Department of Ecology and Evolutionary Biology, The University of Kansas, 2041 Haworth Hall, 1200 Sunnyside Avenue, Lawrence, KS, 66045, USA.
Kansas Biological Survey, The University of Kansas, 106 Higuchi Hall, 2101 Constant Ave, Lawrence, KS, 66047, USA.
Mycorrhiza. 2022 Mar;32(2):145-153. doi: 10.1007/s00572-022-01068-3. Epub 2022 Jan 31.
Arbuscular mycorrhizal fungi (AMF; Glomeromycota) are difficult to culture; therefore, establishing a robust amplicon-based approach to taxa identification is imperative to describe AMF diversity. Further, due to low and biased sampling of AMF taxa, molecular databases do not represent the breadth of AMF diversity, making database matching approaches suboptimal. Therefore, a full description of AMF diversity requires a tool to determine sequence-based placement in the Glomeromycota clade. Nonetheless, commonly used gene regions, including the SSU and ITS, do not enable reliable phylogenetic placement. Here, we present an improved database and pipeline for the phylogenetic determination of AMF using amplicons from the large subunit (LSU) rRNA gene. We improve our database and backbone tree by including additional outgroup sequences. We also improve an existing bioinformatics pipeline by aligning forward and reverse reads separately, using a universal alignment for all tree building, and implementing a BLAST screening prior to tree building to remove non-homologous sequences. Finally, we present a script to extract AMF belonging to 11 major families as well as an amplicon sequencing variant (ASV) version of our pipeline. We test the utility of the pipeline by testing the placement of known AMF, known non-AMF, and Acaulospora sp. spore sequences. This work represents the most comprehensive database and pipeline for phylogenetic placement of AMF LSU amplicon sequences within the Glomeromycota clade.
丛枝菌根真菌 (AMF;球囊霉门) 难以培养;因此,建立一种强大的基于扩增子的分类鉴定方法对于描述 AMF 多样性至关重要。此外,由于 AMF 分类群的采样率低且存在偏差,分子数据库无法代表 AMF 多样性的广度,使得数据库匹配方法并不理想。因此,要全面描述 AMF 多样性,需要有一种工具来确定 Glomeromycota 进化枝中基于序列的位置。尽管如此,常用的基因区域,包括 SSU 和 ITS,都不能实现可靠的系统发育定位。在这里,我们提出了一种使用大亚基 (LSU) rRNA 基因扩增子进行 AMF 系统发育测定的改进数据库和工作流程。我们通过包含额外的外群序列来改进我们的数据库和骨干树。我们还通过分别对齐正向和反向读取、对所有树构建使用通用对齐以及在构建树之前实施 BLAST 筛选以去除非同源序列,改进了现有的生物信息学工作流程。最后,我们提供了一个脚本来提取属于 11 个主要家族的 AMF 以及我们工作流程的扩增子测序变体 (ASV) 版本。我们通过测试已知 AMF、已知非 AMF 和 Acaulospora sp. 孢子序列的位置来测试该工作流程的实用性。这项工作代表了 Glomeromycota 进化枝内 AMF LSU 扩增子序列系统发育定位的最全面的数据库和工作流程。