Evidence map›Paper›PMID 34297727›Full record

ArticlePLoS computational biology2021

A model explaining mRNA level fluctuations based on activity demands and RNA age.

Zhongneng Xu, Shuichi Asakawa

Open access · goldAbstract read
In one paragraph

Article in PLoS computational biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.6field-weighted citation impact, top 33% of its field
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

2 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. Surfactant Protein Production during Maturation Is Enhanced by Natural Variability in Breathing.American journal of respiratory cell and molecular biology · 2023
    Article
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

2 authors at 2 institutions in 2 countries.

Zhongneng XuDepartment of Ecology, Jinan University, Guangzhou, China.ORCID 0000-0002-2503-478X
Shuichi AsakawaDepartment of Aquatic Bioscience, Graduate School of Agricultural and Life Sciences, The University of Tokyo, Tokyo, Japan.ORCID 0000-0002-7599-0825
Jinan University · CNThe University of Tokyo · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cellular RNA levels typically fluctuate and are influenced by different transcription rates and RNA degradation rates. However, the understanding of the fundamental relationships between RNA abundance, environmental stimuli, RNA activities, and RNA age distributions is incomplete. Furthermore, the rates of RNA degradation and transcription are difficult to measure in transcriptomic experiments in living organisms, especially in studies involving humans. A model based on activity demands and RNA age was developed to explore the mechanisms of RNA level fluctuations. Using single-cell time-series gene expression experimental data, we assessed the transcription rates, RNA degradation rates, RNA life spans, RNA demand, accumulated transcription levels, and accumulated RNA degradation levels. This model could also predict RNA levels under simulation backgrounds, such as stimuli that induce regular oscillations in RNA abundance, stable RNA levels over time that result from long-term shortage of total RNA activity or from uncontrollable transcription, and relationships between RNA/protein levels and metabolic rates. This information contributes to existing knowledge.

Indexed as

Models, BiologicalRNA StabilityComputational BiologyComputer SimulationRNA, FungalRNA, MessengerSaccharomyces cerevisiaeSaccharomyces cerevisiae ProteinsSingle-Cell AnalysisTranscription, GeneticTranscriptomeRNA, FungalRNA, MessengerSaccharomyces cerevisiae Proteins

Identifiers

PMID34297727
PMCPMC8336849
OpenAlexW3185738930

What OpenQuestion holds

Textmetadata
LicenceCC BY
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 OpenQuestion graph.