Assessing copy number from exome sequencing and exome array CGH based on CNV spectrum in a large clinical cohort
Assessing copy number from exome sequencing and exome array CGH based on CNV spectrum in a large clinical cohort
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DOI：
10.1038/gim.2014.160
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发表时间：
2015-08-01
影响因子：
8.8
通讯作者：
Haverfield, Eden
中科院分区：
文献类型：
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作者：
Retterer, Kyle;Scuffins, Julie;Haverfield, Eden
目的：拷贝数变异（CNV）的检测对许多遗传疾病的研究具有重要意义。通过阵列比较基因组杂交测试一个大型临床队列提供了对致病性CNV谱的深入了解。在这种情况下，我们描述了一种生物信息学方法，从全外显子组测序中提取CNV信息，并证明其在临床测试中的实用性。方法：采用外显子聚焦阵列和全基因组染色体微阵列分析，分别检测14228例和14000例个体。基于这些结果，我们开发了一种检测全外显子组测序数据中缺失/重复的算法和一种新的全外显子组阵列。结果：在外显子阵列队列中，我们观察到阳性检出率为2.4%（25个重复，318个缺失），其中39%涉及一个或两个外显子。染色体微阵列分析鉴定出3345个影响单基因的CNVs（18%）。我们证明，我们的全外显子组测序算法解决了三个或更多外显子的CNVs。结论：这些结果证明了单外显子分离在CNV检测中的临床应用。我们的全外显子组测序算法接近这一分辨率，但辅以全外显子组阵列，以明确识别基因内CNVs和单外显子变化。这些数据说明了通过全外显子组测序和全外显子组阵列进行CNV分析的下一步进展。
Purpose: Detection of copy-number variation (CNV) is important for investigating many genetic disorders. Testing a large clinical cohort by array comparative genomic hybridization provides a deep perspective on the spectrum of pathogenic CNV. In this context, we describe a bioinformatics approach to extract CNV information from whole-exome sequencing and demonstrate its utility in clinical testing.Methods: Exon-focused arrays and whole-genome chromosomal microarray analysis were used to test 14,228 and 14,000 individuals, respectively. Based on these results, we developed an algorithm to detect deletions/duplications in whole-exome sequencing data and a novel whole-exome array.Results: In the exon array cohort, we observed a positive detection rate of 2.4% (25 duplications, 318 deletions), of which 39% involved one or two exons. Chromosomal microarray analysis identified 3,345 CNVs affecting single genes (18%). We demonstrate that our whole-exome sequencing algorithm resolves CNVs of three or more exons.Conclusion: These results demonstrate the clinical utility of single-exon resolution in CNV assays. Our whole-exome sequencing algorithm approaches this resolution but is complemented by a whole-exome array to unambiguously identify intragenic CNVs and single-exon changes. These data illustrate the next advancements in CNV analysis through whole-exome sequencing and whole-exome array.