Metagenomic analysis of fungal assemblages at a regional scale in high-altitude temperate forest soils: alternative methods to determine diversity, composition and environmental drivers - Hereira-Pacheco, Stephanie; Arias-Del Razo, Itzel; Miranda-Carrazco, Alejandra; Dendooven, Luc; Estrada-Torres, Arturo; Navarro-Noya, Yendi E. (PeerJ, 2025)
Background Understanding the diversity and distribution of fungal communities at a regional scale is important since fungi play a crucial role in ecosystem functioning. Our study used environmental metagenomics to determine fungal communities in mountainous forest soils in the central highlands of Mexico. Methods We used four different bioinformatic workflows to profile fungal assemblages, i.e., Geneious+UNITE, single- and paired-end microbial community profiling (MiCoP), and Kraken2. Results The workflows yielded different results; one detected a higher abundance of ectomycorrhizal (EcM) and saprophytic fungi, while the other identified more saprophytic and pathogenic fungi. Environmental, vegetation, and geographical factors determined the spatial distribution of soil fungi at a regional scale. Potential hydrogen (pH), calcium (Ca), magnesium (Mg), and silt content were detected as common drivers of fungal communities across different datasets enriched towards a functional guild. Vegetation traits were found to be more influential in shaping symbiotrophic fungi composition than saprotrophic and pathogenic fungi. This highlights the importance of considering vegetation traits when studying fungal community diversity and distribution. Clustering patterns of sampling points near the volcanoes indicated shared environmental and vegetation characteristics. A weak but significant distance decay in taxonomic similarity revealed that dispersal limitation contributed to fungal community composition, although it was not the primary factor in this study. Overall, this study provides important insights into the challenges and opportunities of studying fungal communities at a regional scale using metagenomic data.
Keywords: Bioinformatic workflows; Ecological omics; Environmental DNA; Forest microbiome; Soil mycobiome