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Updated: May 13, 2026
08:45
Whole Genome Sequencing of Candida glabrata for Detection of Markers of Antifungal Drug Resistance
Published on: December 28, 2017
Comparative genome analysis and gene finding in Candida species using CGOB
Sarah L Maguire1, Seán S ÓhÉigeartaigh, Kevin P Byrne
1UCD School of Biomolecular and Biomedical Science, Conway Institute, University College Dublin, Belfield, Dublin, Ireland.
Molecular Biology and Evolution
|March 15, 2013
Summary
The improved Candida Gene Order Browser (CGOB) now analyzes 13 Candida species, revealing over 1,500 new genes and aiding evolutionary studies. This tool enhances understanding of fungal genomics and evolution.
Area of Science:
- Mycology
- Genomics
- Bioinformatics
Background:
- The Candida Gene Order Browser (CGOB) is a crucial tool for visualizing and analyzing synteny in Candida species.
- Accurate orthologous gene sets are essential for evolutionary analyses in fungi.
Purpose of the Study:
- To describe significant upgrades to the CGOB database and functionality.
- To expand the scope of CGOB to include more Candida species and genomic features.
- To facilitate deeper evolutionary and biotechnological insights into Candida fungi.
Main Methods:
- Restructured the database to utilize genome annotations instead of protein sequences.
- Expanded the species coverage to 13 Candida and related species.
- Incorporated updated genome annotations for several species.
Main Results:
- Genomic features now include non-protein elements like centromeres and tRNA genes.
- Discovered over 1,500 previously unannotated genes across the 13 genomes.
- Identified poorly conserved and rapidly evolving genes.
- Reclassified mating type loci for xylose-degrading species, suggesting C. tenuis is heterothallic.
Conclusions:
- The enhanced CGOB provides a more comprehensive resource for Candida comparative genomics and evolutionary research.
- The expanded dataset and new features enable discovery of novel genes and evolutionary patterns.
- CGOB facilitates access to curated genomic data for pathogens and biotechnologically relevant fungi.
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