MEGANTE
MEGANTE annotates plant genomes by executing integrated analyses to predict exon–intron structures, identify open reading frames (ORFs), and assign functional annotations from similarity and domain searches.
Key Features:
- Automated analysis pipeline: Executes multiple analysis programs to determine consensus exon–intron structures and predict ORFs at each genomic locus.
- Similarity searches: Performs similarity searches against known proteins to support functional annotation of predicted sequences.
- Functional domain identification: Identifies functional domains within predicted ORFs to aid annotation of protein features.
- Annotation visualization: Visualizes annotation tracks using GBrowse for genomic interpretation.
- Output formats: Exports annotation results in Microsoft Excel format for downstream analysis.
- Species coverage: Supports 24 plant species across families including Brassicaceae, Fabaceae, Musaceae, Poaceae, Salicaceae, Solanaceae, Rosaceae, and Vitaceae.
- Sequence submission limits: Accepts sequences up to 10 Mb in length and allows saving annotations for up to 100 sequences.
Scientific Applications:
- Gene discovery: Supports identification and structural annotation of genes in plant genomes.
- Functional genomics: Facilitates assignment of putative functions to predicted coding sequences through similarity and domain analyses.
- Comparative genomics: Provides annotated gene models and protein-level information useful for cross-species comparisons.
Methodology:
Integrates multiple bioinformatics algorithms to perform sequence alignment, exon–intron structure prediction, ORF identification, and functional domain searches.
Topics
Details
- Tool Type:
- api
- Operating Systems:
- Linux, Windows, Mac
- Programming Languages:
- JavaScript
- Added:
- 5/17/2018
- Last Updated:
- 12/10/2018
Operations
Publications
Numa H, Itoh T. MEGANTE: A Web-Based System for Integrated Plant Genome Annotation. Plant and Cell Physiology. 2013;55(1):e2-e2. doi:10.1093/pcp/pct157. PMID:24253915. PMCID:PMC3894707.