The Subsystems Approach to Genome Annotation and its Use in the Project to Annotate 1000 Genomes

By R. Overbeek, T. Begley, R. Butler, J. V. Choudhuri, Han-Yu Chuang, Matthew Cohoon, V. de Crécy-Lagard, Naryttza N. Diaz, T. Disz, Robert A. Edwards and 30 more. Nucleic Acids Research, 2005

2,037 citations recorded by the source corpus.

The release of the 1000th complete microbial genome will occur in the next two to three years. In anticipation of this milestone, the Fellowship for Interpretation of Genomes (FIG) launched the Project to Annotate 1000 Genomes. The project is built around the principle that the key to improved accuracy in high-throughput annotation technology is to have experts annotate single subsystems over the complete collection of genomes, rather than having an annotation expert attempt to annotate all of the genes in a single genome. Using the subsystems approach, all of the genes implementing the subsystem are analyzed by an expert in that subsystem. An annotation environment was created where populated subsystems are curated and projected to new genomes. A portable notion of a populated subsystem was defined, and tools developed for exchanging and curating these objects. Tools were also developed to resolve conflicts between populated subsystems. The SEED is the first annotation environment that supports this model of annotation. Here, we describe the subsystem approach, and offer the first release of our growing library of populated subsystems. The initial release of data includes 180 177 distinct proteins with 2133 distinct functional roles. This data comes from 173 subsystems and 383 different organisms.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/a18b748f9165825778ab32d4327953aede8c1e32

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Citations in the corpus

The SEED and the Rapid Annotation of microbial genomes using Subsystems Technology (RAST) (2013, methodology): “(5) Iteratively retrain GLIMMER3 on the set of gene candidates validated by k-mers in step 4.”
The MPI bioinformatics Toolkit as an integrative platform for advanced protein sequence and structure analysis (2016, methodology): “For example, in the ‘Sequence Analysis’ section, we provide links to the function prediction servers The Seed (21) and String (22), and to the de-novo repeat detections servers RADAR (23) and TRUST (24).”
A protocol for generating a high-quality genome-scale metabolic reconstruction (2010, background): “Please refer to the available work and reviews 32–36 .”
Improvements to PATRIC, the all-bacterial Bioinformatics Database and Analysis Resource Center (2016, methodology): “First, they are generated from the PubSEED database, which contains ∼ 12 000 genomes (45,46).”
Metagenomic biomarker discovery and explanation (2011, background): “differ consistently between bacterial microbiomes and viromes across environmental samples described in [70].”
NBC: the Naïve Bayes Classification tool webserver for taxonomic classification of metagenomic reads (2010, background): “Contact: gailr@ece.drexel.edu Received on August 2, 2010; revised on October 12, 2010; accepted on October 29, 2010”
A Bioinformatician's Guide to Metagenomics (2008, background): “There is a variety of Web-based and standalone computational resources available for comparative genomic analyses including ACT (20), MicrobesOnLine (6), CMR (109), ERGO (104), PUMA2 (85), COGENT (52), and IMG (92), but data management systems have only recently been developed specifically for metag”
MaGe: a microbial genome annotation system supported by synteny results (2006, methodology): “In this way, the recently published annotation environment SEED will be integrated into the MaGe system (42).”
Genome-scale models of bacterial metabolism: reconstruction and applications (2008, background): “A reconstruction procedure based on the SEED database was also proposed recently (DeJongh et al ., 2007); it includes a check that the inferred pathways can be properly connected to form a ‘working’ model.”