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Weighted single-step GWAS identified candidate genes associated with semen traits in a Duroc boar population

BACKGROUND: In the pig production industry, artificial insemination (AI) plays an important role in enlarging the beneficial impact of elite boars. Understanding the genetic architecture and detecting genetic markers associated with semen traits can help in improving genetic selection for such trait...

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Autores principales: Gao, Ning, Chen, Yilong, Liu, Xiaohong, Zhao, Yunxiang, Zhu, Lin, Liu, Ali, Jiang, Wei, Peng, Xing, Zhang, Conglin, Tang, Zhenshuang, Li, Xinyun, Chen, Yaosheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6822442/
https://www.ncbi.nlm.nih.gov/pubmed/31666004
http://dx.doi.org/10.1186/s12864-019-6164-5
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author Gao, Ning
Chen, Yilong
Liu, Xiaohong
Zhao, Yunxiang
Zhu, Lin
Liu, Ali
Jiang, Wei
Peng, Xing
Zhang, Conglin
Tang, Zhenshuang
Li, Xinyun
Chen, Yaosheng
author_facet Gao, Ning
Chen, Yilong
Liu, Xiaohong
Zhao, Yunxiang
Zhu, Lin
Liu, Ali
Jiang, Wei
Peng, Xing
Zhang, Conglin
Tang, Zhenshuang
Li, Xinyun
Chen, Yaosheng
author_sort Gao, Ning
collection PubMed
description BACKGROUND: In the pig production industry, artificial insemination (AI) plays an important role in enlarging the beneficial impact of elite boars. Understanding the genetic architecture and detecting genetic markers associated with semen traits can help in improving genetic selection for such traits and accelerate genetic progress. In this study, we utilized a weighted single-step genome-wide association study (wssGWAS) procedure to detect genetic regions and further candidate genes associated with semen traits in a Duroc boar population. Overall, the full pedigree consists of 5284 pigs (12 generations), of which 2693 boars have semen data (143,113 ejaculations) and 1733 pigs were genotyped with 50 K single nucleotide polymorphism (SNP) array. RESULTS: Results show that the most significant genetic regions (0.4 Mb windows) explained approximately 2%~ 6% of the total genetic variances for the studied traits. Totally, the identified significant windows (windows explaining more than 1% of total genetic variances) explained 28.29, 35.31, 41.98, and 20.60% of genetic variances (not phenotypic variance) for number of sperm cells, sperm motility, sperm progressive motility, and total morphological abnormalities, respectively. Several genes that have been previously reported to be associated with mammal spermiogenesis, testes functioning, and male fertility were detected and treated as candidate genes for the traits of interest: Number of sperm cells, TDRD5, QSOX1, BLK, TIMP3, THRA, CSF3, and ZPBP1; Sperm motility, PPP2R2B, NEK2, NDRG, ADAM7, SKP2, and RNASET2; Sperm progressive motility, SH2B1, BLK, LAMB1, VPS4A, SPAG9, LCN2, and DNM1; Total morphological abnormalities, GHR, SELENOP, SLC16A5, SLC9A3R1, and DNAI2. CONCLUSIONS: In conclusion, candidate genes associated with Duroc boars’ semen traits, including the number of sperm cells, sperm motility, sperm progressive motility, and total morphological abnormalities, were identified using wssGWAS. KEGG and GO enrichment analysis indicate that the identified candidate genes were enriched in biological processes and functional terms may be involved into spermiogenesis, testes functioning, and male fertility.
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spelling pubmed-68224422019-11-06 Weighted single-step GWAS identified candidate genes associated with semen traits in a Duroc boar population Gao, Ning Chen, Yilong Liu, Xiaohong Zhao, Yunxiang Zhu, Lin Liu, Ali Jiang, Wei Peng, Xing Zhang, Conglin Tang, Zhenshuang Li, Xinyun Chen, Yaosheng BMC Genomics Research Article BACKGROUND: In the pig production industry, artificial insemination (AI) plays an important role in enlarging the beneficial impact of elite boars. Understanding the genetic architecture and detecting genetic markers associated with semen traits can help in improving genetic selection for such traits and accelerate genetic progress. In this study, we utilized a weighted single-step genome-wide association study (wssGWAS) procedure to detect genetic regions and further candidate genes associated with semen traits in a Duroc boar population. Overall, the full pedigree consists of 5284 pigs (12 generations), of which 2693 boars have semen data (143,113 ejaculations) and 1733 pigs were genotyped with 50 K single nucleotide polymorphism (SNP) array. RESULTS: Results show that the most significant genetic regions (0.4 Mb windows) explained approximately 2%~ 6% of the total genetic variances for the studied traits. Totally, the identified significant windows (windows explaining more than 1% of total genetic variances) explained 28.29, 35.31, 41.98, and 20.60% of genetic variances (not phenotypic variance) for number of sperm cells, sperm motility, sperm progressive motility, and total morphological abnormalities, respectively. Several genes that have been previously reported to be associated with mammal spermiogenesis, testes functioning, and male fertility were detected and treated as candidate genes for the traits of interest: Number of sperm cells, TDRD5, QSOX1, BLK, TIMP3, THRA, CSF3, and ZPBP1; Sperm motility, PPP2R2B, NEK2, NDRG, ADAM7, SKP2, and RNASET2; Sperm progressive motility, SH2B1, BLK, LAMB1, VPS4A, SPAG9, LCN2, and DNM1; Total morphological abnormalities, GHR, SELENOP, SLC16A5, SLC9A3R1, and DNAI2. CONCLUSIONS: In conclusion, candidate genes associated with Duroc boars’ semen traits, including the number of sperm cells, sperm motility, sperm progressive motility, and total morphological abnormalities, were identified using wssGWAS. KEGG and GO enrichment analysis indicate that the identified candidate genes were enriched in biological processes and functional terms may be involved into spermiogenesis, testes functioning, and male fertility. BioMed Central 2019-10-30 /pmc/articles/PMC6822442/ /pubmed/31666004 http://dx.doi.org/10.1186/s12864-019-6164-5 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided 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 Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Gao, Ning
Chen, Yilong
Liu, Xiaohong
Zhao, Yunxiang
Zhu, Lin
Liu, Ali
Jiang, Wei
Peng, Xing
Zhang, Conglin
Tang, Zhenshuang
Li, Xinyun
Chen, Yaosheng
Weighted single-step GWAS identified candidate genes associated with semen traits in a Duroc boar population
title Weighted single-step GWAS identified candidate genes associated with semen traits in a Duroc boar population
title_full Weighted single-step GWAS identified candidate genes associated with semen traits in a Duroc boar population
title_fullStr Weighted single-step GWAS identified candidate genes associated with semen traits in a Duroc boar population
title_full_unstemmed Weighted single-step GWAS identified candidate genes associated with semen traits in a Duroc boar population
title_short Weighted single-step GWAS identified candidate genes associated with semen traits in a Duroc boar population
title_sort weighted single-step gwas identified candidate genes associated with semen traits in a duroc boar population
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6822442/
https://www.ncbi.nlm.nih.gov/pubmed/31666004
http://dx.doi.org/10.1186/s12864-019-6164-5
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