IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0017347.html
   My bibliography  Save this article

Identification of Reference Genes across Physiological States for qRT-PCR through Microarray Meta-Analysis

Author

Listed:
  • Wei-Chung Cheng
  • Cheng-Wei Chang
  • Chaang-Ray Chen
  • Min-Lung Tsai
  • Wun-Yi Shu
  • Chia-Yang Li
  • Ian C Hsu

Abstract

Background: The accuracy of quantitative real-time PCR (qRT-PCR) is highly dependent on reliable reference gene(s). Some housekeeping genes which are commonly used for normalization are widely recognized as inappropriate in many experimental conditions. This study aimed to identify reference genes for clinical studies through microarray meta-analysis of human clinical samples. Methodology/Principal Findings: After uniform data preprocessing and data quality control, 4,804 Affymetrix HU-133A arrays performed by clinical samples were classified into four physiological states with 13 organ/tissue types. We identified a list of reference genes for each organ/tissue types which exhibited stable expression across physiological states. Furthermore, 102 genes identified as reference gene candidates in multiple organ/tissue types were selected for further analysis. These genes have been frequently identified as housekeeping genes in previous studies, and approximately 71% of them fall into Gene Expression (GO:0010467) category in Gene Ontology. Conclusions/Significance: Based on microarray meta-analysis of human clinical sample arrays, we identified sets of reference gene candidates for various organ/tissue types and then examined the functions of these genes. Additionally, we found that many of the reference genes are functionally related to transcription, RNA processing and translation. According to our results, researchers could select single or multiple reference gene(s) for normalization of qRT-PCR in clinical studies.

Suggested Citation

  • 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.
    • Handle: RePEc:plo:pone00:0017347
    DOI: 10.1371/journal.pone.0017347
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0017347
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0017347&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0017347?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. Zhijin Wu & Rafael A. Irizarry & Robert Gentleman & Francisco Martinez-Murillo & Forrest Spencer, 2004. "A Model-Based Background Adjustment for Oligonucleotide Expression Arrays," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 909-917, December.
    2. 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.
    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. Zhijin Wu & Rafael Irizarry & Robert Gentleman & Francisco Martinez Murillo & Forrest Spencer, 2004. "A Model Based Background Adjustment for Oligonucleotide Expression Arrays," Johns Hopkins University Dept. of Biostatistics Working Paper Series 1001, Berkeley Electronic Press.
    5. Adaikalavan Ramasamy & Adrian Mondry & Chris C Holmes & Douglas G Altman, 2008. "Key Issues in Conducting a Meta-Analysis of Gene Expression Microarray Datasets," PLOS Medicine, Public Library of Science, vol. 5(9), pages 1-13, September.
    6. Federica Rizzi & Lucia Belloni & Pellegrino Crafa & Mirca Lazzaretti & Daniel Remondini & Stefania Ferretti & Piero Cortellini & Arnaldo Corti & Saverio Bettuzzi, 2008. "A Novel Gene Signature for Molecular Diagnosis of Human Prostate Cancer by RT-qPCR," PLOS ONE, Public Library of Science, vol. 3(10), pages 1-9, October.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. 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.

    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. Rinku Sharma & Garima Singh & Sudeepto Bhattacharya & Ashutosh Singh, 2018. "Comparative transcriptome meta-analysis of Arabidopsis thaliana under drought and cold stress," PLOS ONE, Public Library of Science, vol. 13(9), pages 1-18, September.
    2. Jin-Xing Liu & Yong Xu & Chun-Hou Zheng & Yi Wang & Jing-Yu Yang, 2012. "Characteristic Gene Selection via Weighting Principal Components by Singular Values," PLOS ONE, Public Library of Science, vol. 7(7), pages 1-10, July.
    3. Nan Li & Matthew N. McCall & Zhijin Wu, 2017. "Establishing Informative Prior for Gene Expression Variance from Public Databases," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 9(1), pages 160-177, June.
    4. Sigrun Helga Lund & Daniel Fannar Gudbjartsson & Thorunn Rafnar & Asgeir Sigurdsson & Sigurjon Axel Gudjonsson & Julius Gudmundsson & Kari Stefansson & Gunnar Stefansson, 2014. "A Method for Detecting Long Non-Coding RNAs with Tiled RNA Expression Microarrays," PLOS ONE, Public Library of Science, vol. 9(6), pages 1-9, June.
    5. Krishanpal Anamika & Àkos Gyenis & Laetitia Poidevin & Olivier Poch & Làszlò Tora, 2012. "RNA Polymerase II Pausing Downstream of Core Histone Genes Is Different from Genes Producing Polyadenylated Transcripts," PLOS ONE, Public Library of Science, vol. 7(6), pages 1-14, June.
    6. Lei Zhang & Linlin Wang & Pu Tian & Suyan Tian, 2016. "Identification of Genes Discriminating Multiple Sclerosis Patients from Controls by Adapting a Pathway Analysis Method," PLOS ONE, Public Library of Science, vol. 11(11), pages 1-13, November.
    7. Upton Graham J. G. & Harrison Andrew P, 2010. "The Detection of Blur in Affymetrix GeneChips," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 9(1), pages 1-19, October.
    8. Ryan Abo & Gregory D Jenkins & Liewei Wang & Brooke L Fridley, 2012. "Identifying the Genetic Variation of Gene Expression Using Gene Sets: Application of Novel Gene Set eQTL Approach to PharmGKB and KEGG," PLOS ONE, Public Library of Science, vol. 7(8), pages 1-11, August.
    9. Jeremiah J Faith & Boris Hayete & Joshua T Thaden & Ilaria Mogno & Jamey Wierzbowski & Guillaume Cottarel & Simon Kasif & James J Collins & Timothy S Gardner, 2007. "Large-Scale Mapping and Validation of Escherichia coli Transcriptional Regulation from a Compendium of Expression Profiles," PLOS Biology, Public Library of Science, vol. 5(1), pages 1-13, January.
    10. Chalise, Prabhakar & Fridley, Brooke L., 2012. "Comparison of penalty functions for sparse canonical correlation analysis," Computational Statistics & Data Analysis, Elsevier, vol. 56(2), pages 245-254.
    11. Marot Guillemette & Mayer Claus-Dieter, 2009. "Sequential Analysis for Microarray Data Based on Sensitivity and Meta-Analysis," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 8(1), pages 1-35, January.
    12. Parker Hilary S. & Leek Jeffrey T., 2012. "The practical effect of batch on genomic prediction," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 11(3), pages 1-22, April.
    13. Suyan Tian & James G Krueger & Katherine Li & Ali Jabbari & Carrie Brodmerkel & Michelle A Lowes & Mayte Suárez-Fariñas, 2012. "Meta-Analysis Derived (MAD) Transcriptome of Psoriasis Defines the “Core” Pathogenesis of Disease," PLOS ONE, Public Library of Science, vol. 7(9), pages 1-15, September.
    14. Akul Singhania & Hitasha Rupani & Nivenka Jayasekera & Simon Lumb & Paul Hales & Neil Gozzard & Donna E Davies & Christopher H Woelk & Peter H Howarth, 2017. "Altered Epithelial Gene Expression in Peripheral Airways of Severe Asthma," PLOS ONE, Public Library of Science, vol. 12(1), pages 1-16, January.
    15. Russell D J Huby & Philip Glaves & Richard Jackson, 2014. "The Incidence of Sexually Dimorphic Gene Expression Varies Greatly between Tissues in the Rat," PLOS ONE, Public Library of Science, vol. 9(12), pages 1-19, December.
    16. Erick da Conceição Amorim & Vinícius Diniz Mayrink, 2020. "Clustering non-linear interactions in factor analysis," METRON, Springer;Sapienza Università di Roma, vol. 78(3), pages 329-352, December.
    17. Miranda van Uitert & Perry D Moerland & Daniel A Enquobahrie & Hannele Laivuori & Joris A M van der Post & Carrie Ris-Stalpers & Gijs B Afink, 2015. "Meta-Analysis of Placental Transcriptome Data Identifies a Novel Molecular Pathway Related to Preeclampsia," PLOS ONE, Public Library of Science, vol. 10(7), pages 1-15, July.
    18. Wojciech Barczak & Simon M. Carr & Geng Liu & Shonagh Munro & Annalisa Nicastri & Lian Ni Lee & Claire Hutchings & Nicola Ternette & Paul Klenerman & Alexander Kanapin & Anastasia Samsonova & Nicholas, 2023. "Long non-coding RNA-derived peptides are immunogenic and drive a potent anti-tumour response," Nature Communications, Nature, vol. 14(1), pages 1-17, December.
    19. Huixia Wang & Xuming He, 2008. "An Enhanced Quantile Approach for Assessing Differential Gene Expressions," Biometrics, The International Biometric Society, vol. 64(2), pages 449-457, June.
    20. 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.

    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:pone00:0017347. 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.