Integrative Systems Biology Analysis Elucidates Mastitis Disease Underlying Functional Modules in Dairy Cattle

Abstract

Background: Mastitis is the most prevalent disease in dairy cattle and one of the most significant bovine pathologies affecting milk production, animal health, and reproduction. In addition, mastitis is the most common, expensive, and contagious infection in the dairy industry.Methods: A meta-analysis of microarray and RNA-seq data was conducted to identify candidate genes and functional modules associated with mastitis disease. The results were then applied to systems biology analysis via weighted gene coexpression network analysis (WGCNA), Gene Ontology, enrichment analysis for the Kyoto Encyclopedia of Genes and Genomes (KEGG), and modeling using machine-learning algorithms.Results: Microarray and RNA-seq datasets were generated for 2,089 and 2,794 meta-genes, respectively. Between microarray and RNA-seq datasets, a total of 360 meta-genes were found that were significantly enriched as “peroxisome,” “NOD-like receptor signaling pathway,” “IL-17 signaling pathway,” and “TNF signaling pathway” KEGG pathways. The turquoise module (n = 214 genes) and the brown module (n = 57 genes) were identified as critical functional modules associated with mastitis through WGCNA. PRDX5, RAB5C, ACTN4, SLC25A16, MAPK6, CD53, NCKAP1L, ARHGEF2, COL9A1, and PTPRC genes were detected as hub genes in identified functional modules. Finally, using attribute weighting and machine-learning methods, hub genes that are sufficiently informative in Escherichia coli mastitis were used to optimize predictive models. The constructed model proposed the optimal approach for the meta-genes and validated several high-ranked genes as biomarkers for E. coli mastitis using the decision tree (DT) method.Conclusion: The candidate genes and pathways proposed in this study may shed new light on the underlying molecular mechanisms of mastitis disease and suggest new approaches for diagnosing and treating E. coli mastitis in dairy cattle.

Transcriptome Analysis of the Liver and Muscle Tissues of Dorper and Small-Tailed Han Sheep

“…These genes were significantly higher in both muscle and liver of DPs than in STH, suggesting that they are likely to be involved in body weight at slaughter in DP. Of the 12 co-expressed down-regulated genes, TFRC and MAPK6 are thought to be associated with immunity and mastitis, LARP1B and ODC1 are associated with reproductive traits, such as oestrogen and sperm quality ( Park et al, 2016 ; Nasser et al, 2020 ; Zhao et al, 2020 ; Ghahramani et al, 2021 ; Zhong et al, 2021 ). In addition, considering that the CDKN1A gene has a negative growth regulatory role as showed in the GO enrichment analysis, the down-regulated expression of these genes may be related to the highly reproductive request, slow growth and developmental characteristics of the STH breed.…”

Recent developments and future directions in meta-analysis of differential gene expression in livestock RNA-Seq

“…In this work, we will focus on the use of meta-analysis of RNA-Seq data across multiple studies with the same phenotypic groups in order to increase the statistical power to detect genes showing consistent differences between groups. To-date, four livestock studies have reported the use of RNA-Seq meta-analysis procedures for differential expression analysis, all of which are cattle studies ( Keel et al, 2018 ; Lindholm-Perry et al, 2020 ; Ghahramani et al, 2021 ; Lindholm-Perry et al, 2022 ). Traits of interest in these studies include those related to feed efficiency and lactation.…”

“…Transcriptomic studies related to bovine lactation have also taken advantage of meta-analysis approaches. Ghahramani et al (2021) combined meta-analysis data from both publicly available RNA-Seq and microarray to investigate DEG associated with E. coli mastitis in dairy cattle. Separate meta-analyses were conducted for RNA-Seq (2 datasets) and microarray (6 datasets).…”

Identifying Key Genes and Functionally Enriched Pathways of Diverse Adipose Tissue Types in Cattle

“…In recent years, it has also been utilized to evaluate complex bovine traits and correlate genes and phenotypes in several studies. For instance, ten genes ( PRDX5 , RAB5C , ACTN4 , SLC25A16 , MAPK6 , CD53 , NCKAP1L , ARHGEF2 , COL9A1 , and PTPRC ) were detected as hub genes from two critical functional modules associated with mastitis via WGCNA ( Ghahramani et al, 2021 ). Five signifcant functional modules and three hub genes ( GJA1 , AP2A2 , and NPAS3 ) related to the lactation process were identifed by WGCNA analysis, providing candidate genes to further explore the complex regulatory networks of the lactation process ( Farhadian et al, 2021 ).…”