New approach for understanding genome variations in KEGG

Abstract

KEGG (Kyoto Encyclopedia of Genes and Genomes; https://www.kegg.jp/ or https://www.genome.jp/kegg/) is a reference knowledge base for biological interpretation of genome sequences and other high-throughput data. It is an integrated database consisting of three generic categories of systems information, genomic information and chemical information, and an additional human-specific category of health information. KEGG pathway maps, BRITE hierarchies and KEGG modules have been developed as generic molecular networks with KEGG Orthology nodes of functional orthologs so that KEGG pathway mapping and other procedures can be applied to any cellular organism. Unfortunately, however, this generic approach was inadequate for knowledge representation in the health information category, where variations of human genomes, especially disease-related variations, had to be considered. Thus, we have introduced a new approach where human gene variants are explicitly incorporated into what we call 'network variants' in the recently released KEGG NETWORK database. This allows accumulation of knowledge about disease-related perturbed molecular networks caused not only by gene variants, but also by viruses and other pathogens, environmental factors and drugs. We expect that KEGG NETWORK will become another reference knowledge base for the basic understanding of disease mechanisms and practical use in clinical sequencing and drug development.

Figure 1.

KEGG consists of eighteen databases in four categories, which are all manually curated except computationally generated SSDB. The databases in the chemical information category are collectively called KEGG LIGAND. The databases in the health information category together with two outside databases, Japanese drug labels obtained from the JAPIC database (http://www.japic.or.jp) and FDA drug labels linked to the DailyMed database (https://dailymed.nlm.nih.gov), are collectively called KEGG MEDICUS.

Figure 2.

A conceptual diagram of the KEGG NETWORK database. In contrast to the traditional approach where Homo sapiens is treated as one of 6000 species in KEGG, the new approach allows variations of human genes and genomes to be explicitly incorporated.

Figure 3.

(A) The MAPK (ERK) signaling pathway in the KEGG pathway map (hsa04010) where the main path from growth factor to ERK kinase is marked in pink. (B) An example of the network variation map (nt06201) as a collection of network elements that correspond to the main path in (A). Coloring of text indicates: green for reference network element, red for gene variant and purple for viral protein.

Figure 4.

Nodes and edges of KEGG network elements.

Figure 5.

A comparison of signaling pathways activated by the oncoprotein K1 of KSHV and the oncogene EML4–ALK in non-small cell lung cancer. The pathways are involved in sustaining proliferative signaling and resisting cell death.

Figure 6.

Examples of drug–target relationships for anticancer drugs that inhibit signaling pathways shown in Figure 3B.

Figure 7.

The EC numbers assigned each year. Blue coloring indicates the fraction of EC numbers in which sequence data for the enzymes used in the original experiments could be identified.