SynFind
SynFind identifies conserved syntenic regions across a query genome and multiple target genomes to predict orthologous and homeologous gene positions and support comparative and functional genomics analyses.
Key Features:
- Comprehensive synteny analysis: Identifies conserved syntenic regions across any set of target genomes given a query genome, enabling prediction of orthologous and homeologous gene locations even when genes are absent.
- Scalability for pairwise and multi-genome comparisons: Supports pairwise comparisons and large-scale analyses across many genomes to study genome evolution, gene loss, and transposition dynamics.
- Per-gene and genome-wide reporting: Produces detailed per-gene output and genome-wide datasets including syntenic gene locations and predicted gene positions.
- Functional homolog inference: Infers syntenic homologs to facilitate correlation of functional changes around genes between related organisms.
- Computational infrastructure and reproducibility: Operates within the CoGe job execution framework, providing scalable execution and support for multiple releases of the same organism.
Scientific Applications:
- Gene family studies: Enables investigation of evolutionary relationships and conservation within specific gene families using syntenic context.
- Genome-scale comparative analyses: Supports analyses of genomic architecture, evolution, and patterns of gene loss and transposition across species.
- Functional genomics: Facilitates study of functional changes and evolutionary pressures around genes by linking synteny with putative homologs.
Methodology:
Compares a query genome against multiple target genomes to identify conserved syntenic regions, with computations executed through the CoGe job execution framework.
Topics
Details
- Tool Type:
- web application
- Operating Systems:
- Linux, Windows, Mac
- Added:
- 5/18/2018
- Last Updated:
- 12/10/2018
Operations
Publications
Tang H, Bomhoff MD, Briones E, Zhang L, Schnable JC, Lyons E. SynFind: Compiling Syntenic Regions across Any Set of Genomes on Demand. Genome Biology and Evolution. 2015;7(12):3286-3298. doi:10.1093/gbe/evv219. PMID:26560340. PMCID:PMC4700967.