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Related Concept Videos

Circadian Rhythms and Gene Regulation02:19

Circadian Rhythms and Gene Regulation

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The biological clock is involved in many aspects of regulating complex physiology in all animals. It was in 1935 when German zoologists, Hans Kalmus and Erwin Bünning, discovered the existence of circadian rhythm in Drosophila melanogaster. However, the internal molecular mechanisms behind the circadian clock remained a mystery until 1984, when Jeffrey C. Hall, Michael Rosbash, and Michael W. Young discovered the expression of the Per gene oscillating over a 24-hour cycle. In subsequent...
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Related Experiment Video

Updated: Jul 24, 2025

Parallel Measurement of Circadian Clock Gene Expression and Hormone Secretion in Human Primary Cell Cultures
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Circadian transcriptome processing and analysis: a workflow for muscle stem cells.

Valentina Sica1, Oleg Deryagin1, Jacob G Smith1

  • 1Department of Medicine and Life Sciences, Universitat Pompeu Fabra, Barcelona, Spain.

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|July 3, 2023
PubMed
Summary
This summary is machine-generated.

This study details isolating muscle stem cells for RNA sequencing to analyze circadian rhythms. It introduces bioinformatics tools for understanding how the circadian clock controls gene transcription in tissues.

Keywords:
bioinformaticscircadian rhythmsmuscle stem cellssatellite cells

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Area of Science:

  • Chronobiology
  • Molecular Biology
  • Genomics

Background:

  • Circadian rhythms are endogenous biological processes synchronized with the 24-hour light-dark cycle.
  • Understanding circadian clock control of transcription is crucial for various biological functions.
  • Bioinformatic tools have advanced the identification of daily oscillating transcripts.

Purpose of the Study:

  • To outline a workflow for isolating muscle stem cells for RNA sequencing in circadian studies.
  • To introduce bioinformatic approaches for analyzing circadian transcriptomes.
  • To facilitate research into tissue-specific circadian gene regulation.

Main Methods:

  • Isolation of muscle stem cells from experimental models.
  • RNA sequencing (RNA-seq) for transcriptome-wide analysis.
  • Application of bioinformatic pipelines for circadian data analysis.

Main Results:

  • A standardized protocol for muscle stem cell isolation in circadian experiments.
  • Identification of key bioinformatic tools for analyzing oscillating transcripts.
  • Demonstration of feasibility for studying circadian gene expression in muscle stem cells.

Conclusions:

  • The described workflow enables robust analysis of circadian transcriptomes in muscle stem cells.
  • This approach supports the investigation of circadian clock mechanisms in tissue regeneration and homeostasis.
  • The study provides a foundation for further research into the role of circadian rhythms in muscle biology.