IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0063125.html
   My bibliography  Save this article

Cross-Platform Microarray Meta-Analysis for the Mouse Jejunum Selects Novel Reference Genes with Highly Uniform Levels of Expression

Author

Listed:
  • Florian R L Meyer
  • Heinrich Grausgruber
  • Claudia Binter
  • Georg E Mair
  • Christian Guelly
  • Claus Vogl
  • Ralf Steinborn

Abstract

Reference genes (RGs) with uniform expression are used for normalization of reverse transcription quantitative PCR (RT-qPCR) data. Their optimization for a specific biological context, e.g. a specific tissue, has been increasingly considered. In this article, we compare RGs identified by expression data meta-analysis restricted to the context tissue, the jejunum of Mus musculus domesticus, i) to traditional RGs, ii) to expressed interspersed repeated DNA elements, and iii) to RGs identified by meta-analysis of expression data from diverse tissues and conditions. To select the set of candidate RGs, we developed a novel protocol for the cross-platform meta-analysis of microarray data. The expression stability of twenty-four putative RGs was analysed by RT-qPCR in at least 14 jejunum samples of the mouse strains C57Bl/6N, CD1, and OF1. Across strains, the levels of expression of the novel RGs Plekha7, Zfx, and Ube2v1 as well as of Oaz1 varied less than two-fold irrespective of genotype, sex or their combination. The gene set consisting of Plekha7 and Oaz1 showed superior expression stability analysed with the tool RefFinder. The novel RGs are functionally diverse. This facilitates expression studies over a wide range of conditions. The highly uniform expression of the optimized RGs in the jejunum points towards their involvement in tightly regulated pathways in this tissue. We also applied our novel protocol of cross-microarray platform meta-analysis to the identification of RGs in the duodenum, the ileum and the entire small intestine. The selection of RGs with improved expression stability in a specific biological context can reduce the number of RGs for the normalization step of RT-qPCR expression analysis, thus reducing the number of samples and experimental costs.

Suggested Citation

  • Florian R L Meyer & Heinrich Grausgruber & Claudia Binter & Georg E Mair & Christian Guelly & Claus Vogl & Ralf Steinborn, 2013. "Cross-Platform Microarray Meta-Analysis for the Mouse Jejunum Selects Novel Reference Genes with Highly Uniform Levels of Expression," PLOS ONE, Public Library of Science, vol. 8(5), pages 1-15, May.
  • Handle: RePEc:plo:pone00:0063125
    DOI: 10.1371/journal.pone.0063125
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0063125
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0063125&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0063125?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. Hendrik J M de Jonge & Rudolf S N Fehrmann & Eveline S J M de Bont & Robert M W Hofstra & Frans Gerbens & Willem A Kamps & Elisabeth G E de Vries & Ate G J van der Zee & Gerard J te Meerman & Arja ter, 2007. "Evidence Based Selection of Housekeeping Genes," PLOS ONE, Public Library of Science, vol. 2(9), pages 1-5, September.
    2. Bradley S Ferguson & Heesun Nam & Robin G Hopkins & Ron F Morrison, 2010. "Impact of Reference Gene Selection for Target Gene Normalization on Experimental Outcome Using Real-Time qRT-PCR in Adipocytes," PLOS ONE, Public Library of Science, vol. 5(12), pages 1-10, December.
    3. Tomokazu Konishi & Fumikazu Konishi & Shigeru Takasaki & Kohei Inoue & Koji Nakayama & Akihiko Konagaya, 2008. "Coincidence between Transcriptome Analyses on Different Microarray Platforms Using a Parametric Framework," PLOS ONE, Public Library of Science, vol. 3(10), pages 1-9, October.
    4. Pingzhao Hu & Celia M. T. Greenwood & Joseph Beyene, 2006. "Statistical Methods for Meta-Analysis of Microarray Data: A Comparative Study," Information Systems Frontiers, Springer, vol. 8(1), pages 9-20, February.
    5. Kai-Florian Storch & Ovidiu Lipan & Igor Leykin & N. Viswanathan & Fred C. Davis & Wing H. Wong & Charles J. Weitz, 2002. "Extensive and divergent circadian gene expression in liver and heart," Nature, Nature, vol. 417(6884), pages 78-83, May.
    6. Wei-Chung Cheng & Cheng-Wei Chang & Chaang-Ray Chen & Min-Lung Tsai & Wun-Yi Shu & Chia-Yang Li & Ian C Hsu, 2011. "Identification of Reference Genes across Physiological States for qRT-PCR through Microarray Meta-Analysis," PLOS ONE, Public Library of Science, vol. 6(2), pages 1-8, 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. Andrey A Ptitsyn & Sanjin Zvonic & Jeffrey M Gimble, 2007. "Digital Signal Processing Reveals Circadian Baseline Oscillation in Majority of Mammalian Genes," PLOS Computational Biology, Public Library of Science, vol. 3(6), pages 1-7, June.
    2. Hao A. Duong & Kenkichi Baba & Jason P. DeBruyne & Alec J. Davidson & Christopher Ehlen & Michael Powell & Gianluca Tosini, 2024. "Environmental circadian disruption re-writes liver circadian proteomes," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
    3. Lieven Thorrez & Katrijn Van Deun & Léon-Charles Tranchevent & Leentje Van Lommel & Kristof Engelen & Kathleen Marchal & Yves Moreau & Iven Van Mechelen & Frans Schuit, 2008. "Using Ribosomal Protein Genes as Reference: A Tale of Caution," PLOS ONE, Public Library of Science, vol. 3(3), pages 1-8, March.
    4. Antía González-Vila & María Luengo-Mateos & María Silveira-Loureiro & Pablo Garrido-Gil & Nataliia Ohinska & Marco González-Domínguez & Jose Luis Labandeira-García & Cristina García-Cáceres & Miguel L, 2023. "Astrocytic insulin receptor controls circadian behavior via dopamine signaling in a sexually dimorphic manner," Nature Communications, Nature, vol. 14(1), pages 1-21, December.
    5. Cheng-Wei Chang & Wei-Chung Cheng & Chaang-Ray Chen & Wun-Yi Shu & Min-Lung Tsai & Ching-Lung Huang & Ian C Hsu, 2011. "Identification of Human Housekeeping Genes and Tissue-Selective Genes by Microarray Meta-Analysis," PLOS ONE, Public Library of Science, vol. 6(7), pages 1-10, July.
    6. Andrey A Ptitsyn & Sanjin Zvonic & Steven A Conrad & L Keith Scott & Randall L Mynatt & Jeffrey M Gimble, 2006. "Circadian Clocks Are Resounding in Peripheral Tissues," PLOS Computational Biology, Public Library of Science, vol. 2(3), pages 1-10, March.
    7. Cheemeng Tan & Robert Phillip Smith & Ming-Chi Tsai & Russell Schwartz & Lingchong You, 2014. "Phenotypic Signatures Arising from Unbalanced Bacterial Growth," PLOS Computational Biology, Public Library of Science, vol. 10(8), pages 1-10, August.
    8. Kevin P Keegan & Suraj Pradhan & Ji-Ping Wang & Ravi Allada, 2007. "Meta-Analysis of Drosophila Circadian Microarray Studies Identifies a Novel Set of Rhythmically Expressed Genes," PLOS Computational Biology, Public Library of Science, vol. 3(11), pages 1-1, November.
    9. Sarah Gehlert & Mark Clanton & on behalf of the Shift Work and Breast Cancer Strategic Advisory Group, 2020. "Shift Work and Breast Cancer," IJERPH, MDPI, vol. 17(24), pages 1-8, December.
    10. Alan L Hutchison & Mark Maienschein-Cline & Andrew H Chiang & S M Ali Tabei & Herman Gudjonson & Neil Bahroos & Ravi Allada & Aaron R Dinner, 2015. "Improved Statistical Methods Enable Greater Sensitivity in Rhythm Detection for Genome-Wide Data," PLOS Computational Biology, Public Library of Science, vol. 11(3), pages 1-29, March.
    11. Wei-Chung Cheng & Cheng-Wei Chang & Chaang-Ray Chen & Min-Lung Tsai & Wun-Yi Shu & Chia-Yang Li & Ian C Hsu, 2011. "Identification of Reference Genes across Physiological States for qRT-PCR through Microarray Meta-Analysis," PLOS ONE, Public Library of Science, vol. 6(2), pages 1-8, February.
    12. Bo Dong & Peng Zhang & Xiaowei Chen & Li Liu & Yunfei Wang & Shunmin He & Runsheng Chen, 2011. "Predicting Housekeeping Genes Based on Fourier Analysis," PLOS ONE, Public Library of Science, vol. 6(6), pages 1-11, June.
    13. Mastrantonio, Gianluca, 2018. "The joint projected normal and skew-normal: A distribution for poly-cylindrical data," Journal of Multivariate Analysis, Elsevier, vol. 165(C), pages 14-26.
    14. Chulhwan Chris Bang, 2015. "Information systems frontiers: Keyword analysis and classification," Information Systems Frontiers, Springer, vol. 17(1), pages 217-237, February.
    15. Yijuan Zhang & Ding Li & Bingyun Sun, 2015. "Do Housekeeping Genes Exist?," PLOS ONE, Public Library of Science, vol. 10(5), pages 1-22, May.
    16. Ian C McDowell & Dinesh Manandhar & Christopher M Vockley & Amy K Schmid & Timothy E Reddy & Barbara E Engelhardt, 2018. "Clustering gene expression time series data using an infinite Gaussian process mixture model," PLOS Computational Biology, Public Library of Science, vol. 14(1), pages 1-27, January.

    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:pone00:0063125. 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.