University of Minnesota Genomics Center, Minneapolis, Minnesota, USA.
Biomedical Informatics and Computational Biology, University of Minnesota, Minneapolis, Minnesota, USA.
Nat Biotechnol. 2016 Sep;34(9):942-9. doi: 10.1038/nbt.3601. Epub 2016 Jul 25.
Amplicon-based marker gene surveys form the basis of most microbiome and other microbial community studies. Such PCR-based methods have multiple steps, each of which is susceptible to error and bias. Variance in results has also arisen through the use of multiple methods of next-generation sequencing (NGS) amplicon library preparation. Here we formally characterized errors and biases by comparing different methods of amplicon-based NGS library preparation. Using mock community standards, we analyzed the amplification process to reveal insights into sources of experimental error and bias in amplicon-based microbial community and microbiome experiments. We present a method that improves on the current best practices and enables the detection of taxonomic groups that often go undetected with existing methods.
基于扩增子的标记基因调查是大多数微生物组和其他微生物群落研究的基础。这种基于 PCR 的方法有多个步骤，每个步骤都容易出错和产生偏差。由于使用了多种下一代测序 (NGS) 扩增子文库制备方法，结果也存在差异。在这里，我们通过比较不同的基于扩增子的 NGS 文库制备方法，正式描述了错误和偏差。使用模拟群落标准，我们分析了扩增过程，揭示了基于扩增子的微生物群落和微生物组实验中实验误差和偏差的来源。我们提出了一种改进现有最佳实践的方法，使我们能够检测到现有方法通常无法检测到的分类群。
