Digital Droplet Multiple Displacement Amplification (ddMDA) for Whole Genome Sequencing of Limited DNA Samples.

Digital Droplet Multiple Displacement Amplification (ddMDA) for Whole Genome Sequencing of Limited DNA Samples.
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DOI:
10.1371/journal.pone.0153699
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发表时间:
2016
期刊:
影响因子:
3.7
通讯作者:
Singh AK
Singh AK
中科院分区:
综合性期刊3区
文献类型:
--
作者:
Rhee M;Light YK;Meagher RJ;Singh AK

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多重置换扩增 (MDA) 是一种广泛使用的技术,用于在全基因组测序之前从含有限量 DNA 的样本(例如不可培养的微生物或临床样本)中扩增 DNA。尽管其具有高产率和保真度的优点,但在扩增亚纳克级模板 DNA 时,它会出现高扩增偏差和非特异性扩增。在这里,我们提出了一种微流控数字液滴 MDA (ddMDA) 技术,其中将模板 DNA 分割成数千个亚纳升液滴,每个液滴包含少量 DNA 片段,大大减少了 DNA 片段之间对引物和聚合酶的竞争,从而大大减少了扩增偏差。因此,ddMDA 方法能够在整个基因组长度上实现更均匀的扩增覆盖,与传统 MDA 相比,偏差和非特异性扩增显着降低。对于含有 0.1 pg/μL 大肠杆菌 DNA 的样品(相当于每个液滴约 3/1000 个大肠杆菌基因组),与传统管 MDA 相比,ddMDA 的从头组装覆盖度提高了 65 倍,特异性(映射到大肠杆菌的读数百分比)提高了 20 倍以上。 ddMDA 提供了一种强大的方法,可用于许多应用,包括医疗诊断、法医学和环境微生物学。
Multiple displacement amplification (MDA) is a widely used technique for amplification of DNA from samples containing limited amounts of DNA (e.g., uncultivable microbes or clinical samples) before whole genome sequencing. Despite its advantages of high yield and fidelity, it suffers from high amplification bias and non-specific amplification when amplifying sub-nanogram of template DNA. Here, we present a microfluidic digital droplet MDA (ddMDA) technique where partitioning of the template DNA into thousands of sub-nanoliter droplets, each containing a small number of DNA fragments, greatly reduces the competition among DNA fragments for primers and polymerase thereby greatly reducing amplification bias. Consequently, the ddMDA approach enabled a more uniform coverage of amplification over the entire length of the genome, with significantly lower bias and non-specific amplification than conventional MDA. For a sample containing 0.1 pg/μL of E. coli DNA (equivalent of ~3/1000 of an E. coli genome per droplet), ddMDA achieves a 65-fold increase in coverage in de novo assembly, and more than 20-fold increase in specificity (percentage of reads mapping to E. coli) compared to the conventional tube MDA. ddMDA offers a powerful method useful for many applications including medical diagnostics, forensics, and environmental microbiology.