Optimizing sequencing protocols for leaderboard metagenomics by combining long and short reads
Optimizing sequencing protocols for leaderboard metagenomics by combining long and short reads
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DOI：
10.1186/s13059-019-1834-9
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发表时间：
2019-10-31
期刊：
影响因子：
12.3
通讯作者：
Knight, Rob
中科院分区：
文献类型：
--
作者：
Sanders, Jon G.;Nurk, Sergey;Knight, Rob
随着宏基因组研究转向越来越多的样本，像人类肠道这样的社区可能会从许多样本中丰富的微生物的组装中受益更多，而不是更少样本的穷尽组装。我们将这种方法称为排行榜宏基因组测序。为了探索真实的样本中排行榜宏基因组学的方案优化，我们引入了使用合成长读技术生成的内部参考的文库制备和测序的基准，使我们能够针对来自样本本身的金标准参考基因组评估高通量文库制备方法。我们介绍了一种低成本的高通量文库制备和测序方案。
As metagenomic studies move to increasing numbers of samples, communities like the human gut may benefit more from the assembly of abundant microbes in many samples, rather than the exhaustive assembly of fewer samples. We term this approach leaderboard metagenome sequencing. To explore protocol optimization for leaderboard metagenomics in real samples, we introduce a benchmark of library prep and sequencing using internal references generated by synthetic long-read technology, allowing us to evaluate high-throughput library preparation methods against gold-standard reference genomes derived from the samples themselves. We introduce a low-cost protocol for high-throughput library preparation and sequencing.