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NCBI prokaryotic genome annotation pipeline

Describes NCBI's Prokaryotic Genome Annotation Pipeline (PGAP), combining homology-based evidence with ab initio gene prediction across prokaryotes.

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NCBI prokaryotic genome annotation pipeline

By T. Tatusova, Michael DiCuccio, Azat Badretdin et al.Nucleic Acids Research
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Advances in sequencing have made it possible to analyze populations of pathogenic species during disease outbreaks and to study diversity across the whole prokaryotic domain, creating a need for timely, comprehensive automatic genome annotation. Developed by NCBI in collaboration with Georgia Tech, the Prokaryotic Genome Annotation Pipeline (PGAP) combines alignment-based methods with methods that predict protein-coding genes, RNA genes, and other functional elements directly from sequence. A gene-finding tool, GeneMarkS+, uses the combined evidence of protein and RNA placement by homology as an initial annotation map to generate and modify ab initio gene predictions across the whole genome.

The pipeline is designed to lean more on sequence similarity when confident comparative data are available and more on statistical predictions when external evidence is absent, balancing the two sources of information. This design gives PGAP a framework capable of generating and analyzing annotation across the full breadth of prokaryotic taxonomy, supporting both outbreak interpretation and broad diversity studies.

Abstract

Large-scale sequencing of pathogen populations and prokaryotic diversity studies demand comprehensive automatic genome annotation. NCBI, with Georgia Tech, built a pipeline combining alignment-based methods with prediction of protein-coding and RNA genes directly from sequence. Its gene finder, GeneMarkS+, uses combined protein and RNA homology placement as an initial map to refine ab initio predictions genome-wide. PGAP leans on sequence similarity when confident comparative data exist and on statistical predictions otherwise, across the breadth of prokaryotic taxonomy.

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genome annotationprokaryotesgene predictionGeneMarkS+bioinformatics pipeline
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