Identification of genetic markers of antifungal drug resistance in Saccharomyces hybrids via QTL mapping

Antifungal drug resistance across fungal and yeast pathogens presents one of the current concerns for public health. Understanding the interactions between genetic background and environment are important for the development of new, effective treatments of infections. Allelic variation within populations of Ascomycota as well as hybridisation impacts the phenotype in response to stressful conditions, including to antifungal drugs. Here, we exploited recent advances in multigenerational breeding of Saccharomyces interspecies hybrids to study the impact of hybridisation on antifungal resistance and identify quantitative trait loci (QTL) responsible for the phenotypes. A library of Saccharomyces cerevisiae x S. kudriavzevii hybrid offspring was screened in the presence of sub-lethal concentrations of six antifungal drugs and revealed a broad phenotypic diversity across the progeny. The QTL analysis was carried out comparing alleles between the pools of high and low fitness offspring, identifying hybrid-specific genetic regions involved in resistance to fluconazole, micafungin and flucytosine. We found both drug specific and pleiotropic regions, and through gene ontology and SIFT analysis we identify potential causal genes, such as BCK2 and DNF1 that were validated via reciprocal hemizygosis analysis.We highlighted 41 regions that contain genes not previously associated with resistance phenotypes in the literature. The result of this screening will help identify new pathways contributing to drug resistance, and lead to greater understanding of how allelic variation, hybridisation and evolution affect antifungal drug resistance in yeast and fungi.

Identifier
Source https://data.blue-cloud.org/search-details?step=~012E2BCC899E32A7428C3056102691E072B1510090B
Metadata Access https://data.blue-cloud.org/api/collections/E2BCC899E32A7428C3056102691E072B1510090B
Provenance
Instrument Illumina HiSeq 4000; ILLUMINA
Publisher Blue-Cloud Data Discovery & Access service; ELIXIR-ENA
Publication Year 2024
OpenAccess true
Contact blue-cloud-support(at)maris.nl
Representation
Discipline Marine Science
Temporal Point 2021-01-01T00:00:00Z