Genes of the RNASE5 pathway contain SNP associated with milk production traits in dairy cattle

Abstract

Background: Identification of the processes and mutations responsible for the large genetic variation in milk production among dairy cattle has proved challenging. One approach is to identify a biological process potentially involved in milk production and to determine the genetic influence of all the genes included in the process or pathway. Angiogenin encoded by angiogenin, ribonuclease, RNase A family 5 (RNASE5) is relatively abundant in milk, and has been shown to regulate protein synthesis and act as a growth factor in epithelial cells in vitro. However, little is known about the role of angiogenin in the mammary gland or if the polymorphisms present in the bovine RNASE5 gene are associated with lactation and milk production traits in dairy cattle. Given the high economic value of increased protein in milk, we have tested the hypothesis that RNASE5 or genes in the RNASE5 pathway are associated with milk production traits. First, we constructed a "RNASE5 pathway" based on upstream and downstream interacting genes reported in the literature. We then tested SNP in close proximity to the genes of this pathway for association with milk production traits in a large dairy cattle dataset.

Results: The constructed RNASE5 pathway consisted of 11 genes. Association analysis between SNP in 1 Mb regions surrounding these genes and milk production traits revealed that more SNP than expected by chance were associated with milk protein percent (P < 0.05 significance). There was no significant association with other traits such as milk fat content or fertility.

Conclusions: These results support a role for the RNASE5 pathway in milk production, specifically milk protein percent, and indicate that polymorphisms in or near these genes explain a proportion of the variation for this trait. This method provides a novel way of understanding the underlying biology of lactation with implications for milk production and can be applied to any pathway or gene set to test whether they are responsible for the variation of complex traits.

Figure 1

The direct pathway of action of RNASE5. The proposed mechanism of action as determined from a review of the literature. Hypoxic stress triggers transcription of RNASE5[37]. RNASE5 triggers the expression of two cell-density dependent receptors. At higher cell densities, RNASE5 binds with the endothelial cell surface via a 42-kDa α-actin receptor which stimulates basement membrane degradation [18]. This complex triggers plasminogen activation which in turn stimulates endothelial cell migration and angiogenesis [18,45]. Once the cell density decreases, the 170 kDa RNASE5 receptor is synthesized [19]. Binding interactions with this 170 kDa cell surface receptor trigger endocytosis of RNASE5[19]. Once internalised, RNASE5 triggers a series of cell signalling pathways including second messenger responses, MAPK activation and phosphorylation of Erk1/2 which stimulate cell proliferation, migration and growth [46-48]. From the cytoplasm, RNASE5 is translocated to the nucleus where it enhances rRNA transcription [20]. RNASE5 cleaves rRNA and tRNA and in turn recombinant angiogenin has been shown to act as a cytotoxic tRNase that abolishes protein synthesis [49-51]. We also revealed a significant number of activators and inhibitors of this pathway e.g. NO, however, only proteins were considered [52]. The path of the RNASE5 protein is highlighted in red boxes, with blue boxes representing the subsequent processes. The genes involved in this process are dictated alongside each process with activators and inhibitors noted outside each process in red (inhibitors) and black (up-regulators and other known binding proteins).

Figure 2

Permutation tests for protein, milk and fertility related traits using 50 k SNP data. Blue represents the null hypothesis distribution. SNP sets were randomised from 11 gene regions with 10 000 repeats and expressed as a ratio (P < 0.05). The red line represents the experimental ratio for each trait of interest: a) protein percent (f-value = 0.270), b) protein yield (f-value = 0.227), c) fertility (f-value = 0.085), d) fat yield (f-value = 0.128), e) fat percent (f-value = 0.128) and f) milk yield (f-value = 0.190).