ArticleScientific reports2020
Metabolomic networks and pathways associated with feed efficiency and related-traits in Duroc and Landrace pigs.
Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed.
- Regulatory networks involved in modulating fat deposition in pigs identified by gene co-expression analysis.BMC genomics · 2026Article
- Host genome regulation of the porcine gut microbiota and its impact on feed conversion efficiency.Animal microbiome · 2026Article
- Integrating Longitudinal Metabolite Profiles Improves Trait Prediction in Pigs in a Trait- and Timepoint-Dependent Manner.bioRxiv : the preprint server for biology · 2025Article
- Metabolomic-genomic prediction realizes small increases in accuracy of estimated breeding values for daily gain in pigs.Genetics, selection, evolution : GSE · 2025Article
- Some plasma biomarkers of residual feed intake in beef cattle remain consistent regardless of intake level.Scientific reports · 2024Article
- Article
- Ruminal and feces metabolites associated with feed efficiency, water intake and methane emission in Nelore bulls.Scientific reports · 2023Article
- Combined transcriptome and metabolome analysis reveal key regulatory genes and pathways of feed conversion efficiency of oriental river prawn Macrobrachium nipponense.BMC genomics · 2023Article
- Feeding an unsalable carrot total-mixed ration altered bacterial amino acid degradation in the rumen of lambs.Scientific reports · 2023Article
- Integrative metabolomic and transcriptomic analysis reveals difference in glucose and lipid metabolism in the longissimus muscle of Luchuan and Duroc pigs.Frontiers in genetics · 2023Article
- GWAS and genetic and phenotypic correlations of plasma metabolites with complete blood count traits in healthy young pigs reveal implications for pig immune response.Frontiers in molecular biosciences · 2023Article
- Identification of biomarkers associated with the feed efficiency by metabolomics profiling: results from the broiler lines divergent for high or low abdominal fat content.Journal of animal science and biotechnology · 2022Article
- Co-Expression Network and Integrative Analysis of Metabolome and Transcriptome Uncovers Biological Pathways for Fertility in Beef Heifers.Metabolites · 2022Article
- Effect of chronic and acute enterotoxigenic E. coli challenge on growth performance, intestinal inflammation, microbiome, and metabolome of weaned piglets.Scientific reports · 2022Article
- Application of Genetic, Genomic and Biological Pathways in Improvement of Swine Feed Efficiency.Frontiers in genetics · 2022Review
- Heritability and genetic correlations of plasma metabolites of pigs with production, resilience and carcass traits under natural polymicrobial disease challenge.Scientific reports · 2021Article
- Using nontargeted LC-MS metabolomics to identify the Association of Biomarkers in pig feces with feed efficiency.Porcine health management · 2021Article
- Article
- Sexual Dimorphism of Metabolite Profiles in Pigs Depends on the Genetic Background.Metabolites · 2021Article
- Lipids and organic acids in three gut locations affect feed efficiency of commercial pigs as revealed by LC-MS-based metabolomics.Scientific reports · 2021Article
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Authors and funding
4 authors.
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Abstract
Improving feed efficiency (FE) is a major goal of pig breeding, reducing production costs and providing sustainability to the pig industry. Reliable predictors for FE could assist pig producers. We carried out untargeted blood metabolite profiling in uncastrated males from Danbred Duroc (n = 59) and Danbred Landrace (n = 50) pigs at the beginning and end of a FE testing phase to identify biomarkers and biological processes underlying FE and related traits. By applying linear modeling and clustering analyses coupled with WGCNA framework, we identified 102 and 73 relevant metabolites in Duroc and Landrace based on two sampling time points. Among them, choline and pyridoxamine were hub metabolites in Duroc in early testing phase, while, acetoacetate, cholesterol sulfate, xanthine, and deoxyuridine were identified in the end of testing. In Landrace, cholesterol sulfate, thiamine, L-methionine, chenodeoxycholate were identified at early testing phase, while, D-glutamate, pyridoxamine, deoxycytidine, and L-2-aminoadipate were found at the end of testing. Validation of these results in larger populations could establish FE prediction using metabolomics biomarkers. We conclude that it is possible to identify a link between blood metabolite profiles and FE. These results could lead to improved nutrient utilization, reduced production costs, and increased FE.
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