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Identification of human HK genes and gene expression regulation study in cancer from transcriptomics data analysis.

ABSTRACT: The regulation of gene expression is essential for eukaryotes, as it drives the processes of cellular differentiation and morphogenesis, leading to the creation of different cell types in multicellular organisms. RNA-Sequencing (RNA-Seq) provides researchers with a powerful toolbox for characterization and quantification of transcriptome. Many different human tissue/cell transcriptome datasets coming from RNA-Seq technology are available on public data resource. The fundamental issue here is how to develop an effective analysis method to estimate expression pattern similarities between different tumor tissues and their corresponding normal tissues. We define the gene expression pattern from three directions: 1) expression breadth, which reflects gene expression on/off status, and mainly concerns ubiquitously expressed genes; 2) low/high or constant/variable expression genes, based on gene expression level and variation; and 3) the regulation of gene expression at the gene structure level. The cluster analysis indicates that gene expression pattern is higher related to physiological condition rather than tissue spatial distance. Two sets of human housekeeping (HK) genes are defined according to cell/tissue types, respectively. To characterize the gene expression pattern in gene expression level and variation, we firstly apply improved K-means algorithm and a gene expression variance model. We find that cancer-associated HK genes (a HK gene is specific in cancer group, while not in normal group) are expressed higher and more variable in cancer condition than in normal condition. Cancer-associated HK genes prefer to AT-rich genes, and they are enriched in cell cycle regulation related functions and constitute some cancer signatures. The expression of large genes is also avoided in cancer group. These studies will help us understand which cell type-specific patterns of gene expression differ among different cell types, and particularly for cancer.

SUBMITTER: Chen M

PROVIDER: S-EPMC3561342 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Identification of human HK genes and gene expression regulation study in cancer from transcriptomics data analysis.

Chen Meili M Xiao Jingfa J Zhang Zhang Z Liu Jingxing J Wu Jiayan J Yu Jun J

PloS one 20130131 1

The regulation of gene expression is essential for eukaryotes, as it drives the processes of cellular differentiation and morphogenesis, leading to the creation of different cell types in multicellular organisms. RNA-Sequencing (RNA-Seq) provides researchers with a powerful toolbox for characterization and quantification of transcriptome. Many different human tissue/cell transcriptome datasets coming from RNA-Seq technology are available on public data resource. The fundamental issue here is how ...[more]

PMID: 23382867

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Project description:BACKGROUND: Reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) is a powerful method for the analysis of gene expression. Target gene expression levels are usually normalized to a consistently expressed reference gene also known as internal standard, in the same sample. However, much effort has not been expended thus far in the search for reference genes suitable for the study of stomach cancer using RT-qPCR, although selection of optimal reference genes is critical for interpretation of results. METHODS: We assessed the suitability of six possible reference genes, beta-actin (ACTB), glyceraldehydes-3-phosphate dehydrogenase (GAPDH), hypoxanthine phosphoribosyl transferase 1 (HPRT1), beta-2-microglobulin (B2M), ribosomal subunit L29 (RPL29) and 18S ribosomal RNA (18S rRNA) in 20 normal and tumor stomach tissue pairs of stomach cancer patients and 6 stomach cancer cell lines, by RT-qPCR. Employing expression stability analyses using NormFinder and geNorm algorithms we determined the order of performance of these reference genes and their variation values. RESULTS: This RT-qPCR study showed that there are statistically significant (p < 0.05) differences in the expression levels of HPRT1 and 18S rRNA in 'normal-' versus 'tumor stomach tissues'. The stability analyses by geNorm suggest B2M-GAPDH, as best reference gene combination for 'stomach cancer cell lines'; RPL29-HPRT1, for 'all stomach tissues'; and ACTB-18S rRNA, for 'all stomach cell lines and tissues'. NormFinder also identified B2M as the best reference gene for 'stomach cancer cell lines', RPL29-B2M for 'all stomach tissues', and 18S rRNA-ACTB for 'all stomach cell lines and tissues'. The comparisons of normalized expression of the target gene, GPNMB, showed different interpretation of target gene expression depend on best single reference gene or combination. CONCLUSION: This study validated RPL29 and RPL29-B2M as the best single reference genes and combination, for RT-qPCR analysis of 'all stomach tissues', and B2M and B2M-GAPDH as the best single reference gene and combination, for 'stomach cancer cell lines'. Use of these validated reference genes should provide more exact interpretation of differential gene expressions at transcription level in stomach cancer.

Dataset Information

Identification of human HK genes and gene expression regulation study in cancer from transcriptomics data analysis.

Publications

Identification of human HK genes and gene expression regulation study in cancer from transcriptomics data analysis.

Similar Datasets

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