Pathogen load and expression of immune-related genes in mesenteric lymph-nodes of pigs experimentally infected with Salmonella typhimurium

Abstract

Lactation persistency (LP), defined as the rate of declining milk yield after milk peak, is an economically important trait for dairy cattle. Improving LP is considered a good alternative method for increasing overall milk production because it does not cause the negative energy balance and other health issues that cows experience during peak milk production. However, little is known about the biology of LP. A genome-wide association study (GWAS) and pathway enrichment were used to explore the genetic mechanisms underlying LP. The GWAS was performed using a univariate regression mixed linear model on LP data of 3,796 cows and 44,100 single nucleotide polymorphisms (SNP). Eight and 47 SNP were significantly and suggestively associated with LP, respectively. The 2 most important quantitative trait loci regions for LP were (1) a region from 106 to 108 Mb on Bos taurus autosome (BTA) 5, where the most significant SNP (ARS-BFGL-NGS-2399) was located and also formed a linkage disequilibrium block with 3 other SNP; and (2) a region from 29.3 to 31.3 Mb on BTA 20, which contained 3 significant SNP. Based on physical positions, MAN1C1, MAP3K5, HCN1, TSPAN9, MRPS30, TEX14, and CCL28 are potential candidate genes for LP because the significant SNP were located in their intronic regions. Enrichment analyses of a list of 536 genes in 0.5-Mb flanking regions of significant and suggestive SNP indicates that synthesis of milk components, regulation of cell apoptosis processes and insulin, and prolactin signaling pathways are important for LP. Upstream regulators relevant for LP positional candidate genes were prolactin (PRL), peroxisome proliferator-activated receptor gamma (PPARG), and Erb-B2 receptor tyrosine kinase 2 (ERBB2). Several networks related to cellular development, proliferation and death were significantly enriched for LP positional candidate genes. In conclusion, this study detected several SNP, genes, and interesting regions for fine mapping and validation of candidate genes and SNP for potential use in selection for improved LP. This study also provided further insights on the biology of LP which will help to prioritize selected candidate genes for functional validation and application.