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This article will explain in detail how to analyze the KEGG Genes database. The content of the article is of high quality, so the editor shares it for you as a reference. I hope you will have a certain understanding of the relevant knowledge after reading this article.

The kegg genes database contains the genetic information of species. Kegg uses its own defined ID to uniquely distinguish each gene, called kegg gene ID.

For each gene, in addition to the corresponding species, chromosome location, ncbi-gene ID,DNA sequence, protein sequence and other basic information, the corresponding KO, module, pathway and other annotation information of the gene will also be given.

KO annotation is the core, and kegg provides two tools for KO annotation of genes.

For the genome of a single species, use the BlastKOALA tool

For environmental microbes, use the GhostKOALA tool to annotate

As of March 7, 2018, the annotations of all genes are as follows:

Http://www.kegg.jp/kegg/docs/genes_statistics.html

Genes are functionally divided into two categories, coding protein genes and non-coding protein genes. From the point of view of annotation information, three kinds of kegg annotations are provided: KO, pathway and Enzyme.

Let's take a closer look at the annotation of the human gene.

At present, there are 20380 protein-coding genes, including 13226 genes with KO annotation, 19172 non-coding genes with KO annotation, only 7376 genes with pathway annotation and only 3261 genes with Enzyme enzyme annotation. Among them, there are only 7376 pathway-related genes, which deserves our attention.

For transcriptome analysis, KEGG enrichment analysis is a commonly used method of functional analysis, but only about 30% of the 20380 protein-coding genes have pathway information, and the rest of the genes without pathway-related information will be ignored in enrichment analysis. Therefore, pathway enrichment analysis still has some limitations.

Here I list the pathway annotations of human, mouse and rat genes.

Orgproteinpathwayhsa20,3807376mmu22,1038197rno23,5038436

Overall, the proportion of genes with pathway annotation information is very low. Pathway is based on our existing cognition. With the deepening and progress of the research, the pathway database will become larger and larger, and there will be more genes with pathway-related information. At present, because of the limitation of our cognition of gene function, we can only study those genes with pathway information. Therefore, in the enrichment analysis, we need to integrate the results of multiple databases, such as GO, Reatcome and other databases.

The kegg genes database contains information about genes, including coding and non-coding genes.

For single genome, BlastKOALA is used for KO annotation, and for macro genome, GhostKOALA is used for annotation.

Due to the limitation of our cognition of gene function at this stage, the proportion of genes with pathway annotation information is relatively low. In functional enrichment analysis, it is suggested to integrate the results of multiple databases.

On how to analyze the KEGG Genes database to share here, I hope that the above content can be of some help to you, can learn more knowledge. If you think the article is good, you can share it for more people to see.

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