ArticleGenetics, selection, evolution : GSE2019
Integrating genome-wide co-association and gene expression to identify putative regulators and predictors of feed efficiency in pigs.
Article in Genetics, selection, evolution : GSE, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed, 78 citations in OpenAlex.
- Single-variant genome-wide association study and regional heritability mapping of protein efficiency and performance traits in Large White pigs.Genetics, selection, evolution : GSE · 2025Article
- Bivariate GWAS performed on rabbits divergently selected for intramuscular fat content reveals pleiotropic genomic regions and genes related to meat and carcass quality traits.Genetics, selection, evolution : GSE · 2025Article
- Expression quantitative trait loci associated with performance traits, blood biochemical parameters, and cytokine profile in pigs.Frontiers in genetics · 2025Article
- Mapping and functional characterization of structural variation in 1060 pig genomes.Genome biology · 2024Article
- Identification of candidate regulatory genes for intramuscular fatty acid composition in pigs by transcriptome analysis.Genetics, selection, evolution : GSE · 2024Article
- Identification of eQTLs using different sets of single nucleotide polymorphisms associated with carcass and body composition traits in pigs.BMC genomics · 2024Article
- Genome-Wide Association Analysis and Genetic Parameters for Feed Efficiency and Related Traits in Yorkshire and Duroc Pigs.Animals : an open access journal from MDPI · 2022Article
- Transcriptome Profile Reveals Genetic and Metabolic Mechanisms Related to Essential Fatty Acid Content of IntramuscularMetabolites · 2022Article
- Transcriptome analysis reveals the potential roles of long non-coding RNAs in feed efficiency of chicken.Scientific reports · 2022Article
- Multi-Omics Integration and Network Analysis Reveal Potential Hub Genes and Genetic Mechanisms Regulating Bovine Mastitis.Current issues in molecular biology · 2022Article
- General Transcription Factor IIF Polypeptide 2: A Novel Therapeutic Target for Depression Identified Using an Integrated Bioinformatic Analysis.Frontiers in aging neuroscience · 2022Article
- Hematology parameters as potential indicators of feed efficiency in pigs.Translational animal science · 2021Article
- Variability in porcine microRNA genes and its association with mRNA expression and lipid phenotypes.Genetics, selection, evolution : GSE · 2021Article
- Transcriptome Analysis Identifies Candidate Genes and Signaling Pathways Associated With Feed Efficiency in Xiayan Chicken.Frontiers in genetics · 2021Article
- A Co-Association Network Analysis Reveals Putative Regulators for Health-Related Traits in Pigs.Frontiers in immunology · 2021Article
- A systems biology framework integrating GWAS and RNA-seq to shed light on the molecular basis of sperm quality in swine.Genetics, selection, evolution : GSE · 2020Article
- Gene networks for three feed efficiency criteria reveal shared and specific biological processes.Genetics, selection, evolution : GSE · 2020Article
- Exploring the Regulatory Potential of Long Non-Coding RNA in Feed Efficiency of Indicine Cattle.Genes · 2020Article
- Gene Networks Driving Genetic Variation in Milk and Cheese-Making Traits of Spanish Assaf Sheep.Genes · 2020Article
- Estimation of Genetic Parameters for Pork Quality, Novel Carcass, Primal-Cut and Growth Traits in Duroc Pigs.Animals : an open access journal from MDPI · 2020Article
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Authors and funding
7 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundFeed 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.
resultsWe 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.
conclusionsCandidate 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.
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