Journal Article

NCBI prokaryotic genome annotation pipeline

Tatiana Tatusova, Michael DiCuccio, Azat Badretdin, Vyacheslav Chetvernin, Eric P. Nawrocki, Leonid Zaslavsky, Alexandre Lomsadze, Kim D. Pruitt, Mark Borodovsky and James Ostell

in Nucleic Acids Research

Volume 44, issue 14, pages 6614-6624
Published in print August 2016 | ISSN: 0305-1048
Published online June 2016 | e-ISSN: 1362-4962 | DOI: http://dx.doi.org/10.1093/nar/gkw569
NCBI prokaryotic genome annotation pipeline

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Recent technological advances have opened unprecedented opportunities for large-scale sequencing and analysis of populations of pathogenic species in disease outbreaks, as well as for large-scale diversity studies aimed at expanding our knowledge across the whole domain of prokaryotes. To meet the challenge of timely interpretation of structure, function and meaning of this vast genetic information, a comprehensive approach to automatic genome annotation is critically needed. In collaboration with Georgia Tech, NCBI has developed a new approach to genome annotation that combines alignment based methods with methods of predicting protein-coding and RNA genes and other functional elements directly from sequence. A new gene finding tool, GeneMarkS+, uses the combined evidence of protein and RNA placement by homology as an initial map of annotation to generate and modify ab initio gene predictions across the whole genome. Thus, the new NCBI's Prokaryotic Genome Annotation Pipeline (PGAP) relies more on sequence similarity when confident comparative data are available, while it relies more on statistical predictions in the absence of external evidence. The pipeline provides a framework for generation and analysis of annotation on the full breadth of prokaryotic taxonomy. For additional information on PGAP see https://www.ncbi.nlm.nih.gov/genome/annotation_prok/ and the NCBI Handbook, https://www.ncbi.nlm.nih.gov/books/NBK174280/.

Journal Article.  6662 words.  Illustrated.

Subjects: Chemistry ; Biochemistry ; Bioinformatics and Computational Biology ; Genetics and Genomics ; Molecular and Cell Biology

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