Investigating the role of non coding RNAs in the etiology of diseases

Abstract

Non-coding RNAs, including non-coding regions of pre-mRNAs, though they do not code for protein, play key functional and regulatory roles in gene expression at the transcriptional and post-transcriptional stages, influencing a wide range of biological processes. Their huge impact on several molecular mechanisms underpins their contribution to the development and progression of a broad spectrum of diseases, including cancer. With the availability of RNA structurome data and that of advanced RNA folding algorithms, it is possible to study the structural and conformational space spanned by these regulatory RNAs. These studies, in conjunction with detailed investigation of the associated regulatory processes and of genetic disease-related variations thereof, could help us in exploring new approaches towards understanding, diagnosing, and managing genetic diseases. We have explored disease-causing RNA structural disruptions called riboSNitches, in the splice junctions of pre-mRNAs, and shortlisted potential riboSNitches associated with somatic cancer mutations, aberrant splice mutations, and genetic diseases. We have developed an approach that is more reliable than other available methods for riboSNitch detection. Circular RNAs (circRNAs), one of the largest classes of non-coding RNAs, have exhibited a regulatory role in gene expression by acting as miRNA sponges. A significant number of studies have explored their capability as therapeutic agents and as biomarkers in several pathological conditions associated with their unique characteristics, such as diversity, stability, and abundance of tissue-specific expression. It was proposed that non-coding RNA transcripts, especially circRNAs and long non-coding RNAs (lncRNAs), form an extensive network by competitively binding to miRNA binding sites. This network, termed ceRNA/competitive endogenous network (circRNA/lncRNA-miRNA-mRNA), was demonstrated to regulate the translation of miRNA target genes. In this study, we proposed ceRNA network construction based on atrial fi