Evidence map›Paper›PMID 27118143›Full record

ArticleBMC genomics2016

Integrative analysis of the Trypanosoma brucei gene expression cascade predicts differential regulation of mRNA processing and unusual control of ribosomal protein expression.

Enoch B Antwi, Jurgen R Haanstra, Gowthaman Ramasamy, Bryan Jensen, Dorothea Droll, Federico Rojas, Igor Minia, Monica Terrao, Clémentine Mercé, Keith Matthews and 3 more

Open access · goldAbstract read
In one paragraph

Article in BMC genomics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed
5.2field-weighted citation impact, top 4% 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

28 citing papers in PubMed, 56 citations in OpenAlex.

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  5. TheRNA (New York, N.Y.) · 2022
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  6. Interactions of theParasitology · 2022
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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

13 authors at 7 institutions in 5 countries.

Enoch B AntwiZentrum für Molekulare Biologie der Universität Heidelberg, DKFZ-ZMBH Alliance, Im Neuenheimer Feld 282, D-69120, Heidelberg, Germany.
Jurgen R HaanstraDepartment of Molecular Cell Physiology, Vrije Universiteit Amsterdam, De Boelelaan 1085, 1081 HV, Amsterdam, The Netherlands.
Gowthaman RamasamyCenter for Infectious Disease Research (formerly Seattle Biomedical Research Institute), 307 Westlake Ave N, Seattle, WA, 98109-5219, USA.
Bryan JensenCenter for Infectious Disease Research (formerly Seattle Biomedical Research Institute), 307 Westlake Ave N, Seattle, WA, 98109-5219, USA.
Dorothea DrollZentrum für Molekulare Biologie der Universität Heidelberg, DKFZ-ZMBH Alliance, Im Neuenheimer Feld 282, D-69120, Heidelberg, Germany.
Federico RojasCentre for Immunity, Infection and Evolution, Institute for Immunology and infection Research, School of Biological Sciences, Ashworth Laboratories, University of Edinburgh, West Mains Road, Edinburgh, EH9 3JT, UK.
Igor MiniaZentrum für Molekulare Biologie der Universität Heidelberg, DKFZ-ZMBH Alliance, Im Neuenheimer Feld 282, D-69120, Heidelberg, Germany.
Monica TerraoZentrum für Molekulare Biologie der Universität Heidelberg, DKFZ-ZMBH Alliance, Im Neuenheimer Feld 282, D-69120, Heidelberg, Germany.
Clémentine MercéZentrum für Molekulare Biologie der Universität Heidelberg, DKFZ-ZMBH Alliance, Im Neuenheimer Feld 282, D-69120, Heidelberg, Germany.
Keith MatthewsCentre for Immunity, Infection and Evolution, Institute for Immunology and infection Research, School of Biological Sciences, Ashworth Laboratories, University of Edinburgh, West Mains Road, Edinburgh, EH9 3JT, UK.
Peter J MylerCenter for Infectious Disease Research (formerly Seattle Biomedical Research Institute), 307 Westlake Ave N, Seattle, WA, 98109-5219, USA.
Marilyn ParsonsCenter for Infectious Disease Research (formerly Seattle Biomedical Research Institute), 307 Westlake Ave N, Seattle, WA, 98109-5219, USA.
Christine ClaytonZentrum für Molekulare Biologie der Universität Heidelberg, DKFZ-ZMBH Alliance, Im Neuenheimer Feld 282, D-69120, Heidelberg, Germany. cclayton@zmbh.uni-heidelberg.de.
DKFZ-ZMBH Alliance · DECenter for Infectious Disease Research · USHeidelberg University · DECentre for Immunity, Infection and Evolution · GBUniversity of Edinburgh · GBUniversity of Washington Medical Center · USVrije Universiteit Amsterdam · NL

Funding

Ribosome profiling of Trypanosoma bruceiR21AI094129 · NIAID · SEATTLE BIOMEDICAL RESEARCH INSTITUTE · PI MYLER, PETER JOHN, PARSONS, MARILYN · 2011 to 2012
$531k
Biotechnology and Biological Sciences Research Council BB/I004602/1NIAID NIH HHS R21 AI094129Wellcome Trust 095831Wellcome Trust 103740Wellcome Trust 103740/Z/14/Z
6 · The paper itself

Abstract

backgroundTrypanosoma brucei is a unicellular parasite which multiplies in mammals (bloodstream form) and Tsetse flies (procyclic form). Trypanosome RNA polymerase II transcription is polycistronic, individual mRNAs being excised by trans splicing and polyadenylation. We previously made detailed measurements of mRNA half-lives in bloodstream and procyclic forms, and developed a mathematical model of gene expression for bloodstream forms. At the whole transcriptome level, many bloodstream-form mRNAs were less abundant than was predicted by the model.

resultsWe refined the published mathematical model and extended it to the procyclic form. We used the model, together with known mRNA half-lives, to predict the abundances of individual mRNAs, assuming rapid, unregulated mRNA processing; then we compared the results with measured mRNA abundances. Remarkably, the abundances of most mRNAs in procyclic forms are predicted quite well by the model, being largely explained by variations in mRNA decay rates and length. In bloodstream forms substantially more mRNAs are less abundant than predicted. We list mRNAs that are likely to show particularly slow or inefficient processing, either in both forms or with developmental regulation. We also measured ribosome occupancies of all mRNAs in trypanosomes grown in the same conditions as were used to measure mRNA turnover. In procyclic forms there was a weak positive correlation between ribosome density and mRNA half-life, suggesting cross-talk between translation and mRNA decay; ribosome density was related to the proportion of the mRNA on polysomes, indicating control of translation initiation. Ribosomal protein mRNAs in procyclics appeared to be exceptionally rapidly processed but poorly translated.

conclusionsLevels of mRNAs in procyclic form trypanosomes are determined mainly by length and mRNA decay, with some control of precursor processing. In bloodstream forms variations in nuclear events play a larger role in transcriptome regulation, suggesting aquisition of new control mechanisms during adaptation to mammalian parasitism.

Indexed as

RNA StabilityHalf-LifeModels, GeneticProtozoan ProteinsRibosomal ProteinsRibosomesRNA, MessengerRNA, ProtozoanTranscription, GeneticTranscriptomeTrypanosoma brucei bruceiProtozoan ProteinsRibosomal ProteinsRNA, MessengerRNA, Protozoan

Identifiers

PMID27118143
PMCPMC4845500
OpenAlexW2344856766

What OpenQuestion holds

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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.