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比较 R9.4.1/Kit10 和 R10/Kit12 Oxford Nanopore 流动池和化学试剂在细菌基因组重建中的应用。

Comparison of R9.4.1/Kit10 and R10/Kit12 Oxford Nanopore flowcells and chemistries in bacterial genome reconstruction.

机构信息

NIHR OxfordBiomedical Research Centre, University of Oxford, Oxford, UK.

Nuffield Department of Medicine, University of Oxford, Oxford, UK.

出版信息

Microb Genom. 2023 Jan;9(1). doi: 10.1099/mgen.0.000910.

Abstract

Complete, accurate, cost-effective, and high-throughput reconstruction of bacterial genomes for large-scale genomic epidemiological studies is currently only possible with hybrid assembly, combining long- (typically using nanopore sequencing) and short-read (Illumina) datasets. Being able to use nanopore-only data would be a significant advance. Oxford Nanopore Technologies (ONT) have recently released a new flowcell (R10.4) and chemistry (Kit12), which reportedly generate per-read accuracies rivalling those of Illumina data. To evaluate this, we sequenced DNA extracts from four commonly studied bacterial pathogens, namely , , and , using Illumina and ONT's R9.4.1/Kit10, R10.3/Kit12, R10.4/Kit12 flowcells/chemistries. We compared raw read accuracy and assembly accuracy for each modality, considering the impact of different nanopore basecalling models, commonly used assemblers, sequencing depth, and the use of duplex versus simplex reads. 'Super accuracy' (sup) basecalled R10.4 reads - in particular duplex reads - have high per-read accuracies and could be used to robustly reconstruct bacterial genomes without the use of Illumina data. However, the per-run yield of duplex reads generated in our hands with standard sequencing protocols was low (typically <10 %), with substantial implications for cost and throughput if relying on nanopore data only to enable bacterial genome reconstruction. In addition, recovery of small plasmids with the best-performing long-read assembler (Flye) was inconsistent. R10.4/Kit12 combined with sup basecalling holds promise as a singular sequencing technology in the reconstruction of commonly studied bacterial genomes, but hybrid assembly (Illumina+R9.4.1 hac) currently remains the highest throughput, most robust, and cost-effective approach to fully reconstruct these bacterial genomes.

摘要

对于大规模基因组流行病学研究,目前只有混合组装才能实现细菌基因组的完整、准确、具有成本效益和高通量重建,该方法结合了长读(通常使用纳米孔测序)和短读(Illumina)数据集。能够仅使用纳米孔数据将是一项重大进展。牛津纳米孔技术(ONT)最近发布了一种新的流动池(R10.4)和化学试剂(Kit12),据称其每个读取的准确性可与 Illumina 数据相媲美。为了评估这一点,我们使用 Illumina 和 ONT 的 R9.4.1/Kit10、R10.3/Kit12、R10.4/Kit12 流动池/化学试剂对四种常见研究细菌病原体的 DNA 提取物进行了测序,这些病原体分别是 、 、 、 。我们比较了每种模式的原始读取准确性和组装准确性,同时考虑了不同纳米孔碱基呼叫模型、常用组装器、测序深度以及使用双链和单链读取的影响。“超级准确性”(sup)碱基呼叫的 R10.4 读取——特别是双链读取——具有较高的每个读取准确性,可以在不使用 Illumina 数据的情况下,稳健地重建细菌基因组。然而,在我们的标准测序方案中,双链读取的每个运行产量都很低(通常 <10%),如果仅依靠纳米孔数据来实现细菌基因组重建,这将对成本和通量产生重大影响。此外,使用表现最佳的长读组装器(Flye)对小质粒的恢复不一致。R10.4/Kit12 与 sup 碱基呼叫相结合,有望成为重建常见研究细菌基因组的单一测序技术,但混合组装(Illumina+R9.4.1 hac)目前仍然是高通量、最稳健和最具成本效益的方法,可以完全重建这些细菌基因组。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7e9c/9973852/6e8926022f55/mgen-9-910-g001.jpg

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