Pattern Recomposition for the Isolation of Independent Signals in Microarrays
Introduction to PRIISM
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.
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.
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.
Figure 1: PRIISM separates (A) the original gene expression patterns under control and treatment conditions (used to calculate the fold change pattern) into (B) treatment-frequency, clock-frequency and noise-frequency gene expression patterns.
Figure 2: The workflow of the PRIISM algorithm. (A) Time-series gene expression data for a 24-hour time window is prepared for input. (B) The Fourier Transform is performed on all genes. (C) Genes identified as core clock components are used to define the circadian clock frequency range (CCFR) and clock weight vector. (D) Frequency spectra for all genes are split into treatment-, clock- and noise-frequency components according to the CCFR; Clock components are modulated by the clock weight vector. (E) The inverse Fourier transform reconstructs the separate frequency components to (F) recomposed gene expression data for treatment, clock and noise frequency components.
The "Download" section of this website contains links to download the PRIISM software as well as sample data. Details on the PRIISM publication can be found in the "About" section