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.
Highlights
Gene expression regulation contains the process that cells and viruses use to regulate the way that the information in genes is turned into gene products, most of which are protein coding genes [1,2,3]
To eliminate contamination and error caused by experiments and instruments, etc., we detect the expression level between exons and intergenic regions to coordinate false positive rate (FPR) and false negative rate (FNR) using the method generated in a previous study [10]
By analyzing maximum ratio values (maxR) and minimum ratio values (minR), we find that most cancerassociated HK genes are corresponding to the maxR#1 and minR#1; cancer emergence actives genes express higher than they do in normal physiological condition
Summary
Gene expression regulation contains the process that cells and viruses use to regulate the way that the information in genes is turned into gene products, most of which are protein coding genes [1,2,3]. Gene expression regulation is essential for eukaryotes [4] because it drives the processes of cellular differentiation and morphogenesis [5]. This leads to the creation of different cell types in multicellular organisms, where different cell types may possess different gene expression profiles, though they all possess the same genome sequence [6]. Gene structure is one important regulation factor for gene expression It is comprised mainly of gene structure composition, gene structure organization, gene variation, protein classes, cellular structure, cellular processes, and molecular mechanisms [10,14,15,16,17,18,19,20,21,22,23,24,25]
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