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Updated: Aug 17, 2026

Isolation, Characterization, and Total DNA Extraction to Identify Endophytic Fungi in Mycoheterotrophic Plants
Published on: May 5, 2023
Evidence from small-subunit ribosomal RNA sequences for a fungal origin of Microsporidia
William M Fischer1, Jeffrey D Palmer
1Biology Department, Indiana University, Jordan Hall 142, Bloomington, IN 47405-3700, USA. wfischer@alumni.indiana.edu
Abstract:
The phylum Microsporidia comprises a species-rich group of minute, single-celled, and intra-cellular parasites. Lacking normal mitochondria and with unique cytology, microsporidians have sometimes been thought to be a lineage of ancient eukaryotes. Although phylogenetic analyses using small-subunit ribosomal RNA (SSU-rRNA) genes almost invariably place the Microsporidia among the earliest branches on the eukaryotic tree, many other molecules suggest instead a relationship with fungi. Using maximum likelihood methods and a diverse SSU-rRNA data set, we have re-evaluated the phylogenetic affiliations of Microsporidia. We demonstrate that tree topologies used to estimate likelihood model parameters can materially affect phylogenetic searches. We present a procedure for reducing this bias: "tree-based site partitioning," in which a comprehensive set of alternative topologies is used to estimate sequence data partitions based on inferred evolutionary rates. This hypothesis-driven approach appears to be capable of utilizing phylogenetic information that is not available to standard likelihood implementations (e.g., approximation to a gamma distribution); we have employed it in maximum likelihood and Bayesian analysis. Applying our method to a phylogenetically diverse SSU-rRNA data set revealed that the early diverging ("deep") placement of Microsporidia typically found in SSU-rRNA trees is no better than a fungal placement, and that the likeliest placement of Microsporidia among non-long-branch eukaryotic taxa is actually within fungi. These results illustrate the importance of hypothesis testing in parameter estimation, provide a way to address certain problems in difficult data sets, and support a fungal origin for the Microsporidia.
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