高通量测序 SSSU rRNA ,分析微生物群落的新方法

Title：
Retrieval of a million high-quality, full-length microbial 16S and 18S rRNA gene sequences without primer bias

DOI：
10.1038/nbt.4045

Abstract：
Small subunit ribosomal RNA (SSU rRNA) genes, 16S in bacteria and 18S in eukaryotes, have been the standard phylogenetic markers used to characterize microbial diversity and evolution for decades. However, the reference databases of full-length SSU rRNA gene sequences are skewed to well-studied ecosystems and subject to primer bias and chimerism, which results in an incomplete view of the diversity present in a sample. We combine poly(A)-tailing and reverse transcription of SSU rRNA molecules with synthetic long-read sequencing to generate high-quality, full-length SSU rRNA sequences, without primer bias, at high throughput. We apply our approach to samples from seven different ecosystems and obtain more than a million SSU rRNA sequences from all domains of life, with an estimated raw error rate of 0.17%. We observe a large proportion of novel diversity, including several deeply branching phylum-level lineages putatively related to the Asgard Archaea. Our approach will enable expansion of the SSU rRNA reference databases by orders of magnitude, and contribute to a comprehensive census of the tree of life.

All Authors：
Søren M Karst, Morten S Dueholm, Simon J McIlroy, Rasmus H Kirkegaard, Per H Nielsen & Mads Albertsen

First Authors：
Søren M Karst & Morten S Dueholm

Correspondence：
Mads Albertsen

摘要：

       通过多步骤优化得到小亚基核糖体RNA（SSU rRNA）的全长cDNA，搭配合成长读测序，可用高通量方法获得高质量、无引物偏倚的SSU rRNA全长序列；用该方法分析7种环境样本的微生物群落构成，得到超过一百万个SSU rRNA序列，涵盖细菌、古细菌和真核生物，原始错误率约0.17%，与鸟枪法RNA测序相比无明显偏差；对比现有SILVA数据库，观察到约半数新多样性；该方法可使现有参考数据库以数量级方式扩展，帮助完善对全球微生物的分类和编目。