Evidence map›Paper›PMID 33318596›Full record

ArticleScientific reports2020

Genome-wide correlation analysis to identify amplitude regulators of circadian transcriptome output.

Evan S Littleton, Madison L Childress, Michaela L Gosting, Ayana N Jackson, Shihoko Kojima

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
0.7field-weighted citation impact, top 35% 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

14 citing papers in PubMed, 13 citations in OpenAlex.

  1. Article
  2. Review
  3. HairTime: A noninvasive assay for estimating circadian phase from a single hair sample.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  4. Article
  5. Review
  6. Article
  7. Review
  8. Coordination of rhythmic RNA synthesis and degradation orchestrates 24- and 12-h RNA expression patterns in mouse fibroblasts.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. Review
  14. Natural antisense transcript ofGenes & development · 2021
    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

5 authors at 1 institution in 1 country.

Evan S LittletonDepartment of Biological Sciences, Fralin Life Sciences Institute, Virginia Tech, Blacksburg, VA, USA.
Madison L ChildressDepartment of Biological Sciences, Fralin Life Sciences Institute, Virginia Tech, Blacksburg, VA, USA.
Michaela L GostingDepartment of Biological Sciences, Fralin Life Sciences Institute, Virginia Tech, Blacksburg, VA, USA.
Ayana N JacksonDepartment of Biological Sciences, Fralin Life Sciences Institute, Virginia Tech, Blacksburg, VA, USA.
Shihoko KojimaDepartment of Biological Sciences, Fralin Life Sciences Institute, Virginia Tech, Blacksburg, VA, USA. skojima@vt.edu.
Virginia Tech · US

Funding

Functional analysis of a non-coding RNA in the mammalian circadian clock systemR01GM126223 · NIGMS · VIRGINIA POLYTECHNIC INST AND ST UNIV · PI KOJIMA, SHIHOKO · 2018 to 2022
$1.7M
NIGMS NIH HHS R01 GM126223NIH HHS R01GM126223
6 · The paper itself

Abstract

Cell-autonomous circadian system, consisting of core clock genes, generates near 24-h rhythms and regulates the downstream rhythmic gene expression. While it has become clear that the percentage of rhythmic genes varies among mouse tissues, it remains unclear how this variation can be generated, particularly when the clock machinery is nearly identical in all tissues. In this study, we sought to characterize circadian transcriptome datasets that are publicly available and identify the critical component(s) involved in creating this variation. We found that the relative amplitude of 13 genes and the average level of 197 genes correlated with the percentage of cycling genes. Of those, the correlation of Rorc in both relative amplitude and the average level was one of the strongest. In addition, the level of Per2AS, a novel non-coding transcript that is expressed at the Period 2 locus, was also linearly correlated, although with a much lesser degree compared to Rorc. Overall, our study provides insight into how the variation in the percentage of clock-controlled genes can be generated in mouse tissues and suggests that Rorc and potentially Per2AS are involved in regulating the amplitude of circadian transcriptome output.

Indexed as

Databases, Nucleic AcidGene Expression ProfilingAnimalsCircadian RhythmGene Expression RegulationGenome-Wide Association StudyPapio anubisTranscriptome

Identifiers

PMID33318596
PMCPMC7736363
OpenAlexW3111362673

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Registered trials

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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.