Meta-analysis of genome-wide association studies for somatic cells score trait in dairy cows

Mastitis is an inflammatory disease in dairy cows that occurs in response to infectious factors. This inflammatory disease have a high negative economic impact on dairy industry. In recent decades, somatic cell score has been used as an indirect method to control mastitis. Resistance to infection disease may be defined as the ability of an animal to have an immune response to prevent the spread of pathogens after infection. Previous studies showed that animals differ in their genetic ability for immune competence. Genetic resistance to mastitis involves interconnected biological mechanisms that result from differences in the response to mastitis that activate and regulate different levels of the immune response. A better understanding of the immune system and the metabolic pathways involved in responding to various pathogens may be used as a complementary approach to control of the disease. Several studies have been evaluated genetic mechanisms affecting somatic cells score in dairy cows. Many candidate genes affecting somatic cells score has been introduced. But the complex relationships between genes and pathways that affect them have not been fully identified yet. The main purpose of this study is to integrate the results of recent genome-wide association studies on somatic cells score using meta-analysis to obtain a set of important genes and pathways.

In this study, a search for the genome-wide association studies dataset in Google Scholar was performed using the keywords Dairy cows, Genome wide association studies, and Somatic cells score. Gene sets were available in different populations of dairy cow breeds (Holstein and Friesian breeds and red cows) in 11 independent studies from 2011 to 2019. 218 candidate genes for somatic cells score were found from genome-wide association studies. The number of common genes in dairy cows was examined using Venn diagram. Then, all available genes were combined and evaluated using meta-analysis. The ClueGO v2.5.4 plugin were used to conduct gene ontology analysis and KEGG pathways. The CluePedia v1.5.4 plugin in Cytoscape v3.7.2 were used to visualize genes and protein-protein interactions.

The results showed that U6, DCK, and NPFFR2 genes as the key candidate genes have an important role in combating infection and pathogens in the development of mastitis. Some biological processes, cellular components, molecular functions, and related pathways were identified. The most important biological process, cellular components and molecular function pathways were mesenchymal cell development (P=3.92e-04), apical plasma membrane (P=2.83e-03), and solute: cation symporter activity (P=3.71e-04), respectively.

Generally, the results of this study showed that meta-analysis based on a large number of original data revealed the most important candidate genes involved in the fight against mastitis pathways, this information provides a solid foundation for the development of new treatments for mastitis. Therefore, identification of important genes and gene ontology term enrichment (with high power and accuracy) can play an effective role in genomic evaluation and design of breeding programs aimed at controlling mastitis in dairy cows.