GC4miRNA - a Pipeline for Examining Impact of GC Content in miRNA Seed Sequences on Expression in Tumor Samples

MicroRNAs (miRNAs) are small RNA molecules that play a crucial role in regulating gene expression by binding to and degrading targeted mRNAs. miRNAs targeting a specific mRNA have a region known as the “seed sequence”, which typically has a high affinity for its complementary sequence in the targeted mRNA. Single Nucleotide Polymorphisms (SNPs) are mutations that refer to the substitution of a single nucleotide. Alterations in the nucleotides of seed sequences can have a significant impact on the targeting strength between miRNAs and mRNAs, potentially resulting in dysregulation of genes, and causing various diseases, including cancers. It is crucial to assess the impact of SNPs will have on nucleotides in specific seed sequences by gauging a common factor (e.g. GC content) reflecting the binding affinity. GC content is an essential aspect in miRNA binding, since high GC content miRNAs are frequently more stable, and may have a stronger affinity for their targets. To reveal the GC content signature for cancer-associated miRNAs, we developed a bioinformatics pipeline called GC4miRNA, which can calculate GC percentage enrichment in a sequence and perform statistical analysis to compare the GC content between the seed sequence and whole sequence for targeting miRNAs using customized BASH and R scripts. The pipeline was implemented as an R Shiny application that carries out several tasks/modules, such as measuring similarities between miRNAs whose dysregulation is linked to cancer and identifying common patterns within miRNAs with greater GC content.