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

Abstract

Motivation: 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.

Results: 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 structural transitions within the cotranscriptional folding pathways of the Escherichia coli signal recognition particle RNA and the Bacillus cereus crcB fluoride riboswitch. We identify previously overlooked features of these datasets such as heightened reactivity patterns in the signal recognition particle RNA about 12 nt lengths before base-pair rearrangement. We then apply a sensitivity analysis to identify tradeoffs when choosing parameter thresholds. Finally, we show that DUETT is tunable across a wide range of contexts, enabling flexible application to study broad classes of RNA folding mechanisms.

Availability and implementation: https://github.com/BagheriLab/DUETT.

Supplementary information: Supplementary data are available at Bioinformatics online.

Fig. 1.

DUETT provides an automated and systematic method to detect cotranscriptional RNA folding events from SHAPE-Seq data. (A) RNA can dynamically alter structure during transcription that affects downstream biological functions. (B) Cotranscriptional SHAPE-Seq probes RNA structural properties during transcription by measuring reactivity patterns for each intermediate length of an RNA. High and low reactivity correspond to unstructured and constrained regions of RNA, respectively. (C) DUETT is a flexible method to identify large and gradual reactivity changes that are indicative of RNA structural transitions that can happen between intermediate RNA lengths. (D) Here DUETT is applied to a mock dataset to identify changes in reactivities in several consecutive nucleotides corresponding to the formation of an RNA loop, which is consistent with the typical ‘low-high-low’ pattern observed for RNA hairpin structures

Fig. 2.

DUETT identifies known RNA folding events in the E.coli SRP RNA cotranscriptional SHAPE-Seq reactivity matrices. Four previously proposed intermediate structural conformations of SRP RNA are shown with arrows linking specific color-coded bases to identified reactivity changes. RNA structures are redrawn from Figure 2 of Watters et al. (2016b) with intermediate hairpin H1 and loops L1–L4 labeled, and the RNAP exit channel footprint annotated in gray. DUETT identifies multiple instances of hairpin formation/rearrangement and previously unidentified events. DUETT displays detected swing and ramp events as a colored box and line, respectively, with red and blue denoting reactivity increase and decrease events, respectively. A green line connects concurrent events between different nucleotides. SHAPE reactivity is normalized to lie in between the range 0–1 and shown in grayscale and box area

Fig. 3.

DUETT identifies changes in the B.cereus fluoride riboswitch with 0 mM fluoride cotranscriptional SHAPE-Seq reactivity matrices. When comparing to events identified with the fluoride added condition (Fig. 4), DUETT identifies multiple known and novel reactivity events, indicated by arrows to nucleotides participating in these events. The figure is annotated as in Figure 2. RNA structures and pseudoknot (highlighted in yellow) are redrawn from Figure 6 of Watters et al. (2016b)

Fig. 4.

DUETT identifies changes in the B.cereus fluoride riboswitch with 10 mM fluoride cotranscriptional SHAPE-Seq reactivity matrices. These results are compared to Figure 3 to identify structural divergences between the fluoride conditions. The figure is annotated as in Figure 3