Expression-based analysis of genes related to single nucleotide polymorphism hits associated with bovine leukemia virus proviral load in Argentinean dairy cattle

Abstract

In dairy cattle infected with bovine leukemia virus (BLV), the proviral load (PVL) level is directly related to the viral transmission from infected animals to their healthy herdmates. Two contrasting phenotypic groups can be identified when assessing PVL in peripheral blood of infected cows. A large number of reports point to bovine genetic variants (single nucleotide polymorphisms) as one of the key determinants underlying PVL level. However, biological mechanisms driving BLV PVL profiles and infection progression in cattle have not yet been elucidated. In this study, we evaluated whether a set of candidate genes affecting BLV PVL level according to whole genome association studies are differentially expressed in peripheral blood mononuclear cells derived from phenotypically contrasting groups of BLV-infected cows. During a 10-mo-long sampling scheme, 129 Holstein cows were phenotyped measuring anti-BLV antibody levels, PVL quantification, and white blood cell subpopulation counts. Finally, the expression of 8 genes (BOLA-DRB3, PRRC2A, ABT1, TNF, BAG6, BOLA-A, LY6G5B, and IER3) located within the bovine major histocompatibility complex region harboring whole genome association SNP hits was evaluated in 2 phenotypic groups: high PVL (n = 7) and low PVL (n = 8). The log2 initial fluorescence value (N0) transformed mean expression values for the ABT1 transcription factor were statistically different in high- and low-PVL groups, showing a higher expression of the ABT1 gene in low-PVL cows. The PRRC2A and IER3 genes had a significant positive (correlation coefficient = 0.61) and negative (correlation coefficient = −0.45) correlation with the lymphocyte counts, respectively. Additionally, the relationships between gene expression values and lymphocyte counts were modeled using linear regressions. Lymphocyte levels in infected cows were better explained (coefficient of determination = 0.56) when fitted a multiple linear regression model using both PRRC2A and IER3 expression values as independent variables. The present study showed evidence of differential gene expression between contrasting BLV infection phenotypes. These genes have not been previously related to BLV pathobiology. This valuable information represents a step forward in understanding the BLV biology and the immune response of naturally infected cows under a commercial milk production system. Efforts to elucidate biological mechanisms leading to BLV infection progression in cows are valuable for BLV control programs. Further studies integrating genotypic data, global transcriptome analysis, and BLV progression phenotypes are needed to better understand the BLV–host interaction.