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

Overview of attention for article published in BMC Genomics, April 2016
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  • Above-average Attention Score compared to outputs of the same age and source (52nd percentile)

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Title
Integrative analysis of the Trypanosoma brucei gene expression cascade predicts differential regulation of mRNA processing and unusual control of ribosomal protein expression
Published in
BMC Genomics, April 2016
DOI 10.1186/s12864-016-2624-3
Pubmed ID
Authors

Enoch B. Antwi, Jurgen R. Haanstra, Gowthaman Ramasamy, Bryan Jensen, Dorothea Droll, Federico Rojas, Igor Minia, Monica Terrao, Clémentine Mercé, Keith Matthews, Peter J. Myler, Marilyn Parsons, Christine Clayton

Abstract

Trypanosoma 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. We 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. Levels 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.

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The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 73 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 1%
Brazil 1 1%
Unknown 71 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 21 29%
Student > Master 12 16%
Researcher 9 12%
Professor > Associate Professor 6 8%
Professor 5 7%
Other 13 18%
Unknown 7 10%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 27 37%
Agricultural and Biological Sciences 25 34%
Immunology and Microbiology 3 4%
Computer Science 3 4%
Nursing and Health Professions 2 3%
Other 3 4%
Unknown 10 14%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 30 April 2016.
All research outputs
#13,392,095
of 22,865,319 outputs
Outputs from BMC Genomics
#4,962
of 10,663 outputs
Outputs of similar age
#145,084
of 298,924 outputs
Outputs of similar age from BMC Genomics
#95
of 202 outputs
Altmetric has tracked 22,865,319 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,663 research outputs from this source. They receive a mean Attention Score of 4.7. This one has gotten more attention than average, scoring higher than 53% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 298,924 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 51% of its contemporaries.
We're also able to compare this research output to 202 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 52% of its contemporaries.