Development of OPRMA, an online tool to analyze RNA – protein interactions and RNA modifications
Zhenzhi Li (Mentor: Dr. Shaojun Tang, Innovation Center for Biomedical Informatics, Georgetown University)
August 29, 2017, 2:30pm, Room 341, Basic Science
RNA binding proteins (RBP) are important regulators of RNA expression and modifications. RBPs can modify RNA in various ways such as RNA editing, 5’/3’ capping, and stabilizing/destabilizing transcripts by binding to specific regions on transcripts. Despite substantial progress, much remains to be learned about RBP-RNA interactions and RBP’s role in RNA modifications. Recent development of combining next generation sequencing and UV crosslinking-immunoprecipitation (CLIP-seq) provides direct insight of RBPs and their RNA binding sites.
However, current bioinformatics tools to fail to address several key components of RBP-RNA interactions. For example, one of the key features of RBP-RNA interaction is the distribution of RBP binding motifs relative to important sub genomic regions (eg. 5’UTR, coding sequence, 3’ UTR) and specific reference points (eg. stop codon, exon/intron junction). To address this issue, we developed an Online Platform for RNA Modification Analysis (OPRMA).
The backend of OPRMA is written in R and its front page is powered by R-Shiny package featuring user-friendly, interactive user interface. OPRMA takes two BED files from peak-calling programs such as MACS. The input files should have chromosome number, start, end and peak location in first four columns. After uploading files and selecting appropriate genomic background (OPRMA currently supports human hg19 and mouse mm10 genome), user can select analysis method OPRMA provided: peak distribution relative to 5’/3’ UTR, last exon/intron junction, and stop codon. Density plot of relative peak distribution will be provided for selected method. OPRMA can also analyze peak distribution within user-provided genes. On OPRMA web page, an optional gene list file can be uploaded to perform additional analysis on selected genes.
CLIP-seq data on AGO2, ALKBH5 and C22ORF28 were obtained from public database starBase v2.0 (http://starbase.sysu.edu.cn/) as test data sets. Not only OPRMA’s analysis is consistent with original publications; OPRMA also allows users to gain additional perspectives on same dataset. We thus conclude OPRMA is an effect tool to analyze interactions between RBP and RNA, and potentially achieve better understanding of RNA modifications.