Combined Pan-, Population-, and Phylo-Genomic Analysis of Aspergillus fumigatus Reveals Population Structure and Lineage-Specific Diversity

Abstract

Aspergillus fumigatus is a deadly agent of human fungal disease, where virulence heterogeneity is thought to be at least partially structured by genetic variation between strains. While population genomic analyses based on reference genome alignments offer valuable insights into how gene variants are distributed across populations, these approaches fail to capture intraspecific variation in genes absent from the reference genome. Pan-genomic analyses based on de novo assemblies offer a promising alternative to reference-based genomics, with the potential to address the full genetic repertoire of a species. Here, we use a combination of population genomics, phylogenomics, and pan-genomics to assess population structure and recombination frequency, phylogenetically structured gene presence-absence variation, evidence for metabolic specificity, and the distribution of putative antifungal resistance genes in A. fumigatus. We provide evidence for three distinct populations of A. fumigatus, structured by both gene variation (SNPs and indels) and distinct gene presence-absence variation with unique suites of accessory genes present exclusively in each clade. Accessory genes displayed functional enrichment for nitrogen and carbohydrate metabolism, hinting that populations may be stratified by environmental niche specialization. Similarly, the distribution of antifungal resistance genes and resistance alleles were often structured by phylogeny. Despite low levels of outcrossing, A. fumigatus demonstrated a large pan-genome including many genes unrepresented in the Af293 reference genome. These results highlight the inadequacy of relying on a single-reference genome based approach for evaluating intraspecific variation, and the power of combined genomic approaches to elucidate population structure, genetic diversity, and putative ecological drivers of clinically relevant fungi.

Examination of genome-wide ortholog variation in clinical and environmental isolates of the fungal pathogen Aspergillus fumigatus

“…In the AC set, the clinical isolates IFM59361 and 12-7504462 had the highest number of AC classified genes, 1,570 and 1,521, respectively (Supplementary Material 7), revealing variation on gene copy numbers (absence, single or multiple gene copies) across isolates (Figure 3A). Other studies suggest that the genetic variants— SNPs, indels, and gene presence absence polymorphisms—across A. fumigatus isolates may provide evidence of distinct populations of A. fumigatus (Lofgren et al, 2021).…”

“…Zhao and Gibbons (2018) looked at gene copy number variation across A. fumigatus isolates and found gene presence-absence polymorphisms associated with virulence. Lofgren et al (2021) analyzed gene sequence and gene presence-absence variation to support the existence of three distinct A. fumigatus populations; specific alleles and genes involved in drug resistance were often distributed in a population-specific manner. Barber and collaborators (2021) described the genomic variation associated with clinical isolates related to triazole resistance and virulence factors.…”

Meiosis in the human pathogen Aspergillus fumigatus has the highest known number of crossovers

“…This can now explain the rapid and global distribution of the azole resistant haplotypes, as sex appears to occur in bulb waste material heaps containing azole residues (42)(43)(44). This high recombination rate also affects the interpretation of population-level genome scans as it practically eliminates linkage between genes/markers (12). Understanding the adaptive advantage, or lack thereof, of this unparalleled number of crossovers requires further enquiry.…”

“…With growing interest in population and mendelian genetics of A. fumigatus (8)(9)(10)(11)(12), understanding the outcome of sexual recombination is increasingly important. To investigate this, we constructed the first recombination map of A. fumigatus.…”

“…The result VCF file was processing using PLINK (v1.90) (61). LD was calculated using the r 2 statistic, up to 25 kb of distance between sites, and results were aggregated using a previously published custom script (12). The VCF file used for the genetic mapping was processed similarly.…”