Evidence map›Paper›PMID 29636505›Full record

ArticleScientific reports2018

A Multi-Parameter Analysis of Cellular Coordination of Major Transcriptome Regulation Mechanisms.

Wen Jiang, Zhanyong Guo, Nuno Lages, W Jim Zheng, Denis Feliers, Fangyuan Zhang, Degeng Wang

Abstract read
In one paragraph

Article in Scientific reports, 2018. 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
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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

7 authors.

Wen JiangDepartment of Environmental Toxicology, Texas Tech University, Lubbock, TX, 79409, USA.
Zhanyong GuoNational Key Laboratory of Wheat and Maize Crop Science, College of Agronomy, Henan Agricultural University, Zhengzhou, Henan, 450002, P. R. China.
Nuno LagesInstituto Superior Técnico, Universidade de Lisboa, IST-Taguspark, 2744-016, Porto Salvo, Portugal.
W Jim ZhengSchool of Biomedical Informatics, The University of Texas Health Science Center at Houston, 7000 Fannin Street, Suite 600, Houston, TX, 77030, USA.
Denis FeliersDepartment of Medicine/Renal Diseases, The University of Texas Health Science Center at San Antonio, San Antonio, TX, USA.
Fangyuan ZhangDepartment of Mathematics & Statistics, Texas Tech University, Lubbock, TX, 79409, USA.
Degeng WangDepartment of Environmental Toxicology, Texas Tech University, Lubbock, TX, 79409, USA. degeng.wang@ttu.edu.

Funding

Genomic Basis of Biochemical Network TopologyR01LM010212 · NLM · UNIVERSITY OF TEXAS HLTH SCIENCE CENTER · PI LI, RONG · 2010 to 2012
$806k
To Combine CRISPR/Cas9 Genome Editing, Nanotech and Chemical Genetics toward in vivo Protein Kinase AnalysisR15GM122006 · NIGMS · TEXAS TECH UNIVERSITY · PI WANG, DEGENG · 2017 to 2019
$535k
NIGMS NIH HHS R15 GM122006NLM NIH HHS R01 LM010212
6 · The paper itself

Abstract

To understand cellular coordination of multiple transcriptome regulation mechanisms, we simultaneously measured transcription rate (TR), mRNA abundance (RA) and translation activity (TA). This revealed multiple insights. First, the three parameters displayed systematic statistical differences. Sequentially more genes exhibited extreme (low or high) expression values from TR to RA, and then to TA; that is, cellular coordination of multiple transcriptome regulatory mechanisms leads to sequentially enhanced gene expression selectivity as the genetic information flow from the genome to the proteome. Second, contribution of the stabilization-by-translation regulatory mechanism to the cellular coordination process was assessed. The data enabled an estimation of mRNA stability, revealing a moderate but significant positive correlation between mRNA stability and translation activity. Third, the proportion of mRNA occupied by un-translated regions (UTR) exhibited a negative relationship with the level of this correlation, and was thus a major determinant of the mode of regulation of the mRNA. High-UTR-proportion mRNAs tend to defy the stabilization-by-translation regulatory mechanism, staying out of the polysome but remaining stable; mRNAs with little UTRs largely followed this regulation. In summary, we quantitatively delineated the relationship among multiple transcriptome regulation parameters, i.e., cellular coordination of corresponding regulatory mechanisms.

Indexed as

Computational BiologyGene Expression RegulationModels, BiologicalTranscriptomeAnimalsCell Line, TumorHumansProtein BiosynthesisRNA, MessengerRNA StabilityUntranslated RegionsRNA, MessengerUntranslated Regions

Identifiers

PMID29636505
PMCPMC5893539

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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.