we provide an improved understanding of the genetic diversity and the genomic footprints under positive selection or the adaptations to the local environments in the domestic goat genome. Nature Publishing Group UK 2018-07-10 /pmc/articles/PMC6039503/ /pubmed/29991772 http://dx.doi.org/10.1038/s41598-018-28719-w Text en © The Author(s) 2018 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
Guo, Jiazhong
Tao, Haixi
Li, Pengfei
Li, Li
Zhong, Tao
Wang, Linjie
Ma, Jinying
Chen, Xiaoying
Song, Tianzeng
Zhang, Hongping
Whole-genome sequencing reveals selection signatures associated with important traits in six goat breeds
title Whole-genome sequencing reveals selection signatures associated with important traits in six goat breeds
title_full Whole-genome sequencing reveals selection signatures associated with important traits in six goat breeds
title_fullStr Whole-genome sequencing reveals selection signatures associated with important traits in six goat breeds
title_full_unstemmed Whole-genome sequencing reveals selection signatures associated with important traits in six goat breeds
title_short Whole-genome sequencing reveals selection signatures associated with important traits in six goat breeds
title_sort whole-genome sequencing reveals selection signatures associated with important traits in six goat breeds
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6039503/
https://www.ncbi.nlm.nih.gov/pubmed/29991772
http://dx.doi.org/10.1038/s41598-018-28719-w
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