ArticleBMC genomics2026
Gene co-expression networks related to intramuscular fatty acid composition across different pig genotypes.
Article in BMC genomics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundThe nutritional quality of pork, a vital source of protein in the human diet, is being increasingly studied due to health concerns regarding pork fatty acid (FA) composition. Therefore, the primary objective of this study was to identify the relationship between muscle gene expression and the composition of different FAs in pigs, focusing on the two prevalent genotypes (AA and AB) from hotspot expression quantitative trait loci (eQTL) regions within the study population. This was achieved through the application of weighted gene co-expression network analyses (WGCNA) based on RNA-Seq data from 72 pigs to construct gene co-expression clusters and correlate them with the FA profile of skeletal muscle in pigs. The WGCNA was constructed using RNA-Seq data normalized to transcripts per million (TPM) across three hotspot eQTL regions: SSC3 (102,983,783 bp), SSC2 (67,926,641 bp), and SSC6 (93,742,864 bp).
resultsFor the hotspot located in SSC3, the AA genotype exhibited five significant co-expressed gene modules, while the BB genotype had only one. At the hotspot on SSC2, the AA genotype had four significant gene modules compared to five in the AB genotype. Notably, at the hotspot located in SSC6, 15 significant gene modules were identified for the AA genotype, whereas none were observed for the AB genotype. The co-expression networks revealed differences in gene connectivity, functional enrichment of identified modules, and hub genes, highlighting significant variations between the genotypes.
conclusionsThe observed differences in co-expression related to FA composition in the AA and AB genotypes suggest that the genotypes influence gene co-expression. Furthermore, we identified genes co-expressed with metabolic processes indicative of diseases such as diabetes, alongside genes related to immunity and inflammatory response, including MAPK8, TFG, CCL17, TBX21, ELP2, and GYS1. These results enhance our understanding of the mechanisms in which genetic variations located in specific genomic regions impact the co-expression of genes related to metabolic regulation, thereby influencing relevant traits in pig breeding programs.
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