Seaver, S. M., Gerdes, S., Frelin, O., Lerma-Ortiz, C., Bradbury, L. M., Zallot, R., Hasnain, G., Niehaus, T. D., El Yacoubi, B., Pasternak, S., Olson, R., Pusch, G., Overbeek, R., Stevens, R., de Crecy-Lagard, V., Ware, D., Hanson, A. D., Henry, C. S. (June 2014) High-throughput comparison, functional annotation, and metabolic modeling of plant genomes using the PlantSEED resource. Proceedings of the National Academy of Sciences of the United States of America, 111 (26). pp. 9645-9650. ISSN 0027-8424
Preview |
PDF (Paper)
Ware PNAS 2014b.pdf - Published Version Download (724kB) | Preview |
Abstract
The increasing number of sequenced plant genomes is placing new demands on the methods applied to analyze, annotate, and model these genomes. Today's annotation pipelines result in inconsistent gene assignments that complicate comparative analyses and prevent efficient construction of metabolic models. To overcome these problems, we have developed the PlantSEED, an integrated, metabolism-centric database to support subsystems-based annotation and metabolic model reconstruction for plant genomes. PlantSEED combines SEED subsystems technology, first developed for microbial genomes, with refined protein families and biochemical data to assign fully consistent functional annotations to orthologous genes, particularly those encoding primary metabolic pathways. Seamless integration with its parent, the prokaryotic SEED database, makes PlantSEED a unique environment for cross-kingdom comparative analysis of plant and bacterial genomes. The consistent annotations imposed by PlantSEED permit rapid reconstruction and modeling of primary metabolism for all plant genomes in the database. This feature opens the unique possibility of model-based assessment of the completeness and accuracy of gene annotation and thus allows computational identification of genes and pathways that are restricted to certain genomes or need better curation. We demonstrate the PlantSEED system by producing consistent annotations for 10 reference genomes. We also produce a functioning metabolic model for each genome, gapfilling to identify missing annotations and proposing gene candidates for missing annotations. Models are built around an extended biomass composition representing the most comprehensive published to date. To our knowledge, our models are the first to be published for seven of the genomes analyzed.
| Item Type: | Paper |
|---|---|
| Subjects: | bioinformatics > genomics and proteomics > annotation bioinformatics > genomics and proteomics bioinformatics > genomics and proteomics > genetics & nucleic acid processing > genomes Investigative techniques and equipment > assays > next generation sequencing organism description > plant Investigative techniques and equipment > assays > whole genome sequencing |
| CSHL Authors: | |
| Communities: | CSHL labs > Ware lab |
| Depositing User: | Matt Covey |
| Date: | 9 June 2014 |
| Date Deposited: | 20 Jun 2014 19:37 |
| Last Modified: | 16 Jul 2021 20:17 |
| PMCID: | PMC4084441 |
| Related URLs: | |
| URI: | https://repository.cshl.edu/id/eprint/30316 |
Actions (login required)
 |
Administrator's edit/view item |
