Web of Science: 17 cites, Scopus: 17 cites, Google Scholar: cites,
Integrating genome-wide co-association and gene expression to identify putative regulators and predictors of feed efficiency in pigs
Ramayo-Caldas, Yuliaxis (Institut de Recerca i Tecnologia Agroalimentàries)
Mármol-Sánchez, Emilio (Centre de Recerca en Agrigenòmica)
Ballester Devis, Maria (Institut de Recerca i Tecnologia Agroalimentàries)
Sánchez Serrano, Juan Pablo (Institut de Recerca i Tecnologia Agroalimentàries)
González Prendes, Rayner (Centre de Recerca en Agrigenòmica)
Amills i Eras, Marcel (Centre de Recerca en Agrigenòmica)
Quintanilla, Raquel (Institut de Recerca i Tecnologia Agroalimentàries)

Data: 2019
Resum: Background: Feed efficiency (FE) has a major impact on the economic sustainability of pig production. We used a systems-based approach that integrates single nucleotide polymorphism (SNP) co-association and gene-expression data to identify candidate genes, biological pathways, and potential predictors of FE in a Duroc pig population. Results: We applied an association weight matrix (AWM) approach to analyse the results from genome-wide association studies (GWAS) for nine FE associated and production traits using 31K SNPs by defining residual feed intake (RFI) as the target phenotype. The resulting co-association network was formed by 829 SNPs. Additive effects of this SNP panel explained 61% of the phenotypic variance of RFI, and the resulting phenotype prediction accuracy estimated by cross-validation was 0. 65 (vs. 0. 20 using pedigree-based best linear unbiased prediction and 0. 12 using the 31K SNPs). Sixty-eight transcription factor (TF) genes were identified in the co-association network; based on the lossless approach, the putative main regulators were COPS5, GTF2H5, RUNX1, HDAC4, ESR1, USP16, SMARCA2 and GTF2F2. Furthermore, gene expression data of the gluteus medius muscle was explored through differential expression and multivariate analyses. A list of candidate genes showing functional and/or structural associations with FE was elaborated based on results from both AWM and gene expression analyses, and included the aforementioned TF genes and other ones that have key roles in metabolism, e. g. ESRRG, RXRG, PPARGC1A, TCF7L2, LHX4, MAML2, NFATC3, NFKBIZ, TCEA1, CDCA7L, LZTFL1 or CBFB. The most enriched biological pathways in this list were associated with behaviour, immunity, nervous system, and neurotransmitters, including melatonin, glutamate receptor, and gustation pathways. Finally, an expression GWAS allowed identifying 269 SNPs associated with the candidate genes' expression (eSNPs). Addition of these eSNPs to the AWM panel of 829 SNPs did not improve the accuracy of genomic predictions. Conclusions: Candidate genes that have a direct or indirect effect on FE-related traits belong to various biological processes that are mainly related to immunity, behaviour, energy metabolism, and the nervous system. The pituitary gland, hypothalamus and thyroid axis, and estrogen signalling play fundamental roles in the regulation of FE in pigs. The 829 selected SNPs explained 61% of the phenotypic variance of RFI, which constitutes a promising perspective for applying genetic selection on FE relying on molecular-based prediction.
Ajuts: Ministerio de Economía y Competitividad AGL2013-48742-C2-2-R
Ministerio de Economía y Competitividad AGL2013-48742-C2-1-R
Ministerio de Economía y Competitividad AGL2010-22208-C02-01
Ministerio de Economía y Competitividad AGL2010-22208-C02-02
European Commission 6655919
Ministerio de Educación y Ciencia FPU15/01733
Ministerio de Economía y Competitividad RYC-2013-12573
Agència de Gestió d'Ajuts Universitaris i de Recerca 2017/SGR-1719
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. Creative Commons
Llengua: Anglès
Document: Article ; recerca ; Versió publicada
Publicat a: Genetics, selection, evolution, Vol. 51 (September 2019) , art. 48, ISSN 1297-9686

DOI: 10.1186/s12711-019-0490-6
PMID: 31477014

17 p, 1.8 MB

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