Genetic mechanisms regulating the host response during mastitis

Abstract

Mastitis is a very costly and common disease in the dairy industry. The study of the transcriptome from healthy and mastitic milk somatic cell samples using RNA-Sequencing technology can provide measurements of transcript levels associated with the immune response to the infection. The objective of this study was to characterize the Holstein milk somatic cell transcriptome from 6 cows to determine host response to intramammary infections. RNA-Sequencing was performed on 2 samples from each cow from 2 separate quarters, one classified as healthy (n = 6) and one as mastitic (n = 6). In total, 449 genes were differentially expressed between the healthy and mastitic quarters (false discovery rate <0.05, fold change >±2). Among the differentially expressed genes, the most expressed genes based on reads per kilobase per million mapped reads (RPKM) in the healthy group were associated with milk components (CSN2 and CSN3), and in the mastitic group they were associated with immunity (B2M and CD74). In silico functional analysis was performed using the list of 449 differentially expressed genes, which identified 36 significantly enriched metabolic pathways (false discovery rate <0.01), some of which were associated with the immune system, such as cytokine-cytokine interaction and cell adhesion molecules. Seven functional candidate genes were selected, based on the criteria of being highly differentially expressed between healthy and mastitic groups and significantly enriched in metabolic pathways that are relevant to the inflammatory process (GLYCAM1, B2M, CD74, BoLA-DRA, FCER1G, SDS, and NFK-BIA). Last, we identified the differentially expressed genes that are located in quantitative trait locus regions previously known to be associated with mastitis, specifically clinical mastitis, somatic cell count, and somatic cell score. It was concluded that multiple genes within quantitative trait locus regions could potentially affect host response to mastitis-causing agents, making some cows more susceptible to intramammary infections. The identification of potential candidate genes with functional, statistical, biological, and positional relevance associated with host defense to infection will contribute to a better understanding of the underlying genetic architecture associated with mastitis. This in turn will improve the sustainability of agricultural practices by facilitating the selection of cows with improved host defense leading to increased resistance to mastitis.

Genome-wide association study to identify genomic regions and positional candidate genes associated with male fertility in beef cattle

“…The proportion of variance explained by non-overlapping windows were estimated using the PostGSf90 algorithm by summing the variance of SNPs within 1 Mb 82 . Windows that explained greater than 1% of the genetic variance for SC and SM were selected for QTL and gene annotation 83 , conducted using R (Version 4.0.0.; R Core Team, 2020) and the R package: Genomic Annotation in Livestock for positional candidate LOci (GALLO— https://github.com/pablobio/GALLO ). The .gtf annotation file corresponding to the bovine gene annotation from ARS-UCD1.2 assembly and the .gff file with the QTL information from Animal QTL Database 84 , using the same reference genome (ARS-UCD1.2) to map the QTLs, were used for gene and QTL annotation, respectively.…”

“…The proportion of variance explained by non-overlapping windows were estimated using the PostGSf90 algorithm by summing the variance of SNPs within 1 Mb 82 . Windows that explained greater than 1% of the genetic variance for SC and SM were selected for QTL and gene annotation 83 www.nature.com/scientificreports/ enrichment analysis was also conducted using the GALLO R package for all the QTL information annotated within the candidate windows using a chromosome-based enrichment analysis. Briefly, a bootstrap approach was used to compare the observed number of QTL for each trait in each chromosome annotated using GALLO with the expected number for each trait estimated using 1000 iteration rounds of random sampling from the whole Cattle QTLdb.…”

Comprehensive RNA-Seq Profiling Reveals Temporal and Tissue-Specific Changes in Gene Expression in Sprague–Dawley Rats as Response to Heat Stress Challenges

“…Differential gene expression analyses were performed using the CLC Genomics Workbench software 20.0 as described by Asselstine et al (2019) using a negative binomial generalized linear model (GLM). The GLM assumes that the expression levels follow a negative binomial distribution.…”

Staphylococcus aureus and Dairy Udder

“…Some of the variants are common throughout the globe as ruminant specific S. aureus while others are geographic related in the literature [23]. Inflammatory respondent metabolic pathways (BoLA-DRA, GLYCAM1, FCER1G, B2M, CD74, NFKBIA and SDS), milk constituent associated (CSN2 and CSN3) and immunity related (B2M and CD74) are also specific strains of S. aureus of dairy mastitis [24,25].…”