ArticleScientific reports2022
Analysis of merged transcriptomic and genomic datasets to identify genes and pathways underlying residual feed intake in growing pigs.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed, 27 citations in OpenAlex.
- Bayesian Genome-Wide Association Study of Feed Efficiency Traits in Pigs.Animals : an open access journal from MDPI · 2026Article
- Unraveling quantitative trait loci (QTL) overlapping epigenomic regulatory regions associated with feeding behavior in pigs.Frontiers in genetics · 2026Article
- Whole genome and transcriptome analyses identify genetic markers associated with growth traits in Qinchuan black pig.BMC genomics · 2025Article
- Article
- Expression genome-wide association study identifies key regulatory variants enriched with metabolic and immune functions in four porcine tissues.BMC genomics · 2024Article
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Authors and funding
6 authors at 2 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
Improvement of feed efficiency (FE) in pigs is an important milestone in order to reduce the economic and environmental impact of pig production. The goal of finding biomarkers for FE has persisted for decades. However, due to the complexity of the FE trait, these goals have still not been met. Here, we search for quantitative trait loci (QTL), candidate genes, and biological pathways associated with FE using both genotype and RNA-seq data. We obtained genotype and colon epithelium RNA-seq data for 375 and 96 pigs, respectively. In total, a genome-wide association study (GWAS) and differential expression (DE) analysis led to detection of three QTL on SSC9 and 17 DE-genes associated with FE. Possible intersection points between genes located in QTL and DE-genes were found on levels of transcription factor-target interaction. Moreover, cis-eQTL analysis revealed associations between genotype and expression levels of three DE-genes and three genes located in the GWAS QTLs, which may establish the connection between genotype and phenotype through DE. Finally, single nucleotide polymorphism calling using RNA-seq data for genes located in GWAS QTLs revealed 53 polymorphisms of which eleven were missense variants.
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