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Translational contributions to tissue specificity in rhythmic and constitutive gene expression

Overview of attention for article published in Genome Biology, June 2017
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (83rd percentile)

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16 X users
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82 Mendeley
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Title
Translational contributions to tissue specificity in rhythmic and constitutive gene expression
Published in
Genome Biology, June 2017
DOI 10.1186/s13059-017-1222-2
Pubmed ID
Authors

Violeta Castelo-Szekely, Alaaddin Bulak Arpat, Peggy Janich, David Gatfield

Abstract

The daily gene expression oscillations that underlie mammalian circadian rhythms show striking differences between tissues and involve post-transcriptional regulation. Both aspects remain poorly understood. We have used ribosome profiling to explore the contribution of translation efficiency to temporal gene expression in kidney and contrasted our findings with liver data available from the same mice. Rhythmic translation of constantly abundant messenger RNAs (mRNAs) affects largely non-overlapping transcript sets with distinct phase clustering in the two organs. Moreover, tissue differences in translation efficiency modulate the timing and amount of protein biosynthesis from rhythmic mRNAs, consistent with organ specificity in clock output gene repertoires and rhythmicity parameters. Our comprehensive datasets provided insights into translational control beyond temporal regulation. Between tissues, many transcripts show differences in translation efficiency, which are, however, of markedly smaller scale than mRNA abundance differences. Tissue-specific changes in translation efficiency are associated with specific transcript features and, intriguingly, globally counteracted and compensated transcript abundance variations, leading to higher similarity at the level of protein biosynthesis between both tissues. We show that tissue specificity in rhythmic gene expression extends to the translatome and contributes to define the identities, the phases and the expression levels of rhythmic protein biosynthesis. Moreover, translational compensation of transcript abundance divergence leads to overall higher similarity at the level of protein production across organs. The unique resources provided through our study will serve to address fundamental questions of post-transcriptional control and differential gene expression in vivo.

X Demographics

X Demographics

The data shown below were collected from the profiles of 16 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 82 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Switzerland 1 1%
Unknown 81 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 25 30%
Researcher 17 21%
Student > Master 6 7%
Professor > Associate Professor 4 5%
Student > Doctoral Student 3 4%
Other 11 13%
Unknown 16 20%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 28 34%
Agricultural and Biological Sciences 24 29%
Engineering 3 4%
Computer Science 2 2%
Social Sciences 2 2%
Other 5 6%
Unknown 18 22%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 12. 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 01 December 2023.
All research outputs
#3,133,279
of 25,808,886 outputs
Outputs from Genome Biology
#2,309
of 4,521 outputs
Outputs of similar age
#52,617
of 318,384 outputs
Outputs of similar age from Genome Biology
#47
of 65 outputs
Altmetric has tracked 25,808,886 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,521 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.5. This one is in the 48th percentile – i.e., 48% 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 318,384 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 83% of its contemporaries.
We're also able to compare this research output to 65 others from the same source and published within six weeks on either side of this one. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.