DNA芯片技术中利用内标对数据归一化后检测基因的表达变化

在DNA芯片技术中 ,通过反转录反应 ,由mRNA合成带有荧光标记物的cDNA的过程中 ,往往要参入已知质量的poly(A) + RNA ,以对DNA芯片的检测灵敏度进行归一化处理 .通过体外转录的方法 ,以真核生物的cDNA克隆中的DNA片段为模板合成poly(A) +RNA ,对之定量后 ,以不同的质量比参入到样品的反转录体系中 ,代表不同的RNA拷贝丰度 ,从而对DNA芯片检测的灵敏度进行了定量 ,并得到DNA芯片上杂交点的荧光信号强度与基因表达的RNA拷贝数成正相关的关系 .利用含有内标的DNA芯片检测了热击反应后酵母细胞的基因表达变化 ,结果与Northern印迹方法检测结果是相符的     

Coupled analysis of gene expression and chromosomal location

Microarray technology can be used to assess simultaneously global changes in expression of mRNA or genomic DNA copy number among thousands of genes in different biological states. In many cases, it is desirable to determine if altered patterns of gene expression correlate with chromosomal abnormalities or assess expression of genes that are contiguous in the genome. We describe a method, differential gene locus mapping (DIGMAP), which aligns the known chromosomal location of a gene to its expression value deduced by microarray analysis. The method partitions microarray data into subsets by chromosomal location for each gene interrogated by an array. Microarray data in an individual subset can then be clustered by physical location of genes at a subchromosomal level based upon ordered alignment in genome sequence. A graphical display is generated by representing each genomic locus with a colored cell that quantitatively reflects its differential expression value. The clustered patterns can be viewed and compared based on their expression signatures as defined by differential values between control and experimental samples. In this study, DIGMAP was tested using previously published studies of breast cancer analyzed by comparative genomic hybridization (CGH) and prostate cancer gene expression profiles assessed by cDNA microarray experiments. Analysis of the breast cancer CGH data demonstrated the ability of DIGMAP to deduce gene amplifications and deletions. Application of the DIGMAP method to the prostate data revealed several carcinoma-related loci, including one at 16q13 with marked differential expression encompassing 19 known genes including 9 encoding metallothionein proteins. We conclude that DIGMAP is a powerful computational tool enabling the coupled analysis of microarray data with genome location.     

基因组织特异性相关研究进展

研究基因的组织特异性是了解生命活动进程和组织功能的重要一步.尽管对于看家基因和组织特异基因的研究由来已久,但是对于它们仍缺少统一的定义方式和检测方法.在定义方式上,可以从基因的组织表达数和在各组织间的表达变化情况来分别定义看家基因和组织特异基因.通常将在大多数正常组织中有表达,且表达水平较稳定的基因称为看家基因,而将在一个或少数组织中优势表达的基因定义为组织特异基因或组织选择基因.在检测方法上,高通量实验技术,包括基因芯片、RNA-seq和质谱技术等已成为检测基因组织特异性的主要方法.通过比较多个典型研究的实验结果,发现不同检测方法的覆盖度和灵敏度存在很大差异,其中RNA-seq技术最为灵敏,获得的看家基因数目最多,质谱技术检测出来的看家基因和组织特异基因数目较少,而基因芯片方法给出的多个检测结果间差别较大.尽管不同的定义方式和检测方法所导致的看家基因(或组织特异基因)的集合不完全一致,但不同的看家基因数据集(或组织特异基因)却展现出非常一致的功能和特性.看家基因通常实现所有组织和细胞都必须的基本功能,而看家基因与其他组织表达基因间的相互作用以及组织特异基因间的相互作用则实现了组织的特有功能.同时,基因的组织特异性与疾病之间具有密切联系,相比其他基因,看家基因更有可能成为癌基因,而组织特异基因则更有希望发展成为药物靶标.     

Molecular chemoprevention by selenium: a genomic approach

Basic research and clinical chemoprevention trials support the protective role of selenium in cancer prevention but the mechanisms based on the molecular level remain to be fully defined. This mini-review focuses only on the elucidation of the molecular mechanisms of cancer prevention by selenium using the genomics approach; target organs discussed here are breast, prostate, colon and lung. The results described here support the utility of microarray technology in delineating the molecular mechanisms of cancer prevention by selenium. These results are based on studies employing human and rodent cell lines and tissues from animal models ranging from normal to frank cancer. The dose and the form of selenium are determining factors in cancer chemoprevention. The results of the microarray analysis reviewed here indicate that selenium, independent of its form and the target organ examined, alters several genes in a manner that can account for cancer prevention. Selenium can up regulate genes related to phase II detoxification enzymes, certain selenium-binding proteins and select apoptotic genes, while down regulating those related to phase I activating enzymes and cell proliferation. Independent of tissue type, selenium arrests cells in G1 phase of cell cycle, inhibits CYCLIN A, CYCLIN D1, CDC25A, CDK4, PCNA and E2F gene expressions while induces the expressions of P19, P21, P53, GST, SOD, NQO1, GADD153 and certain CASPASES. In addition to those described above, genes such as OPN, which is mainly involved in metastasis and recently reported to be down regulated by selenium, should be considered as potential molecular marker in clinical chemoprevention trials. Collectively, literature data indicate that some of these genes that were altered by selenium are also involved in the development of human cancers described in this review. It appears that androgen receptor status may influence the effect of selenium on gene expression profile in prostate cancer; whether estrogen receptor may influence the effect of selenium on gene expression in breast cancer requires further studies. Knowledge from gene array data in combination with proteomics approaches, using homogenous population of cell types with the aid of laser capture microdissection, may provide an individualized dimension of information on cancer risk and potential targets for its prevention. The molecular (genetic) biomarkers presented in this review will provide the foundation for future studies of the chemopreventive properties of structurally varied selenium compounds.     

Prostate cancer and the genomic revolution: Advances using microarray analyses

The emerging technology of microarray analysis allows the establishment of molecular portraits of prostate cancer and the discovery of novel genes involved in the carcinogenesis process. Many novel genes have already been identified using this technique, and functional analyses of these genes are currently being tested. The combination of microarray analysis with other recently developed high-throughput techniques, such as proteomics, tissue arrays, and gene promoter-methylation, especially using tissue microdissection methods, will provide us with more comprehensive insights into how prostate cancer develops and responds to gene-targeted therapies. Animal models of prostate cancer are being characterized by high throughput techniques to better define the similarities and differences between those models and the human disease, and to determine whether particular models may be useful for specific targeted therapies in pre-clinical studies. Although profiling of mRNA expression provides important information of gene expression, the development of proteomic technologies will allow for an even more precise global insight into cellular signaling and structural alterations during prostate carcinogenesis. Not only will the "omic" revolution change basic science, but it will lead to a new era of molecular medicine.     

Inhibition of SIRT6 in prostate cancer reduces cell viability and increases sensitivity to chemotherapeutics

SI RT6 is an important histone modifying protein that regulates DNA repair, telomere maintenance, energy metabolism, and target gene expression. Recently SIRT6 has been identifi ed as a tumor suppressor and is downregulated in certain cancer types, but not in other cancers. From deposited gene profi ling studies we found that SIRT6 was overexpressed in prostate tumors, compared with normal or paratumor prostate tissues. Tissue microarray studies confi rmed the higher levels of SIRT6 in both prostate tumor tissues and prostate cancer cells than in their normal counterparts. Knockdown of SIRT6 in human prostate cancer cells led to sub-G1 phase arrest of cell cycle, increased apoptosis, elevated DNA damage level and decrease in BCL2 gene expression. Moreover, SIRT6-deficiency reduced cell viability and enhanced chemotherapeutics sensitivity. Taken together, this study provides the fi rst evidence of SIRT6 overexpression in human prostate cancer, and SIRT6 regulation could be exploited for prostate cancer therapy.     

Effector CD4+ T cell expression signatures and immune-mediated disease associated genes

Genome-wide association studies (GWAS) in immune-mediated diseases have identified over 150 associated genomic loci. Many of these loci play a role in T cell responses, and regulation of T cell differentiation plays a critical role in immune-mediated diseases; however, the relationship between implicated disease loci and T cell differentiation is incompletely understood. To further address this relationship, we examined differential gene expression in na?ve human CD4+ T cells, as well as in in vitro differentiated Th1, memory Th17-negative and Th17-enriched CD4+ T cells subsets using microarray and RNASeq. We observed a marked enrichment for increased expression in memory CD4+ compared to na?ve CD4+ T cells of genes contained among immune-mediated disease loci. Within memory T cells, expression of disease-associated genes was typically increased in Th17-enriched compared to Th17-negative cells. Utilizing RNASeq and promoter methylation studies, we identified a differential regulation pattern for genes solely expressed in Th17 cells (IL17A and CCL20) compared to genes expressed in both Th17 and Th1 cells (IL23R and IL12RB2), where high levels of promoter methylation are correlated to near zero RNASeq levels for IL17A and CCL20. These findings have implications for human Th17 celI plasticity and for the regulation of Th17-Th1 expression signatures. Importantly, utilizing RNASeq we found an abundant isoform of IL23R terminating before the transmembrane domain that was enriched in Th17 cells. In addition to molecular resolution, we find that RNASeq provides significantly improved power to define differential gene expression and identify alternative gene variants relative to microarray analysis. The comprehensive integration of differential gene expression between cell subsets with disease-association signals, and functional pathways provides insight into disease pathogenesis.     

Cancer classification from the gene expression profiles by Discriminant Kernel-PLS

Cancer diagnosis depending on microarray technology has drawn more and more attention in the past few years. Accurate and fast diagnosis results make gene expression profiling produced from microarray widely used by a large range of researchers. Much research work highlights the importance of gene selection and gains good results. However, the minimum sets of genes derived from different methods are seldom overlapping and often inconsistent even for the same set of data, partially because of the complexity of cancer disease. In this paper, cancer classification was attempted in an alternative way of the whole gene expression profile for all samples instead of partial gene sets. Here, the three common sets of data were tested by NIPALS-KPLS method for acute leukemia, prostate cancer and lung cancer respectively. Compared to other conventional methods, the results showed wide improvement in classification accuracy. This paper indicates that sample profile of gene expression may be explored as a better indicator for cancer classification, which deserves further investigation.     

Differential gene expression analysis by DNA microarrays technology and its application in molecular oncology

Accumulation of genetic and epigenetic aberrations leads to malignant transformation of normal cells. Functional studies of cancer using genomic and proteomic tools will help to reveal the true complexity of the processes leading to cancer development in humans. Until recently, diagnosis and prognosis of cancer was based on conventional pathologic criteria and epidemiological evidence. Certain tumors were divided only into relatively broad histological and morphological subcategories. Rapidly developing methods of differential gene expression analysis promote the search for clinically relevant genes changing their expression levels during malignant transformation. DNA microarrays offer a unique possibility to rapidly assess the global expression picture of thousands genes in any given time point and compare the detailed combinatory analysis results of global expression profiles for normal and malignant cells at various functional stages or separate experimental conditions. Acquisition of such "genetic portraits" allows searching for regularity and difference in expression patterns of certain genes, understanding their function and pathological importance, and ultimately developing the "molecular nosology" of cancer. This review describes the basis of DNA microarray technology and methodology, and focuses on their applications in molecular classification of tumors, drug sensitivity and resistance studies, and identification of biological markers of cancer.     

Monitoring of representational difference analysis subtraction procedures by global microarrays

Various approaches to the study of differential gene expression are applied to compare cell lines and tissue samples in a wide range of biological contexts. The compromise between focusing on only the important genes in certain cellular processes and achieving a complete picture is critical for the selection of strategy. We demonstrate how global microarray technology can be used for the exploration of the differentially expressed genes extracted through representational difference analysis (RDA). The subtraction of ubiquitous gene fragments from the two samples was demonstrated using cDNA microarrays including more than 32 000 spotted, PCR-amplified human clones. Hybridizations indicated the expression of 9100 of the microarray elements in a macrophage/foam cell atherosclerosis model system, of which many were removed during the RDA process. The stepwise subtraction procedure was demonstrated to yield an efficient enrichment of gene fragments overrepresented in either sample (18% in the representations, 86% after the first subtraction, and 88% after the second subtraction), many of which were impossible to detect in the starting material. Interestingly, the method allowed for the observation of the differential expression of several members of the low-abundant nuclear receptor gene family. We also observed a certain background level in the difference products of nondifferentially expressed gene fragments, warranting a verification strategy for selected candidate genes. The differential expression of several genes was verified by real-time PCR.     

A statistical method for identifying differential gene-gene co-expression patterns

MOTIVATION: To understand cancer etiology, it is important to explore molecular changes in cellular processes from normal state to cancerous state. Because genes interact with each other during cellular processes, carcinogenesis related genes may form differential co-expression patterns with other genes in different cell states. In this study, we develop a statistical method for identifying differential gene-gene co-expression patterns in different cell states. RESULTS: For efficient pattern recognition, we extend the traditional F-statistic and obtain an Expected Conditional F-statistic (ECF-statistic), which incorporates statistical information of location and correlation. We also propose a statistical method for data transformation. Our approach is applied to a microarray gene expression dataset for prostate cancer study. For a gene of interest, our method can select other genes that have differential gene-gene co-expression patterns with this gene in different cell states. The 10 most frequently selected genes, include hepsin, GSTP1 and AMACR, which have recently been proposed to be associated with prostate carcinogenesis. However, genes GSTP1 and AMACR cannot be identified by studying differential gene expression alone. By using tumor suppressor genes TP53, PTEN and RB1, we identify seven genes that also include hepsin, GSTP1 and AMACR. We show that genes associated with cancer may have differential gene-gene expression patterns with many other genes in different cell states. By discovering such patterns, we may be able to identify carcinogenesis related genes.     

Expression of heat shock proteins and heat shock protein messenger ribonucleic acid in human prostate carcinoma in vitro and in tumors in vivo

Heat shock proteins (HSPs) are thought to play a role in the development of cancer and to modulate tumor response to cytotoxic therapy. In this study, we have examined the expression of hsf and HSP genes in normal human prostate epithelial cells and a range of prostate carcinoma cell lines derived from human tumors. We have observed elevated expressions of HSF1, HSP60, and HSP70 in the aggressively malignant cell lines PC-3, DU-145, and CA-HPV-10. Elevated HSP expression in cancer cell lines appeared to be regulated at the post-messenger ribonucleic acid (mRNA) levels, as indicated by gene chip microarray studies, which indicated little difference in heat shock factor (HSF) or HSP mRNA expression between the normal and malignant prostate cell lines. When we compared the expression patterns of constitutive HSP genes between PC-3 prostate carcinoma cells growing as monolayers in vitro and as tumor xenografts growing in nude mice in vivo, we found a marked reduction in expression of a wide spectrum of the HSPs in PC-3 tumors. This decreased HSP expression pattern in tumors may underlie the increased sensitivity to heat shock of PC-3 tumors. However, the induction by heat shock of HSP genes was not markedly altered by growth in the tumor microenvironment, and HSP40, HSP70, and HSP110 were expressed abundantly after stress in each growth condition. Our experiments indicate therefore that HSF and HSP levels are elevated in the more highly malignant prostate carcinoma cells and also show the dominant nature of the heat shock-induced gene expression, leading to abundant HSP induction in vitro or in vivo.     

Selection of reference genes for gene expression studies in human neutrophils by real-time PCR

Background  

Reference genes, which are often referred to housekeeping genes, are frequently used to normalize mRNA levels between different samples. However the expression level of these genes may vary among tissues or cells, and may change under certain circumstances. Thus the selection of reference gene(s) is critical for gene expression studies. For this purpose, 10 commonly used housekeeping genes were investigated in isolated human neutrophils.     

Individual-specific variation of gene expression in peripheral blood leukocytes

DNA microarray technology is used to determine gene expression profiles of various cell types, especially abnormal cells, such as cancer. By contrast, relatively little attention has been given to expression profiling of normal tissues. Here we describe studies of gene expression in peripheral blood leukocytes (PBL) from normal individuals sampled multiple times over periods ranging from several weeks up to 6 months. We demonstrate stable patterns of gene expression that differ between individuals. Among the genes whose expression varies by individual is a group of genes responsive to interferon stimulation. Certain individuals ( approximately 10-20% of those tested) showed higher baseline levels and lower inducibility of these genes in response to in vitro interferon stimulation. These studies demonstrate the feasibility of using DNA microarrays to measure the variations in gene expression of PBL from different individuals in response to environmental and genetic factors.