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Comparison of Normalization Methods for Construction of Large Multiplex Amplicon Pools for Next-Generation Sequencing

机译:用于下一代测序的大型多重扩增子库构建标准化方法的比较

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摘要

Constructing mixtures of tagged or bar-coded DNAs for sequencing is an important requirement for the efficient use of next-generation sequencers in applications where limited sequence data are required per sample. There are many applications in which next-generation sequencing can be used effectively to sequence large mixed samples; an example is the characterization of microbial communities where ≤1,000 sequences per samples are adequate to address research questions. Thus, it is possible to examine hundreds to thousands of samples per run on massively parallel next-generation sequencers. However, the cost savings for efficient utilization of sequence capacity is realized only if the production and management costs associated with construction of multiplex pools are also scalable. One critical step in multiplex pool construction is the normalization process, whereby equimolar amounts of each amplicon are mixed. Here we compare three approaches (spectroscopy, size-restricted spectroscopy, and quantitative binding) for normalization of large, multiplex amplicon pools for performance and efficiency. We found that the quantitative binding approach was superior and represents an efficient scalable process for construction of very large, multiplex pools with hundreds and perhaps thousands of individual amplicons included. We demonstrate the increased sequence diversity identified with higher throughput. Massively parallel sequencing can dramatically accelerate microbial ecology studies by allowing appropriate replication of sequence acquisition to account for temporal and spatial variations. Further, population studies to examine genetic variation, which require even lower levels of sequencing, should be possible where thousands of individual bar-coded amplicons are examined in parallel.
机译:构建带标签或条形码的DNA混合物进行测序是在每个样品需要有限序列数据的应用中有效利用下一代测序仪的重要要求。在许多应用中,下一代测序都可以有效地用于对大型混合样品进行测序。一个例子是微生物群落的表征,其中每个样品≤1,000个序列足以解决研究问题。因此,有可能在大规模并行的下一代测序仪上每次运行检查数百至数千个样本。但是,只有在与多路复用池建设相关的生产和管理成本也可扩展的情况下,才能实现有效利用序列容量的成本节省。多重化池构建中的一个关键步骤是归一化过程,在此过程中要混合等摩尔量的每个扩增子。在这里,我们比较了三种方法(光谱学,尺寸受限光谱学和定量结合)对大型多重扩增子池的归一化性能和效率的影响。我们发现,定量结合方法是一种优越的方法,代表了一种非常有效的可扩展过程,可用于构建包含数百甚至数千个单个扩增子的大型多重池。我们证明了更高的通量鉴定出增加的序列多样性。大规模平行测序可以通过允许适当地重复序列采集以解决时间和空间变化,从而极大地加速微生物生态学研究。此外,在并行检查成千上万个单独的条形码扩增子的情况下,应该进行需要更低水平测序的人群研究,以研究遗传变异。

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