RSQ: a statistical method for quantification of isoform-specific structurome using transcriptome-wide structural profiling data

BioRxiv : the Preprint Server for Biology
Yunfei WangShikui Tu

Abstract

The structure of RNA, which is considered to be a second layer of information alongside the genetic code, provides fundamental insights into the cellular function of both coding and non-coding RNAs. Several high-throughput technologies have been developed to profile transcriptome-wide RNA structures, i.e., the structurome. However, it is challenging to interpret the profiling data because the observed data represent an average over different RNA conformations and isoforms with different abundance. To address this challenge, we developed an RNA structurome quantification method (RSQ) to statistically model the distribution of reads over both isoforms and RNA conformations, and thus provide accurate quantification of the isoform-specific structurome. The quantified RNA structurome enables the comparison of isoform-specific conformations between different conditions, the exploration of RNA conformation variation affected by single nucleotide polymorphism (SNP) , and the measurement of RNA accessibility for binding of either small RNAs in RNAi-based assays or RNA binding protein in transcriptional regulation. The model used in our method sheds new light on the potential impact of the RNA structurome on gene regulation.

Related Concepts

Small Nuclear RNA
Transcriptional Regulation
Exons
RNA, Untranslated
PNO1 gene
Binding (Molecular Function)
RNAi Therapeutics
Structure
Protein Isoforms
Statistical Technique

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