In silico prediction of target SNPs affecting miR-mRNA interaction

MicroRNAs (miRs) are a large family of short 20-25-nt single-stranded noncoding RNAs, recently identified in many eukaryotes from nematode to human, which play an important role in gene regulation. Single nucleotide polymorphisms (SNPs) are the most common genetic variants in the human genome, and an immense source of information for localizing and identifying disease susceptible genes. Here, we investigate how the SNPs located in transcribed regions of protein coding genes will affect the miR-mRNA interaction by altering the Minimum Free Energy (MFE) of the miR-mRNA duplex, thus destroying the existing miR target sites or creating the new target sites. We propose that a combination of multiple allelic variants in miR target regions can alter the gene regulation and contribute to the likelihood of disease development. We developed a bioinformatics pipeline to predict the target SNPs, which can potentially influence the miR-mRNA interaction, based on the SNPs' ability to alter the MFE of the miR-mRNA duplex. We annotated and integrated such target SNPs, miRs, and the target gene annotation information into an integrated database, called miR-SNPDB (http://bioinformatics.wistar.upenn.edu/mir-snpdb) as a public resource for research community.