Metabarcoding of insect-associated fungal communities: a comparison of internal transcribed spacer (ITS) and large-subunit (LSU) rRNA markers

昆虫相关真菌群落的宏条形码分析:内部转录间隔区(ITS)和大亚基(LSU)rRNA标记的比较

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Abstract

Full taxonomic characterisation of fungal communities is necessary for establishing ecological associations and early detection of pathogens and invasive species. Complex communities of fungi are regularly characterised by metabarcoding using the Internal Transcribed Spacer (ITS) and the Large-Subunit (LSU) gene of the rRNA locus, but reliance on a single short sequence fragment limits the confidence of identification. Here we link metabarcoding from the ITS2 and LSU D1-D2 regions to characterise fungal communities associated with bark beetles (Scolytinae), the likely vectors of several tree pathogens. Both markers revealed similar patterns of overall species richness and response to key variables (beetle species, forest type), but identification against the respective reference databases using various taxonomic classifiers revealed poor resolution towards lower taxonomic levels, especially the species level. Thus, Operational Taxonomic Units (OTUs) could not be linked via taxonomic classifiers across ITS and LSU fragments. However, using phylogenetic trees (focused on the epidemiologically important Sordariomycetes) we placed OTUs obtained with either marker relative to reference sequences of the entire rRNA cistron that includes both loci and demonstrated the largely similar phylogenetic distribution of ITS and LSU-derived OTUs. Sensitivity analysis of congruence in both markers suggested the biologically most defensible threshold values for OTU delimitation in Sordariomycetes to be 98% for ITS2 and 99% for LSU D1-D2. Studies of fungal communities using the canonical ITS barcode require corroboration across additional loci. Phylogenetic analysis of OTU sequences aligned to the full rRNA cistron shows higher success rate and greater accuracy of species identification compared to probabilistic taxonomic classifiers.

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