Introduction. Histoplasma capsulatum is an important fungal pathogen of humans, especially in immunocompromised patients, and the World Health Organisation has listed Histoplasma as a High Priority fungal pathogen. The taxonomy of the genus Histoplasma is still under development, but its only species H. capsulatum has at least of seven lineages, and a range of sublineages. Gap Statement. Allelic multilocus sequence typing (MLST) has been very successfully applied for typing and epidemiology of pathogenic bacteria, but its adoption for fungal pathogens is more limited. Genome sequence-based MLST approaches promise much a higher resolution for comparative phylogenetics, but there are only a small number of genome assemblies available for H. capsulatum. Aim. To develop and validate genome-based MLST typing for H. capsulatum. Methodology. A total of 406 genome assemblies were generated from publicly available Illumina short-read sequencing samples. Selected genome assemblies were subsequently used to generate MLST schemes with chewBBACA, based on whole genome sequences (wgMLST), NCBI-obtained annotations (annMLST) and annotations obtained with Funannotate (fanMLST), and used for lineage identification, and comparative analyses of population structure. Results. Genome assemblies were successfully generated for 406 H. capsulatum samples, with BUSCO completeness scores of over 98%. A subset of 60 genome assemblies was used to generate and validate MLST schemes based on the 60 genome assemblies, 5 genome annotations obtained from Genbank, and 13 genome annotations generated using Funannotate, resulting in schemes with > 8,000 markers. Each of the MLST schemes allowed reproducible separation of all 7 lineages and 6 H. capsulatum Suramericanum sublineages, without the need for high-performance clusters or powerful computing equipment. Comparison of the different schemes using tanglegrams and scatter plots showed good reproducibility (r2 values of 0.8-1.0). Comparison of total sizes of genome assemblies showed significant lineage-dependent size differences, with the Suramericanum, LAmB, India, Capsulatum and Mississippiense lineages averaging a total genome size of 30-33 million bp, and the Africa and Ohiense lineages averaging at 39 million bp. Conclusion. Genome sequence- and especially genome annotation-based MLST analyses are a promising approach that can be adapted as a rapid, high-throughput method for genomic clustering and epidemiological tracing of pathogenic fungi. ### Competing Interest Statement The authors have declared no competing interest.

* Disclaimer: This is not a scientific review, just a few thoughts I had while reading..

CLIMB is a cloud computing infrastructure for microbial bioinformatics — notebook servers, shared storage and reproducible workflows for genomics, metagenomics and pathogen surveillance researchers ac...

Please, please, please do not use ‘dplyr::ntile()’ in an analysis that will be submitted to a regulatory agency. It’s secretly an ill-conceived SQL tool that doesn’t do what you probably want it to, a...

The London and South East University Group (LASE) will be the third largest higher education institution in the UK.

Phylopic, NIH Bioart, Bioicons, Scidraw, Open Science Art, Health Icons, Servier Medical Art, Biodiversity Heritage Library, the Noun Project, Segment Anything, Excalidraw, draw.io, Biographics

Letter to the Editor

Anthropic is now watermarking Claude's output. The mechanism is statistical (not lexical) and a detection hit doesn't mean what most people will assume.

Existing notions of pangenome coordinates rely on hard-to-compute multiple sequence alignments. On the other hand, pangenome-wide exact unique matches (multi-MUMs) can be computed efficiently, and rep...

Influential themed journal issues across the physical mathematical and engineering sciences.

Even with federal grants largely restored, scientists say the Trump administration is still preventing those funds from reaching them. The consequences, they say, are already becoming clear.

Randomness is a powerful tool in the design and analysis of algorithms and data structures for nucleotide sequence data. Nucleotide sequences are not themselves random but are often randomized using hash functions. Despite their widespread use in genomics, there is no comprehensive review of the types of hash functions used and their various applications. In this survey intended for bioinformatic methods developers, we divide hash functions into four categories: scattering hash functions, permutations, minimum perfect hash functions, and locality-sensitive hash functions. For each category, we provide examples of both general-use hash functions that have been applied in nucleotide sequence analysis and hash functions that have been designed specifically for nucleotide sequence analysis. We highlight their salient properties, commonalities, differences, and application areas.