Sample-Independent Expression Stability Analysis of Human Housekeeping Genes Using the GeNORM Algorithm

Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 269)


The quantification of mRNAs has been used with great success in many medical research techniques. All of them can use housekeeping genes as internal standards. While most of the commonly used housekeeping genes may have varied expression stability in different human tissue samples or experimental conditions. In this study, 566 housekeeping genes were investigated by conducting a statistical analysis on a large human genome microarray database. The sample-independent expression stability value of every gene was calculated and ranked by using the GeNORM algorithm. Furthermore, microarray expression data of another mammalian model were used to evaluate the variation coefficient of the candidate genes expressed in the mouse models. Most of the candidate housekeeping genes exhibited similar expression stabilities in the two models. This analysis presents the sample-independent expression stability of a set of housekeeping genes.


Normalization Housekeeping genes Internal control Human genome microarray 



This research was supported by the Sciences and Technologies Projects of Science and Information Technology Bureau of GuangZhou. China (Grant No. 2005Z12E4023).


  1. 1.
    Suzuki T, Higgins PJ, Crawford DR (2000) Control selection for RNA quantitation. Biotechniques 29:6Google Scholar
  2. 2.
    de Kok JB, Roelofs RW, Giesendorf BA, Pennings JL, Waas ET, Feuth T, Swinkels DW, Span PN (2004) Normalization of gene expression measurements in tumor tissues: comparison of 13 endogenous control genes. Lab Invest 85:154–159CrossRefGoogle Scholar
  3. 3.
    Gokal PK, Cavanaugh AH, Thompson EA (1986) The effects of cycloheximide upon transcription of rRNA, 5s RNA, and tRNA genes. J Biol Chem 261:2536–2541Google Scholar
  4. 4.
    Ayrault O, Andrique L, Fauvin D, Eymin B, Gazzeri S, Seite P (2006) Human tumor suppressor p14ARF negatively regulates rRNA transcription and inhibits UBF1 transcription factor phosphorylation. Oncogene 25:7577–7586CrossRefGoogle Scholar
  5. 5.
    Brunner A, Yakovlev I, Strauss S (2004) Validating internal controls for quantitative plant gene expression studies. BMC Plant Biol 4:14CrossRefGoogle Scholar
  6. 6.
    De Ferrari L, Aitken S (2006) Mining housekeeping genes with a Naive Bayes classifier. BMC Genomics 7:277CrossRefGoogle Scholar
  7. 7.
    Nico J, Michel J, Tim P, Annette B (2004) Housekeeping Genes as Internal Standards in Cancer Research. Molecular Diagnosis 8:107–113Google Scholar
  8. 8.
    Thellin O, Zorzi W, Lakaye B, De Borman B, Coumans B, Hennen G, Grisar T, Igout A, Heinen E (1999) Housekeeping genes as internal standards: use and limits. J Biotechnol 75:291–295CrossRefGoogle Scholar
  9. 9.
    Lee PD, Sladek R, Greenwood CMT, Hudson TJ (2002) Control genes and variability: absence of ubiquitous reference transcripts in diverse mammalian expression studies. Genome Res 12:292–297CrossRefGoogle Scholar
  10. 10.
    Rubie C, Kempf K, Hans J, Su T, Tilton B, Georg T, Brittner B, Ludwig B, Schilling M (2005) Housekeeping gene variability in normal and cancerous colorectal, pancreatic, esophageal, gastric and hepatic tissues. Mol Cell Probes 19:101–109CrossRefGoogle Scholar
  11. 11.
    Radonić A, Thulke S, Mackay IM, Landt O, Siegert W, Nitsche A (2004) Guideline to reference gene selection for quantitative real-time PCR. Biochem Biophys Res Commun 313:856–862CrossRefGoogle Scholar
  12. 12.
    Banda M, Bommineni A, Thomas RA, Luckinbill LS, Tucker JD (2008) Evaluation and validation of housekeeping genes in response to ionizing radiation and chemical exposure for normalizing RNA expression in real-time PCR. Mutat Res 649:126–134CrossRefGoogle Scholar
  13. 13.
    Vandesompele J, De Preter K, Pattyn F et al (2002) Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes, Genome Biol 3:research0034.0031–research0034.0011Google Scholar
  14. 14.
    Eisenberg E, Levanon EY (2003) Human housekeeping genes are compact. Trends Genet 19:362–365CrossRefGoogle Scholar
  15. 15.
    Barrett T, Troup DB, Wilhite SE, Ledoux P, Rudnev D, Evangelista C, Kim IF, Soboleva A, Tomashevsky M, Edgar R (2007) NCBI GEO: mining tens of millions of expression profiles–database and tools update. Nucleic Acids Res 35:760–765CrossRefGoogle Scholar
  16. 16.
    Wall TCL, Orwant J (2000) Programming perl. 3rd edn. O’Reilly Media, CambridgeGoogle Scholar
  17. 17.
    Reed GF, Lynn F, Meade BD (2002) Use of coefficient of variation in assessing variability of quantitative assays. Clin Diagn Lab Immunol 9:1235–1239Google Scholar
  18. 18.
    Edgar R, Domrachev M, Lash AE (2002) Gene expression omnibus: NCBI gene expression and hybridization array data repository. Nucleic Acids Res 30:207–210CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  1. 1.Department of Bioscience and BioengineeringSouth China University of TechnologyGuangzhouChina

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