Performance comparison of four exome capture systems for deep sequencing.
Performance comparison of four exome capture systems for deep sequencing.
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DOI：
10.1186/1471-2164-15-449
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发表时间：
2014-06-09
期刊：
影响因子：
4.4
通讯作者：
Meza-Zepeda LA
中科院分区：
文献类型：
--
作者：
Chilamakuri CS;Lorenz S;Madoui MA;Vodák D;Sun J;Hovig E;Myklebost O;Meza-Zepeda LA
深度(下一代)测序技术的最新发展正在对医学研究产生重大影响。通过整个外显子组测序对基因组中的蛋白质编码区进行全局分析是一个广泛使用的应用。许多外显子组捕获技术已经商业化；在这里，我们比较四种技术的性能：NimbleGen的SeqCap EZ v3.0，Agilent的SureSelect v4.0，Illumina的TruSeq Exome和Illumina的NextEra Exome，所有这些技术都适用于相同的人类肿瘤DNA样本。评估了每种捕获技术对不同外显子组数据库的覆盖、靶标覆盖效率、GC偏倚、单核苷酸变异检测的灵敏度、小内切检测的灵敏度以及技术的重复性。总体而言，所有技术都表现良好；然而，我们的数据显示了四种捕获技术之间的微小但一致的差异。Illumina技术覆盖了编码和非翻译区域的更多基础。此外，虽然大多数技术在GC含量低或高的地区提供的覆盖范围较小，但NextEra技术倾向于偏向GC含量高的目标地区。我们展示了这四种技术在性能上的主要差异。我们的数据应该有助于计划外显子组测序的研究人员为他们的特定应用选择合适的外显子组捕获技术。本文的在线版本(DOI：10.1186/1471-2164-15-449)包含补充材料，授权用户可以使用。
Recent developments in deep (next-generation) sequencing technologies are significantly impacting medical research. The global analysis of protein coding regions in genomes of interest by whole exome sequencing is a widely used application. Many technologies for exome capture are commercially available; here we compare the performance of four of them: NimbleGen’s SeqCap EZ v3.0, Agilent’s SureSelect v4.0, Illumina’s TruSeq Exome, and Illumina’s Nextera Exome, all applied to the same human tumor DNA sample. Each capture technology was evaluated for its coverage of different exome databases, target coverage efficiency, GC bias, sensitivity in single nucleotide variant detection, sensitivity in small indel detection, and technical reproducibility. In general, all technologies performed well; however, our data demonstrated small, but consistent differences between the four capture technologies. Illumina technologies cover more bases in coding and untranslated regions. Furthermore, whereas most of the technologies provide reduced coverage in regions with low or high GC content, the Nextera technology tends to bias towards target regions with high GC content. We show key differences in performance between the four technologies. Our data should help researchers who are planning exome sequencing to select appropriate exome capture technology for their particular application. The online version of this article (doi:10.1186/1471-2164-15-449) contains supplementary material, which is available to authorized users.
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影响因子：
46.9
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影响因子：
12.3
作者：
Sulonen AM;Ellonen P;Almusa H;Lepistö M;Eldfors S;Hannula S;Miettinen T;Tyynismaa H;Salo P;Heckman C;Joensuu H;Raivio T;Suomalainen A;Saarela J
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影响因子：
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通讯作者：
McCombie WR
影响因子：
4.4
作者：
Marine, Rachel;Polson, Shawn W.;Wommack, K. Eric
通讯作者：
Wommack, K. Eric
影响因子：
46.9
作者：
Gnirke A;Melnikov A;Maguire J;Rogov P;LeProust EM;Brockman W;Fennell T;Giannoukos G;Fisher S;Russ C;Gabriel S;Jaffe DB;Lander ES;Nusbaum C
通讯作者：
Nusbaum C