Identifying Conserved Human RNA Structures Using RNAz-LocARNA-RNAz Analysis Pipeline
I’ve just submitted my first conference paper to 10th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM-BCB 2019): Identifying Conserved Human RNA Structures Using RNAz-LocARNA-RNAz Analysis Pipeline, co-authored with Hosna Jabbari. Keep your fingers crossed for us.
Abstract: Identification of conserved RNA structures is of great importance in establishing causes of and potential therapeutic targets for genetic diseases. It has been estimated that over half of human genetic disease is due to alternative or disrupted RNA splicing, possibly caused by interrupted/damaged common structural functional motifs. Here we adapt the recently described analysis pipeline of Thiel, et al. to identify conserved RNA structures. While the original pipeline was used for identification of conserved structural features in a large mammalian set referenced to mouse genome, we restrict our model to seven mammalian species — mouse, human, rhesus, rabbit, pig, horse, and dog. These species are mostly used as models for human disease. Our objective is to assess the utility of this analysis pipeline when used with smaller, more focused data sets. While we reproduced the results of Thiel, et al. on similar species, we successfully identified two transcripts tagged as novel in the Ensemble transcript database: 458769.1 and 408377.1, Both are microRNAs. We have also identified 43 genes tagged as novel, including CASC17 and LINC00536, both of which are associated with human diseases (including atrial fibrillation, breast cancer, prostate cancer, schizophrenia, and systemic juvenile idiopathic arthritis). The majority of genes thus identified have multiple transcripts (splicing variants).