Delaware Biotechnology Institute, University of Delaware, Newark, DE 19711, USA.
Appl Environ Microbiol. 2011 Nov;77(22):8071-9. doi: 10.1128/AEM.05610-11. Epub 2011 Sep 23.
Construction of DNA fragment libraries for next-generation sequencing can prove challenging, especially for samples with low DNA yield. Protocols devised to circumvent the problems associated with low starting quantities of DNA can result in amplification biases that skew the distribution of genomes in metagenomic data. Moreover, sample throughput can be slow, as current library construction techniques are time-consuming. This study evaluated Nextera, a new transposon-based method that is designed for quick production of DNA fragment libraries from a small quantity of DNA. The sequence read distribution across nine phage genomes in a mock viral assemblage met predictions for six of the least-abundant phages; however, the rank order of the most abundant phages differed slightly from predictions. De novo genome assemblies from Nextera libraries provided long contigs spanning over half of the phage genome; in four cases where full-length genome sequences were available for comparison, consensus sequences were found to match over 99% of the genome with near-perfect identity. Analysis of areas of low and high sequence coverage within phage genomes indicated that GC content may influence coverage of sequences from Nextera libraries. Comparisons of phage genomes prepared using both Nextera and a standard 454 FLX Titanium library preparation protocol suggested that the coverage biases according to GC content observed within the Nextera libraries were largely attributable to bias in the Nextera protocol rather than to the 454 sequencing technology. Nevertheless, given suitable sequence coverage, the Nextera protocol produced high-quality data for genomic studies. For metagenomics analyses, effects of GC amplification bias would need to be considered; however, the library preparation standardization that Nextera provides should benefit comparative metagenomic analyses.
构建用于下一代测序的 DNA 片段文库可能具有挑战性,尤其是对于 DNA 产量低的样品。为解决与 DNA 起始量低相关的问题而设计的方案可能导致扩增偏差,从而使宏基因组数据中的基因组分布发生偏斜。此外,由于当前的文库构建技术耗时较长,因此样品通量可能较慢。本研究评估了 Nextera,这是一种新的基于转座子的方法,旨在快速从小量 DNA 中生成 DNA 片段文库。在模拟病毒组合中,九个噬菌体基因组的序列读取分布符合六种丰度最低的噬菌体的预测;然而,丰度最高的噬菌体的等级顺序与预测略有不同。来自 Nextera 文库的从头基因组组装提供了跨越噬菌体基因组一半以上的长连续序列;在四个情况下,有完整基因组序列可供比较,共识序列与基因组的匹配度超过 99%,几乎完全一致。对噬菌体基因组中低和高序列覆盖区域的分析表明,GC 含量可能会影响来自 Nextera 文库的序列覆盖。使用 Nextera 和标准 454 FLX Titanium 文库制备协议制备的噬菌体基因组的比较表明,Nextera 文库中观察到的根据 GC 含量的覆盖偏差主要归因于 Nextera 方案的偏差,而不是 454 测序技术的偏差。尽管如此,在适当的序列覆盖范围内,Nextera 方案可为基因组研究提供高质量的数据。对于宏基因组分析,需要考虑 GC 扩增偏差的影响;然而,Nextera 提供的文库制备标准化应有利于比较宏基因组分析。