Omics & gene networks

Module eigengenes from weighted gene co-expression network analysis of blood of healthy pigs as potential genetic indicators of disease resilience

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Abstract

Weighted gene co-expression network analysis (WGCNA) summarizes correlated gene-expression patterns in transcriptome data into quantitative measures known as module eigengenes (MEs), which serve as multivariate summaries of gene-network activity and have the potential to reveal molecular mechanisms underlying genetic variation in complex traits. This study aimed to investigate the genetics of MEs derived from blood transcriptome of clinically young healthy pigs and their genetic (rÌ‚g) correlations with performance and disease resilience traits. mRNA abundance of 16,545 genes in blood was obtained from 2,322 young healthy Yorkshire à— Landrace barrows before their exposure to a polymicrobial disease challenge using 3′mRNA sequencing with globin-blocking. Gene expression data were adjusted for systematic environmental effects with (WI) or without (WO) accounting for white blood cell composition. Performance and disease resilience phenotypes were recorded on these and another 1,773 pigs from the same parental lines before, during, and after exposure to a polymicrobial disease challenge, including subjective health scores, clinical treatment rates, mortality, average daily gain, average daily feed intake and feeding duration, feed conversion rate, residual feed intake, and carcass traits. Pigs were genotyped for 650K or 50K SNPs and imputed to 650K SNPs. WGCNA detected 16 (WI) and 25 (WO) MEs, with heritabilities (ĥ²) ranging from 0.04 to 0.39. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to characterize the genes in these MEs, which revealed that MEs with significant enrichment for DNA-related processes tended to have higher ĥ². One ME from WI (186 genes, ĥ²=0.19±0.04) and one from WO (93 genes, 87/93 overlapped, ĥ²=0.10±0.04) showed significant enrichment for immune and inflammatory pathways, including innate and antiviral responses. Both MEs had low to moderate rÌ‚g with performance and disease resilience traits, ranging from -0.56 to 0.62, some of which were significant (pDDX58, IFIH1, ZNFX1, STAT1, MX1/MX2, RSAD2, and PARP14, indicating involvement of cytosolic viral RNA sensing, interferon signaling, and induction of interferon-stimulated antiviral effector genes. Although some rÌ‚g with disease resilience had high standard errors, our findings indicate that higher baseline expression of these genes in blood of young healthy pigs reflects constitutive immune activation rather than enhanced protective capacity, which is genetically associated with reduced growth and less favorable health outcomes under disease. Overall, the identified WGCNA modules represent moderately heritable transcriptomic networks with potential as genetic indicators for disease resilience. This work was funded by Genome Canada, Genome Alberta, Genome Prairie, and USDA-NIFA #2017-67007-26144 and #2021-67015-34562

Keywords: 2026

How to Cite:

Pham, H., Kayondo, F., Lim, K., Tuggle, C. & Dyck, M., (2026) “Module eigengenes from weighted gene co-expression network analysis of blood of healthy pigs as potential genetic indicators of disease resilience”, World Congress on Genetics Applied to Livestock Production Digital Archive 2026(1): 2286795. doi: https://doi.org/10.31274/wcgalp.24122

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