Protax-fungi: a web-based tool for probabilistic taxonomic placement of fungal internal transcribed spacer sequences
Protax-fungi: a web-based tool for probabilistic taxonomic placement of fungal internal transcribed spacer sequences
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DOI：
10.1111/nph.15301
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发表时间：
2018-10-01
期刊：
影响因子：
9.4
通讯作者：
Ovaskainen, Otso
中科院分区：
文献类型：
--
作者：
Abarenkov, Kessy;Somervuo, Panu;Ovaskainen, Otso
参考序列数据库的不完整性和未解决的分类关系使真菌序列的分类位置复杂化。我们开发了Protax-fungi，一种用于真菌内部转录间隔区（ITS）序列分类放置的通用工具，并将其实现到UNITE数据库的PlutoF平台中，用于真菌的分子鉴定。根据根和木材相关真菌的经验数据，Protax-fungi可靠地识别了（至少90%的识别概率）大多数序列的顺序，但只有大约五分之一的物种水平，反映了目前有限的数据库覆盖范围。Protax真菌优于Sintax和Rdb分类器在提高准确性和降低校准误差时，适用于模拟社区的数据，代表物种组的序列数据库覆盖率差。我们应用Protax-fungi来检查Index Fungorum和UNITE数据库的内部索引。这揭示了分类学数据库中的不一致以及参考数据库中的错误标记和序列质量问题。在两个数据库中实施了相应的改进。尽管现存的参考序列数据库的不完整性和未解决的分类学关系，Protax-fungi提供了一个强大的工具，用于进行统计学上可靠的真菌鉴定。
Incompleteness of reference sequence databases and unresolved taxonomic relationships complicates taxonomic placement of fungal sequences. We developed Protax-fungi, a general tool for taxonomic placement of fungal internal transcribed spacer (ITS) sequences, and implemented it into the PlutoF platform of the UNITE database for molecular identification of fungi. With empirical data on root- and wood-associated fungi, Protax-fungi reliably identified (with at least 90% identification probability) the majority of sequences to the order level but only around one-fifth of them to the species level, reflecting the current limited coverage of the databases. Protax-fungi outperformed the Sintax and Rdb classifiers in terms of increased accuracy and decreased calibration error when applied to data on mock communities representing species groups with poor sequence database coverage. We applied Protax-fungi to examine the internal consistencies of the Index Fungorum and UNITE databases. This revealed inconsistencies in the taxonomy database as well as mislabelling and sequence quality problems in the reference database. The according improvements were implemented in both databases. Protax-fungi provides a robust tool for performing statistically reliable identifications of fungi in spite of the incompleteness of extant reference sequence databases and unresolved taxonomic relationships.