Xie Chao, Goi Chin Lui Wesley, Huson Daniel H, Little Peter F R, Williams Rohan B H
Singapore Centre for Environmental Life Sciences Engineering, National University of Singapore, Singapore, 117456, Singapore.
Current address: Human Longevity Inc, Singapore, Singapore.
BMC Bioinformatics. 2016 Dec 22;17(Suppl 19):508. doi: 10.1186/s12859-016-1378-x.
Taxonomic profiling of microbial communities is often performed using small subunit ribosomal RNA (SSU) amplicon sequencing (16S or 18S), while environmental shotgun sequencing is often focused on functional analysis. Large shotgun datasets contain a significant number of SSU sequences and these can be exploited to perform an unbiased SSU--based taxonomic analysis.
Here we present a new program called RiboTagger that identifies and extracts taxonomically informative ribotags located in a specified variable region of the SSU gene in a high-throughput fashion.
RiboTagger permits fast recovery of SSU-RNA sequences from shotgun nucleic acid surveys of complex microbial communities. The program targets all three domains of life, exhibits high sensitivity and specificity and is substantially faster than comparable programs.
微生物群落的分类学分析通常使用小亚基核糖体RNA（SSU）扩增子测序（16S或18S）来进行，而环境鸟枪法测序通常侧重于功能分析。大型鸟枪测序数据集包含大量的SSU序列，这些序列可用于进行基于SSU的无偏分类学分析。
在此，我们展示了一个名为RiboTagger的新程序，它能够以高通量方式识别并提取位于SSU基因特定可变区域的具有分类学信息的核糖体标签。
RiboTagger能够从复杂微生物群落的鸟枪法核酸调查中快速恢复SSU-RNA序列。该程序针对生命的所有三个域，具有高灵敏度和特异性，并且比同类程序快得多。
