RT Journal Article SR Electronic T1 DNA-metabarcoding uncovers the diversity of soil-inhabiting fungi in the tropical island of Puerto Rico JF bioRxiv FD Cold Spring Harbor Laboratory SP 025668 DO 10.1101/025668 A1 Hector Urbina A1 Douglas G. Scofield A1 Matias Cafaro A1 Anna Rosling YR 2015 UL http://biorxiv.org/content/early/2015/08/28/025668.abstract AB Soil fungal communities in tropical regions remain poorly understood. In order to increase the knowledge of diversity of soil-inhabiting fungi, we extracted total DNA from top-organic soil collected in seven localities dominated by four major ecosystems in the tropical island of Puerto Rico. In order to comprehensively characterize the fungal community, we PCR-amplified the ITS2 fungal barcode using newly designed degenerated primers and varying annealing temperatures to minimize primer bias. Sequencing results, obtained using Ion Torrent technology, comprised a total of 566,613 sequences after quality filtering. These sequences were clustered into 4,140 molecular operational taxonomic units (MOTUs) after removing low frequency sequences and rarefaction to account for differences in read depth between samples. Our results demonstrate that soil fungal communities in Puerto Rico are structured by ecosystem. Ascomycota, followed by Basidiomycota, dominates the diversity of fungi in soil. Amongst Ascomycota, the recently described soil-inhabiting class Archaeorhizomycetes was present in all the localities and taxa in this class were among the most commonly observed MOTUs. The Basidiomycota community was dominated by soil decomposers and ectomycorrhizal fungi with a distribution strongly affected by local variation to a greater degree than Ascomycota.DNADeoxyribonucleic acidEMFEctomycorrhizal fungiHBHigh abundanceITSInternal transcribed spacer 2 of the rRNA geneLBLow abundanceLSULarge subunit of rRNA geneMOTUMolecular operational taxonomic unitNCBINational Center for Biotechnology InformationNFNational forestNGSNext generation sequencingNMDSNon-metric multidimensional scalingPCRPolymerase chain reactionqPCRQuantitative PCRSFState forestTSCTwo step clustering