Abstract 2454: Cancer RNA:DNA interactome analysis and prediction

Abstract

Abstract Transcriptional R-loops are three-stranded RNA:DNA hybrid structures essential for many normal and pathobiological processes. Previously, we have proposed and validated a quantitative R-loop forming structure (RLFS) model, QmRLFS, and predicted about 660,000 RLFSs in the human genome; most of them are localized in total within 75% of the coding and non-coding genes and gene-flanking regions, transcribed enhancer and pseudogene regions. RLFSs are also commonly co-localized as the singleton or clusters at regulatory sites and disease-associated genomic loci. Recently, it was computationally predicted and experimentally shown that RNA:DNA hybrid/R-loop interactome may play critical roles in mutagenesis, chromosome breaks, genome instability and cancer development. Herein, we conducted a comprehensive comparative analysis between the RLFSs, their clusters, publically available DRIP-seq and DRIPc-seq, and our own experimental datasets. QmRLFS demonstrated high accuracy (82-92%) and unbiased performance with resolution on the nucleotide, gene and genome scales. A preferential co-localization of the RLFSs with promoters, U1 splice sites, gene ends, enhancers and non-B DNA structures, such as G-quadruplexes, provides evidences for the mechanic links between RLFSs and dynamical DNA tertiary structures, transcription initiation and critical regulatory genome signals. We introduced and characterized a class of 25000 paired reverse-forward RLFS clusters highly enriched with non-B DNA structures, which co-localized in the transcribed promoters of sense-antisense gene pairs and enhancer’s flanks. In the cancer genomes, we found the RLFSs that form RNA:DNA hybrids/R-loops and could preferentially link open promoters and transcriptionally active enhancer regions. This suggests new mechanisms for in trans RNA:DNA hybrid-mediated 3D-chromatin loop formation. Finally, we found the RLFS clusters supported by cancer cell RNA:DNA hybrids/R-loop data, which were overlapped with hyper-mutated clusters, kataegis expression signatures. Overall, our study provides a rationale for the prediction, discovery, and characterization of the RLFSs as novel functional structures for an emerging quantitative biology and pathobiology of RNA-DNA interactomes. Citation Format: Vladimir A. Kuznetsov. Cancer RNA:DNA interactome analysis and prediction [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 2454.