Sample-Independent Expression Stability Analysis of Human Housekeeping Genes Using the GeNORM Algorithm
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 diff
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Sample-Independent Expression Stability Analysis of Human Housekeeping Genes Using the GeNORM Algorithm Li Li, Xiaofang Mao, Qiang Gao and Yicheng Cao
Abstract 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. Keywords Normalization genome microarray
Housekeeping genes
Internal control
Human
L. Li X. Mao Q. Gao Y. Cao (&) Department of Bioscience and Bioengineering, South China University of Technology, Guangzhou, China e-mail: [email protected] L. Li e-mail: [email protected] X. Mao e-mail: [email protected] Q. Gao e-mail: [email protected]
S. Li et al. (eds.), Frontier and Future Development of Information Technology in Medicine and Education, Lecture Notes in Electrical Engineering 269, DOI: 10.1007/978-94-007-7618-0_8, Springer Science+Business Media Dordrecht 2014
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8.1 Introduction RNA expression analysis is playing an important role in many field of medical research. Microarrays, real-time reverse-transcription polymerase chain reaction, Northern blots, and RNase protection assays are the most commonly used quantitative analysis methods for RNA expression. To correct for sample-to-sample variation, normalization of the expression data is required in all these methods [1]. The conventional way to perform normalization is to select a reference gene whose expression is believed to remain stable across all experimental conditions. The 18s or 28s rRNA molecules are widely considered as the representatives for mRNA integrity because of their capability to remain intact in experiment samples with degraded mRNAs. However, several problems exist with using rRNAs as control genes. First, rRNAs have a different polymerase transcription system from mRNAs. Many changes in the polymerase activity do not affect both types of RNA expressions [2]. rRNA transcription is also reportedly affected by many experimental conditions and biological factors [3, 4], and the effect of partial RNA degradation in 18s rRNA expression levels is smaller than in mRNA expression [5]. Housekeeping genes are also widely used as internal standards in quantitative analysis because their synthesis occurs in all nucleated cel
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