Höps Wolfram, Weiss Marjan M, Derks Ronny, Galbany Jordi Corominas, Ouden Amber den, van den Heuvel Simone, Timmermans Raoul, Smits Jos, Mokveld Tom, Dolzhenko Egor, Chen Xiao, van den Wijngaard Arthur, Eberle Michael A, Yntema Helger G, Hoischen Alexander, Gilissen Christian, Vissers Lisenka E L M
Department of Human Genetics, Radboud University Medical Center, Nijmegen, the Netherlands; Radboudumc Research Institute for Medical Innovation, Radboud University Medical Center, Nijmegen, the Netherlands.
Department of Human Genetics, Radboud University Medical Center, Nijmegen, the Netherlands.
Am J Hum Genet. 2025 Feb 6;112(2):450-456. doi: 10.1016/j.ajhg.2024.12.013. Epub 2025 Jan 13.
Clinical short-read exome and genome sequencing approaches have positively impacted diagnostic testing for rare diseases. Yet, technical limitations associated with short reads challenge their use for the detection of disease-associated variation in complex regions of the genome. Long-read sequencing (LRS) technologies may overcome these challenges, potentially qualifying as a first-tier test for all rare diseases. To test this hypothesis, we performed LRS (30× high-fidelity [HiFi] genomes) for 100 samples with 145 known clinically relevant germline variants that are challenging to detect using short-read sequencing and necessitate a broad range of complementary test modalities in diagnostic laboratories. We show that relevant variant callers readily re-identified the majority of variants (120/145, 83%), including ∼90% of structural variants, SNVs/insertions or deletions (indels) in homologous sequences, and expansions of short tandem repeats. Another 10% (n = 14) was visually apparent in the data but not automatically detected. Our analyses also identified systematic challenges for the remaining 7% (n = 11) of variants, such as the detection of AG-rich repeat expansions. Titration analysis showed that 90% of all automatically called variants could also be identified using 15-fold coverage. Long-read genomes thus identified 93% of challenging pathogenic variants from our dataset. Even with reduced coverage, the vast majority of variants remained detectable, possibly enhancing cost-effective diagnostic implementation. Most importantly, we show the potential to use a single technology to accurately identify all types of clinically relevant variants.
临床短读长外显子组和基因组测序方法对罕见病的诊断检测产生了积极影响。然而,与短读长相关的技术局限性对其在基因组复杂区域检测疾病相关变异的应用提出了挑战。长读长测序(LRS)技术可能克服这些挑战,有潜力成为所有罕见病的一线检测方法。为了验证这一假设,我们对100个样本进行了LRS(30倍高保真[HiFi]基因组)检测,这些样本带有145个已知的临床相关种系变异,使用短读长测序检测具有挑战性,在诊断实验室需要广泛的互补检测方式。我们发现,相关的变异检测工具能够轻松重新识别大多数变异(120/145,83%),包括约90%的结构变异、同源序列中的单核苷酸变异/插入或缺失(indels)以及短串联重复序列的扩增。另外10%(n = 14)在数据中肉眼可见但未被自动检测到。我们的分析还确定了其余7%(n = 11)变异存在的系统性挑战,例如富含AG的重复序列扩增的检测。滴定分析表明,所有自动检测到的变异中有90%也可以使用15倍覆盖度进行识别。因此,长读长基因组从我们的数据集中识别出了93%具有挑战性的致病变异。即使覆盖度降低,绝大多数变异仍然可以检测到,这可能会提高诊断实施的成本效益。最重要的是,我们展示了使用单一技术准确识别所有类型临床相关变异的潜力。