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Differential rhythmicity: detecting altered rhythmicity in biological data.

Paul F Thaben1, Pål O Westermark1

  • 1Institute for Theoretical Biology, Charité - Universitätsmedizin Berlin, D-10115 Berlin, Germany.

Bioinformatics (Oxford, England)
|May 22, 2016
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Summary

New methods reveal how light-dark cycles alter circadian rhythms in mouse liver gene expression. This differential rhythmicity analysis highlights immune system involvement and is available as the R package DODR.

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Area of Science:

  • Biological rhythms are crucial for cell physiology, including gene expression.
  • Investigating rhythmicity differences across conditions or genotypes offers insights into biological mechanisms and functions.

Background:

  • Comparing biological rhythms under varying conditions or genotypes is common in biological research.
  • Understanding alterations in rhythmicity is key to deciphering cellular processes.

Purpose of the Study:

  • To present and benchmark statistical and computational methods for differential rhythmicity analysis.
  • To detect changes in rhythm amplitude, phase, and signal-to-noise ratio between experimental groups.
  • To analyze circadian rhythms in mouse liver mRNA expression under different lighting conditions.

Main Methods:

  • Development and benchmarking of statistical and computational methods for differential rhythmicity analysis.
  • Application of these methods to compare circadian rhythms in mouse liver mRNA expression.
  • Analysis of changes in rhythm amplitude, phase, and signal-to-noise ratio.

Main Results:

  • Differential rhythmicity analysis revealed widespread and reproducible increases in circadian rhythm amplitude in mice under light-dark cycles compared to constant darkness.
  • Further analysis indicated the involvement of the immune system in mediating the effects of ambient light-dark cycles on rhythmic transcriptional activities.
  • The developed methods are suitable for genome-wide and proteome-wide studies and provide rigorous P-values.

Conclusions:

  • The study introduces robust methods for analyzing differential rhythmicity.
  • The findings suggest a significant role for the immune system in mediating light-dark cycle effects on circadian gene expression.
  • The methods are implemented in the R software package DODR for broader accessibility.