Multi-Omics Integration and Network Analysis Reveal Potential Hub Genes and Genetic Mechanisms Regulating Bovine Mastitis

Abstract

Mastitis, inflammation of the mammary gland, is the most prevalent disease in dairy cattle that has a potential impact on profitability and animal welfare. Specifically designed multi-omics studies can be used to prioritize candidate genes and identify biomarkers and the molecular mechanisms underlying mastitis in dairy cattle. Hence, the present study aimed to explore the genetic basis of bovine mastitis by integrating microarray and RNA-Seq data containing healthy and mastitic samples in comparative transcriptome analysis with the results of published genome-wide association studies (GWAS) using a literature mining approach. The integration of different information sources resulted in the identification of 33 common and relevant genes associated with bovine mastitis. Among these, seven genes—CXCR1, HCK, IL1RN, MMP9, S100A9, GRO1, and SOCS3—were identified as the hub genes (highly connected genes) for mastitis susceptibility and resistance, and were subjected to protein-protein interaction (PPI) network and gene regulatory network construction. Gene ontology annotation and enrichment analysis revealed 23, 7, and 4 GO terms related to mastitis in the biological process, molecular function, and cellular component categories, respectively. Moreover, the main metabolic-signalling pathways responsible for the regulation of immune or inflammatory responses were significantly enriched in cytokine–cytokine-receptor interaction, the IL-17 signaling pathway, viral protein interaction with cytokines and cytokine receptors, and the chemokine signaling pathway. Consequently, the identification of these genes, pathways, and their respective functions could contribute to a better understanding of the genetics and mechanisms regulating mastitis and can be considered a starting point for future studies on bovine mastitis.

Multi-omics integration identifies regulatory factors underlying bovine subclinical mastitis

“…We provide deeper insights into the multi-level signatures simultaneously involved in the regulation of mammary gland response to subclinical mastitis. Our data is consistent with previous studies about bovine mastitis that focused on the integration of two omics data sets [ 26 – 28 , 30 – 32 , 50 ] and at the same time provided deeper insights into the molecular signatures of subclinical mastitis.…”

Veterinary systems biology for bridging the phenotype–genotype gap via computational modeling for disease epidemiology and animal welfare

“…An effective method for linking a particular genetic background to a disease or a trait is to conduct genome-wide association studies (GWAS). Nevertheless, single-omics data offer limited insights into biological mechanisms, and to enhance the precision of predicting the link between genotype and phenotype, it is essential to incorporate multi-omics data [ 23 , 78 , 79 ]. Several studies have demonstrated the utility of systems biology in integrating multi-omics data.…”

Genetic architecture of inter-specific and -generic grass hybrids by network analysis on multi-omics data

“…Reliable inferences in high dimensions require specific statistical procedures and an in-depth understanding of the underlining phenomena. Among the methods proposed for the analysis of high dimensional omics data [ 10 ], the reconstruction and analysis of regulatory networks offer the possibility to prioritize omic features [ 11 ], significantly reducing the searching space for downstream analyses. Organizing omic features in interacting networks can be seen as an approximation of the true existent interconnected biological system that reads the information encoded on the genome and ends with a functional organism.…”