Evidence map›Paper›PMID 24737000›Full record

ArticlePLoS biology2014

Machine learning helps identify CHRONO as a circadian clock component.

Ron C Anafi, Yool Lee, Trey K Sato, Anand Venkataraman, Chidambaram Ramanathan, Ibrahim H Kavakli, Michael E Hughes, Julie E Baggs, Jacqueline Growe, Andrew C Liu and 2 more

Open access · goldAbstract read
In one paragraph

Article in PLoS biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 76 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
76citing papers in PubMed, 1 pooled it
4.0field-weighted citation impact, top 5% 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

76 citing papers in PubMed, 1 synthesis or guideline pooled it, 146 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Review
  4. Review
  5. Review
  6. Review
  7. Article
  8. Article
  9. Review
  10. Article
  11. The Relationship between Circadian Rhythm and Cancer Disease.International journal of molecular sciences · 2024
    Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Review
  18. Mood phenotypes in rodent models with circadian disturbances.Neurobiology of sleep and circadian rhythms · 2022
    Review
  19. Article
  20. Article

16 more citing papers are in PubMed but not listed here.

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

12 authors at 6 institutions in 2 countries.

Ron C AnafiDivision of Sleep Medicine, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania, United States of America; Center for Sleep and Circadian Neurobiology, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania, United States of America.
Yool LeeDepartment of Pharmacology and the Institute for Translational Medicine and Therapeutics, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania, United States of America.
Trey K SatoDepartment of Pharmacology and the Institute for Translational Medicine and Therapeutics, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania, United States of America.
Anand VenkataramanDepartment of Pharmacology and the Institute for Translational Medicine and Therapeutics, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania, United States of America.
Chidambaram RamanathanDepartment of Biological Sciences, University of Memphis, Memphis, Tennessee, United States of America.
Ibrahim H KavakliDepartment of Chemical and Biological Engineering, Koc University, Istanbul, Turkey.
Michael E HughesDepartment of Biology, University of Missouri-St. Louis, St. Louis, Missouri, United States of America.
Julie E BaggsDepartment of Pharmacology, Morehouse School of Medicine, Atlanta, Georgia, United States of America.
Jacqueline GroweDivision of Sleep Medicine, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania, United States of America; Center for Sleep and Circadian Neurobiology, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania, United States of America.
Andrew C LiuDepartment of Biological Sciences, University of Memphis, Memphis, Tennessee, United States of America.
Junhyong KimDepartment of Biology, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.
John B HogeneschCenter for Sleep and Circadian Neurobiology, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania, United States of America; Department of Pharmacology and the Institute for Translational Medicine and Therapeutics, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania, United States of America.
University of Pennsylvania · USTranslational Therapeutics (United States) · USUniversity of Memphis · USKoç University · TRMorehouse School of Medicine · USUniversity of Missouri–St. Louis · US

Funding

THE ROLE OF SLEEP IN MEMORY STORAGEP01AG017628 · NIA · UNIVERSITY OF PENNSYLVANIA · PI PACK, ALLAN I · 2001 to 2017
$19.2M
Molecular, Cellular and Physiological Mechanisms of the Mammalian Circadian ClockR01NS054794 · NINDS · UNIVERSITY OF PENNSYLVANIA · PI HOGENESCH, JOHN B, LIU, ANDREW C. · 2007 to 2022
$8.1M
Career Development for Genomic/Genetic Studies in Lung DiseasesK12HL090021 · NHLBI · UNIVERSITY OF PENNSYLVANIA · PI PACK, ALLAN I · 2007 to 2012
$2.0M
NHLBI NIH HHS 5K12HL090021-05NHLBI NIH HHS K12 HL090021NIA NIH HHS 2P01AG017628-11NIA NIH HHS P01 AG017628NINDS NIH HHS 1R01NS054794-06NINDS NIH HHS R01 NS054794Wellcome Trust
6 · The paper itself

Abstract

Over the last decades, researchers have characterized a set of "clock genes" that drive daily rhythms in physiology and behavior. This arduous work has yielded results with far-reaching consequences in metabolic, psychiatric, and neoplastic disorders. Recent attempts to expand our understanding of circadian regulation have moved beyond the mutagenesis screens that identified the first clock components, employing higher throughput genomic and proteomic techniques. In order to further accelerate clock gene discovery, we utilized a computer-assisted approach to identify and prioritize candidate clock components. We used a simple form of probabilistic machine learning to integrate biologically relevant, genome-scale data and ranked genes on their similarity to known clock components. We then used a secondary experimental screen to characterize the top candidates. We found that several physically interact with known clock components in a mammalian two-hybrid screen and modulate in vitro cellular rhythms in an immortalized mouse fibroblast line (NIH 3T3). One candidate, Gene Model 129, interacts with BMAL1 and functionally represses the key driver of molecular rhythms, the BMAL1/CLOCK transcriptional complex. Given these results, we have renamed the gene CHRONO (computationally highlighted repressor of the network oscillator). Bi-molecular fluorescence complementation and co-immunoprecipitation demonstrate that CHRONO represses by abrogating the binding of BMAL1 to its transcriptional co-activator CBP. Most importantly, CHRONO knockout mice display a prolonged free-running circadian period similar to, or more drastic than, six other clock components. We conclude that CHRONO is a functional clock component providing a new layer of control on circadian molecular dynamics.

Indexed as

3T3 CellsAmino Acid SequenceAnimalsARNTL Transcription FactorsArtificial IntelligenceCell LineCircadian ClocksCircadian RhythmCircadian Rhythm Signaling Peptides and ProteinsCryptochromesHEK293 CellsHistone DeacetylasesHumansMaleMiceMice, Inbred C57BLARNTL Transcription FactorsBmal1 protein, mouseCiart protein, mouseCircadian Rhythm Signaling Peptides and ProteinsCry1 protein, mouseCry2 protein, mouseCryptochromesHistone DeacetylasesNr1d1 protein, mouseNr1d2 protein, mouseNuclear Receptor Subfamily 1, Group D, Member 1Receptors, Cytoplasmic and NuclearReceptors, GlucocorticoidRepressor Proteins

Identifiers

PMID24737000
PMCPMC3988006
OpenAlexW2027565749

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.