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Stochastic resonance reveals "pilot light" expression in mammalian genes.

Ptitsyn A - PLoS ONE (2008)

Bottom Line: This effect is corroborated by the analysis of oscillating gene expression in mouse (M. musculus) and yeast (S. cerevisae).Most genes usually considered silent are in fact expressed at a very low level.Stochastic resonance can be applied to detect changes in expression pattern of low-expressed genes as well as for the validation of the probe performance in microarrays.

View Article: PubMed Central - PubMed

Affiliation: Center for Bioinformatics, Department of Microbiology, Immunology and Pathology, College of Veterinary and Biomedical Sciences, Colorado State University, Fort Collins, Colorado, United States of America. Andrey.Ptitsyn@colostate.edu

ABSTRACT

Background: Microarrays are widely used for estimation of expression of thousands of genes in a biological sample. The resolution ability of this method is limited by the background noise. Low expressed genes are detected with insufficient reliability and expression of many genes is never detected at all.

Methodology/principal findings: We have applied the principles of stochastic resonance to detect expression of genes from microarray signals below the background noise level. We report the periodic pattern detected in genes called "Absent" by traditional analysis. The pattern is consistent with expression of the conventionally detected genes and specific to the tissue of origin. This effect is corroborated by the analysis of oscillating gene expression in mouse (M. musculus) and yeast (S. cerevisae).

Conclusion/significance: Most genes usually considered silent are in fact expressed at a very low level. Stochastic resonance can be applied to detect changes in expression pattern of low-expressed genes as well as for the validation of the probe performance in microarrays.

Show MeSH
Circadian expression pattern in transcripts never called present.In spite of being considered silent most genes called absent are expressed in a daily changing pattern of elevated (red) and lowered expression level (green) over the 48h period of alternating light and darkness (bottom), consistent with circadian pattern in highly expressed genes. The plot shows four phase groups (roman numbers) in four murine tissues (data from [10] and [12]). On each pane expression profiles are stacked in order of autocorrelation with 24h lag (Ac, vertical axis).
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pone-0001842-g001: Circadian expression pattern in transcripts never called present.In spite of being considered silent most genes called absent are expressed in a daily changing pattern of elevated (red) and lowered expression level (green) over the 48h period of alternating light and darkness (bottom), consistent with circadian pattern in highly expressed genes. The plot shows four phase groups (roman numbers) in four murine tissues (data from [10] and [12]). On each pane expression profiles are stacked in order of autocorrelation with 24h lag (Ac, vertical axis).

Mentions: The heat map plot in Figure 1 shows the pattern of circadian expression in approximately 30% of all genes interrogated by the Affymetrix mouse expression microarray. At first glance the pattern of two red (zenith) and two green (nadirs) areas over two-day period is remarkably similar to the previously published circadian expression patterns in mice [10],[14]. However in this case none of the genes selected for analysis has been called “Present” even once at any of the 12 time points. This effect is not specific to a particular tissue and observed in all mouse and yeast data sets considered in this paper.


Stochastic resonance reveals "pilot light" expression in mammalian genes.

Ptitsyn A - PLoS ONE (2008)

Circadian expression pattern in transcripts never called present.In spite of being considered silent most genes called absent are expressed in a daily changing pattern of elevated (red) and lowered expression level (green) over the 48h period of alternating light and darkness (bottom), consistent with circadian pattern in highly expressed genes. The plot shows four phase groups (roman numbers) in four murine tissues (data from [10] and [12]). On each pane expression profiles are stacked in order of autocorrelation with 24h lag (Ac, vertical axis).
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2266998&req=5

pone-0001842-g001: Circadian expression pattern in transcripts never called present.In spite of being considered silent most genes called absent are expressed in a daily changing pattern of elevated (red) and lowered expression level (green) over the 48h period of alternating light and darkness (bottom), consistent with circadian pattern in highly expressed genes. The plot shows four phase groups (roman numbers) in four murine tissues (data from [10] and [12]). On each pane expression profiles are stacked in order of autocorrelation with 24h lag (Ac, vertical axis).
Mentions: The heat map plot in Figure 1 shows the pattern of circadian expression in approximately 30% of all genes interrogated by the Affymetrix mouse expression microarray. At first glance the pattern of two red (zenith) and two green (nadirs) areas over two-day period is remarkably similar to the previously published circadian expression patterns in mice [10],[14]. However in this case none of the genes selected for analysis has been called “Present” even once at any of the 12 time points. This effect is not specific to a particular tissue and observed in all mouse and yeast data sets considered in this paper.

Bottom Line: This effect is corroborated by the analysis of oscillating gene expression in mouse (M. musculus) and yeast (S. cerevisae).Most genes usually considered silent are in fact expressed at a very low level.Stochastic resonance can be applied to detect changes in expression pattern of low-expressed genes as well as for the validation of the probe performance in microarrays.

View Article: PubMed Central - PubMed

Affiliation: Center for Bioinformatics, Department of Microbiology, Immunology and Pathology, College of Veterinary and Biomedical Sciences, Colorado State University, Fort Collins, Colorado, United States of America. Andrey.Ptitsyn@colostate.edu

ABSTRACT

Background: Microarrays are widely used for estimation of expression of thousands of genes in a biological sample. The resolution ability of this method is limited by the background noise. Low expressed genes are detected with insufficient reliability and expression of many genes is never detected at all.

Methodology/principal findings: We have applied the principles of stochastic resonance to detect expression of genes from microarray signals below the background noise level. We report the periodic pattern detected in genes called "Absent" by traditional analysis. The pattern is consistent with expression of the conventionally detected genes and specific to the tissue of origin. This effect is corroborated by the analysis of oscillating gene expression in mouse (M. musculus) and yeast (S. cerevisae).

Conclusion/significance: Most genes usually considered silent are in fact expressed at a very low level. Stochastic resonance can be applied to detect changes in expression pattern of low-expressed genes as well as for the validation of the probe performance in microarrays.

Show MeSH