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del Olmo, V.

Publications and source records attributed to del Olmo, V..

2 recordsLinked to original sources

Reversible haploidisation and convergent genomic routes to antifungal resistance in the Candida parapsilosis species complex

Antifungal resistance is rising among non-albicans Candida, with outbreaks increasingly linked to drug-resistant Candida parapsilosis. Using large-scale experimental evolution under fluconazole and anidulafungin, coupled to phenotyping and genome sequencing, we define resistance strategies across C. parapsilosis, Candida metapsilosis and Candida orthopsilosis. Despite diverse genetic backgrounds, adaptation repeatedly converged on a shared genomic toolkit that combines protein-altering mutations in key regulators and drug targets (including MRR1 and FKS1) with copy-number changes, aneuploidy, as well as loss of heterozygosity driving resistance alleles to homozygosity. Strikingly, drug selection triggered recurrent but reversible haploidisation in C. orthopsilosis, revealing ploidy reduction as a transient, selectable survival strategy. Resistance, particularly after fluconazole selection, imposed fitness costs that promoted compensatory evolution and resistance loss after drug withdrawal. Together, antifungal adaptation in this complex affects convergent targets, while being plastic in its genomic routes, with implications for resistance surveillance and drug cycling therapies.

microbiology↗

JLOH: Inferring Loss of Heterozygosity Blocks from Sequencing Data

Heterozygosity is a genetic condition in which two or more alleles are found at a genomic locus. Among the organisms that are more prone to heterozygosity are hybrids, i.e. organisms that are the offspring of genetically divergent yet still interfertile individuals. One of the most studied aspects is the loss of heterozygosity (LOH) within genomes, where multi-allelic sites lose one of their two alleles by converting it to the other, or by remaining hemizygous at that site. LOH is deeply interconnected with adaptation, especially in hybrids, but the in silico techniques to infer LOH blocks are hardly standardized, and a general tool to infer and analyse them in most genomic contexts and species is missing. Here, we present JLOH, a computational toolkit for the inference and exploration of LOH blocks which only requires commonly available genomic data as input. Starting from mapped reads, called variants and a reference genome sequence, JLOH infers candidate LOH blocks based on single-nucleotide polymorphism density (SNPs/kbp) and read coverage per position. If working with a hybrid organism of known parentals, JLOH is also able to assign each LOH block to its subgenome of origin.

bioinformatics↗