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    • Lecture QC reads
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  • Annotation
    • Introduction
    • Data preparation
    • QC pre annotation
    • Structural annotation (Concept)
    • Structural annotation (Practical)
    • QC post annotation
    • Visualisation
    • Functional annotation (Concept)
    • Functional annotation (Practical)
    • AMR genes and virulence factors
  • Metabarcoding
    • Introduction to the study
    • 16S rRNA amplicon sequencing
    • Diversity Analysis
  • Pangenome and phylogenomics
  • PanExplorer
  • Shotgun Metagenomics
    • Lecture shotgun MG
    • Taxonomic profiling
    • MAG assembly and binning
  • Cheat sheets
    • Genome annotation tools
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    • Functional Annotation

    Functional Annotation


    Functional annotation assigns biological meaning to genomic features by predicting the functions of their gene products and linking them to known biological knowledge. While structural annotation identifies genes and their genomic organization, functional annotation seeks to understand what these genes do and how their products contribute to cellular processes.

    For protein-coding genes, functional annotation can identify protein families, conserved domains, enzymatic activities, metabolic pathways, and functional relationships. Resources such as InterPro, eggNOG, KEGG, and Gene Ontology (GO) provide complementary information for characterizing gene products and organizing them into broader biological systems.

    Functional annotation can also help reconstruct the metabolic potential of an organism by identifying enzymes and evaluating the completeness of metabolic pathways and functional modules. At the genome level, these annotations provide insight into an organism’s physiology, ecological adaptations, and potential biological capabilities.

    However, functional annotation is largely predictive: sequence similarity or the presence of a conserved domain does not necessarily establish the precise function of a gene product. Annotation reliability depends on the quality of reference databases, the evolutionary relationships between proteins, and the specificity of the available evidence. Predicted functions should therefore be interpreted according to their supporting evidence, with experimental validation providing stronger confirmation when available.