From cytogenetics to cytogenomics: whole-genome sequencing as a first-line test comprehensively captures the diverse spectrum of disease-causing genetic variation underlying intellectual disability
From cytogenetics to cytogenomics: whole-genome sequencing as a first-line test comprehensively captures the diverse spectrum of disease-causing genetic variation underlying intellectual disability
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DOI：
10.1186/s13073-019-0675-1
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发表时间：
2019-11-07
期刊：
影响因子：
12.3
通讯作者：
Nilsson, Daniel
中科院分区：
文献类型：
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作者：
Lindstrand, Anna;Eisfeldt, Jesper;Nilsson, Daniel
由于不同类型的遗传变异，从单核苷酸变异（SNVs）到大的染色体重排，都可能导致智力残疾，我们评估了使用全基因组测序（WGS）而不是染色体微阵列分析（CMA）作为一线遗传诊断测试的可能性。方法：我们分析了三个短读WGS队列：(i)具有有效拷贝数变异（CNVs）的回顾性队列（队列1，n=68）， （ii）用于单基因多基因面板的个体（队列2，n=156）， （iii）用于CMA中心的100例前瞻性连续病例（队列3）。开发的生物信息学工具包括FindSV、SVDB、Rhocall、Rhoviz和vcf2cytosure。首先，我们在队列1上验证了我们的结构变异（SV）调用管道，包括三个三体和79个缺失和重复，中位大小为850kb（最小500bp，最大155Mb）。所有的变体都被检测到。其次，我们在队列2中使用相同的管道，并使用单基因WGS面板进行分析，将诊断率提高到8%。接下来，对队列3进行CMA和WGS分析。WGS数据在全基因组范围内处理了大的（bbb10kb） SVs，并在887个与智力残疾相关的基因组中处理了外显子SVs和snv，以及与患者特异性人类表型本体（HPO）表型匹配的基因。共获得25个致病变异（snv或SVs），其中12个也被CMA检测到。我们还应用短串联重复扩增（STR）检测，在ATXN7中发现了一个病理扩增。最后，在WGS数据中验证了一例Prader-Willi综合征合并单亲二体（UPD）。在所有队列中都获得了重要的位置信息。值得注意的是，7%的分析病例中存在复杂的结构变异，例如环状染色体和两个重复，分别是插入易位和隐性不平衡易位的一部分。结论总诊断率为27%，比临床微阵列（12%）提高了一倍以上。使用WGS，我们检测到的SVs范围广，精度高。由于WGS数据还允许分析snv、UPD和STRs，因此它代表了临床诊断实验室环境中强大的综合基因检测。
BackgroundSince different types of genetic variants, from single nucleotide variants (SNVs) to large chromosomal rearrangements, underlie intellectual disability, we evaluated the use of whole-genome sequencing (WGS) rather than chromosomal microarray analysis (CMA) as a first-line genetic diagnostic test.MethodsWe analyzed three cohorts with short-read WGS: (i) a retrospective cohort with validated copy number variants (CNVs) (cohort 1, n=68), (ii) individuals referred for monogenic multi-gene panels (cohort 2, n=156), and (iii) 100 prospective, consecutive cases referred to our center for CMA (cohort 3). Bioinformatic tools developed include FindSV, SVDB, Rhocall, Rhoviz, and vcf2cytosure.ResultsFirst, we validated our structural variant (SV)-calling pipeline on cohort 1, consisting of three trisomies and 79 deletions and duplications with a median size of 850kb (min 500bp, max 155Mb). All variants were detected. Second, we utilized the same pipeline in cohort 2 and analyzed with monogenic WGS panels, increasing the diagnostic yield to 8%. Next, cohort 3 was analyzed by both CMA and WGS. The WGS data was processed for large (>10kb) SVs genome-wide and for exonic SVs and SNVs in a panel of 887 genes linked to intellectual disability as well as genes matched to patient-specific Human Phenotype Ontology (HPO) phenotypes. This yielded a total of 25 pathogenic variants (SNVs or SVs), of which 12 were detected by CMA as well. We also applied short tandem repeat (STR) expansion detection and discovered one pathologic expansion in ATXN7. Finally, a case of Prader-Willi syndrome with uniparental disomy (UPD) was validated in the WGS data.Important positional information was obtained in all cohorts. Remarkably, 7% of the analyzed cases harbored complex structural variants, as exemplified by a ring chromosome and two duplications found to be an insertional translocation and part of a cryptic unbalanced translocation, respectively.ConclusionThe overall diagnostic rate of 27% was more than doubled compared to clinical microarray (12%). Using WGS, we detected a wide range of SVs with high accuracy. Since the WGS data also allowed for analysis of SNVs, UPD, and STRs, it represents a powerful comprehensive genetic test in a clinical diagnostic laboratory setting.