Data processing, analysis method of gene expression data to identify endogenous reference genes
Inventors
Shin, Young Kee • Kwon, Mi J. • Oh, En Sel • In, Yong H. • Koh, Sang S.
Assignees
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Publication Number
US-10304561-B2
Publication Date
2019-05-28
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 a gene-expression data analysis framework for identifying endogenous reference genes for normalization in quantitative gene expression measurements. It computes gene expression levels of genes from EST, SAGE and microarray datasets, and introduces zero’s proportion to quantify tissue ubiquity of expression across multiple tissue types. Coefficient of variation (CV) is used to assess expression stability.
Constitutively expressed genes are identified from more than one tissue type based on the computed gene expression level and zero (0)’s proportions thereof. Candidate endogenous reference genes are then ranked in an ascending order of CV to select constitutively stable reference genes. The framework yields a final set of 13 selected constitutively stable, lower-abundance reference/guide genes rather than using traditional reference genes such as GAPDH/ACTB.
The selected endogenous reference/guide genes are used as the basis for normalizing target gene expression in real-time PCR/qRT-PCR quantification. The document provides evaluation across multiple datasets, including comparisons involving Cp/CV, and validation using qRT-PCR across human tissue/cell line samples with additional stability metrics (geNorm, NormFinder) to support higher stability than traditional genes.
Claims Coverage
Two independent claims are provided, and both focus on a real-time PCR-based quantification workflow where the key inventive element is the selection of an endogenous reference gene CUL1 using computed expression levels from EST, SAGE, and microarray datasets combined with constitutive expression across more than one tissue type and, in one claim, CV-based ranking.
Endogenous reference gene selection from multiple expression datasets using zero’s proportions to identify constitutively expressed genes
The method amplifies a target gene and then performs real-time PCR to amplify an endogenous reference gene CUL1, wherein CUL1 is selected 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 level and zero (0)’s proportions thereof.
Coefficient of variation based ranking of endogenous reference gene candidates
The method further includes determining the coefficient of variation (CV) for the endogenous reference gene and ranking the endogenous gene in an ascending order of CV as part of the selection of CUL1 for normalization.
Overall, the claims cover quantifying a target gene by normalizing to an endogenous reference gene CUL1 selected through dataset-based identification of constitutively expressed genes using computed expression levels and zero (0)’s proportions, with one claim additionally requiring CV determination and ascending-CV ranking of candidates.
Stated Advantages
Provides higher stability of the selected reference genes than traditional genes.
Selects constitutively stable, lower-abundance reference/guide genes for normalization.
Documented Applications
Normalization for real-time PCR/qRT-PCR quantification of target gene expression using primer and probe sets for endogenous reference gene CUL1 and selected reference/guide genes.
Validation of reference gene stability using qRT-PCR across human tissue/cell line samples and additional stability metrics (geNorm, NormFinder).
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