RNA 3D structurome reconstruction and characterization

Project Summary/Abstract This research program will focus on the development and application of computational methodologies to deter- mine in vivo RNA 3D structure as well as characterizing the structural organization of functional elements for all RNA transcripts (termed transcriptome). The fates and functions of RNAs in health and diseases are determined by their structures. However, little is know about the folding of the transcriptome in the 3D space. Recently, high- throughput sequencing couple with proximity-ligation by chemical crosslinkers have been developed to investigate spatial RNA-RNA interactions at transcriptome scale. Current computational approaches are not readily suitable for analyzing the new types of RNA proximity-ligation sequencing datasets to dissect the higher-order structures, especially the 3D structures of all RNAs (termed RNA 3D structurome). To overcome these challenges, I will build a unique research program to develop statistical and computational methodologies for analyzing proximity- ligation sequencing data to reconstruct and characterize the 3D organization of RNAs in living cells. Over the next five years, the goals of my research program are to comprehensively elucidate the in vivo RNA 3D struc- tuome in high resolution and precision and decode the organization features of RNA functional elements. We will develop a methodological framework for inferring the 3D structures of RNAs using proximity-ligation sequencing data from living cells and verify them using experimentally verified 3D structures. We will use this the framework to study the 3D organization of RNAs from diverse categories (i.e., ribosome RNAs, messenger RNAs, and long noncoding RNAs) and from various cell types. Successful development of the proposed approaches will improve the understanding of RNAs folding in 3D and their functional impact on health and disease.