Frequency-based time-series gene expression recomposition using PRIISM

Bruce A. Rosa, Yuhua Jiao, Sookyung Oh, Beronda L. Montgomery, Wensheng Qin, Jin Chen

Research output: Contribution to journalArticlepeer-review

9 Scopus citations


Background: Circadian rhythm pathways influence the expression patterns of as much as 31% of the Arabidopsis genome through complicated interaction pathways, and have been found to be significantly disrupted by biotic and abiotic stress treatments, complicating treatment-response gene discovery methods due to clock pattern mismatches in the fold change-based statistics. The PRIISM (Pattern Recomposition for the Isolation of Independent Signals in Microarray data) algorithm outlined in this paper is designed to separate pattern changes induced by different forces, including treatment-response pathways and circadian clock rhythm disruptions.Results: Using the Fourier transform, high-resolution time-series microarray data is projected to the frequency domain. By identifying the clock frequency range from the core circadian clock genes, we separate the frequency spectrum to different sections containing treatment-frequency (representing up- or down-regulation by an adaptive treatment response), clock-frequency (representing the circadian clock-disruption response) and noise-frequency components. Then, we project the components' spectra back to the expression domain to reconstruct isolated, independent gene expression patterns representing the effects of the different influences.By applying PRIISM on a high-resolution time-series Arabidopsis microarray dataset under a cold treatment, we systematically evaluated our method using maximum fold change and principal component analyses. The results of this study showed that the ranked treatment-frequency fold change results produce fewer false positives than the original methodology, and the 26-hour timepoint in our dataset was the best statistic for distinguishing the most known cold-response genes. In addition, six novel cold-response genes were discovered. PRIISM also provides gene expression data which represents only circadian clock influences, and may be useful for circadian clock studies.Conclusion: PRIISM is a novel approach for overcoming the problem of circadian disruptions from stress treatments on plants. PRIISM can be integrated with any existing analysis approach on gene expression data to separate circadian-influenced changes in gene expression, and it can be extended to apply to any organism with regular oscillations in gene expression patterns across a large portion of the genome.

Original languageEnglish
Article number69
JournalBMC Systems Biology
StatePublished - Jun 15 2012

Bibliographical note

Funding Information:
We thank Dr. Michael Thomashow and Dr. Eva Farré for their feedback and helpful advice. This project has been funded by the U.S. Department of Energy (Chemical Sciences, Geosciences and Biosciences Division, grant no. DE–FG02–91ER20021 to J.C. and B.L.M), The National Science Foundation (grant no. MCB-0919100 to B.L.M.), the Natural Sciences and Engineering Research Council of Canada (NSERC) through a Post-Graduate Scholarship to B.R. and NSERC Collaborative Research and Development grant to W.Q., and Ontario Research Chair funding to W.Q.

ASJC Scopus subject areas

  • Structural Biology
  • Modeling and Simulation
  • Molecular Biology
  • Computer Science Applications
  • Applied Mathematics


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