Oncomine数据库在肿瘤研究中的应用

Oncomine 是目前世界上最大的癌基因芯片数据库和综合数据挖掘平台之一,该数据库整合了GEO、TCGA和已发表文献来源的RNA和DNA-seq数据。数据库目前含有715个基因表达数据集（datasheet）、86 733个人体肿瘤组织和正常组织样本的信息,且有新的数据不断更新。Oncomine 数据库囊括的肿瘤类型有19种,包括：膀胱癌、脑/中枢神经系统肿瘤、乳腺癌、宫颈癌、结直肠癌、食管癌、胃癌、头/颈肿瘤、肾癌、白血病、肝癌、肺癌、淋巴瘤、黑色素瘤、骨髓瘤、卵巢癌、胰腺癌、前列腺癌、肉瘤。本文就如何利用Oncomine数据库,进行肿瘤组织中癌基因表达差异性分析以及基因共表达分析、癌基因在肿瘤组织中的表达及拷贝数分析、多组研究数据集的荟萃分析（meta analysis）、以及癌基因表达与患者生存率关系等进行分析。通过该数据库可以对肿瘤癌基因进行研究前的筛查,有利于发现新的肿瘤生物标记物或治疗靶点,为临床科学研究奠定一定的理论基础。     

Graph-based analysis and visualization of experimental results with ONDEX

MOTIVATION: Assembling the relevant information needed to interpret the output from high-throughput, genome scale, experiments such as gene expression microarrays is challenging. Analysis reveals genes that show statistically significant changes in expression levels, but more information is needed to determine their biological relevance. The challenge is to bring these genes together with biological information distributed across hundreds of databases or buried in the scientific literature (millions of articles). Software tools are needed to automate this task which at present is labor-intensive and requires considerable informatics and biological expertise. RESULTS: This article describes ONDEX and how it can be applied to the task of interpreting gene expression results. ONDEX is a database system that combines the features of semantic database integration and text mining with methods for graph-based analysis. An overview of the ONDEX system is presented, concentrating on recently developed features for graph-based analysis and visualization. A case study is used to show how ONDEX can help to identify causal relationships between stress response genes and metabolic pathways from gene expression data. ONDEX also discovered functional annotations for most of the genes that emerged as significant in the microarray experiment, but were previously of unknown function.     

Expansion of the BioCyc collection of pathway/genome databases to 160 genomes

The BioCyc database collection is a set of 160 pathway/genome databases (PGDBs) for most eukaryotic and prokaryotic species whose genomes have been completely sequenced to date. Each PGDB in the BioCyc collection describes the genome and predicted metabolic network of a single organism, inferred from the MetaCyc database, which is a reference source on metabolic pathways from multiple organisms. In addition, each bacterial PGDB includes predicted operons for the corresponding species. The BioCyc collection provides a unique resource for computational systems biology, namely global and comparative analyses of genomes and metabolic networks, and a supplement to the BioCyc resource of curated PGDBs. The Omics viewer available through the BioCyc website allows scientists to visualize combinations of gene expression, proteomics and metabolomics data on the metabolic maps of these organisms. This paper discusses the computational methodology by which the BioCyc collection has been expanded, and presents an aggregate analysis of the collection that includes the range of number of pathways present in these organisms, and the most frequently observed pathways. We seek scientists to adopt and curate individual PGDBs within the BioCyc collection. Only by harnessing the expertise of many scientists we can hope to produce biological databases, which accurately reflect the depth and breadth of knowledge that the biomedical research community is producing.     

The Pathway Tools software

MOTIVATION: Bioinformatics requires reusable software tools for creating model-organism databases (MODs). RESULTS: The Pathway Tools is a reusable, production-quality software environment for creating a type of MOD called a Pathway/Genome Database (PGDB). A PGDB such as EcoCyc (see http://ecocyc.org) integrates our evolving understanding of the genes, proteins, metabolic network, and genetic network of an organism. This paper provides an overview of the four main components of the Pathway Tools: The PathoLogic component supports creation of new PGDBs from the annotated genome of an organism. The Pathway/Genome Navigator provides query, visualization, and Web-publishing services for PGDBs. The Pathway/Genome Editors support interactive updating of PGDBs. The Pathway Tools ontology defines the schema of PGDBs. The Pathway Tools makes use of the Ocelot object database system for data management services for PGDBs. The Pathway Tools has been used to build PGDBs for 13 organisms within SRI and by external users.     

Global Metabolic Reconstruction and Metabolic Gene Evolution in the Cattle Genome

The sequence of cattle genome provided a valuable opportunity to systematically link genetic and metabolic traits of cattle. The objectives of this study were 1) to reconstruct genome-scale cattle-specific metabolic pathways based on the most recent and updated cattle genome build and 2) to identify duplicated metabolic genes in the cattle genome for better understanding of metabolic adaptations in cattle. A bioinformatic pipeline of an organism for amalgamating genomic annotations from multiple sources was updated. Using this, an amalgamated cattle genome database based on UMD_3.1, was created. The amalgamated cattle genome database is composed of a total of 33,292 genes: 19,123 consensus genes between NCBI and Ensembl databases, 8,410 and 5,493 genes only found in NCBI or Ensembl, respectively, and 266 genes from NCBI scaffolds. A metabolic reconstruction of the cattle genome and cattle pathway genome database (PGDB) was also developed using Pathway Tools, followed by an intensive manual curation. The manual curation filled or revised 68 pathway holes, deleted 36 metabolic pathways, and added 23 metabolic pathways. Consequently, the curated cattle PGDB contains 304 metabolic pathways, 2,460 reactions including 2,371 enzymatic reactions, and 4,012 enzymes. Furthermore, this study identified eight duplicated genes in 12 metabolic pathways in the cattle genome compared to human and mouse. Some of these duplicated genes are related with specific hormone biosynthesis and detoxifications. The updated genome-scale metabolic reconstruction is a useful tool for understanding biology and metabolic characteristics in cattle. There has been significant improvements in the quality of cattle genome annotations and the MetaCyc database. The duplicated metabolic genes in the cattle genome compared to human and mouse implies evolutionary changes in the cattle genome and provides a useful information for further research on understanding metabolic adaptations of cattle.     

Axeldb: a Xenopus laevis database focusing on gene expression

Axeldb is a database storing and integrating gene expression patterns and DNA sequences identified in a large-scale in situ hybridization study in Xenopus laevis embryos. The data are organised in a format appropriate for comprehensive analysis, and enable comparison of images of expression pattern for any given set of genes. Information on literature, cDNA clones and their availability, nucleotide sequences, expression pattern and accompanying pictures are available. Current developments are aimed toward the interconnection with other databases and the integration of data from the literature. Axeldb is implemented using an ACEDB database system, and available through the web at http://www.dkfz-heidelberg.de/abt0135/axeldb.htm     

PseudoCyc,a pathway-genome database for Pseudomonas aeruginosa

A pathway-genome database (PGDB) describes the entire genome of an organism, as well as its biochemical pathways, reactions, and enzymes. Our PathoLogic software can generate a PGDB from an annotated genome of an organism, predicting the metabolic reactions and pathways corresponding to the enzymes present in the annotation. We have used PathoLogic to generate a PGDB for PSEUDOMONAS AERUGINOSA, strain PAO1, called 'PseudoCyc', which includes 139 predicted pathways and 800 predicted reactions involving 623 chemical species and 718 enzymes. Analysis of the PathoLogic predictions of arginine metabolism and the beta-ketoadipate pathway, which are landmark pathways in P. AERUGINOSA, showed that they were for the most part correctly predicted. These studies also provided possible locations for two genes involved in the beta-ketoadipate pathway, PCAI and PCAJ, which are missing from the PAO1 annotation. PseudoCyc adds an extended dimension to the genome of P. AERUGINOSA, providing researchers with a helpful tool for the analysis of the genomic, proteomic, and metabolic information of the organism. The finding of the probable location of the PCAI and PCAJ genes is but one example of the discoveries facilitated by such a PGDB. PseudoCyc, along with PGDBs for 12 other organisms, is available at http://BioCyc.org/.     

GENEVESTIGATOR. Arabidopsis microarray database and analysis toolbox

High-throughput gene expression analysis has become a frequent and powerful research tool in biology. At present, however, few software applications have been developed for biologists to query large microarray gene expression databases using a Web-browser interface. We present GENEVESTIGATOR, a database and Web-browser data mining interface for Affymetrix GeneChip data. Users can query the database to retrieve the expression patterns of individual genes throughout chosen environmental conditions, growth stages, or organs. Reversely, mining tools allow users to identify genes specifically expressed during selected stresses, growth stages, or in particular organs. Using GENEVESTIGATOR, the gene expression profiles of more than 22,000 Arabidopsis genes can be obtained, including those of 10,600 currently uncharacterized genes. The objective of this software application is to direct gene functional discovery and design of new experiments by providing plant biologists with contextual information on the expression of genes. The database and analysis toolbox is available as a community resource at https://www.genevestigator.ethz.ch.     

CVD: the intestinal crypt/villus in situ hybridization database

The intestinal crypt/villus in situ hybridization database (CVD) query interface is a web-based tool to search for genes with similar relative expression patterns along the crypt/villus axis of the mammalian intestine. The CVD is an online database holding information for relative gene expression patterns in the mammalian intestine and is based on the scoring of in situ hybridization experiments reported in the literature. CVD contains expression data for 88 different genes collected from 156 different in situ hybridization profiles. The web-based query interface allows execution of both single gene queries and pattern searches. The query results provide links to the most relevant public gene databases. AVAILABILITY: http://pc113.imbg.ku.dk/ps/     

The KEGG databases at GenomeNet

The Kyoto Encyclopedia of Genes and Genomes (KEGG) is the primary database resource of the Japanese GenomeNet service (http://www.genome.ad.jp/) for understanding higher order functional meanings and utilities of the cell or the organism from its genome information. KEGG consists of the PATHWAY database for the computerized knowledge on molecular interaction networks such as pathways and complexes, the GENES database for the information about genes and proteins generated by genome sequencing projects, and the LIGAND database for the information about chemical compounds and chemical reactions that are relevant to cellular processes. In addition to these three main databases, limited amounts of experimental data for microarray gene expression profiles and yeast two-hybrid systems are stored in the EXPRESSION and BRITE databases, respectively. Furthermore, a new database, named SSDB, is available for exploring the universe of all protein coding genes in the complete genomes and for identifying functional links and ortholog groups. The data objects in the KEGG databases are all represented as graphs and various computational methods are developed to detect graph features that can be related to biological functions. For example, the correlated clusters are graph similarities which can be used to predict a set of genes coding for a pathway or a complex, as summarized in the ortholog group tables, and the cliques in the SSDB graph are used to annotate genes. The KEGG databases are updated daily and made freely available (http://www.genome.ad.jp/kegg/).     

Rank of Correlation Coefficient as a Comparable Measure for Biological Significance of Gene Coexpression

Information regarding gene coexpression is useful to predict gene function. Several databases have been constructed for gene coexpression in model organisms based on a large amount of publicly available gene expression data measured by GeneChip platforms. In these databases, Pearson''s correlation coefficients (PCCs) of gene expression patterns are widely used as a measure of gene coexpression. Although the coexpression measure or GeneChip summarization method affects the performance of the gene coexpression database, previous studies for these calculation procedures were tested with only a small number of samples and a particular species. To evaluate the effectiveness of coexpression measures, assessments with large-scale microarray data are required. We first examined characteristics of PCC and found that the optimal PCC threshold to retrieve functionally related genes was affected by the method of gene expression database construction and the target gene function. In addition, we found that this problem could be overcome when we used correlation ranks instead of correlation values. This observation was evaluated by large-scale gene expression data for four species: Arabidopsis, human, mouse and rat.     

Prostate cancer expression profiling by cDNA sequencing analysis.

Prostate cancer is a frequently diagnosed solid tumor that is originated mostly from prostate epithelium. One of the key issues in prostate cancer research is to develop molecular markers that can effectively detect and distinguish the progression and malignancy of prostate tumors. Automated, single-pass cDNA sequencing was utilized to rapidly identify expressed genes in a number of cDNA libraries constructed from various normal and tumor prostatic tissues. These included cell lines as well as short-term epithelial culture. A total of 6604 expressed sequence tags (ESTs) were generated and searched against on-line nucleotide and protein databases. A relational database centric software system was constructed to process, store, and analyze EST data rapidly. cDNA contigs were also obtained by assembly of multiple EST sequences. Protein structural signatures were annotated using motif analysis tools including BLOCKS and an in-house-designed neural network. Cross-library comparisons revealed their unique gene expression profiles. Several differentially expressed cDNA clones were identified, and their expression patterns were confirmed by RNA dot blot and RT-PCR analyses.     

Gene expression profile of human bone marrow stromal cells: high-throughput expressed sequence tag sequencing analysis

Human bone marrow stromal cells (HBMSC) are pluripotent cells with the potential to differentiate into osteoblasts, chondrocytes, myelosupportive stroma, and marrow adipocytes. We used high-throughput DNA sequencing analysis to generate 4258 single-pass sequencing reactions (known as expressed sequence tags, or ESTs) obtained from the 5' (97) and 3' (4161) ends of human cDNA clones from a HBMSC cDNA library. Our goal was to obtain tag sequences from the maximum number of possible genes and to deposit them in the publicly accessible database for ESTs (dbEST of the National Center for Biotechnology Information). Comparisons of our EST sequencing data with nonredundant human mRNA and protein databases showed that the ESTs represent 1860 gene clusters. The EST sequencing data analysis showed 60 novel genes found only in this cDNA library after BLAST analysis against 3.0 million ESTs in NCBI's dbEST database. The BLAST search also showed the identified ESTs that have close homology to known genes, which suggests that these may be newly recognized members of known gene families. The gene expression profile of this cell type is revealed by analyzing both the frequency with which a message is encountered and the functional categorization of expressed sequences. Comparing an EST sequence with the human genomic sequence database enables assignment of an EST to a specific chromosomal region (a process called digital gene localization) and often enables immediate partial determination of intron/exon boundaries within the genomic structure. It is expected that high-throughput EST sequencing and data mining analysis will greatly promote our understanding of gene expression in these cells and of growth and development of the skeleton.     

Congruence of tissue expression profiles from Gene Expression Atlas,SAGEmap and TissueInfo databases

Background

Extracting biological knowledge from large amounts of gene expression information deposited in public databases is a major challenge of the postgenomic era. Additional insights may be derived by data integration and cross-platform comparisons of expression profiles. However, database meta-analysis is complicated by differences in experimental technologies, data post-processing, database formats, and inconsistent gene and sample annotation.

Results

We have analysed expression profiles from three public databases: Gene Expression Atlas, SAGEmap and TissueInfo. These are repositories of oligonucleotide microarray, Serial Analysis of Gene Expression and Expressed Sequence Tag human gene expression data respectively. We devised a method, Preferential Expression Measure, to identify genes that are significantly over- or under-expressed in any given tissue. We examined intra- and inter-database consistency of Preferential Expression Measures. There was good correlation between replicate experiments of oligonucleotide microarray data, but there was less coherence in expression profiles as measured by Serial Analysis of Gene Expression and Expressed Sequence Tag counts. We investigated inter-database correlations for six tissue categories, for which data were present in the three databases. Significant positive correlations were found for brain, prostate and vascular endothelium but not for ovary, kidney, and pancreas.

Conclusion

We show that data from Gene Expression Atlas, SAGEmap and TissueInfo can be integrated using the UniGene gene index, and that expression profiles correlate relatively well when large numbers of tags are available or when tissue cellular composition is simple. Finally, in the case of brain, we demonstrate that when PEM values show good correlation, predictions of tissue-specific expression based on integrated data are very accurate.

     

Web Tools for Rice Transcriptome Analyses

Gene expression databases provide profiling data for the expression of thousands of genes to researchers worldwide. Oligonucleotide microarray technology is a useful tool that has been employed to produce gene expression profiles in most species. In rice, there are five genome-wide DNA microarray platforms: NSF 45K, BGI/Yale 60K, Affymetrix, Agilent Rice 44K, and NimbleGen 390K. Presently, more than 1,700 hybridizations of microarray gene expression data are available from public microarray depositing databases such as NCBI gene expression omnibus and Arrayexpress at EBI. More processing or reformatting of public gene expression data is required for further applications or analyses. Web-based databases for expression meta-analyses are useful for guiding researchers in designing relevant research schemes. In this review, we summarize various databases for expression meta-analyses of rice genes and web tools for further applications, such as the development of co-expression network or functional gene network.