FlaGs

FlaGs analyzes and visualizes conservation of gene neighborhoods to investigate operon and gene cluster evolution and infer functional associations between genes.


Key Features:

  • Input (NCBI accessions): Accepts lists of NCBI protein accessions as input for extraction of gene neighborhoods.
  • Homologous grouping: Clusters neighborhood-encoded proteins into homologous groups using sensitive sequence searching.
  • BLASTP against reduced RefSeq: Performs BLASTP searches against a reduced RefSeq database to identify homologs and expand accession sets.
  • Graphical visualization: Produces graphical representations of gene neighborhood conservation across genomes.
  • Phylogenetic annotation: Generates phylogenetic trees annotated with flanking gene conservation.

Scientific Applications:

  • Operon and gene cluster evolution: Comparative analysis of gene neighborhood conservation across evolutionary levels to study operon and cluster evolution.
  • Functional association inference: Prediction of functional linkages between genes based on conserved flanking gene arrangements.
  • Discovery of novel genetic systems: Identification of novel systems such as toxin-antitoxin modules in prokaryotes and bacteriophages.

Methodology:

Accepts NCBI protein accession lists; optionally performs BLASTP searches against a reduced RefSeq database; applies sensitive sequence searching to cluster neighborhood-encoded proteins into homologous groups; generates graphical gene neighborhood maps and can produce phylogenetic trees annotated with flanking gene conservation.

Topics

Details

License:
GPL-3.0
Tool Type:
command-line tool, web application
Programming Languages:
Python
Added:
1/18/2021
Last Updated:
11/24/2024

Operations

Publications

Saha CK, Sanches Pires R, Brolin H, Delannoy M, Atkinson GC. FlaGs and webFlaGs: discovering novel biology through the analysis of gene neighbourhood conservation. Bioinformatics. 2020;37(9):1312-1314. doi:10.1093/bioinformatics/btaa788. PMID:32956448. PMCID:PMC8189683.

PMID: 32956448
PMCID: PMC8189683
Funding: - Vetenskapsrådet (the Swedish Research Council: 2015-04746, 2019-01085

Links