Department of Biomolecular Medicine, Ghent University, Ghent, Belgium.
Center for Medical Genetics Ghent, Ghent University Hospital, Ghent, Belgium.
Sci Rep. 2024 Nov 25;14(1):29142. doi: 10.1038/s41598-024-80068-z.
Structural variants (SVs) are important contributors to human disease. Their characterization remains however difficult due to their size and association with repetitive regions. Long-read sequencing (LRS) and optical genome mapping (OGM) can aid as their molecules span multiple kilobases and capture SVs in full. In this study, we selected six individuals who presented with unresolved SVs. We applied LRS onto all individuals and OGM to a subset of three complex cases. LRS detected and fully resolved the interrogated SV in all samples. This enabled a precise molecular diagnosis in two individuals. Overall, LRS identified 100% of the junctions at single-basepair level, providing valuable insights into their formation mechanisms without need for additional data sources. Application of OGM added straightforward variant phasing, aiding in the unravelment of complex rearrangements. These results highlight the potential of LRS and OGM as follow-up molecular tests for complete SV characterization. We show that they can assess clinically relevant structural variation at unprecedented resolution. Additionally, they detect (complex) cryptic rearrangements missed by conventional methods. This ultimately leads to an increased diagnostic yield, emphasizing their added benefit in a diagnostic setting. To aid their rapid adoption, we provide detailed laboratory and bioinformatics workflows in this manuscript.
结构变异（SVs）是人类疾病的重要致病因素。然而，由于其大小和与重复区域的关联，它们的特征仍然难以确定。长读测序（LRS）和光学基因组图谱（OGM）可以辅助进行分析，因为它们的分子跨越多个千碱基，可以完整捕获 SV。在这项研究中，我们选择了 6 名存在未解决 SV 的个体。我们对所有个体进行了 LRS 分析，并对 3 个复杂病例的子集进行了 OGM 分析。LRS 在所有样本中均检测到并完全解析了被检测的 SV。这使其中 2 名个体能够获得精确的分子诊断。总体而言，LRS 在单碱基对水平上准确地识别了所有的 SV 断点，无需额外的数据来源即可深入了解其形成机制。OGM 的应用增加了简单的变异相位，有助于解析复杂的重排。这些结果突出了 LRS 和 OGM 作为后续分子测试的潜力，可用于完整的 SV 特征分析。我们表明，它们可以以前所未有的分辨率评估具有临床意义的结构变异。此外，它们还可以检测到传统方法遗漏的（复杂）隐匿性重排。这最终提高了诊断率，强调了它们在诊断环境中的附加价值。为了促进它们的快速采用，我们在本文中提供了详细的实验室和生物信息学工作流程。
