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      Stochastic Resonance Reveals “Pilot Light” Expression in Mammalian Genes

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      Author(s): *
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      Publication date (Electronic):
      Journal: PLoS ONE
      Publisher: Public Library of Science

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          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.

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          Most cited references17

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          A chromatin landmark and transcription initiation at most promoters in human cells.

          Matthew Guenther, Stuart S. Levine, Laurie A. Boyer … (2007)
          We describe the results of a genome-wide analysis of human cells that suggests that most protein-coding genes, including most genes thought to be transcriptionally inactive, experience transcription initiation. We found that nucleosomes with H3K4me3 and H3K9,14Ac modifications, together with RNA polymerase II, occupy the promoters of most protein-coding genes in human embryonic stem cells. Only a subset of these genes produce detectable full-length transcripts and are occupied by nucleosomes with H3K36me3 modifications, a hallmark of elongation. The other genes experience transcription initiation but show no evidence of elongation, suggesting that they are predominantly regulated at postinitiation steps. Genes encoding most developmental regulators fall into this group. Our results also identify a class of genes that are excluded from experiencing transcription initiation, at which mechanisms that prevent initiation must predominate. These observations extend to differentiated cells, suggesting that transcription initiation at most genes is a general phenomenon in human cells.
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            Model-based analysis of oligonucleotide arrays: expression index computation and outlier detection.

            Jason Wong, Linda C. Li (2001)
            Recent advances in cDNA and oligonucleotide DNA arrays have made it possible to measure the abundance of mRNA transcripts for many genes simultaneously. The analysis of such experiments is nontrivial because of large data size and many levels of variation introduced at different stages of the experiments. The analysis is further complicated by the large differences that may exist among different probes used to interrogate the same gene. However, an attractive feature of high-density oligonucleotide arrays such as those produced by photolithography and inkjet technology is the standardization of chip manufacturing and hybridization process. As a result, probe-specific biases, although significant, are highly reproducible and predictable, and their adverse effect can be reduced by proper modeling and analysis methods. Here, we propose a statistical model for the probe-level data, and develop model-based estimates for gene expression indexes. We also present model-based methods for identifying and handling cross-hybridizing probes and contaminating array regions. Applications of these results will be presented elsewhere.
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              Extensive and divergent circadian gene expression in liver and heart.

              Kai-Florian Storch, Ovidiu Lipan, Igor Leykin … (2002)
              Many mammalian peripheral tissues have circadian clocks; endogenous oscillators that generate transcriptional rhythms thought to be important for the daily timing of physiological processes. The extent of circadian gene regulation in peripheral tissues is unclear, and to what degree circadian regulation in different tissues involves common or specialized pathways is unknown. Here we report a comparative analysis of circadian gene expression in vivo in mouse liver and heart using oligonucleotide arrays representing 12,488 genes. We find that peripheral circadian gene regulation is extensive (> or = 8-10% of the genes expressed in each tissue), that the distributions of circadian phases in the two tissues are markedly different, and that very few genes show circadian regulation in both tissues. This specificity of circadian regulation cannot be accounted for by tissue-specific gene expression. Despite this divergence, the clock-regulated genes in liver and heart participate in overlapping, extremely diverse processes. A core set of 37 genes with similar circadian regulation in both tissues includes candidates for new clock genes and output genes, and it contains genes responsive to circulating factors with circadian or diurnal rhythms.
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                Author and article information

                Contributors
                : Role: Editor
                Journal
                Journal ID (nlm-ta): PLoS ONE
                Journal ID (publisher-id): plos
                Journal ID (pmc): plosone
                Title: PLoS ONE
                Publisher: Public Library of Science (San Francisco, USA )
                ISSN (Electronic): 1932-6203
                Publication date Collection: 2008
                Publication date (Electronic): 26 March 2008
                Volume: 3
                Issue: 3
                Electronic Location Identifier: e1842
                Affiliations
                [1]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
                University of Nottingham, United Kingdom
                Author notes

                Conceived and designed the experiments: AP. Analyzed the data: AP. Contributed reagents/materials/analysis tools: AP. Wrote the paper: AP.

                Article
                Publisher ID: 07-PONE-RA-02692R2
                DOI: 10.1371/journal.pone.0001842
                PMC ID: 2266998
                PubMed ID: 18365000
                SO-VID: 9d5faac9-af8b-433f-b5dd-7f552a94069f
                Copyright © Andrey Ptitsyn. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                History
                Date received : 5 November 2007
                Date accepted : 12 February 2008
                Page count
                Pages: 6
                Categories
                Subject: Research Article
                Subject: Cell Biology/Gene Expression
                Subject: Computational Biology/Metabolic Networks
                Subject: Computational Biology/Signaling Networks
                Subject: Computational Biology/Systems Biology

                ScienceOpen disciplines: Uncategorized
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                ScienceOpen disciplines: Uncategorized

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