ArticleMethods in molecular biology (Clifton, N.J.)2027
A Workflow for Identifying Helicase-Dependent RNA Structural Changes in Transcriptional Termination: From DMS Sequencing Analysis to Reporter Assay-Based Validation.
Article in Methods in molecular biology (Clifton, N.J.), 2027. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
RNA helicases are essential in all aspects of RNA biology where they remodel RNA secondary structures and RNA-protein (RNP) complexes. DEAD-box RNA helicases represent the largest RNA helicase family in eukaryotes. However, identification of biological targets for such helicases has been challenging. Structural probing methods involving treatment of cells with reagents such as SHAPE or dimethyl sulfate (DMS) coupled with sequencing (seq) have now enabled identification of RNA targets for these enzymes. These methods require extensive bioinformatics to derive RNA secondary structure predictions from readouts. Predicted targets must then be experimentally validated to determine the biological relevance of a given RNA structural rearrangement. We have utilized DMS-seq to identify RNA secondary structure targets of the DEAD-box RNA helicase Dbp2 in Saccharomyces cerevisiae and further linked their remodeling to transcription termination efficiency. This chapter outlines a data-analysis workflow for extracting DMS reactivity signals from short-read sequencing data and identifying regions of differential RNA structure between wild-type and dbp2Δ strains. It also describes a reporter assay-based method to assess if predicted structural rearrangements are linked to transcription termination efficiency. These approaches establish an integrated computational framework followed by experimental validation for elucidating helicase-dependent RNA structural dynamics and their functional interplay.
Indexed as
Identifiers
42862226What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.