Principle of KEGG Pathway Annotation and Enrichment Analysis

In bioinformatics and systems biology, the Kyoto Encyclopedia of Genes and Genomes (KEGG) database is a major resource for the systematic study of biomolecular functions. The KEGG database contains extensive information on metabolic and signaling pathways, making it an essential tool for understanding molecular networks and gene functions. By using KEGG pathway annotation and enrichment analysis, researchers gain a comprehensive view of gene interactions and functional distributions within specific biological processes. This approach is commonly applied in differential gene expression (DEG) or protein analysis, aiming to explore their functional roles and biological significance across various pathways.

 

Principle of KEGG Pathway Annotation

The core principle of KEGG pathway annotation involves aligning gene or protein sequences with standardized pathways in the KEGG database, allowing researchers to identify their functional roles within biological systems. KEGG pathways are categorized into five main classes: Cellular Processes, Environmental Information Processing, Genetic Information Processing, Metabolism, and Organismal Systems. By incorporating genes or proteins into these pathways, KEGG pathway annotation enables researchers to observe their interactions and placements within molecular networks.

 

1. Mapping Gene or Protein Functions

First, target genes or proteins are aligned with sequences in the KEGG database to identify their pathways. Each pathway in KEGG is annotated as a “KEGG Orthology” (KO), representing genes with similar functions across species. KO numbers are assigned to genes through sequence alignment, mapping them to specific pathway locations.

 

2. Extracting Pathway Information

Once mapped onto a pathway, information on signal cascades, metabolic chains, and molecular interactions is extracted from the database. This provides insight into each molecule’s role within the pathway and its connections with other molecules, forming a structured molecular network.

 

3. Functional Annotation and Classification

Based on mapping results, genes or proteins are categorized into specific biological processes and molecular functions. KEGG pathway annotation thus allows for explicit categorization and description of target gene functions within biological roles.

 

Principle of KEGG Enrichment Analysis

Enrichment analysis determines which pathways are statistically overrepresented among differentially expressed genes. By comparing these pathways under specific biological conditions with their random occurrences, researchers identify any statistically significant enrichment. The principle involves comparing the number of target genes in each pathway to the expected random distribution of genes in the database.

 

1. Defining Background and Target Gene Sets

Enrichment analysis requires defining a background gene set and a target gene set. Typically, the background set represents the entire genome, while the target set includes differentially expressed genes. Pathway distributions are then determined through gene alignment.

 

2. Calculating Enrichment

Statistical methods, such as the hypergeometric distribution or Fisher’s exact test, calculate pathway enrichment of target genes based on their pathway frequencies and distribution differences compared to the background set.

 

3. Adjusting P-Values

To correct for multiple comparisons, p-values are adjusted (e.g., via the Benjamini-Hochberg method). Adjusted p-values, often called q-values, signify the statistical significance of pathway enrichment, highlighting pathways with potentially significant biological roles in the study conditions.

 

Importance of KEGG Pathway Annotation and Enrichment Analysis

KEGG pathway annotation and enrichment analysis are widely used in high-throughput omics data analysis. The KEGG database enables researchers to construct genetic and pathway networks quickly, uncovering the potential functions of target genes. Enrichment analysis reveals pathway changes under different conditions or pathological states, providing insights for disease research and drug discovery.

 

KEGG pathway annotation and enrichment analysis align gene or protein sequences with standardized pathways to infer functional roles within biological systems. Enrichment analysis further identifies significant pathways and their biological implications under specific conditions, providing a robust basis for exploring mechanisms and designing experiments.