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Weighted single-step GWAS and gene network analysis reveal new candidate genes for semen traits in pigs

BACKGROUND: In recent years, there has been increased interest in the study of the molecular processes that affect semen traits. In this study, our aim was to identify quantitative trait loci (QTL) regions associated with four semen traits (motility, progressive motility, number of sperm cells per e...

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Autores principales: Marques, Daniele B. D., Bastiaansen, John W. M., Broekhuijse, Marleen L. W. J., Lopes, Marcos S., Knol, Egbert F., Harlizius, Barbara, Guimarães, Simone E. F., Silva, Fabyano F., Lopes, Paulo S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6080523/
https://www.ncbi.nlm.nih.gov/pubmed/30081822
http://dx.doi.org/10.1186/s12711-018-0412-z
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author Marques, Daniele B. D.
Bastiaansen, John W. M.
Broekhuijse, Marleen L. W. J.
Lopes, Marcos S.
Knol, Egbert F.
Harlizius, Barbara
Guimarães, Simone E. F.
Silva, Fabyano F.
Lopes, Paulo S.
author_facet Marques, Daniele B. D.
Bastiaansen, John W. M.
Broekhuijse, Marleen L. W. J.
Lopes, Marcos S.
Knol, Egbert F.
Harlizius, Barbara
Guimarães, Simone E. F.
Silva, Fabyano F.
Lopes, Paulo S.
author_sort Marques, Daniele B. D.
collection PubMed
description BACKGROUND: In recent years, there has been increased interest in the study of the molecular processes that affect semen traits. In this study, our aim was to identify quantitative trait loci (QTL) regions associated with four semen traits (motility, progressive motility, number of sperm cells per ejaculate and total morphological defects) in two commercial pig lines (L1: Large White type and L2: Landrace type). Since the number of animals with both phenotypes and genotypes was relatively small in our dataset, we conducted a weighted single-step genome-wide association study, which also allows unequal variances for single nucleotide polymorphisms. In addition, our aim was also to identify candidate genes within QTL regions that explained the highest proportions of genetic variance. Subsequently, we performed gene network analyses to investigate the biological processes shared by genes that were identified for the same semen traits across lines. RESULTS: We identified QTL regions that explained up to 10.8% of the genetic variance of the semen traits on 12 chromosomes in L1 and 11 chromosomes in L2. Sixteen QTL regions in L1 and six QTL regions in L2 were associated with two or more traits within the population. Candidate genes SCN8A, PTGS2, PLA2G4A, DNAI2, IQCG and LOC102167830 were identified in L1 and NME5, AZIN2, SPATA7, METTL3 and HPGDS in L2. No regions overlapped between these two lines. However, the gene network analysis for progressive motility revealed two genes in L1 (PLA2G4A and PTGS2) and one gene in L2 (HPGDS) that were involved in two biological processes i.e. eicosanoid biosynthesis and arachidonic acid metabolism. PTGS2 and HPGDS were also involved in the cyclooxygenase pathway. CONCLUSIONS: We identified several QTL regions associated with semen traits in two pig lines, which confirms the assumption of a complex genetic determinism for these traits. A large part of the genetic variance of the semen traits under study was explained by different genes in the two evaluated lines. Nevertheless, the gene network analysis revealed candidate genes that are involved in shared biological pathways that occur in mammalian testes, in both lines. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12711-018-0412-z) contains supplementary material, which is available to authorized users.
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spelling pubmed-60805232018-08-09 Weighted single-step GWAS and gene network analysis reveal new candidate genes for semen traits in pigs Marques, Daniele B. D. Bastiaansen, John W. M. Broekhuijse, Marleen L. W. J. Lopes, Marcos S. Knol, Egbert F. Harlizius, Barbara Guimarães, Simone E. F. Silva, Fabyano F. Lopes, Paulo S. Genet Sel Evol Research Article BACKGROUND: In recent years, there has been increased interest in the study of the molecular processes that affect semen traits. In this study, our aim was to identify quantitative trait loci (QTL) regions associated with four semen traits (motility, progressive motility, number of sperm cells per ejaculate and total morphological defects) in two commercial pig lines (L1: Large White type and L2: Landrace type). Since the number of animals with both phenotypes and genotypes was relatively small in our dataset, we conducted a weighted single-step genome-wide association study, which also allows unequal variances for single nucleotide polymorphisms. In addition, our aim was also to identify candidate genes within QTL regions that explained the highest proportions of genetic variance. Subsequently, we performed gene network analyses to investigate the biological processes shared by genes that were identified for the same semen traits across lines. RESULTS: We identified QTL regions that explained up to 10.8% of the genetic variance of the semen traits on 12 chromosomes in L1 and 11 chromosomes in L2. Sixteen QTL regions in L1 and six QTL regions in L2 were associated with two or more traits within the population. Candidate genes SCN8A, PTGS2, PLA2G4A, DNAI2, IQCG and LOC102167830 were identified in L1 and NME5, AZIN2, SPATA7, METTL3 and HPGDS in L2. No regions overlapped between these two lines. However, the gene network analysis for progressive motility revealed two genes in L1 (PLA2G4A and PTGS2) and one gene in L2 (HPGDS) that were involved in two biological processes i.e. eicosanoid biosynthesis and arachidonic acid metabolism. PTGS2 and HPGDS were also involved in the cyclooxygenase pathway. CONCLUSIONS: We identified several QTL regions associated with semen traits in two pig lines, which confirms the assumption of a complex genetic determinism for these traits. A large part of the genetic variance of the semen traits under study was explained by different genes in the two evaluated lines. Nevertheless, the gene network analysis revealed candidate genes that are involved in shared biological pathways that occur in mammalian testes, in both lines. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12711-018-0412-z) contains supplementary material, which is available to authorized users. BioMed Central 2018-08-06 /pmc/articles/PMC6080523/ /pubmed/30081822 http://dx.doi.org/10.1186/s12711-018-0412-z Text en © The Author(s) 2018 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
Marques, Daniele B. D.
Bastiaansen, John W. M.
Broekhuijse, Marleen L. W. J.
Lopes, Marcos S.
Knol, Egbert F.
Harlizius, Barbara
Guimarães, Simone E. F.
Silva, Fabyano F.
Lopes, Paulo S.
Weighted single-step GWAS and gene network analysis reveal new candidate genes for semen traits in pigs
title Weighted single-step GWAS and gene network analysis reveal new candidate genes for semen traits in pigs
title_full Weighted single-step GWAS and gene network analysis reveal new candidate genes for semen traits in pigs
title_fullStr Weighted single-step GWAS and gene network analysis reveal new candidate genes for semen traits in pigs
title_full_unstemmed Weighted single-step GWAS and gene network analysis reveal new candidate genes for semen traits in pigs
title_short Weighted single-step GWAS and gene network analysis reveal new candidate genes for semen traits in pigs
title_sort weighted single-step gwas and gene network analysis reveal new candidate genes for semen traits in pigs
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6080523/
https://www.ncbi.nlm.nih.gov/pubmed/30081822
http://dx.doi.org/10.1186/s12711-018-0412-z
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