Noise-driven cellular heterogeneity in circadian periodicity

Proc Natl Acad Sci U S A. 2020 May 12;117(19):10350-10356. doi: 10.1073/pnas.1922388117. Epub 2020 May 1.


Nongenetic cellular heterogeneity is associated with aging and disease. However, the origins of cell-to-cell variability are complex and the individual contributions of different factors to total phenotypic variance are still unclear. Here, we took advantage of clear phenotypic heterogeneity of circadian oscillations in clonal cell populations to investigate the underlying mechanisms of cell-to-cell variability. Using a fully automated tracking and analysis pipeline, we examined circadian period length in thousands of single cells and hundreds of clonal cell lines and found that longer circadian period is associated with increased intercellular heterogeneity. Based on our experimental results, we then estimated the contributions of heritable and nonheritable factors to this variation in circadian period length using a variance partitioning model. We found that nonheritable noise predominantly drives intercellular circadian period variation in clonal cell lines, thereby revealing a previously unrecognized link between circadian oscillations and intercellular heterogeneity. Moreover, administration of a noise-enhancing drug reversibly increased both period length and variance. These findings suggest that circadian period may be used as an indicator of cellular noise and drug screening for noise control.

Keywords: circadian oscillation; heterogeneity/variance; period; single-cell imaging; transcriptional noise.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Cells, Cultured
  • Circadian Clocks*
  • Circadian Rhythm*
  • Luminescent Measurements
  • Mice
  • Models, Biological*
  • Mouse Embryonic Stem Cells / cytology
  • Mouse Embryonic Stem Cells / metabolism*
  • Period Circadian Proteins / genetics
  • Period Circadian Proteins / metabolism*
  • Single-Cell Analysis / methods*
  • Stochastic Processes


  • Period Circadian Proteins