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Extensive and divergent circadian gene expression in liver and heart

Author

Listed:
  • Kai-Florian Storch

    (Northeastern University)

  • Ovidiu Lipan

    (Harvard School of Public Health, Northeastern University)

  • Igor Leykin

    (Harvard School of Public Health, Northeastern University)

  • N. Viswanathan

    (Northeastern University)

  • Fred C. Davis

    (Northeastern University)

  • Wing H. Wong

    (Harvard School of Public Health, Northeastern University
    Harvard University)

  • Charles J. Weitz

    (Northeastern University)

Abstract

Many mammalian peripheral tissues have circadian clocks1,2,3,4; endogenous oscillators that generate transcriptional rhythms thought to be important for the daily timing of physiological processes5,6. The extent of circadian gene regulation in peripheral tissues is unclear, and to what degree circadian regulation in different tissues involves common or specialized pathways is unknown. Here we report a comparative analysis of circadian gene expression in vivo in mouse liver and heart using oligonucleotide arrays representing 12,488 genes. We find that peripheral circadian gene regulation is extensive (≥8–10% of the genes expressed in each tissue), that the distributions of circadian phases in the two tissues are markedly different, and that very few genes show circadian regulation in both tissues. This specificity of circadian regulation cannot be accounted for by tissue-specific gene expression. Despite this divergence, the clock-regulated genes in liver and heart participate in overlapping, extremely diverse processes. A core set of 37 genes with similar circadian regulation in both tissues includes candidates for new clock genes and output genes, and it contains genes responsive to circulating factors with circadian or diurnal rhythms.

Suggested Citation

  • Kai-Florian Storch & Ovidiu Lipan & Igor Leykin & N. Viswanathan & Fred C. Davis & Wing H. Wong & Charles J. Weitz, 2002. "Extensive and divergent circadian gene expression in liver and heart," Nature, Nature, vol. 417(6884), pages 78-83, May.
    • Handle: RePEc:nat:nature:v:417:y:2002:i:6884:d:10.1038_nature744
    DOI: 10.1038/nature744
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    Cited by:

    1. Cheemeng Tan & Robert Phillip Smith & Ming-Chi Tsai & Russell Schwartz & Lingchong You, 2014. "Phenotypic Signatures Arising from Unbalanced Bacterial Growth," PLOS Computational Biology, Public Library of Science, vol. 10(8), pages 1-10, August.
    2. Mastrantonio, Gianluca, 2018. "The joint projected normal and skew-normal: A distribution for poly-cylindrical data," Journal of Multivariate Analysis, Elsevier, vol. 165(C), pages 14-26.
    3. Antía González-Vila & María Luengo-Mateos & María Silveira-Loureiro & Pablo Garrido-Gil & Nataliia Ohinska & Marco González-Domínguez & Jose Luis Labandeira-García & Cristina García-Cáceres & Miguel L, 2023. "Astrocytic insulin receptor controls circadian behavior via dopamine signaling in a sexually dimorphic manner," Nature Communications, Nature, vol. 14(1), pages 1-21, December.
    4. Florian R L Meyer & Heinrich Grausgruber & Claudia Binter & Georg E Mair & Christian Guelly & Claus Vogl & Ralf Steinborn, 2013. "Cross-Platform Microarray Meta-Analysis for the Mouse Jejunum Selects Novel Reference Genes with Highly Uniform Levels of Expression," PLOS ONE, Public Library of Science, vol. 8(5), pages 1-15, May.
    5. Kevin P Keegan & Suraj Pradhan & Ji-Ping Wang & Ravi Allada, 2007. "Meta-Analysis of Drosophila Circadian Microarray Studies Identifies a Novel Set of Rhythmically Expressed Genes," PLOS Computational Biology, Public Library of Science, vol. 3(11), pages 1-1, November.
    6. Andrey A Ptitsyn & Sanjin Zvonic & Jeffrey M Gimble, 2007. "Digital Signal Processing Reveals Circadian Baseline Oscillation in Majority of Mammalian Genes," PLOS Computational Biology, Public Library of Science, vol. 3(6), pages 1-7, June.
    7. Sarah Gehlert & Mark Clanton & on behalf of the Shift Work and Breast Cancer Strategic Advisory Group, 2020. "Shift Work and Breast Cancer," IJERPH, MDPI, vol. 17(24), pages 1-8, December.
    8. Alan L Hutchison & Mark Maienschein-Cline & Andrew H Chiang & S M Ali Tabei & Herman Gudjonson & Neil Bahroos & Ravi Allada & Aaron R Dinner, 2015. "Improved Statistical Methods Enable Greater Sensitivity in Rhythm Detection for Genome-Wide Data," PLOS Computational Biology, Public Library of Science, vol. 11(3), pages 1-29, March.
    9. Andrey A Ptitsyn & Sanjin Zvonic & Steven A Conrad & L Keith Scott & Randall L Mynatt & Jeffrey M Gimble, 2006. "Circadian Clocks Are Resounding in Peripheral Tissues," PLOS Computational Biology, Public Library of Science, vol. 2(3), pages 1-10, March.
    10. Ian C McDowell & Dinesh Manandhar & Christopher M Vockley & Amy K Schmid & Timothy E Reddy & Barbara E Engelhardt, 2018. "Clustering gene expression time series data using an infinite Gaussian process mixture model," PLOS Computational Biology, Public Library of Science, vol. 14(1), pages 1-27, January.

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