Evidence map›Paper›PMID 26331722›Full record

ArticlePloS one2015

Allele-Selective Transcriptome Recruitment to Polysomes Primed for Translation: Protein-Coding and Noncoding RNAs, and RNA Isoforms.

Roshan Mascarenhas, Maciej Pietrzak, Ryan M Smith, Amy Webb, Danxin Wang, Audrey C Papp, Julia K Pinsonneault, Michal Seweryn, Grzegorz Rempala, Wolfgang Sadee

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
1.2field-weighted citation impact, top 22% 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

11 citing papers in PubMed, 19 citations in OpenAlex.

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  10. Gene expression profiling of brain samples from patients with Lewy body dementia.Biochemical and biophysical research communications · 2016
    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

10 authors at 2 institutions in 2 countries.

Roshan MascarenhasCenter for Pharmacogenomics, College of Medicine, The Ohio State University Wexner Medical Center, Columbus, Ohio, United States of America.
Maciej PietrzakCenter for Pharmacogenomics, College of Medicine, The Ohio State University Wexner Medical Center, Columbus, Ohio, United States of America; Division of Biostatistics, College of Public Health, The Ohio State University, Columbus, Ohio, United States of America.
Ryan M SmithCenter for Pharmacogenomics, College of Medicine, The Ohio State University Wexner Medical Center, Columbus, Ohio, United States of America.
Amy WebbDepartment of Biomedical Informatics, College of Medicine, The Ohio State University Wexner Medical Center, Columbus, Ohio, United States of America.
Danxin WangCenter for Pharmacogenomics, College of Medicine, The Ohio State University Wexner Medical Center, Columbus, Ohio, United States of America.
Audrey C PappCenter for Pharmacogenomics, College of Medicine, The Ohio State University Wexner Medical Center, Columbus, Ohio, United States of America.
Julia K PinsonneaultCenter for Pharmacogenomics, College of Medicine, The Ohio State University Wexner Medical Center, Columbus, Ohio, United States of America.
Michal SewerynDivision of Biostatistics, College of Public Health, The Ohio State University, Columbus, Ohio, United States of America; Department of Mathematics and Computer Science, University of Lodz, Lodz, Poland; Mathematical Biosciences Institute, The Ohio State University, Columbus, Ohio, United States of America.
Grzegorz RempalaCenter for Pharmacogenomics, College of Medicine, The Ohio State University Wexner Medical Center, Columbus, Ohio, United States of America; Division of Biostatistics, College of Public Health, The Ohio State University, Columbus, Ohio, United States of America; Mathematical Biosciences Institute, The Ohio State University, Columbus, Ohio, United States of America.
Wolfgang SadeeCenter for Pharmacogenomics, College of Medicine, The Ohio State University Wexner Medical Center, Columbus, Ohio, United States of America; Department of Medical Genetics, College of Medicine, The Ohio State University Wexner Medical Center, Columbus, Ohio, United States of America.
The Ohio State University Wexner Medical Center · USThe Ohio State University · US

Funding

Expression Genetics in Drug TherapyU01GM092655 · NIGMS · OHIO STATE UNIVERSITY · PI SADEE, WOLFGANG · 2010 to 2014
$8.6M
NIGMS NIH HHS U01 GM092655NIGMS NIH HHS U01GM092655
6 · The paper itself

Abstract

mRNA translation into proteins is highly regulated, but the role of mRNA isoforms, noncoding RNAs (ncRNAs), and genetic variants remains poorly understood. mRNA levels on polysomes have been shown to correlate well with expressed protein levels, pointing to polysomal loading as a critical factor. To study regulation and genetic factors of protein translation we measured levels and allelic ratios of mRNAs and ncRNAs (including microRNAs) in lymphoblast cell lines (LCL) and in polysomal fractions. We first used targeted assays to measure polysomal loading of mRNA alleles, confirming reported genetic effects on translation of OPRM1 and NAT1, and detecting no effect of rs1045642 (3435C>T) in ABCB1 (MDR1) on polysomal loading while supporting previous results showing increased mRNA turnover of the 3435T allele. Use of high-throughput sequencing of complete transcript profiles (RNA-Seq) in three LCLs revealed significant differences in polysomal loading of individual RNA classes and isoforms. Correlated polysomal distribution between protein-coding and non-coding RNAs suggests interactions between them. Allele-selective polysome recruitment revealed strong genetic influence for multiple RNAs, attributable either to differential expression of RNA isoforms or to differential loading onto polysomes, the latter defining a direct genetic effect on translation. Genes identified by different allelic RNA ratios between cytosol and polysomes were enriched with published expression quantitative trait loci (eQTLs) affecting RNA functions, and associations with clinical phenotypes. Polysomal RNA-Seq combined with allelic ratio analysis provides a powerful approach to study polysomal RNA recruitment and regulatory variants affecting protein translation.

Indexed as

AllelesProtein BiosynthesisTranscriptomeAnimalsArylamine N-AcetyltransferaseATP Binding Cassette Transporter, Subfamily BCell LineCHO CellsCricetulusHeLa CellsHumansIsoenzymesPolymorphism, Single NucleotidePolyribosomesReceptors, Opioid, muRNA IsoformsABCB1 protein, humanArylamine N-AcetyltransferaseATP Binding Cassette Transporter, Subfamily BIsoenzymesN-acetyltransferase 1OPRM1 protein, humanReceptors, Opioid, muRNA IsoformsRNA, MessengerRNA, Untranslated

Identifiers

PMID26331722
PMCPMC4558023
OpenAlexW1849637625

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.