A Systematic Review And Meta-Analysis Of Gwas And Gene Expression Results Of Holstein Cattle Under Negative Energy Balance And Ketosis

Abstract Development of ketosis in high-producing dairy cows contributes to animal health issues and highlights the need for better understanding the genetic basis of metabolic diseases. Thus, the aim of this study was to evaluate the pattern of differential gene expression in liver of cows under negative energy balance (NEB), subclinical, and clinical ketosis through a systematic review and meta-analysis of published gene expression and genome-wide association studies (GWAS) results. After screening of the 118 articles found in the systematic review, 20 articles were included in the analysis. For this, 430 significant SNPs identified by GWAS were investigated to see if they were located within genes reported in gene expression studies. A permutation approach was used to identify the biological pathways associated with the metabolic conditions studied. A gene network was created using the differentially expressed genes harboring significant SNPs and a QTL enrichment analysis was performed to identify potential positional candidate loci. This study revealed 14 genes that are differentially expressed in the liver of cows in different metabolic conditions, which harbor 24 significant polymorphisms in reported GWAS. Three significant metabolic pathways were associated with NEB, subclinical and clinical ketosis. In addition, two important genes, PPARA and ACACA, were identified as differentially expressed in the three metabolic conditions. Gene network analysis revealed co-expression interactions among 34 genes associated with functions involving fatty acid transport and metabolism. The genes FN1 and PTK2 were enriched for QTL previously associated with the trait “ketosis” on chromosome 2 and with the trait “milk iron content” on chromosome 14, respectively. These findings improve the understanding of negative energy balance and ketosis in dairy cows, which could enhance selection for cows less susceptible to ketosis and help with the development of potential biomarkers for early diagnosis and prevention of ketosis.