Performance comparison of exome DNA sequencing technologies.
Performance comparison of exome DNA sequencing technologies.
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DOI：
10.1038/nbt.1975
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发表时间：
2011-09-25
影响因子：
46.9
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通过靶富集的基因组DNA的高通量测序的全外显子组测序（exome-seq）作为以相对低的成本询问人类基因组的可解释部分的手段在基础和翻译研究中已经变得常见。这里呈现的是来自Agilent、Illumina和Nimblegen的三种主要商业外显子组测序平台应用于相同人类血液样品的比较。Nimblegen平台是唯一一个使用高密度重叠诱饵的平台，它提供了更高的富集效率和检测变异的灵敏度，但覆盖的基因组区域比其他平台少。因此，Nimblegen需要最少的测序来灵敏地检测小的变体，但Agilent和Illumina能够通过额外的测序检测更多的变体。Illumina特别捕获了Nimblegen和Agilent平台缺失的非翻译区。还比较了同一样品的外显子组测序和全基因组测序（WGS），证明了外显子组-seq允许检测被WGS遗漏的其他小变体。这些数据表明，WGS实验受益于补充靶向外显子组-seq数据。这项研究有助于社区为他们的实验选择最佳的exome-seq平台，并证明exome-seq能够识别典型WGS实验遗漏的重要编码变异。
Whole exome sequencing by high-throughput sequencing of target-enriched genomic DNA (exome-seq) has become common in basic and translational research as a means of interrogating the interpretable part of the human genome at relatively low cost. Presented here is a comparison of three major commercial exome sequencing platforms from Agilent, Illumina and Nimblegen applied to the same human blood sample. The Nimblegen platform, which is the only one to use high-density overlapping baits, provides increased efficiency of enrichment and sensitivity for detecting variants but covers fewer genomic regions than the other platforms. As a result, Nimblegen requires the least amount of sequencing to sensitively detect small variants, but Agilent and Illumina are able to detect a greater total number of variants with additional sequencing. Illumina in particular captures the untranslated regions, which are missing from the Nimblegen and Agilent platforms. Exome sequencing and whole genome sequencing (WGS) of the same sample were also compared, demonstrating that exome-seq allows for the detection of additional small variants missed by WGS. These data suggest that WGS experiments benefit from being supplemented with targeted exome-seq data. This study serves to assist the community in selecting the optimal exome-seq platform for their experiments, as well as proving that exome-seq is capable of identifying important coding variations that are missed by a typical WGS experiment.
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