Identification of Candidate Genes and eQTLs Related to Porcine Reproductive Function.

Animals (Basel)

National Engineering Laboratory for Animal Breeding, Department of Animal Genetics and Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China.

Published: April 2025


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Article Abstract

Expression quantitative trait locus (eQTL) mapping is an effective tool for identifying genetic variations that regulate gene expression. An increasing number of studies suggested that SNPs associated with complex traits in farm animals are considered as expression quantitative trait loci. Identifying eQTLs associated with gene expression levels in the endometrium helps to unravel the regulatory mechanisms of genes related to reproductive functions in this tissue and provides molecular markers for the genetic improvement of high-fertility sow breeding. In this study, 218 RNA-seq data from pig endometrial tissue were used for eQTL analysis to identify genetic variants regulating gene expression. Additionally, weighted gene co-expression network analysis (WGCNA) was performed to identify hub genes involved in reproductive functions. The eQTL analysis identified 34,876 significant cis-eQTLs regulating the expression of 5632 genes (FDR ≤ 0.05), and 90 hub genes were identified by WGCNA analysis. By integrating eQTL and WGCNA results, 14 candidate genes and 16 fine-mapped cis-eQTLs were identified, including , , , , , , , , , , , , , and , which were involved in the physiological processes of reproduction in sows through hormone regulation, cell adhesion, and amino acid and lipid metabolism. These eQTLs regulate the high expression of candidate genes in the endometrium, thereby affecting reproductive-related physiological functions. These findings enhance our understanding of the genetic basis of reproductive traits and provide valuable genetic markers for marker-assisted selection (MAS), which can be applied to improve sow fecundity and optimize breeding strategies for high reproductive performance.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11987867PMC
http://dx.doi.org/10.3390/ani15071038DOI Listing

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