期刊
FUNGAL ECOLOGY
卷 26, 期 -, 页码 74-84出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.funeco.2016.11.009
关键词
Bayesian; Coalescent; Mycorrhizae; Orchid mycorrhizal fungi; Phylogeny; Sebacina; Serendipita; Caladenia; Species delimitation
资金
- Australian Research Council [LP110100408]
- Research School of Biology, The Australian National University
- Australian Research Council [LP110100408] Funding Source: Australian Research Council
The increasing availability of DNA sequence data enables exciting new opportunities for fungal ecology. However, it amplifies the challenge of how to objectively classify the diversity of fungal sequences into meaningful units, often in the absence of morphological characters. Here, we test the utility of modern multilocus Bayesian coalescent-based methods for delimiting cryptic fungal diversity in the orchid mycorrhiza morphospecies Serendipita vermifera. We obtained 147 fungal isolates from Caladenia, a speciose Glade of Australian orchids known to associate with Serendipita fungi. DNA sequence data for 7 nuclear and mtDNA loci were used to erect competing species hypotheses by clustering isolates based on: (a) ITS sequence divergence, (b) Bayesian admixture analysis, and (c) mtDNA variation. We implemented two coalescent-based Bayesian methods to determine which species hypothesis best fitted our data. Both methods found strong support for eight species of Serendipita among our isolates, supporting species boundaries reflected in ITS divergence. Patterns of host plant association showed evidence for both generalist and specialist associations within the host genus Caladenia. Our findings demonstrate the utility of Bayesian species delimitation methods and suggest that wider application of these techniques will readily uncover new species in other cryptic fungal lineages. (C) 2016 Elsevier Ltd and British Mycological Society. All rights reserved.
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