Data from: Evaluating multilocus Bayesian species delimitation for discovery of cryptic mycorrhizal diversity

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 clade 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.

Usage Notes
FUNECO_605_SerendipitaATP6Sequence data: locus ATP6FUNECO_605_SerendipitaC11488Sequence data: locus C11488FUNECO_605_SerendipitaC11804Sequence data: locus C11804FUNECO_605_SerendipitaC16699Sequence data: locus C16699FUNECO_605_SerendipitaC28586Sequence data: locus C28586FUNECO_605_SerendipitaITS1-4Sequence data: locus ITSFUNECO_605_SerendipitaLSUSequence data: locus LSUFUNECO_605_StarbeastXMLStarbeast XML files for four species delimitation hypotheses: T=2, T=3, T=7, and T=8

随着 DNA 序列数据的日益丰富，真菌生态学领域迎来了令人振奋的新机遇。然而，这同时也加剧了如何客观地将真菌序列多样性划分为具有意义的单元的挑战，尤其是在缺乏形态特征的情况下。本研究旨在检验现代基于多位点贝叶斯合并方法的效用，以界定兰科菌根形态种 Serendipita vermifera 中的隐秘真菌多样性。我们自澳大利亚兰花属 Caladenia（一大家族，已知与 Serendipita 真菌有关联）中获得了 147 株真菌分离株。通过分析 7 个核基因和线粒体 DNA 位点的 DNA 序列数据，我们基于以下三个方面构建了竞争性物种假说：(a) ITS 序列差异，(b) 贝叶斯混合分析，以及 (c) 线粒体 DNA 变异。我们实施了两种基于合并的贝叶斯方法，以确定哪种物种假说最符合我们的数据。两种方法均对 Serendipita 中的八个物种假说提供了强有力的支持，支持了反映在 ITS 差异中的物种界限。宿主植物关联模式显示出在宿主属 Caladenia 中的泛系和专系关联的证据。我们的研究结果表明，贝叶斯物种界定方法的有效性，并暗示这些技术的更广泛应用将迅速揭示其他隐秘真菌谱系中的新物种。

使用说明
FUNECO_605_SerendipitaATP6 序列数据：位点 ATP6
FUNECO_605_SerendipitaC11488 序列数据：位点 C11488
FUNECO_605_SerendipitaC11804 序列数据：位点 C11804
FUNECO_605_SerendipitaC16699 序列数据：位点 C16699
FUNECO_605_SerendipitaC28586 序列数据：位点 C28586
FUNECO_605_SerendipitaITS1-4 序列数据：位点 ITS
FUNECO_605_SerendipitaLSU 序列数据：位点 LSU
FUNECO_605_StarbeastXML 四种物种界定假说的 Starbeast XML 文件：T=2，T=3，T=7，和 T=8