Functional genomic analyses of emerging Cryptococcus subtypes in North America

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DESCRIPTION (provided by applicant): Clinically and epidemiologically novel populations of Cryptococcus gattii have recently emerged in North America. It is now feasible, and necessary, to examine the "population genome" of C. gattii subtypes to identify genomic associations with its phenotypic differences. The plan described in this proposal is to elucidate genomic causes of clinical disease, outcome and other differences by conducting large-scale whole genome sequence and expression comparisons among the major groups and subgroups of C. gattii in North America. Although some recent studies have identified apparent gene expression variation that may help explain some phenotypic differences, there have been inconsistent results, perhaps due to the limited number of isolates analyzed within the targeted subtypes. The first part of the described approach is to sequence 200 genomes of C. gattii (~18Mb genome), including all known isolates of the new North American strain (VGIIc), and highly diverse samples of the other VGII populations in North America and from around the world, providing more data than previously available for comparative analysis. In addition, we will conduct transcriptome analysis of each genotype under various growth conditions. This bioinformatic-based analytical approach will include genomic component comparisons within and between populations, targeted gene sequence variations, recombination analysis, phylogenetics, and expression analysis. This will permit the identification of the pan genome within these populations, including the stable (core) genome as well as the plastic (accessory) genome which maybe more mutable and prone to recombination. The availability of comprehensive metadata sets with the sequenced isolates will allow for statistical analyses of the association between genomic changes and clinical and epidemiological features. This genomic-transcriptomic-epidemiologic approach can provide improved clinical outcome prediction based on genome content. Beyond the design, a major strength of this proposal is that it brings together world-class genomics, bioinformatics, mycological, clinical and epidemiological expertise. In addition, access to comprehensive strain repositories with associated clinical and epidemiological metadata will allow for further targeted and exploratory approaches to this emerging health problem. These are foundational studies essential for translating genomic information into diagnostics and therapeutic actions.