The structure of associations: Method insights from analyzing 28 clinical isolates of Cryptococcus neoformans. (7th March 2023) - Vélez, Nórida; Vega-Vela, Nelson; Clay, Oliver Keatinge; Parra-Giraldo, Claudia-Marcela
Abstract: Clinical isolates of a fungal pathogen from a single region or country often exhibit structural clonality or phylogenetic clustering at the sequence or MLST level; such population structure can persist also in larger samples. In efforts to improve causal understanding of pathogenesis at the molecular level, genome-wide association screening methods initially designed for other kingdoms have been applied to fungi. The example of a Colombian dataset of 28 clinical Cryptococcus neoformans VNI isolates indicates where the output from standard pipelines may need to be analyzed in new ways in order to efficiently extract hypotheses for experiments from fungal genotype–phenotype data. Lay Summary: Collections of clinical isolates of a human fungal pathogen can consist of clusters of genetically similar isolates. Such clustering complicates the screening for genetic associations with clinically relevant traits. We propose new methods, illustrating them for the fungus causing cryptococcosis.