Cited by 37Circadian rhythm and melatoninSleep and Work-Related FatigueSleep and Wakefulness Research

Exploiting human and mouse transcriptomic data: Identification of circadian genes and pathways influencing health

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Laing, Emma E., Johnston, Jonathan D., Möller‐Levet, Carla S., Bucca, Giselda, Smith, Colin P., Dijk, Derk‐Jan, Archer, Simon N.·2015·BioEssays

Abstract

The power of the application of bioinformatics across multiple publicly available transcriptomic data sets was explored. Using 19 human and mouse circadian transcriptomic data sets, we found that NR1D1 and NR1D2 which encode heme-responsive nuclear receptors are the most rhythmic transcripts across sleep conditions and tissues suggesting that they are at the core of circadian rhythm generation. Analyzes of human transcriptomic data show that a core set of transcripts related to processes including immune function, glucocorticoid signalling, and lipid metabolism is rhythmically expressed independently of the sleep-wake cycle. We also identify key transcripts associated with transcription and translation that are disrupted by sleep manipulations, and through network analysis identify putative mechanisms underlying the adverse health outcomes associated with sleep disruption, such as diabetes and cancer. Comparative bioinformatics applied to existing and future data sets will be a powerful tool for the identification of core circadian- and sleep-dependent molecules.

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  • The SCN influence sleep-wake cycles that themselves influence circadian rhythmicity and partially dictate feed-fast behavior, which is believed to be a key synchronizer of peripheral clocks.

    “Furthermore, the SCN influence sleep-wake cycles that themselves influence circadian rhythmicity (17) and partially dictate feed-fast behavior, which is believed to be a key synchronizer of peripheral clocks (see below).”
  • Analysis of multiple human and mouse transcriptomic data sets highlights a close linkage between circadian rhythms and metabolic gene expression.

    “Analysis of multiple human and mouse transcriptomic data sets highlights the close linkage between circadian rhythms and metabolic gene expression (17).”

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Authors
Laing, E. E., Johnston, J. D., Möller‐Levet, C. S., Bucca, G., Smith, C. P., Dijk, D., & Archer, S. N.
Affiliations
University of Surrey (GB)
Corresponding author
Archer, Simon N.
Venue
BioEssays
Publisher
Wiley
Published
2015-03-14
Volume
37
Issue
5
Pages
544-556
ISSN
  • 0265-9247 (ISSN-L)
  • 1521-1878
OpenAlex
W2018297674
Cited by
37
References
63
Citations by year
2026: 1 · 2025: 3 · 2024: 2 · 2023: 2 · 2022: 4 · 2021: 2 · 2020: 1 · 2019: 5 · 2018: 5 · 2017: 4 · 2016: 6 · 2015: 2
FWCI
0.62
Type
journal article
Language
en
Open access
Locations
  • BioEssays (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • University of Brighton Repository (University of Brighton) (publishedVersion, cc-by)
  • Surrey Research Insight Open Access (The University of Surrey) (submittedVersion)
Funders
  • Biotechnology and Biological Sciences Research Council (BB/F022883)
  • US Air Force Office of Scientific Research (FA9550-08-1-0080)
Topics
  • Life Sciences › Neuroscience › Endocrine and Autonomic Systems › Circadian rhythm and melatonin
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Sleep and Work-Related Fatigue
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Sleep and Wakefulness Research
Keywords
circadian rhythm, circadian genes, NR1D1, NR1D2, rhythmic gene expression, sleep-wake cycle, sleep disruption, glucocorticoid signaling, lipid metabolism, immune function, transcription and translation, diabetes mellitus, cancer, comparative transcriptomics
MeSH terms
Animals, Circadian Rhythm, Humans, Nuclear Proteins, Sleep, Mice, Circadian Clocks

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