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Open AccessJournal ArticleDOI

The RAST Server: Rapid Annotations using Subsystems Technology

TLDR
A fully automated service for annotating bacterial and archaeal genomes that identifies protein-encoding, rRNA and tRNA genes, assigns functions to the genes, predicts which subsystems are represented in the genome, uses this information to reconstruct the metabolic network and makes the output easily downloadable for the user.
Abstract
The number of prokaryotic genome sequences becoming available is growing steadily and is growing faster than our ability to accurately annotate them. We describe a fully automated service for annotating bacterial and archaeal genomes. The service identifies protein-encoding, rRNA and tRNA genes, assigns functions to the genes, predicts which subsystems are represented in the genome, uses this information to reconstruct the metabolic network and makes the output easily downloadable for the user. In addition, the annotated genome can be browsed in an environment that supports comparative analysis with the annotated genomes maintained in the SEED environment. The service normally makes the annotated genome available within 12–24 hours of submission, but ultimately the quality of such a service will be judged in terms of accuracy, consistency, and completeness of the produced annotations. We summarize our attempts to address these issues and discuss plans for incrementally enhancing the service. By providing accurate, rapid annotation freely to the community we have created an important community resource. The service has now been utilized by over 120 external users annotating over 350 distinct genomes.

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Journal ArticleDOI

Prokka: Rapid Prokaryotic Genome Annotation

TL;DR: Prokka is introduced, a command line software tool to fully annotate a draft bacterial genome in about 10 min on a typical desktop computer, and produces standards-compliant output files for further analysis or viewing in genome browsers.
Journal ArticleDOI

The Effect of Diet on the Human Gut Microbiome: A Metagenomic Analysis in Humanized Gnotobiotic Mice

TL;DR: A translational medicine pipeline is described where human gut microbial communities and diets are re-created in gnotobiotic mice and the impact on microbe and host is defined using metagenomics, creating a well-defined, representative animal model of the human gut ecosystem.
Journal ArticleDOI

BlastKOALA and GhostKOALA: KEGG Tools for Functional Characterization of Genome and Metagenome Sequences.

TL;DR: Both BlastKOALA and GhostKOalA are automatic annotation servers for genome and metagenome sequences, which perform KO (KEGG Orthology) assignments to characterize individual gene functions and reconstruct KEGG pathways, BRITE hierarchies and K EGG modules to infer high-level functions of the organism or the ecosystem.
References
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Journal ArticleDOI

KEGG: Kyoto Encyclopedia of Genes and Genomes

TL;DR: The Kyoto Encyclopedia of Genes and Genomes (KEGG) as discussed by the authors is a knowledge base for systematic analysis of gene functions in terms of the networks of genes and molecules.
Journal ArticleDOI

tRNAscan-SE: a program for improved detection of transfer RNA genes in genomic sequence.

TL;DR: A program is described, tRNAscan-SE, which identifies 99-100% of transfer RNA genes in DNA sequence while giving less than one false positive per 15 gigabases.
Journal ArticleDOI

KEGG for linking genomes to life and the environment

TL;DR: KEGG PATHWAY is now supplemented with a new global map of metabolic pathways, which is essentially a combined map of about 120 existing pathway maps, and the KEGG resource is being expanded to suit the needs for practical applications.
Journal ArticleDOI

KAAS: an automatic genome annotation and pathway reconstruction server

TL;DR: An implementation of a rapid method to automatically assign K numbers to genes in the genome, enabling reconstruction of KEGG pathways and BRITE hierarchies and achieving a high degree of accuracy when compared with the manually curated K EGG GENES database.
Journal ArticleDOI

Improved microbial gene identification with GLIMMER

TL;DR: Significant technical improvements to GLIMMER are reported that improve its accuracy still further, and a comprehensive evaluation demonstrates that the accuracy of the system is likely to be higher than previously recognized.
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