Evidence map›Paper›PMID 40473516›Full record

ReviewTrends in genetics : TIG2025

Investigating RNA dynamics from single molecule transcriptomes.

Sahiti Somalraju, Doaa Hassan Salem, Sarath Chandra Janga

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Trends in genetics : TIG, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Long-Read Sequencing Reveals RNA Splicing Complexity in Human Diseases.Computational and structural biotechnology journal · 2026
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Sahiti SomalrajuDepartment of Biomedical Engineering and Informatics, Luddy School of Informatics, Computing and Engineering, Indiana University Indianapolis (IUI), Indianapolis, IN, USA.
Doaa Hassan SalemDepartment of Biomedical Engineering and Informatics, Luddy School of Informatics, Computing and Engineering, Indiana University Indianapolis (IUI), Indianapolis, IN, USA; Computers and Systems Department, National Telecommunication Institute, Cairo, Egypt.
Sarath Chandra JangaDepartment of Biomedical Engineering and Informatics, Luddy School of Informatics, Computing and Engineering, Indiana University Indianapolis (IUI), Indianapolis, IN, USA; Department of Medical and Molecular Genetics, Indiana University School of Medicine, Medical Research and Library Building, 975 West Walnut Street, Indianapolis, IN, USA; Centre for Computational Biology and Bioinformatics, Indiana University School of Medicine, 5021 Health Information and Translational Sciences (HITS), 410 West 10th Street, Indianapolis, IN, USA. Electronic address: scjanga@iu.edu.

Funding

Mapping RNA protein interaction networks in the human genomeR01GM123314 · NIGMS · INDIANA UNIVERSITY INDIANAPOLIS · PI JANGA, SARATH CHANDRA · 2017 to 2021
$1.7M
DataWiz-IN scholars program for Biomedical Informatics workforce in IndianaR25LM014209 · NLM · INDIANA UNIVERSITY INDIANAPOLIS · PI Sarath Chandra Janga, Saptarshi Purkayastha · 2022 to 2026
$675k
NIGMS NIH HHS R01 GM123314NLM NIH HHS R25 LM014209
6 · The paper itself

Abstract

Investigating RNA dynamics is crucial for uncovering fundamental mechanisms, such as alternative splicing, RNA stability, and post-transcriptional modifications, all processes with implications for identifying therapeutic targets and advancing knowledge of cellular function and regulation. Advances in long-read sequencing technologies, particularly from Pacific Biosciences (PacBio) and Oxford Nanopore Technologies (ONT), offer unprecedented insights into RNA dynamics at single molecule and single nucleotide resolutions. In this review, we examine protocols and methods for analyzing RNA dynamics, focusing on isoform detection, poly(A) tail length quantification, and mapping of RNA modifications. We envision that these high-throughput, transcriptome-wide data sets, combined with integrated software systems, will transform workflows for studying single molecule RNA dynamics. Such advances will help unravel the complexities of gene regulation and deepen our understanding of cellular processes.

Indexed as

RNATranscriptomeAlternative SplicingAnimalsHigh-Throughput Nucleotide SequencingHumansRNA Processing, Post-TranscriptionalRNA StabilitySequence Analysis, RNARNApoly(A) tailRNA bioinformaticsRNA isoformRNA modificationssingle molecule sequencingtranscriptomics

Identifiers

PMID40473516
PMCPMC12353502

What Socratic holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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 Socratic graph.