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Related Concept Videos

Circadian Rhythms and Gene Regulation02:19

Circadian Rhythms and Gene Regulation

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 years,...
Circadian Rhythms and Gene Regulation02:19

Circadian Rhythms and Gene Regulation

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 years,...
Biological Clocks and Seasonal Responses02:45

Biological Clocks and Seasonal Responses

The circadian—or biological—clock is an intrinsic, timekeeping, molecular mechanism that allows plants to coordinate physiological activities over 24-hour cycles called circadian rhythms. Photoperiodism is a collective term for the biological responses of plants to variations in the relative lengths of dark and light periods. The period of light-exposure is called the photoperiod.
Regulation of Expression at Multiple Steps01:23

Regulation of Expression at Multiple Steps

The gene expression in cells is regulated at different stages: (i) transcription, (ii) RNA processing, (iii) RNA localization, and (iv) translation. Transcriptional regulation is mediated by regulatory proteins such as transcription factors, activators, or repressors—these control gene expression by initiating or inhibiting the transcription of genes. Once a precursor or pre-mRNA is produced, it undergoes post-transcriptional modification, including 5' capping, splicing, and the addition of a...
Regulation of Expression Occurs at Multiple Steps02:24

Regulation of Expression Occurs at Multiple Steps

Gene expression can be regulated at almost every step from gene to protein. Transcription is the step that is most commonly regulated. This involves the binding of proteins to short regulatory sequences on the DNA. This association can either promote or inhibit the transcription of a gene associated with the respective sequence.
Transcription results in the generation of precursor (pre-mRNA) that consists of both exons and introns, which needs further processing before being translated to a...
Regulation of Expression Occurs at Multiple Steps02:24

Regulation of Expression Occurs at Multiple Steps

Gene expression can be regulated at almost every step from gene to protein. Transcription is the step that is most commonly regulated. This involves the binding of proteins to short regulatory sequences on the DNA. This association can either promote or inhibit the transcription of a gene associated with the respective sequence.
Transcription results in the generation of precursor (pre-mRNA) that consists of both exons and introns, which needs further processing before being translated to a...

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Related Experiment Video

Updated: May 17, 2026

Monitoring Cell-autonomous Circadian Clock Rhythms of Gene Expression Using Luciferase Bioluminescence Reporters
10:38

Monitoring Cell-autonomous Circadian Clock Rhythms of Gene Expression Using Luciferase Bioluminescence Reporters

Published on: September 27, 2012

[Analysis of gene expression data regulated by clock-genes: methodological approach and optimization].

M-L Vuillaume1, F Kwiatkowski, N Uhrhammer

  • 1Laboratoire d'oncologie moléculaire, centre Jean-Perrin, 58, rue Montalembert, 63011 Clermont-Ferrand, France.

Pathologie-Biologie
|November 6, 2012
PubMed
Summary

This study introduces a new method to correct for spurious correlations in microarray data, improving the identification of genes related to conditions like BRCA1 mutations. The approach helps uncover true biological signals obscured by noise, enhancing gene discovery.

Keywords:
CircadianCircadienClock-geneCorrelationCorrélationGène du rythmeMethodologyMéthodologieTranscriptomTranscriptome

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A User-friendly and Powerful R Analysis of Large-scale Datasets

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Parallel Measurement of Circadian Clock Gene Expression and Hormone Secretion in Human Primary Cell Cultures

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A User-friendly and Powerful R Analysis of Large-scale Datasets

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Area of Science:

  • Genomics
  • Bioinformatics
  • Systems Biology

Context:

  • Microarray analysis often suffers from numerous correlations, leading to false discoveries and the potential loss of subtly or indirectly related genes.
  • Existing methods to control false discovery rates may be overly stringent, discarding potentially relevant genes with weak or indirect associations.
  • Circadian rhythm introduces complex correlations in gene expression data, complicating the identification of true biological signals.

Purpose:

  • To develop a straightforward methodology for correcting spurious correlations in microarray data without discarding weak but genuine biological signals.
  • To evaluate the effectiveness of this methodology in identifying genes associated with BRCA1 mutation status, considering circadian rhythm effects.
  • To refine gene expression analysis by accounting for known biological correlation networks, such as the circadian system.

Summary:

  • A novel method was applied to microarray data to distinguish BRCA1 mutation carriers, addressing correlations from circadian rhythms.
  • Two strategies were employed: dividing or multiplying gene expression by a period gene (e.g., Per1) based on correlation sign.
  • This approach successfully recovered BRCA1-interacting proteins missed in initial analyses, demonstrating its utility in gene discovery.

Impact:

  • The proposed methodology effectively corrects for spurious correlations, improving the accuracy of gene expression analysis in microarray studies.
  • It enables the recovery of biologically relevant genes, including those with indirect or weak associations, that might otherwise be missed.
  • This simple and adaptable method can be valuable for various studies involving well-characterized biological correlation networks, enhancing the discovery of disease-related genes.