Windows下16S rRNA基因扩增子测序数据分析的简易流程

微生物组数据分析需要掌握Linux系统操作,这对缺乏计算机知识的生物研究人员是一个很大的障碍。为此我们设计了一套在Windows的Linux子系统(WSL)下分析16S rRNA基因扩增子高通量测序数据的简易流程。本流程整合常用的开源软件VSEARCH与QIIME等,能对16S rRNA测序数据进行质量控制、OTU聚类、多样性分析及结果可视化呈现。以唾液微生物组分析为例,详细介绍从原始数据到多样性统计分析过程的参数和命令,及结果解读。教学实践证明,此流程易于学习,并有助于掌握微生物组的基本概念与方法。利用Windows系统最新的WSL功能,本流程方便Windows用户使用大量在Linux上运行的生物信息工具,有助于促进微生物组研究的发展。流程的安装程序与测序数据可从网址(http://www. ligene. cn/win16s/)免费下载使用。     

Bioinformatics matters: The accuracy of plant and soil fungal community data is highly dependent on the metabarcoding pipeline

Fungal communities associated with plants and soil influence plant fitness and ecosystem functioning. They are frequently studied by metabarcoding approaches targeting the ribosomal internal transcribed spacer (ITS), but there is no consensus concerning the most appropriate bioinformatic approach for the analysis of these data. We sequenced an artificial fungal community composed of 189 strains covering a wide range of Ascomycota and Basidiomycota, to compare the performance of 360 software and parameter combinations. The most sensitive approaches, based on the USEARCH and VSEARCH clustering algorithms, detected almost all fungal strains but greatly overestimated the total number of strains. By contrast, approaches using DADA2 to detect amplicon sequence variants were the most effective for recovering the richness and composition of the fungal community. Our results suggest that analyzing single forward (R1) sequences with DADA2 and no filter other than the removal of low-quality and chimeric sequences is a good option for fungal community characterization.