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Protein functional features are reflected in the patterns of mRNA translation speed

Overview of attention for article published in BMC Genomics, July 2015
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Title
Protein functional features are reflected in the patterns of mRNA translation speed
Published in
BMC Genomics, July 2015
DOI 10.1186/s12864-015-1734-7
Pubmed ID
Authors

Daniel López, Florencio Pazos

Abstract

The degeneracy of the genetic code makes it possible for the same amino acid string to be coded by different messenger RNA (mRNA) sequences. These "synonymous mRNAs" may differ largely in a number of aspects related to their overall translational efficiency, such as secondary structure content and availability of the encoded transfer RNAs (tRNAs). Consequently, they may render different yields of the translated polypeptides. These mRNA features related to translation efficiency are also playing a role locally, resulting in a non-uniform translation speed along the mRNA, which has been previously related to some protein structural features and also used to explain some dramatic effects of "silent" single-nucleotide-polymorphisms (SNPs). In this work we perform the first large scale analysis of the relationship between three experimental proxies of mRNA local translation efficiency and the local features of the corresponding encoded proteins. We found that a number of protein functional and structural features are reflected in the patterns of ribosome occupancy, secondary structure and tRNA availability along the mRNA. One or more of these proxies of translation speed have distinctive patterns around the mRNA regions coding for certain protein local features. In some cases the three patterns follow a similar trend. We also show specific examples where these patterns of translation speed point to the protein's important structural and functional features. This support the idea that the genome not only codes the protein functional features as sequences of amino acids, but also as subtle patterns of mRNA properties which, probably through local effects on the translation speed, have some consequence on the final polypeptide. These results open the possibility of predicting a protein's functional regions based on a single genomic sequence, and have implications for heterologous protein expression and fine-tuning protein function.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 57 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 4%
Netherlands 1 2%
Iran, Islamic Republic of 1 2%
China 1 2%
Spain 1 2%
United States 1 2%
Unknown 50 88%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 21 37%
Researcher 11 19%
Student > Master 8 14%
Student > Postgraduate 3 5%
Student > Bachelor 2 4%
Other 5 9%
Unknown 7 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 23 40%
Biochemistry, Genetics and Molecular Biology 20 35%
Computer Science 3 5%
Medicine and Dentistry 2 4%
Engineering 2 4%
Other 1 2%
Unknown 6 11%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 15 March 2016.
All research outputs
#13,949,913
of 22,816,807 outputs
Outputs from BMC Genomics
#5,347
of 10,653 outputs
Outputs of similar age
#130,154
of 262,224 outputs
Outputs of similar age from BMC Genomics
#143
of 259 outputs
Altmetric has tracked 22,816,807 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,653 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 46th percentile – i.e., 46% of its peers scored the same or lower than it.
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 262,224 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 259 others from the same source and published within six weeks on either side of this one. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.