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A clustering optimization strategy to estimate species richness of Sebacinales in the tropical Andes based on molecular sequences from distinct DNA regions

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Abstract

Fungi are believed to be diverse in the tropics, but because many groups are only known from their DNA sequences this hampers comparative diversity studies. We investigated mycorrhizal Sebacinales (Basidiomycota) of 67 individuals of Ericaceae and Orchidaceae in a tropical mountain ecosystem in Southern Ecuador to provide a first estimate of whether these fungi are particularly diverse in the Northern Andes. We partially sequenced the internal transcribed spacer (ITS) and large subunit (LSU) regions of the nuclear ribosomal DNA and analyzed them together with all Sebacinales sequences available from GenBank. The clustering optimization technique was used to determine clustering parameters that maximize the comparability between molecular operational taxonomic units (MOTUs) obtained from the distinct loci. Sampling effort and species richness were estimated with rarefaction-accumulation curves and non-parametric estimation using Chao2 and compared between Southern Ecuador and France. Clustering optimization indicated that a 1% LSU distance threshold corresponds to the commonly used 3% dissimilarity threshold for ITS, and that a clustering algorithm close to single-linkage clustering is optimal. The resulting clusters show that about 8–9% of observed Sebacinales MOTUs occur in the study area and that most of these MOTUs are endemic (74%). The widespread MOTUs from Southern Ecuador were also found in Panama, North America and Europe. The estimation of species richness revealed unsaturated sampling of Sebacinales in general and also in our study area. Our results suggest a high diversity of Sebacinales associated with Ericaceae and Orchidaceae at the study site in Southern Ecuador, but no hotspot of Sebacinales in comparison with other areas.

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Abbreviations

BLAST:

Basic local alignment search tool

F :

Linkage fraction

ITS:

Internal transcribed spacer

LSU:

Large subunit (beginning of LSU to primer region LR3)

nrDNA:

Nuclear ribosomal DNA

MOTU:

Molecular operational taxonomic unit

MRI:

Modified Rand index

NCBI:

National Center for Biotechnology Information

PCR:

Polymerase chain reaction

RBSF+S:

Reserva Biológica San Francisco and surroundings

SSU:

Small subunit

T :

Threshold (distance)

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Acknowledgments

We thank Jim Luteyn and Paola Pedraza for help with species identification of Neotropical Ericaceae and Michael Weiß for kindly providing Sebacinales-specific primers. We also express our gratitude to Ingrid Kottke for valuable comments and Tanja Schuster for critically revising earlier versions of this manuscript. We thank Jörg Bendix, Rüttger Rollenbeck and Christoph Reudenbach for providing a map of Ecuador. In addition, the support and assistance of the UTPL in Loja, Ecuador and members of the research group FOR 816 are highly appreciated. This project was funded by the DFG as part of the research unit FOR 816.

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Authors and Affiliations

  1. Department of Biology, Wake Forest University, 1834 Wake Forest Road, Winston-Salem, NC, 27106, USA

    Sabrina D. Setaro

  2. Institut für Evolution und Ökologie, Organismische Botanik, Universität Tübingen, Auf der Morgenstelle 1, 72076, Tübingen, Germany

    Sigisfredo Garnica

  3. Centro de Biología Celular y Molecular, Universidad Técnica Particular de Loja, San Cayetano Alto s/n C.P., 11 01 608, Loja, Ecuador

    Paulo I. Herrera & Juan Pablo Suárez

  4. DSMZ—German Collection of Microorganisms and Cell Cultures, Inhoffenstraße 7B, 38124, Braunschweig, Germany

    Markus Göker

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  1. Sabrina D. Setaro
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Correspondence to Sabrina D. Setaro.

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10531_2011_205_MOESM1_ESM.tif

Fig. S1: Plot of modified Rand indices (MRI) observed during cluster optimization with a linkage fraction of 0.1 (TIFF 404 kb)

Table S1: General information about sequences from all three data sets (XLS 341 kb)

10531_2011_205_MOESM3_ESM.xls

Table S2: Numbers of molecular operational taxonomic units (MOTUs) of Sebacinales obtained with distinct clustering approaches (XLS 24 kb)

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Setaro, S.D., Garnica, S., Herrera, P.I. et al. A clustering optimization strategy to estimate species richness of Sebacinales in the tropical Andes based on molecular sequences from distinct DNA regions. Biodivers Conserv 21, 2269–2285 (2012). https://doi.org/10.1007/s10531-011-0205-y

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