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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...
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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.
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Related Experiment Video

Updated: Sep 1, 2025

Metabolic Labeling of Newly Transcribed RNA for High Resolution Gene Expression Profiling of RNA Synthesis, Processing and Decay in Cell Culture
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Metabolic Labeling of Newly Transcribed RNA for High Resolution Gene Expression Profiling of RNA Synthesis, Processing and Decay in Cell Culture

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Quantifying the phenotypic information in mRNA abundance.

Evan Maltz1,2, Roy Wollman1,2,3

  • 1Department of Chemistry and Biochemistry, UCLA, Los Angeles, CA, USA.

Molecular Systems Biology
|August 15, 2022
PubMed
Summary
This summary is machine-generated.

This study quantifies how mRNA levels predict cellular behavior, finding that gene expression explains a significant portion of calcium signaling dynamics. Redundancy among genes is high, with smaller gene sets retaining substantial information.

Keywords:
cellular heterogeneitygene expressioninformation theorymutual informationsignaling dynamics

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Assessment of Selective mRNA Translation in Mammalian Cells by Polysome Profiling
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Area of Science:

  • Systems Biology
  • Computational Biology
  • Molecular Biology

Background:

  • Understanding the link between gene expression (mRNA abundance) and cellular function (phenotypes) is crucial in biology.
  • Multimodal single-cell technologies offer new ways to study gene contributions to phenotypes.

Purpose of the Study:

  • To quantify the information content of mRNA abundance for a specific cellular phenotype.
  • To determine how much information about calcium signaling dynamics is encoded in the expression of genes within the calcium signaling network.

Main Methods:

  • Applied an information theory approach to analyze multimodal single-cell data.
  • Measured mRNA expression of 83 genes in the calcium (Ca2+) signaling network and the dynamic Ca2+ response in the same cells.

Main Results:

  • The expression levels of 83 genes explained approximately 60% of the calcium signal entropy.
  • Individual genes contributed an average of 17% to the information content, indicating significant gene redundancy.
  • A set of 53 genes was estimated to contain 54% of the information about Ca2+ signaling.

Conclusions:

  • This study provides the first direct quantification of information about complex cellular phenotypes present in mRNA abundance measurements.
  • mRNA expression levels contain substantial predictive information about downstream cellular responses like calcium signaling.