Caught in the middle with multiple displacement amplification: the myth of pooling for avoiding multiple displacement amplification bias in a metagenome

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• 作者：Rachel Marine (1)
  Coleen McCarren (2)
  Vansay Vorrasane (3)
  Dan Nasko (1)
  Erin Crowgey (1)
  Shawn W Polson (1)
  K Eric Wommack (1)
  
• 关键词：Metagenomics ; Microbial ecology ; Multiple displacement amplification ; PacBio SMRT sequencing ; DNA library construction
• 刊名：Microbiome
• 出版年：2014
• 出版时间：December 2014
• 年：2014
• 卷：2
• 期：1
• 全文大小：1,988 KB
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• 作者单位：Rachel Marine (1)
  Coleen McCarren (2)
  Vansay Vorrasane (3)
  Dan Nasko (1)
  Erin Crowgey (1)
  Shawn W Polson (1)
  K Eric Wommack (1)
  
  1. Delaware Biotechnology Institute, University of Delaware, 15 Innovation Way, Newark, DE, 19716, USA
  2. Washington College, 300 Washington Avenue, Chestertown, MD, 21620, USA
  3. Delaware Technical Community College, 400 Stanton-Christiana Road, Newark, DE, 19713, USA
  
• ISSN：2049-2618

文摘

Background Shotgun metagenomics has become an important tool for investigating the ecology of microorganisms. Underlying these investigations is the assumption that metagenome sequence data accurately estimates the census of microbial populations. Multiple displacement amplification (MDA) of microbial community DNA is often used in cases where it is difficult to obtain enough DNA for sequencing; however, MDA can result in amplification biases that may impact subsequent estimates of population census from metagenome data. Some have posited that pooling replicate MDA reactions negates these biases and restores the accuracy of population analyses. This assumption has not been empirically tested. Results Using mock viral communities, we examined the influence of pooling on population-scale analyses. In pooled and single reaction MDA treatments, sequence coverage of viral populations was highly variable and coverage patterns across viral genomes were nearly identical, indicating that initial priming biases were reproducible and that pooling did not alleviate biases. In contrast, control unamplified sequence libraries showed relatively even coverage across phage genomes. Conclusions MDA should be avoided for metagenomic investigations that require quantitative estimates of microbial taxa and gene functional groups. While MDA is an indispensable technique in applications such as single-cell genomics, amplification biases cannot be overcome by combining replicate MDA reactions. Alternative library preparation techniques should be utilized for quantitative microbial ecology studies utilizing metagenomic sequencing approaches.