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

机译:陷入多重置换扩增的中间:避免在一个基因组中避免多重置换扩增偏差的合并神话

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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.
机译:背景技术Shot弹枪宏基因组学已成为研究微生物生态学的重要工具。这些研究的基础是,假设基因组基因组序列数据可以准确估计微生物种群的普查。在难以获得足够的DNA进行测序的情况下,经常使用微生物群落DNA的多重置换扩增(MDA)。但是,MDA可能会导致扩增偏倚,可能会影响随后根据后代基因组数据进行的人口普查估计。一些人认为,合并重复MDA反应可以消除这些偏差,并恢复总体分析的准确性。该假设尚未经过经验检验。结果使用模拟病毒群落,我们检查了合并对人口规模分析的影响。在合并和单一反应的MDA处理中,病毒种群的序列覆盖率是高度可变的,并且整个病毒基因组的覆盖模式几乎相同,这表明初始启动偏倚是可重现的,并且合并不能缓解偏倚。相反,未扩增的对照序列文库显示了跨噬菌体基因组的相对均匀的覆盖范围。结论对于需要定量评估微生物分类群和基因功能组的宏基因组研究,应避免使用MDA。尽管MDA是单细胞基因组学等应用中必不可少的技术,但不能通过合并重复的MDA反应来克服扩增偏差。应使用替代性的文库制备技术,以利用宏基因组测序方法进行定量微生物生态学研究。

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