Introducing ribosomal tandem repeat barcoding for fungi
Introducing ribosomal tandem repeat barcoding for fungi
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DOI：
10.1111/1755-0998.12944
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发表时间：
2019-01-01
影响因子：
7.7
通讯作者：
Nilsson, R. Henrik
中科院分区：
文献类型：
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作者：
Wurzbacher, Christian;Larsson, Ellen;Nilsson, R. Henrik
各种核糖体遗传标记的序列比较和分析是鉴定和描述真菌的主要分子方法。然而，新的环境真菌谱系只知道从DNA数据显示显着的差距，在我们的采样真菌王国的分类和标记覆盖率的参考序列数据库。为了便于整合所有核糖体标记的参考数据，我们提出了三套通用引物，允许从核糖体串联重复序列扩增完整的核糖体操纵子。引物覆盖所有核糖体标记：ETS、SSU、ITS1、5.8S、ITS2、LSU和IGS。我们成功地将这些引物与第三代测序（PacBio和Nanopore测序）结合起来，展示了我们对真实真菌标本（Basidiomycota），水生壶菌（Chytridiomycota）和早期分歧真菌（Nephridiophagidae）的一个鲜为人知的谱系的方法。特别是，我们能够以高通量的方式用纳米孔测序生成高质量的参考数据，这表明参考数据的生成可以在常规台式计算机上实现，而无需任何大规模测序设施的参与。Nanopore产生的序列的质量为99.85%，这与桑格测序所述的99.78%准确度相当。通过这项工作，我们希望刺激核糖体参考数据的新的综合标准的产生，最终目标是缩小我们参考数据集中的巨大差距。
Sequence comparison and analysis of the various ribosomal genetic markers are the dominant molecular methods for identification and description of fungi. However, new environmental fungal lineages known only from DNA data reveal significant gaps in our sampling of the fungal kingdom in terms of both taxonomy and marker coverage in the reference sequence databases. To facilitate the integration of reference data from all of the ribosomal markers, we present three sets of general primers that allow for amplification of the complete ribosomal operon from the ribosomal tandem repeats. The primers cover all ribosomal markers: ETS, SSU, ITS1, 5.8S, ITS2, LSU and IGS. We coupled these primers successfully with third-generation sequencing (PacBio and Nanopore sequencing) to showcase our approach on authentic fungal herbarium specimens (Basidiomycota), aquatic chytrids (Chytridiomycota) and a poorly understood lineage of early diverging fungi (Nephridiophagidae). In particular, we were able to generate high-quality reference data with Nanopore sequencing in a high-throughput manner, showing that the generation of reference data can be achieved on a regular desktop computer without the involvement of any large-scale sequencing facility. The quality of the Nanopore generated sequences was 99.85%, which is comparable with the 99.78% accuracy described for Sanger sequencing. With this work, we hope to stimulate the generation of a new comprehensive standard of ribosomal reference data with the ultimate aim to close the huge gaps in our reference datasets.