Evidence map›Paper›PMID 42341034›Full record

ArticlePLoS computational biology2026

The transcriptional gradient in negative-strand RNA viruses suggests a common RNA transcription mechanism.

Connor R King, Casey-Tyler Berezin, Brian Munsky, Jean Peccoud

Abstract read
In one paragraph

Article in PLoS computational biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Connor R KingLSI Genomics, Princeton University, Princeton, New Jersey, United States of America.ORCID https://orcid.org/0000-0001-5863-9876
Casey-Tyler BerezinSchool of Biomedical and Chemical Engineering, Colorado State University, Fort Collins, Colorado, United States of America.
Brian MunskySchool of Biomedical and Chemical Engineering, Colorado State University, Fort Collins, Colorado, United States of America.
Jean PeccoudSchool of Biomedical and Chemical Engineering, Colorado State University, Fort Collins, Colorado, United States of America.ORCID https://orcid.org/0000-0001-7649-6127

Funding

Using cellular fluctuations and computational analyses to probe biological mechanismsR35GM124747 · NIGMS · COLORADO STATE UNIVERSITY · PI Brian Munsky · 2017 to 2026
$3.3M
NIGMS NIH HHS R35 GM124747
6 · The paper itself

Abstract

Nonsegmented negative-strand RNA viruses (NNSV) are a diverse class of medically relevant viruses which display a conserved attenuation gradient in the transcription of their genomes. This gradient has been traditionally explained by the Stop-Start model which attributes attenuation to polymerase behavior at gene junctions. In this article, we evaluate an alternative explanation where the gradient arises from polymerase dynamics during transcription. We introduce the RNA Polymerase Association Mechanism (RAM) model, a coarse-grained stochastic framework that describes transcription using two parameters related to polymerase processivity and the ability of the polymerase to backtrack. The RAM model accurately reproduces transcriptional gradients across diverse NNSVs as well as in gene-shuffled VSV variants. Additionally, the inferred polymerase processivity appears correlated to the length of the viral genomes suggesting a conserved constraint on transcription across these viruses. While the RAM model does not account for all known molecular features of NNSV transcription, it provides a parsimonious and predictive framework for relating genome architecture and transcription. These results support the view that, in tandem with the traditional junction-centric mechanisms governing transcription, nonspecific attenuation mechanisms contribute to the NNSV transcriptional gradient and warrant closer inspection in future studies which could lead to better rational genome design in viral studies and biomedical applications.

Indexed as

Models, GeneticNegative-Sense RNA VirusesRNA, ViralRNA VirusesTranscription, GeneticViral TranscriptionComputer SimulationDNA-Directed RNA PolymerasesGenome, ViralDNA-Directed RNA PolymerasesRNA, Viral

Identifiers

PMID42341034
PMCPMC13313335

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LicenceCC BY
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Registered trials

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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.