Evidence map›Paper›PMID 30478415›Full record

ArticleNature communications2018

Quantifying post-transcriptional regulation in the development of Drosophila melanogaster.

Kolja Becker, Alina Bluhm, Nuria Casas-Vila, Nadja Dinges, Mario Dejung, Sergi Sayols, Clemens Kreutz, Jean-Yves Roignant, Falk Butter, Stefan Legewie

Open access · goldAbstract read
In one paragraph

Article in Nature communications, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 59 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
59citing papers in PubMed, 1 pooled it
2.9field-weighted citation impact, top 8% 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

59 citing papers in PubMed, 1 synthesis or guideline pooled it, 109 citations in OpenAlex.

  1. Pooled it
  2. Bacterial stress responses lower mRNA-protein level correlations.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Review
  19. Article
  20. Article
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 1 country.

Kolja BeckerInstitute of Molecular Biology (IMB), Ackermannweg 4, 55128, Mainz, Germany.
Alina BluhmInstitute of Molecular Biology (IMB), Ackermannweg 4, 55128, Mainz, Germany.
Nuria Casas-VilaInstitute of Molecular Biology (IMB), Ackermannweg 4, 55128, Mainz, Germany.
Nadja DingesInstitute of Molecular Biology (IMB), Ackermannweg 4, 55128, Mainz, Germany.
Mario DejungInstitute of Molecular Biology (IMB), Ackermannweg 4, 55128, Mainz, Germany.
Sergi SayolsInstitute of Molecular Biology (IMB), Ackermannweg 4, 55128, Mainz, Germany.
Clemens KreutzCenter for Biosystems Analysis (ZBSA), University of Freiburg, Habsburger Str. 49, 79104, Freiburg, Germany.
Jean-Yves RoignantInstitute of Molecular Biology (IMB), Ackermannweg 4, 55128, Mainz, Germany.
Falk ButterInstitute of Molecular Biology (IMB), Ackermannweg 4, 55128, Mainz, Germany. f.butter@imb.de.
Stefan LegewieInstitute of Molecular Biology (IMB), Ackermannweg 4, 55128, Mainz, Germany. s.legewie@imb.de.
Institute of Molecular Biology · DEUniversity of Freiburg · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Even though proteins are produced from mRNA, the correlation between mRNA levels and protein abundances is moderate in most studies, occasionally attributed to complex post-transcriptional regulation. To address this, we generate a paired transcriptome/proteome time course dataset with 14 time points during Drosophila embryogenesis. Despite a limited mRNA-protein correlation (ρ = 0.54), mathematical models describing protein translation and degradation explain 84% of protein time-courses based on the measured mRNA dynamics without assuming complex post transcriptional regulation, and allow for classification of most proteins into four distinct regulatory scenarios. By performing an in-depth characterization of the putatively post-transcriptionally regulated genes, we postulate that the RNA-binding protein Hrb98DE is involved in post-transcriptional control of sugar metabolism in early embryogenesis and partially validate this hypothesis using Hrb98DE knockdown. In summary, we present a systems biology framework for the identification of post-transcriptional gene regulation from large-scale, time-resolved transcriptome and proteome data.

Indexed as

Gene Expression RegulationTranscription, GeneticAnimalsBase SequenceDrosophila melanogasterDrosophila ProteinsEmbryonic DevelopmentGlucoseKineticsProteomeRNA, MessengerTranscriptomeDrosophila ProteinsGlucoseProteomeRNA, Messenger

Identifiers

PMID30478415
PMCPMC6255845
OpenAlexW2901411431

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.