Poster abstracts
Poster number 138 submitted by Mansi Srivastava
Transcriptome-wide high-throughput mapping of protein-RNA occupancy profiles using an integrated phase separation and crosslinking approach
Mansi Srivastava (BioHealth Informatics,School of Informatics and Computing, IUPUI), Rajneesh Srivastava (BioHealth Informatics,School of Informatics and Computing, IUPUI), Sarath Chandra Janga (BioHealth Informatics,School of Informatics and Computing, IUPUI)
Abstract:
RNA-binding proteins (RBPs) associate physically with RNA to regulate multiple biological processes such as capping, splicing, polyadenylation, export and localization in a dynamic manner (1). Several transcriptome- wide approaches that determine the binding pockets of RBPs on its target RNA rely largely on the capture of polyadenylated RNAs (2,3). Recently a phase separation strategy using Trizol has emerged as a robust technology that has expanded the identification of RBP binding sites independent of the poly-A capture (4,5). Here, we present POP-seq (Protein-occupancy profile-sequencing) that employs UV and formaldehyde crosslinking to enhance the cellular RBP-RNA interactions followed by multi-step phase separation strategy using Trizol to yield RBP bound protected RNA regions of 30-50 bases. POP-seq libraries (in replicates) were sequenced to generate ~20 million of reads each, in Non cross-linked (NCL), formaldehyde cross-linked (FCL) and UV cross-linked (UCL) K562 cells respectively. We implemented a Next Generation Sequencing (NGS) pipeline to facilitate the analysis of the POP-seq data which included quality control, read alignment followed by peak calling, resulting in the identification of 321039, 289025 and 321541 unique peaks in NCL, FCL and UCL samples respectively, with ~35% peak overlap across the three protocols and ~85% of total peaks had length below 50 bp. We annotated these peaks onto human reference genome (hg38) and found that ~93.6% of the peaks were mapped to protein-coding genes followed by ~2.8% to lincRNA, ~1.7% to miRNA and ~1.9 to other RNA genes. Comparison of POP-seq peaks with the ENCODE eCLIP profile of RBPs in K562 cells revealed a high confident protein-RNA interaction capture with ~70% precision. Overall, this study illustrates a novel and cost-effective methodology to precisely capture the RNA-protein interaction sites with increased signal to noise ratio. Thus, application of POP-seq to additional cell lines originating from different tissue types would provide the first comprehensive understanding of the global occupancy profiles of RBPs across tissue types.
References:
1. Hentze, M. W., Castello, A., Schwarzl, T. & Preiss, T. A brave new world of RNA-binding proteins. Nat. Rev. Mol. Cell Biol. 19, 327–341 (2018).
2. Baltz, A. G. et al. The mRNA-bound proteome and its global occupancy profile on protein-coding transcripts. Mol. Cell 46, 674–690 (2012).
3. Schueler, M. et al. Differential protein occupancy profiling of the mRNA transcriptome. Genome Biol. 15, R15 (2014).
4. Queiroz, R. M. L. et al. Comprehensive identification of RNA-protein interactions in any organism using orthogonal organic phase separation (OOPS). Nat. Biotechnol. 37, 169–178 (2019).
5. Trendel, J. et al. The Human RNA-Binding Proteome and Its Dynamics during Translational Arrest. Cell 176, 391-403.e19 (2019).
Keywords: RNA binding proteins, Protein occupancy profile, Phase separation