IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0097734.html
   My bibliography  Save this article

Striking Differences between Knockout and Wild-Type Mice in Global Gene Expression Variability

Author

Listed:
  • Satish A Eraly

Abstract

Microarray analyses of gene knockouts have traditionally focused on the identification of genes whose mean expression is different in knockout and wild-type mice. However, recent work suggests that changes in the variability of gene expression can have important phenotypic consequences as well. Here, in an unbiased sample of publicly available microarray data on gene expression in various knockouts, highly significant differences from wild-type (either increases or decreases) are noted in the gene expression coefficients of variation (CVs) of virtually every knockout considered. Examination of the distribution of gene-by-gene CV differences indicates that these findings are not attributable to a few outlier genes, but rather to broadly increased or decreased CV in the various knockouts over all the (tens of thousands of) transcripts assayed. These global differences in variability may reflect either authentic biological effects of the knockouts or merely experimental inconsistencies. However, regardless of the underlying explanation, the variability differences are of importance as they will influence both the statistical detection of gene expression changes and, potentially, the knockout phenotype itself.

Suggested Citation

  • Satish A Eraly, 2014. "Striking Differences between Knockout and Wild-Type Mice in Global Gene Expression Variability," PLOS ONE, Public Library of Science, vol. 9(5), pages 1-7, May.
  • Handle: RePEc:plo:pone00:0097734
    DOI: 10.1371/journal.pone.0097734
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0097734
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0097734&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0097734?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Arjun Raj & Scott A. Rifkin & Erik Andersen & Alexander van Oudenaarden, 2010. "Variability in gene expression underlies incomplete penetrance," Nature, Nature, vol. 463(7283), pages 913-918, February.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sarah R. Fausett & Asma Sandjak & Bénédicte Billard & Christian Braendle, 2023. "Higher-order epistasis shapes natural variation in germ stem cell niche activity," Nature Communications, Nature, vol. 14(1), pages 1-15, December.
    2. Aisha Hassan & Li Cui-Xia & Naveed Ahmad & Muzaffar Iqbal & Kramat Hussain & Muhammad Ishtiaq & Maira Abrar, 2021. "Safety Failure Factors Affecting Dairy Supply Chain: Insights from a Developing Economy," Sustainability, MDPI, vol. 13(17), pages 1-24, August.
    3. Elijah Roberts & Andrew Magis & Julio O Ortiz & Wolfgang Baumeister & Zaida Luthey-Schulten, 2011. "Noise Contributions in an Inducible Genetic Switch: A Whole-Cell Simulation Study," PLOS Computational Biology, Public Library of Science, vol. 7(3), pages 1-21, March.
    4. McFarland, Michael J. & Wagner, Brandon G., 2015. "Does a college education reduce depressive symptoms in American young adults?," Social Science & Medicine, Elsevier, vol. 146(C), pages 75-84.
    5. Lixin Wang & B. Bishal Paudel & R. Anthony McKnight & Kevin A. Janes, 2023. "Nucleocytoplasmic transport of active HER2 causes fractional escape from the DCIS-like state," Nature Communications, Nature, vol. 14(1), pages 1-17, December.
    6. Chen, Aimin & Tian, Tianhai & Chen, Yiren & Zhou, Tianshou, 2022. "Stochastic analysis of a complex gene-expression model," Chaos, Solitons & Fractals, Elsevier, vol. 160(C).
    7. Kemal Keseroglu & Oriana Q. H. Zinani & Sevdenur Keskin & Hannah Seawall & Eslim E. Alpay & Ertuğrul M. Özbudak, 2023. "Stochastic gene expression and environmental stressors trigger variable somite segmentation phenotypes," Nature Communications, Nature, vol. 14(1), pages 1-9, December.
    8. Suzanne Gaudet & Sabrina L Spencer & William W Chen & Peter K Sorger, 2012. "Exploring the Contextual Sensitivity of Factors that Determine Cell-to-Cell Variability in Receptor-Mediated Apoptosis," PLOS Computational Biology, Public Library of Science, vol. 8(4), pages 1-15, April.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0097734. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.