Seo Seung Bum, Zeng Xiangpei, King Jonathan L, Larue Bobby L, Assidi Mourad, Al-Qahtani Mohamed H, Sajantila Antti, Budowle Bruce
BMC Genomics. 2015;16 Suppl 1(Suppl 1):S4. doi: 10.1186/1471-2164-16-S1-S4. Epub 2015 Jan 15.
Massively parallel sequencing (MPS) technologies have the capacity to sequence targeted regions or whole genomes of multiple nucleic acid samples with high coverage by sequencing millions of DNA fragments simultaneously. Compared with Sanger sequencing, MPS also can reduce labor and cost on a per nucleotide basis and indeed on a per sample basis. In this study, whole genomes of human mitochondria (mtGenome) were sequenced on the Personal Genome Machine (PGMTM) (Life Technologies, San Francisco, CA), the out data were assessed, and the results were compared with data previously generated on the MiSeqTM (Illumina, San Diego, CA). The objectives of this paper were to determine the feasibility, accuracy, and reliability of sequence data obtained from the PGM.
24 samples were multiplexed (in groups of six) and sequenced on the at least 10 megabase throughput 314 chip. The depth of coverage pattern was similar among all 24 samples; however the coverage across the genome varied. For strand bias, the average ratio of coverage between the forward and reverse strands at each nucleotide position indicated that two-thirds of the positions of the genome had ratios that were greater than 0.5. A few sites had more extreme strand bias. Another observation was that 156 positions had a false deletion rate greater than 0.15 in one or more individuals. There were 31-98 (SNP) mtGenome variants observed per sample for the 24 samples analyzed. The total 1237 (SNP) variants were concordant between the results from the PGM and MiSeq. The quality scores for haplogroup assignment for all 24 samples ranged between 88.8%-100%.
In this study, mtDNA sequence data generated from the PGM were analyzed and the output evaluated. Depth of coverage variation and strand bias were identified but generally were infrequent and did not impact reliability of variant calls. Multiplexing of samples was demonstrated which can improve throughput and reduce cost per sample analyzed. Overall, the results of this study, based on orthogonal concordance testing and phylogenetic scrutiny, supported that whole mtGenome sequence data with high accuracy can be obtained using the PGM platform.
大规模平行测序（MPS）技术能够通过同时对数百万个DNA片段进行测序，以高覆盖率对多个核酸样本的靶向区域或全基因组进行测序。与桑格测序相比，MPS在每个核苷酸以及每个样本的基础上还能减少人力和成本。在本研究中，人类线粒体全基因组（mtGenome）在个人基因组测序仪（PGM™）（美国加利福尼亚州旧金山市的生命技术公司）上进行测序，对输出数据进行评估，并将结果与之前在MiSeq™（美国加利福尼亚州圣地亚哥市的Illumina公司）上生成的数据进行比较。本文的目的是确定从PGM获得的序列数据的可行性、准确性和可靠性。
24个样本进行多重测序（每组6个样本），并在至少10兆碱基通量的314芯片上进行测序。所有24个样本的覆盖深度模式相似；然而，全基因组的覆盖情况有所不同。对于链偏性，每个核苷酸位置上正向链与反向链的平均覆盖比率表明，基因组中三分之二的位置其比率大于0.5。少数位点具有更极端的链偏性。另一观察结果是，156个位置在一个或多个个体中的错误缺失率大于0.15。在所分析的24个样本中，每个样本观察到31 - 98个（单核苷酸多态性）mtGenome变异。PGM和MiSeq的结果之间总共有1237个（单核苷酸多态性）变异是一致的。所有24个样本的单倍群分型质量分数在88.8% - 100%之间。
在本研究中，对从PGM生成的mtDNA序列数据进行了分析并对输出结果进行了评估。识别出了覆盖深度变异和链偏性，但通常并不常见，且不影响变异位点检测的可靠性。证明了样本的多重测序，这可以提高通量并降低每个分析样本的成本。总体而言，基于正交一致性测试和系统发育分析，本研究结果支持使用PGM平台能够获得高精度的完整mtGenome序列数据。
