Molecular identification methods, in particular high-throughput sequencing tools, have greatly improved our knowledge about fungal diversity and biogeography, but many of the recovered taxa from natural environments cannot be identified to species or even higher taxonomic levels. This study addresses the phylogenetic placement of previously unrecognized fungal groups by using two complementary approaches: (i) third-generation amplicon sequencing analysis of DNA from global soil samples, screening out ITS reads of < 90% similarity to other available Sanger sequences, and (ii) analysis of common fungal taxa that were previously indicated to be enigmatic in terms of taxonomic placement based on the ITS sequences alone (so-called top50 sequences). For the global soil samples, we chose to amplify the full rRNA gene operon using four partly overlapping amplicons and multiple newly developed primers or primer combinations that cover nearly all fungi and a vast majority of non-fungal eukaryotes. We extracted the rRNA 18S (SSU) and 28S (LSU) genes and performed phylogenetic analyses against carefully selected reference material. Both SSU and LSU analyses placed most soil sequences and top50 sequences to known orders and classes, but tens of monophyletic groups and single sequences remained outside described taxa. Furthermore, the LSU analyses recovered a few small groups of sequences that may potentially represent novel phyla. We conclude that rRNA genes-based phylogenetic analyses are efficient tools for determining phylogenetic relationships of fungal taxa that cannot be placed to any order or class using ITS sequences alone. However, in many instances, longer rRNA gene sequences and availability of both SSU and LSU reads are needed to improve taxonomic resolution. By leveraging third-generation sequencing from global soil samples, we successfully provided phylogenetic placement for many previously unidentified sequences and broadened our view on the fungal tree of life, with 10–20% new order-level taxa. In addition, the PacBio sequence data greatly extends fungal class-level information in reference databases.

分子鉴定方法，特别是高通量测序工具，极大地提高了我们对真菌多样性和生物地理学的认识，但是从自然环境中回收的许多分类单元无法鉴定到物种甚至更高的分类学水平。这项研究通过使用两种补充方法解决了先前无法识别的真菌群的系统发育定位：（i）对全球土壤样品中DNA进行第三代扩增子测序分析，筛选出与其他可用的Sanger序列相似度小于90％的ITS读数，以及（ ii）普通真菌分类群的分析，以前仅根据ITS序列（所谓的top50序列），就分类学放置而言已被认为是神秘的。对于全球土壤样本，我们选择使用四个部分重叠的扩增子和多个新开发的引物或覆盖几乎所有真菌和绝大多数非真菌真核生物的引物组合来扩增完整的rRNA基因操纵子。我们提取了rRNA 18S（SSU）和28S（LSU）基因，并对精心挑选的参考材料进行了系统发育分析。SSU和LSU分析都将大多数土壤序列和top50序列置于已知的顺序和类别，但是数十个单系群和单个序列仍然不在描述的分类单元之内。此外，LSU分析回收了一些可能潜在代表新门的小序列序列。我们得出结论，基于rRNA基因的系统发育分析是确定真菌类群系统发育关系的有效工具，这些真菌类群不能单独使用ITS序列进行任何排序或分类。但是，在许多情况下，需要更长的rRNA基因序列以及SSU和LSU读数的可用性来提高分类学分辨率。通过利用来自全球土壤样品的第三代测序，我们成功地为许多先前未鉴定的序列提供了系统发育定位，并以10–20％的新订单级分类群拓宽了我们对真菌生命树的视野。此外，PacBio序列数据极大地扩展了参考数据库中的真菌类级别信息。通过利用来自全球土壤样品的第三代测序，我们成功地为许多以前未鉴定的序列提供了系统发育定位，并以10–20％的新订单级分类群拓宽了我们对真菌生命树的视野。此外，PacBio序列数据极大地扩展了参考数据库中的真菌类级别信息。通过利用来自全球土壤样品的第三代测序，我们成功地为许多先前未鉴定的序列提供了系统发育定位，并以10–20％的新订单级分类群拓宽了我们对真菌生命树的视野。此外，PacBio序列数据极大地扩展了参考数据库中的真菌类级别信息。