In silico profiling of miRNAs and their target polymorphisms in leukemia associated genes

Abstract

Single Nucleotide Polymorphisms (SNPs) within microRNA (miRNA) encoding regions of the genome are a large potential source for biologically relevant variation. SNPs along with miRNA act as a powerful tool to study the biology of a disease and also have the potential in monitoring disease prognosis and diagnosis. Therefore, evaluating the functional role of target mRNA will be a major challenge of future studies in the field of cancer biomarker research in leukemia. To assess, whether miRNA target SNPs are implicated in leukemia associated genes, we conducted an in silico approach along with the availability of publicly available web based tools for miRNA prediction and comprehensive genomic databases of SNPs. In this in-depth report, we attempted to use two computational approaches: prediction of miRNA in leukemia associated genes, and identifying the functional role of mRNAs targeted by miRNA. Our results from this study suggest that the application of in silico algorithms miRdSNP, PupaSuite and UTRScan analyses might provide an alternative approach to select target untranslated region (UTR) SNPs and understand the effect of SNPs on the functional attributes or molecular phenotype of a protein.