KEGG: Kyoto Encyclopedia of Genes and Genomes.

Kyoto Encyclopedia of Genes and Genomes (KEGG) is a knowledge base for systematic analysis of gene functions in terms of the networks of genes and molecules. The major component of KEGG is the PATHWAY database that consists of graphical diagrams of biochemical pathways including most of the known metabolic pathways and some of the known regulatory pathways. The pathway information is also represented by the ortholog group tables summarizing orthologous and paralogous gene groups among different organisms. KEGG maintains the GENES database for the gene catalogs of all organisms with complete genomes and selected organisms with partial genomes, which are continuously re-annotated, as well as the LIGAND database for chemical compounds and enzymes. Each gene catalog is associated with the graphical genome map for chromosomal locations that is represented by Java applet. In addition to the data collection efforts, KEGG develops and provides various computational tools, such as for reconstructing biochemical pathways from the complete genome sequence and for predicting gene regulatory networks from the gene expression profiles. The KEGG databases are daily updated and made freely available (http://www.genome.ad.jp/kegg/).     

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/).     

KEGG: kyoto encyclopedia of genes and genomes

KEGG (Kyoto Encyclopedia of Genes and Genomes) is a knowledge base for systematic analysis of gene functions, linking genomic information with higher order functional information. The genomic information is stored in the GENES database, which is a collection of gene catalogs for all the completely sequenced genomes and some partial genomes with up-to-date annotation of gene functions. The higher order functional information is stored in the PATHWAY database, which contains graphical representations of cellular processes, such as metabolism, membrane transport, signal transduction and cell cycle. The PATHWAY database is supplemented by a set of ortholog group tables for the information about conserved subpathways (pathway motifs), which are often encoded by positionally coupled genes on the chromosome and which are especially useful in predicting gene functions. A third database in KEGG is LIGAND for the information about chemical compounds, enzyme molecules and enzymatic reactions. KEGG provides Java graphics tools for browsing genome maps, comparing two genome maps and manipulating expression maps, as well as computational tools for sequence comparison, graph comparison and path computation. The KEGG databases are daily updated and made freely available (http://www. genome.ad.jp/kegg/).     

变异链球菌和血链球菌全代谢途径比对分析

为了比较变异链球菌和血链球菌全代谢途径,依据KEGG数据库(http://www.genome.ad.jp/kegg)对变异链球菌和血链球菌的全部代谢途径作逐项比对。结果显示,二者参与了85个代谢途径,包括多数以相同的酶参与的中央代谢途径,即糖酵解、三羧酸循环、磷酸戊糖途径等,和多数以不同的酶参与的双组分感应系统等。通过变异链球菌和血链球菌整体代谢网络对比,了解了变异链球菌和血链球菌理论上的全部代谢途径,为全面揭示二者代谢交流研究奠定了基础。     

Toward understanding the origin and evolution of cellular organisms

In this era of high‐throughput biology, bioinformatics has become a major discipline for making sense out of large‐scale datasets. Bioinformatics is usually considered as a practical field developing databases and software tools for supporting other fields, rather than a fundamental scientific discipline for uncovering principles of biology. The KEGG resource that we have been developing is a reference knowledge base for biological interpretation of genome sequences and other high‐throughput data. It is now one of the most utilized biological databases because of its practical values. For me personally, KEGG is a step toward understanding the origin and evolution of cellular organisms.     

KEGG as a glycome informatics resource

Bioinformatics approaches to carbohydrate research have recently begun using large amounts of protein and carbohydrate data. In this field called glycome informatics, the foremost necessity is a comprehensive resource for genome-scale bioinformatics analysis of glycan data. Although the accumulation of experimental data may be useful as a reference of biological and biochemical information on carbohydrates, this is insufficient for bioinformatics analysis. Thus, we have developed a glycome informatics resource (http://www.genome.jp/kegg/glycan/) in KEGG (Kyoto Encyclopedia of Genes and Genomes), an integrated knowledge base of protein networks, genomic information, and chemical information. This review describes three noteworthy features: (1) GLYCAN, a database of carbohydrate structures; (2) glycan-related pathways; and (3) Composite Structure Map (CSM), a map illustrating all possible variations of carbohydrate structures within organisms. GLYCAN includes two useful tools: an intuitive drawing tool called KegDraw, and an efficient glycan search and alignment tool called KEGG Carbohydrate Matcher (KCaM). KEGG's glycan biosynthesis and metabolism pathways, integrating carbohydrate structures, proteins, and reactions, are also a pivotal resource. CSM is constructed as a bridge between carbohydrate functions and structures. CSM is able to display, for example, expression data of glycosyltransferases in a compact manner. In all the KEGG resources, various objects including KEGG pathways, chemical compounds, as well as carbohydrate structures are commonly represented as graphs, which are widely studied and utilized in the computer science field.     

Apoptosis pathways and osteoporosis: An approach to genomic analysis

Background

Osteoporosis is a disease of the bone system that causes a decrease in skeletal density and degrades skeletal tissue. Decreased bone quality, so that bones are easily broken, damaged and fractured, is an important public health problem. Previous studies have shown that the maintenance of adult bone mass is not only due to changes in bone marrow and bone cells. By regulating apoptosis, they change the lifespan of each individual. This study influences understanding of the function of apoptosis in the pathogenesis of osteoporosis and the importance of controlling the mechanisms of osteoporosis.

Methods

On the National Institute of Biotechnology Information website, Gene Expression Omnibus (GEO) microarray data and GSE551495 GEO profiles were collected. The gene set enrichment analysis tool was used to confirm the enrichment of genetic sets in relation to the gene set. The collection of C2 gene sets is compiled from the KEGG ( https://www.gsea-msigdb.org/gsea/msigdb/human/search.jsp and https://www.kegg.jp/kegg/ ) online database and REACTOME ( https://www.gsea-msigdb.org/gsea/msigdb/human/search.jsp and https://reactome.org/ ) pathway analysis. The Search Tool for the Retrieval of Interaction Genes (STRING) website was used to construct and select proteins and genes. The comparative toxicological genomic database (CTD) tools can be used to predict the relationship between apoptosis, osteoporosis-related genes and interactions between central genes and osteoporosis.

Results

These results generally expand our understanding of the path of apoptosis in osteoporosis. We have discovered genes CASP9, CASP8, CASP3, BAX and TP53 associated with osteoporosis. In activation of KEGG apoptosis and REACTOME, caspase activation through the extrinsic apoptotic signaling pathway is characterized by the identification of a subcollection of C2. Other STRINGs show the formation of protein networks and central gene selection, and CTD can accurately predict the relationship between these apoptosis pathways and central genes.

Conclusions

Our research has highlighted the importance of the osteoporosis pathway associated with osteoporosis apoptosis with several analytical approaches. These results have broadened our understanding of the pathways of osteoporosis apoptosis. It is particularly possible to predict the sensitivity and vulnerability to osteoporosis.     

LIGAND: chemical database of enzyme reactions

LIGAND is a composite database comprising three sections: ENZYME for the information of enzyme molecules and enzymatic reactions, COMPOUND for the information of metabolites and other chemical compounds, and REACTION for the collection of substrate-product relations. The current release includes 3390 enzymes, 5645 compounds and 5207 reactions. The database is indispensable for the reconstruction of metabolic pathways in the completely sequenced organisms. The LIGAND database can be accessed through the WWW (http://www.genome.ad.jp/dbget/ligand.html ) or may be downloaded by anonymous FTP (ftp://kegg.genome.ad.jp/molecules/ligand/ ).     

LIGAND: database of chemical compounds and reactions in biological pathways

LIGAND is a composite database comprising three sections: COMPOUND for the information about metabolites and other chemical compounds, REACTION for the collection of substrate–product relations representing metabolic and other reactions, and ENZYME for the information about enzyme molecules. The current release (as of September 7, 2001) includes 7298 compounds, 5166 reactions and 3829 enzymes. In addition to the keyword search provided by the DBGET/LinkDB system, a substructure search to the COMPOUND and REACTION sections is now available through the World Wide Web (http://www.genome.ad.jp/ligand/). LIGAND may be also downloaded by anonymous FTP (ftp://ftp.genome.ad.jp/pub/kegg/ligand/).     

Comprehensive DNA microarray analysis of Bacillus subtilis two-component regulatory systems.

It has recently been shown through DNA microarray analysis of Bacillus subtilis two-component regulatory systems (DegS-DegU, ComP-ComA, and PhoR-PhoP) that overproduction of a response regulator of the two-component systems in the background of a deficiency of its cognate sensor kinase affects the regulation of genes, including its target ones. The genome-wide effect on gene expression caused by the overproduction was revealed by DNA microarray analysis. In the present work, we newly analyzed 24 two-component systems by means of this strategy, leaving out 8 systems to which it was unlikely to be applicable. This analysis revealed various target gene candidates for these two-component systems. It is especially notable that interesting interactions appeared to take place between several two-component systems. Moreover, the probable functions of some unknown two-component systems were deduced from the list of their target gene candidates. This work is heuristic but provides valuable information for further study toward a comprehensive understanding of the B. subtilis two-component regulatory systems. The DNA microarray data obtained in this work are available at the KEGG Expression Database website (http://www.genome.ad.jp/kegg/expression).     

The commonality of protein interaction networks determined in neurodegenerative disorders (NDDs)

MOTIVATION: Neurodegenerative disorders (NDDs) are progressive and fatal disorders, which are commonly characterized by the intracellular or extracellular presence of abnormal protein aggregates. The identification and verification of proteins interacting with causative gene products are effective ways to understand their physiological and pathological functions. The objective of this research is to better understand common molecular pathogenic mechanisms in NDDs by employing protein-protein interaction networks, the domain characteristics commonly identified in NDDs and correlation among NDDs based on domain information. RESULTS: By reviewing published literatures in PubMed, we created pathway maps in Kyoto Encyclopedia of Genes and Genomes (KEGG) for the protein-protein interactions in six NDDs: Alzheimer's disease (AD), Parkinson's disease (PD), amyotrophic lateral sclerosis (ALS), Huntington's disease (HD), dentatorubral-pallidoluysian atrophy (DRPLA) and prion disease (PRION). We also collected data on 201 interacting proteins and 13 compounds with 282 interactions from the literature. We found 19 proteins common to these six NDDs. These common proteins were mainly involved in the apoptosis and MAPK signaling pathways. We expanded the interaction network by adding protein interaction data from the Human Protein Reference Database and gene expression data from the Human Gene Expression Index Database. We then carried out domain analysis on the extended network and found the characteristic domains, such as 14-3-3 protein, phosphotyrosine interaction domain and caspase domain, for the common proteins. Moreover, we found a relatively high correlation between AD, PD, HD and PRION, but not ALS or DRPLA, in terms of the protein domain distributions. AVAILABILITY: http://www.genome.jp/kegg/pathway/hsa/hsa01510.html (KEGG pathway maps for NDDs).     

A grid layout algorithm for automatic drawing of biochemical networks

MOTIVATION: Visualization is indispensable in the research of complex biochemical networks. Available graph layout algorithms are not adequate for satisfactorily drawing such networks. New methods are required to visualize automatically the topological architectures and facilitate the understanding of the functions of the networks. RESULTS: We propose a novel layout algorithm to draw complex biochemical networks. A network is modeled as a system of interacting nodes on squared grids. A discrete cost function between each node pair is designed based on the topological relation and the geometric positions of the two nodes. The layouts are produced by minimizing the total cost. We design a fast algorithm to minimize the discrete cost function, by which candidate layouts can be produced efficiently. A simulated annealing procedure is used to choose better candidates. Our algorithm demonstrates its ability to exhibit cluster structures clearly in relatively compact layout areas without any prior knowledge. We developed Windows software to implement the algorithm for CADLIVE. AVAILABILITY: All materials can be freely downloaded from http://kurata21.bio.kyutech.ac.jp/grid/grid_layout.htm; http://www.cadlive.jp/ SUPPLEMENTARY INFORMATION: http://kurata21.bio.kyutech.ac.jp/grid/grid_layout.htm; http://www.cadlive.jp/     

Automated interpretation of metabolic capacity from genome and metagenome sequences

The KEGG pathway maps are widely used as a reference data set for inferring high-level functions of the organism or the ecosystem from its genome or metagenome sequence data. The KEGG modules, which are tighter functional units often corresponding to subpathways in the KEGG pathway maps, are designed for better automation of genome interpretation. Each KEGG module is represented by a simple Boolean expression of KEGG Orthology (KO) identifiers (K numbers), enabling automatic evaluation of the completeness of genes in the genome. Here we focus on metabolic functions and introduce reaction modules for improving annotation and signature modules for inferring metabolic capacity. We also describe how genome annotation is performed in KEGG using the manually created KO database and the computationally generated SSDB database. The resulting KEGG GENES database with KO (K number) annotation is a reference sequence database to be compared for automated annotation and interpretation of newly determined genomes.     

A web platform for the network analysis of high-throughput data in melanoma and its use to investigate mechanisms of resistance to anti-PD1 immunotherapy

Cellular phenotypes are established and controlled by complex and precisely orchestrated molecular networks. In cancer, mutations and dysregulations of multiple molecular factors perturb the regulation of these networks and lead to malignant transformation. High-throughput technologies are a valuable source of information to establish the complex molecular relationships behind the emergence of malignancy, but full exploitation of this massive amount of data requires bioinformatics tools that rely on network-based analyses.In this report we present the Virtual Melanoma Cell, an online tool developed to facilitate the mining and interpretation of high-throughput data on melanoma by biomedical researches. The platform is based on a comprehensive, manually generated and expert-validated regulatory map composed of signaling pathways important in malignant melanoma. The Virtual Melanoma Cell is a tool designed to accept, visualize and analyze user-generated datasets. It is available at: https://www.vcells.net/melanoma. To illustrate the utilization of the web platform and the regulatory map, we have analyzed a large publicly available dataset accounting for anti-PD1 immunotherapy treatment of malignant melanoma patients.     

An interspecific linkage map of SSR and intronic polymorphism markers in tomato

Despite the collection and availability of abundant tomato genome sequences, PCR-based markers adapted to large scale analysis have not been developed in tomato species. Therefore, using public genome sequence data in tomato, we developed three types of DNA markers: expressed sequence tag (EST)-derived simple sequence repeat (SSR) markers (TES markers), genome-derived SSR markers (TGS markers) and EST-derived intronic polymorphism markers (TEI markers). A total of 2,047 TES, 3,510 TGS and 674 TEI markers were established and used in the polymorphic analysis of a cultivated tomato (Solanum lycopersicum) ‘LA925’ and its wild relative Solanum pennellii ‘LA716’, parents of the Tomato-EXPEN 2000 mapping population. The polymorphic ratios between parents revealed by the TES, TGS and TEI markers were 37.3, 22.6 and 80.0%, respectively. Those showing polymorphisms were used to genotype the Tomato-EXPEN 2000 mapping population, and a high-density genetic linkage map composed of 1,433 new and 683 existing marker loci was constructed on 12 chromosomes, covering 1,503.1 cM. In the present map, 48% of the mapped TGS loci were located within heterochromatic regions, while 18 and 21% of TES and TEI loci, respectively, were located in heterochromatin. The large number of SSR and SNP markers developed in this study provide easily handling genomic tools for molecular breeding in tomato. Information on the DNA markers developed in this study is available at http://www.kazusa.or.jp/tomato/.     

MPSS: an integrated database system for surveying a set of proteins

SUMMARY: We design and implement an integrated database system called 'multi-protein survey system' (MPSS), which provides a platform to retrieve information about many proteins at a time. This system integrates several important and widely used databases including SwissProt, TrEMBL, PDB and InterPro, plus useful references such as GO and KEGG to other databases. Users may submit a group of protein IDs, entry names, SwissProt/TrEMBL accession numbers or GenBank GIs through MPSS' web interface, and obtain protein annotation information from public databases and pre-computed molecular properties speedily. MPSS can also supply comprehensive information about query proteins, including 3D structures, domains, pathway, gene ontology and visual presentation of mapping to the GO tree and KEGG pathway, to provide an up-to-date view of available knowledge with regard to the structures and molecular functions of proteins under study. AVAILABILITY: MPSS is freely accessible at http://www.scbit.org/mpss/     

LinkinPath: from sequence to interconnected pathway

SUMMARY: LinkinPath is a pathway mapping and analysis tool that enables users to explore and visualize the list of gene/protein sequences through various Flash-driven interactive web interfaces including KEGG pathway maps, functional composition maps (TreeMaps), molecular interaction/reaction networks and pathway-to-pathway networks. Users can submit single or multiple datasets of gene/protein sequences to LinkinPath to (i) determine the co-occurrence and co-absence of genes/proteins on animated KEGG pathway maps; (ii) compare functional compositions within and among the datasets using TreeMaps; (iii) analyze the statistically enriched pathways across the datasets; (iv) build the pathway-to-pathway networks for each dataset; (v) explore potential interaction/reaction paths between pathways; and (vi) identify common pathway-to-pathway networks across the datasets. AVAILABILITY: LinkinPath is freely available to all interested users at http://www.biotec.or.th/isl/linkinpath/.     

The effect of interaction between EtOH dosage and exposure time on gene expression in DPSC

Alcohol (EtOH) dosage and exposure time can affect gene expression. However, whether there exists synergistic effect is unknown. Here, we analyzed the hDPSC gene microarray dataset GSE57255 downloaded from Gene Expression Omnibus and found that the interaction between EtOH dosage and exposure time on gene expression are statistically significant for two probes: 201917_s_at near gene SLC25A36 and 217649_at near gene ZFAND5. GeneMania showed that SLC25A36 and ZFAND5 were related to 20 genes, three of which had alcohol-related functions. WebGestalt revealed that the 22 genes were enriched in 10 KEGG pathways, four of which are related to alcoholic diseases. We explored the possible nonlinear interaction effect and got 172 gene probes with significant p-values. However, no significantly enriched pathways based on the 172 probes were detected. Our analyses indicated a possible molecular mechanism that could help explain why alcohol consumption has both deleterious and beneficial effects on human health.