Cancer Genetics Laboratory, BC Cancer Agency, Vancouver, British Columbia, Canada; Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, British Columbia, Canada.
J Mol Diagn. 2013 Nov;15(6):796-809. doi: 10.1016/j.jmoldx.2013.07.004. Epub 2013 Oct 4.
Individuals who inherit mutations in BRCA1 or BRCA2 are predisposed to breast and ovarian cancers. However, identifying mutations in these large genes by conventional dideoxy sequencing in a clinical testing laboratory is both time consuming and costly, and similar challenges exist for other large genes, or sets of genes, with relevance in the clinical setting. Second-generation sequencing technologies have the potential to improve the efficiency and throughput of clinical diagnostic sequencing, once clinically validated methods become available. We have developed a method for detection of variants based on automated small-amplicon PCR followed by sample pooling and sequencing with a second-generation instrument. To demonstrate the suitability of this method for clinical diagnostic sequencing, we analyzed the coding exons and the intron-exon boundaries of BRCA1 and BRCA2 in 91 hereditary breast cancer patient samples. Our method generated high-quality sequence coverage across all targeted regions, with median coverage greater than 4000-fold for each sample in pools of 24. Sensitive and specific automated variant detection, without false-positive or false-negative results, was accomplished with a standard software pipeline using bwa for sequence alignment and samtools for variant detection. We experimentally derived a minimum threshold of 100-fold sequence depth for confident variant detection. The results demonstrate that this method is suitable for sensitive, automatable, high-throughput sequence variant detection in the clinical laboratory.
个体遗传 BRCA1 或 BRCA2 突变易患乳腺癌和卵巢癌。然而，在临床检测实验室中通过传统的双脱氧测序鉴定这些大型基因中的突变既耗时又昂贵，对于其他在临床环境中具有相关性的大型基因或基因集也存在类似的挑战。第二代测序技术具有提高临床诊断测序效率和通量的潜力，一旦有了临床验证的方法。我们开发了一种基于自动化小扩增子 PCR 检测变异的方法，然后进行样本混合和第二代仪器测序。为了证明这种方法适用于临床诊断测序，我们分析了 91 例遗传性乳腺癌患者样本中 BRCA1 和 BRCA2 的编码外显子和内含子-外显子边界。我们的方法在所有靶向区域都产生了高质量的序列覆盖，每个样本在 24 个样本池中的中位数覆盖度大于 4000 倍。使用 bwa 进行序列比对和 samtools 进行变异检测的标准软件管道实现了敏感、特异、自动化的变异检测，没有假阳性或假阴性结果。我们通过实验得出了 100 倍序列深度的置信变异检测最小阈值。结果表明，该方法适用于临床实验室中敏感、自动化、高通量的序列变异检测。
