DUETT quantitatively identifies known and novel events in nascent RNA structural dynamics from chemical probing data

Bioinformatics
Albert Y XueNeda Bagheri

Abstract

RNA molecules can undergo complex structural dynamics, especially during transcription, which influence their biological functions. Recently developed high-throughput chemical probing experiments that study RNA cotranscriptional folding generate nucleotide-resolution 'reactivities' for each length of a growing nascent RNA that reflect structural dynamics. However, the manual annotation and qualitative interpretation of reactivity across these large datasets can be nuanced, laborious, and difficult for new practitioners. We developed a quantitative and systematic approach to automatically detect RNA folding events from these datasets to reduce human bias/error, standardize event discovery and generate hypotheses about RNA folding trajectories for further analysis and experimental validation. Detection of Unknown Events with Tunable Thresholds (DUETT) identifies RNA structural transitions in cotranscriptional RNA chemical probing datasets. DUETT employs a feedback control-inspired method and a linear regression approach and relies on interpretable and independently tunable parameter thresholds to match qualitative user expectations with quantitatively identified folding events. We validate the approach by identifying known RNA st...Continue Reading

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Datasets Mentioned

BETA
PRJNA342175

Methods Mentioned

BETA
SHAPE-Seq
optical tweezer
NMR

Software Mentioned

SHAPE
RNAstructure
NUPACK
DUETT
Seq
- Fold

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