A systems biology framework integrating GWAS and RNA-seq to shed light on the molecular basis of sperm quality in swine
Gòdia, Marta (Centre de Recerca en Agrigenòmica)
Reverter, Antonio (Queensland Bioscience Precinct. CSIRO Agriculture and Food (Australia))
González Prendes, Rayner (Wageningen University & Research. Animal Breeding and Genomics (The Netherlands))
Ramayo-Caldas, Yuliaxis (Institut de Recerca i Tecnologia Agroalimentàries. Departament de Genètica i Millora Animal)
Castelló Farré, Anna (Centre de Recerca en Agrigenòmica)
Rodríguez Gil, Joan Enric (Universitat Autònoma de Barcelona. Departament de Medicina i Cirurgia Animals)
Sánchez Bonastre, Armando (Universitat Autònoma de Barcelona. Departament de Ciència Animal i dels Aliments)
Clop, Alex (Centre de Recerca en Agrigenòmica)

Data:	2020
Resum:	Background: Genetic pressure in animal breeding is sparking the interest of breeders for selecting elite boars with higher sperm quality to optimize ejaculate doses and fertility rates. However, the molecular basis of sperm quality is not yet fully understood. Our aim was to identify candidate genes, pathways and DNA variants associated to sperm quality in swine by analysing 25 sperm-related phenotypes and integrating genome-wide association studies (GWAS) and RNA-seq under a systems biology framework. Results: By GWAS, we identified 12 quantitative trait loci (QTL) associated to the percentage of head and neck abnormalities, abnormal acrosomes and motile spermatozoa. Candidate genes included CHD2, KATNAL2, SLC14A2 and ABCA1. By RNA-seq, we identified a wide repertoire of mRNAs (e. g. PRM1, OAZ3, DNAJB8, TPPP2 and TNP1) and miRNAs (e. g. ssc-miR-30d, ssc-miR-34c, ssc-miR-30c-5p, ssc-miR-191, members of the let-7 family and ssc-miR-425-5p) with functions related to sperm biology. We detected 6128 significant correlations (P-value ≤ 0. 05) between sperm traits and mRNA abundances. By expression (e)GWAS, we identified three trans-expression QTL involving the genes IQCJ, ACTR2 and HARS. Using the GWAS and RNA-seq data, we built a gene interaction network. We considered that the genes and interactions that were present in both the GWAS and RNA-seq networks had a higher probability of being actually involved in sperm quality and used them to build a robust gene interaction network. In addition, in the final network we included genes with RNA abundances correlated with more than four semen traits and miRNAs interacting with the genes on the network. The final network was enriched for genes involved in gamete generation and development, meiotic cell cycle, DNA repair or embryo implantation. Finally, we designed a panel of 73 SNPs based on the GWAS, eGWAS and final network data, that explains between 5% (for sperm cell concentration) and 36% (for percentage of neck abnormalities) of the phenotypic variance of the sperm traits. Conclusions: By applying a systems biology approach, we identified genes that potentially affect sperm quality and constructed a SNP panel that explains a substantial part of the phenotypic variance for semen quality in our study and that should be tested in other swine populations to evaluate its relevance for the pig breeding sector.
Ajuts:	Ministerio de Economía y Competitividad AGL2013-44978-R Ministerio de Economía y Competitividad AGL2017-86946-R Agència de Gestió d'Ajuts Universitaris i de Recerca 2014/SGR-1528 Agència de Gestió d'Ajuts Universitaris i de Recerca 2017/SGR-1060 Ministerio de Economía y Competitividad SEV-2015-0533 Ministerio de Economía y Competitividad BES-2014-070560 Ministerio de Economía y Competitividad EEBB-I-18-12860
Nota:	Altres ajuts: CERCA Programme/Generalitat de Catalunya
Drets:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original.
Llengua:	Anglès
Document:	Article ; recerca ; Versió publicada
Publicat a:	Genetics, selection, evolution, Vol. 52 (December 2020) , art. 72, ISSN 1297-9686

DOI: 10.1186/s12711-020-00592-0
PMID: 33292187

21 p, 2.5 MB

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