In silico analysis of coding SNPs and 3-UTR associated miRNAs in DCAF17 gene that may affect the regulation and pathogenesis of Woodhouse-Sakati Syndrome

Background: Woodhouse-Sakati Syndrome refers to a group of inherited disorders characterized by alopecia, hypogonadism, diabetes mellitus, hypothyroidism and progressive extrapyramidal signs. The aim of this study is to identify the pathogenic SNPs in the DCAF17 gene with their related mciroRNAs and their effect on the structure and function of the protein. Material and Methods: We used different bioinformatics tools to predict the effect of each SNP on the structure and function of the protein. After that we defined the miRNAs founded in the 39-UTR region on the DCAF17 gene and studied the annotations relative to it. Results: Ten deleterious SNPs out of 339 were found to have a damaging effect on the protein structure and function, with one significant micoRNA in the 3-UTR region. Conclusion: This was the first in silico analysis of DCAF17 gene, in which 10 novel mutations were found using different bioinformatics tools that could be used as a diagnostic markers for Woodhouse-Sakati syndrome, with one relevant microRNA that can regulate the function of the protein. Keywords: Woodhouse-Sakati Syndrome, DCAF17 gene, SNPs, 3-UTR ,in silico analysis, diagnostic markers.