Predicting CpG Islands and DNA Methlation in the Cow Genome Using DNA Microarray Meta-Analysis and Genome Wide Scanning

DNA methylation is a type of epigenetic changes that directly affects DNA. In mammals, DNA methylation is essential for fetal development and stem cell differentiation and this phenomenon essentially occurs within the CpG islands. In this study, two methods were used to study the DNA methylation profile of cow genome. In the first method, the DNA methylation profile of the differentially expressed genes from meta-analysis of DNA microarray data on mastitis were obtained. In order to perform the meta-analysis in the first method, the metaDE package in R environment, was used. Then five algorithms including TJ, GF, CpG cluster, HMM and GHMM were used to predict CpG islands in different genes. In the second method, DNA methylation profiling was performed using whole cow genome scanning. Also, for prediction of methylated CpG islands in whole genome, HMM algorithm was first estimated in bovine genome for each chromosome and then CpG overlap with Hypo / Hyper-Methylation was calculated by Galaxy Online database. The results of the first method showed that among 32 differentially expressed genes, 14 genes involved methylated CpG islands. These genes included LTF, APP, CCL5, CD40, CSNK1D, CX3CL1, DAPP1, NFKBIZ, S100A9, ISG15, MAP3K8, MX1, RDAD2, ZC3H12A. Results of the second method identified a total 90668 Hypo / Hyper-Methylation in the bovine genome, among which 9942 (10.96%) CpG islands overlapped with Hypo / Hyper-Methylation and were considered as methylated CpG. Genomic comparisons were also made between species for DNA methylation. The results showed that the overall DNA methylation profile was almost similar for majority of studied species and it seems that the overall profile of DNA methylation is likely to be conserved between different species. The results of this study showed that DNA methylation seems necessary in diseases with low heritability and which are more influenced by epigenetic processes.