Graphite: painting genomes using a colored de Bruijn graph.

Area of Science:

• Genomics
• Bioinformatics
• Microbial Ecology

Background:

• The exponential growth of microbial sequence data presents challenges in large-scale comparative genomics.
• Interpreting thousands of genome matches is computationally intensive and time-consuming.

Purpose of the Study:

• To develop a computational tool for efficient and accurate analysis of large microbial genomic datasets.
• To reduce the complexity of genomic comparisons and facilitate the identification of significant biological findings.

Main Methods:

• Development of Graphite, a novel tool utilizing colored de Bruijn graphs (cDBGs).
• Graphite employs a 'genome painting' approach to identify local best matches along query genomes.
• The method focuses on the most relevant genomic matches for each query region.

Main Results:

• Graphite effectively reduces the number of matches requiring interpretation.
• The tool successfully identified extensive gene sharing among hundreds of *Campylobacter* genomes.
• A previously unknown plasmid in *C. coli* was found to match a *C. jejuni* chromosome.

Conclusions:

• Genome painting with cDBGs, as implemented in Graphite, overcomes computational hurdles in large-scale genomic analysis.
• This approach can uncover novel biological phenomena and facilitate microbial strain tracking and genomic forensics.