Data processing, analysis method of gene expression data to identify endogenous reference genes
Inventors
Shin, Young Kee • Kwon, Mi Jeong • Oh, En Sel • In, Yong Ho • Koh, Sang Seok
Assignees
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Publication Number
US-9639660-B2
Publication Date
2017-05-02
Expiration Date
Abstract
Disclosed are data processing and analysis methods for gene expression data for identifying endogenous reference genes and a composition for the quantitative analysis of gene expression, comprising a pair of primers and/or probes useful in amplifying the identified endogenous reference genes. Introduced with the concepts of “Zero's proportion” and CV, the method allows different datasets to be integrally analyzed, thereby searching for novel reference genes. By the method, 2,087 genes are first found as housekeeping genes which are expressed in most tissues, and the usefulness thereof in the relative quantification of different target genes is determined by analyzing their expression stability. Of the 2,087 genes, 13 genes show higher expression stability with lower expression levels across a wide range of samples than traditional reference genes such as GAPDH and ACTS, and therefore are suitable for the normalization of universal genes having relatively low expression levels.
Core Innovation
The invention relates to quantifying an expression level of a target gene by synthesizing cDNA from RNA of a subject and performing real-time PCR to amplify the target gene and an endogenous reference gene, with the cDNA serving as a template. The target gene expression level is normalized to the endogenous reference gene expression level.
A key aspect of the invention is selecting the endogenous reference gene by computing expression levels of genes from EST, SAGE, and microarray datasets. Constitutively expressed genes are identified from more than one tissue type based on the computed gene expression levels and zero(0)’s proportions thereof.
In a further selection approach, the method determines the coefficient of variation (CV) for the endogenous reference gene and ranks the endogenous reference gene in an ascending order of CV. The selected endogenous reference gene is used for normalizing the target gene expression signal.
Claims Coverage
Two independent claims are present. The claims share real-time PCR quantification and normalization to an endogenous reference gene, with reference selection based on EST, SAGE, and microarray datasets, constitutive expression across more than one tissue type, zero(0)’s proportions, and in one claim CV-based ranking.
Real-time PCR quantification with endogenous reference gene normalization
A method for quantifying an expression level of a target gene by synthesizing cDNA from RNA of a subject, performing real-time PCR to amplify the target gene and an endogenous reference gene using a pair of primers and/or probes with the cDNA as a template, and normalizing an expression level of the target gene to the endogenous reference gene.
Constitutively expressed reference selection using zero(0)'s proportion from multiple platforms
Selecting an endogenous reference gene by computing expression levels of genes from EST, SAGE, and microarray datasets, and identifying constitutively expressed genes from more than one tissue type based on the computed gene expression levels and zero(0)’s proportions thereof.
Stable reference ranking using coefficient of variation
Selecting an endogenous reference gene by determining the coefficient of variation (CV) for the endogenous reference gene and ranking the endogenous reference gene in an ascending order of CV.
The central coverage is directed to quantifying a target gene by real-time PCR and normalizing to an endogenous reference gene selected from EST, SAGE, and microarray datasets using constitutive expression across more than one tissue type via zero(0)’s proportions, with one claim further using CV-based ascending ranking for stability.
Stated Advantages
Not explicitly described in patent.
Documented Applications
Not explicitly described in patent.
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