Innovations in sequencing technology have led to the discovery of novel mutations that cause inherited diseases. However, many patients with suspected genetic diseases remain undiagnosed. Long-read sequencing technologies are expected to significantly improve the diagnostic rate by overcoming the limitations of short-read sequencing. In addition, Oxford Nanopore Technologies (ONT) offers adaptive sampling and computationally driven target enrichment technology. This enables more affordable intensive analysis of target gene regions compared to standard non-selective long-read sequencing. In this study, we developed an efficient computational workflow for target adaptive sampling long-read sequencing (TAS-LRS) and evaluated it through application to 33 genomes collected from suspected hereditary cancer patients. Our workflow can identify single nucleotide variants with nearly the same accuracy as the short-read platform and elucidate complex forms of structural variations. We also newly identified several SINE-R/VNTR/Alu (SVA) elements affecting the APC gene in two patients with familial adenomatous polyposis, as well as their sites of origin. In addition, we demonstrated that off-target reads from adaptive sampling, which is typically discarded, can be effectively used to accurately genotype common single-nucleotide polymorphisms (SNPs) across the entire genome, enabling the calculation of a polygenic risk score. Furthermore, we identified allele-specific MLH1 promoter hypermethylation in a Lynch syndrome patient. In summary, our workflow with TAS-LRS can simultaneously capture monogenic risk variants including complex structural variations, polygenic background as well as epigenetic alterations, and will be an efficient platform for genetic disease research and diagnosis.

测序技术的创新导致了导致遗传性疾病的新突变的发现。然而，许多疑似遗传性疾病的患者仍未得到诊断。长读长测序技术有望通过克服短读长测序的局限性来显着提高诊断率。此外，Oxford Nanopore Technologies (ONT) 还提供自适应采样和计算驱动的目标富集技术。与标准非选择性长读长测序相比，这使得对目标基因区域进行更经济的密集分析成为可能。在这项研究中，我们开发了一种用于目标自适应采样长读长测序 (TAS-LRS) 的高效计算工作流程，并通过应用于从疑似遗传性癌症患者收集的 33 个基因组来对其进行评估。我们的工作流程可以以与短读长平台几乎相同的精度识别单核苷酸变异，并阐明结构变异的复杂形式。我们还新鉴定了两名家族性腺瘤性息肉病患者中影响APC基因的几个 SINE-R/VNTR/Alu (SVA) 元件及其起源位点。此外，我们证明，通常被丢弃的自适应采样的脱靶读数可以有效地用于准确地对整个基因组中常见的单核苷酸多态性（SNP）进行基因分型，从而能够计算多基因风险评分。此外，我们在林奇综合征患者中发现了等位基因特异性MLH1启动子高甲基化。总之，我们的 TAS-LRS 工作流程可以同时捕获单基因风险变异，包括复杂的结构变异、多基因背景以及表观遗传改变，并将成为遗传病研究和诊断的有效平台。