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Related Experiment Video

Updated: May 21, 2026

A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq
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Published on: May 28, 2021

Frequency-based time-series gene expression recomposition using PRIISM.

Bruce A Rosa1, Yuhua Jiao, Sookyung Oh

  • 1Department of Biology, Lakehead University, ON, Canada.

BMC Systems Biology
|June 19, 2012
PubMed
Summary
This summary is machine-generated.

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The PRIISM algorithm separates plant gene expression patterns disrupted by stress and circadian rhythms. This novel approach reduces false positives in cold-response gene discovery and aids circadian studies.

Area of Science:

  • Plant biology
  • Genomics
  • Bioinformatics

Background:

  • Circadian rhythms regulate up to 31% of the Arabidopsis genome.
  • Biotic and abiotic stresses disrupt circadian pathways, complicating gene expression analysis.
  • Existing methods struggle with clock pattern mismatches in fold change statistics.

Purpose of the Study:

  • To introduce the Pattern Recomposition for the Isolation of Independent Signals in Microarray data (PRIISM) algorithm.
  • To separate gene expression patterns influenced by treatment responses and circadian clock disruptions.
  • To improve gene discovery methods in plants under stress.

Main Methods:

  • Utilized Fourier transform to project time-series microarray data into the frequency domain.
  • Separated frequency spectrum into treatment, circadian clock, and noise components.

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Last Updated: May 21, 2026

A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq
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Published on: May 28, 2021

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  • Reconstructed isolated gene expression patterns by projecting spectral components back to the expression domain.

    • Main Results:

    • PRIISM application on Arabidopsis cold treatment data yielded fewer false positives than original methods.
    • Identified the 26-hour timepoint as optimal for distinguishing cold-response genes.
    • Discovered six novel cold-response genes and provided data for circadian clock studies.

    Conclusions:

    • PRIISM offers a novel solution for analyzing plant gene expression disrupted by circadian rhythms and stress.
    • The algorithm can enhance existing gene expression analysis approaches.
    • PRIISM is adaptable to any organism with genome-wide gene expression oscillations.