In silico characterization of functional SNP within the oestrogen receptor gene

Single-nucleotide polymorphism (SNP) association studies have become crucial in uncovering the genetic correlations of genomic variants with complex diseases, quantitative traits and physiological responses to drugs. However, the identification of SNPs responsible for specific phenotypes is a difficult problem to solve, requiring multiple testing of hundreds or thousands of SNPs in candidate genes. In this study, we performed an analysis of the genetic variations that can alter the structure and function of oestrogen receptor α using different computational tools. Among the nonsynonymous SNPs, a total of four SNPs were found to be damaging by both a sequence homology-based tool (SIFT) and a structural homology-based method (polyphen-2, SNAP), as well as by the ESEfinder program, and one nonsense nsSNP was found. For noncoding SNPs, we found that one SNP in 5' UTR may potentially change protein expression level, nine SNPs were found to affect miRNA binding site and 28 SNPs might affect transcriptional regulation of the ESR1 gene. Reviewing the literature, 89 SNPs were found to be functional among which only four were located in exons.