Evidence map›Paper›PMID 26576534›Full record

SynthesisBMC systems biology2015

Mining for novel candidate clock genes in the circadian regulatory network.

Anuprabha Bhargava, Hanspeter Herzel, Bharath Ananthasubramaniam

Open access · diamondAbstract readMeta-Analysis
In one paragraph

Synthesis in BMC systems biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.2field-weighted citation impact, top 25% 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

6 citing papers in PubMed, 12 citations in OpenAlex.

  1. Co-expression network analysis reveals repression ofbioRxiv : the preprint server for biology · 2026
    Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. 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

3 authors at 2 institutions in 1 country.

Anuprabha BhargavaInstitute for Theoretical Biology, Charité Universitätsmedizin, Phillipstr. 13, Haus 4, Berlin, 10115, Germany. anuprabhargava@gmail.com.
Hanspeter HerzelInstitute for Theoretical Biology, Humboldt Universität zu Berlin, Invalidenstr. 43, Berlin, 10115, Germany. h.herzel@biologie.hu-berlin.de.
Bharath AnanthasubramaniamInstitute for Theoretical Biology, Charité Universitätsmedizin, Phillipstr. 13, Haus 4, Berlin, 10115, Germany. bharath.ananth@charite.de.
Charité - Universitätsmedizin Berlin · DEHumboldt-Universität zu Berlin · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMost physiological processes in mammals are temporally regulated by means of a master circadian clock in the brain and peripheral oscillators in most other tissues. A transcriptional-translation feedback network of clock genes produces near 24 h oscillations in clock gene and protein expression. Here, we aim to identify novel additions to the clock network using a meta-analysis of public chromatin immunoprecipitation sequencing (ChIP-seq), proteomics and protein-protein interaction data starting from a published list of 1000 genes with robust transcriptional rhythms and circadian phenotypes of knockdowns.

resultsWe identified 20 candidate genes including nine known clock genes that received significantly high scores and were also robust to the relative weights assigned to different data types. Our scoring was consistent with the original ranking of the 1000 genes, but also provided novel complementary insights. Candidate genes were enriched for genes expressed in a circadian manner in multiple tissues with regulation driven mainly by transcription factors BMAL1 and REV-ERB α,β. Moreover, peak transcription of candidate genes was remarkably consistent across tissues. While peaks of the 1000 genes were distributed uniformly throughout the day, candidate gene peaks were strongly concentrated around dusk. Finally, we showed that binding of specific transcription factors to a gene promoter was predictive of peak transcription at a certain time of day and discuss combinatorial phase regulation.

conclusionsCombining complementary publicly-available data targeting different levels of regulation within the circadian network, we filtered the original list and found 11 novel robust candidate clock genes. Using the criteria of circadian proteomic expression, circadian expression in multiple tissues and independent gene knockdown data, we propose six genes (Por, Mtss1, Dgat2, Pim3, Ppp1r3b, Upp2) involved in metabolism and cancer for further experimental investigation. The availability of public high-throughput databases makes such meta-analysis a promising approach to test consistency between sources and tap their entire potential.

Indexed as

Gene Expression RegulationAnimalsCircadian Rhythm Signaling Peptides and ProteinsData MiningFeedback, PhysiologicalMammalsMiceModels, GeneticNIH 3T3 CellsPromoter Regions, GeneticProteomicsTime FactorsTranscription FactorsTranscription, GeneticCircadian Rhythm Signaling Peptides and ProteinsTranscription Factors

Identifiers

PMID26576534
PMCPMC4650315
OpenAlexW2245126444

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.