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Revealing the architecture of genetic and epigenetic regulation: a maximum likelihood model
Abstract:
Gene expression is modulated by multiple mechanisms, including genetic and/or epigenetic regulation, and associated with the processes of cellular differentiation and morphogenesis. Single nucleotide polymorphisms (SNPs) and DNA methylation play important roles in regulating gene expression. In this study, we focused on revealing the relationship between SNPs, DNA methylation and gene expression in two human populations genome-wide through proposing four regulation patterns and developed maximum likelihood estimate models. Using simulated data with different correlation coefficients between any two traits, the power of our approach showed a favourable performance and relative stability. In all, 6733 SNP-CpG-gene pairs including 957 genes were obtained in Northern European ancestry (CEU) population. As the results showed, SNPs and DNA methylation had approximately the same effect on expression regulation of 49% genes, which was termed cooperative/antagonistic regulation pattern. Less than 30% of genes are controlled only by one of the factors (SNP/DNA methylation). The others showed SNPs that affect methylation have no consequent effects or crosstalk regulation on gene expression. Similar result was shown in Yourba (YRI) population. Specific genes were inferred using the different mechanisms of gene regulation involved in complex diseases by combining literature. This approach provides a method to comprehensively assess regulation patterns of gene expression in the whole genome.
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