A unique long-read genome sequencing approach to identify structural variants predisposing to hereditary breast cancer

一种独特的长读长基因组测序方法，用于识别易患遗传性乳腺癌的结构变异

• 批准号: 417977121
• 负责人: Professor Dr. Bernd Wollnik
• 金额: --
• 依托单位: Institut für Humangenetik
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2019
• 资助国家: 德国
• 起止时间: 2018-12-31 至 2022-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/417977121?language=en
• 关键词: unique; long; read; genome; sequencing

Mutations in the DNA repair genes BRCA1 and BRCA2 as well as several interaction partners and downstream targets predispose to hereditary breast and ovarian cancer (HBOC). However, only approximately 35% of cases with HBOC fulfilling the clinical criteria for molecular testing can be associated with causative mutations in described HBOC-genes. Surprisingly, negative testing results are also obtained in a substantial number of large families including numerous affected individuals, and also in cases presenting with a very early onset of the disease. In addition, recent molecular studies suggest the presence of genomic structural mutations, e.g. in regulatory regions of known and unknown HBOC-genes, which cannot be detected by short-read sequencing approaches. Based on the observation that (i) identified HBOC-associated genes explain the familial risk in only ~35% of patients and (ii) current strategies for the identification of causative mutations in novel HBOC-predisposing genes, namely WES in large cohorts of patients, have not been very successful, our newly established Lower Saxony consortium developed an innovative, new strategy for the identification of novel genes and novel molecular mechanisms in HBOC. Under the hypothesis that de novo or recessive mutations play an important causative role in the molecular pathogenesis of very early onset HBOC, we will perform both, low-coverage long-read (Pacific Biosciences) WGS and high-coverage short-read (Illumina) WGS in four selected trios (mother, father, HBOC index [negative for all known HBOC-genes]) with an early onset of breast cancer (<28 years of age) and negative family history. Long-read WGS aims to detect structural variants, and short-read WGS will detect causative single nucleotide variants. In addition to this trio approach, we have selected four large, HBOC-gene negative families with several affected individuals in different generations, and we aim to identify novel causative mutations and genes by the combination of PacBio- and Illumina-WGS. Both will be done in two individuals from different generations in each of the four families. The bioinformatics analysis will be provided by the teams in Düsseldorf and Cologne, which also includes the secondary analysis using the SMRT Link pipeline on the basis of a scientific cooperation. To ensure successful variant interpretation of WGS data sets, our MutationMining (MM) team at the Institute of Human Genetics in Göttingen will be involved in the project. The MM team is a unique team consisting of 21 clinicians and scientists with different expertise in e.g. clinical genetics, molecular genetics, molecular biology, biochemistry and bioinformatics, and it has a long-standing experience in NGS-based gene identification studies. Novel HBOC-associated genes and mutations profiles will be subsequently tested in larger HBOC cohorts in order to determine the frequency and relative risk of mutations.

DNA 修复基因 BRCA1 和 BRCA2 以及一些相互作用伴侣和下游靶点的突变容易导致遗传性乳腺癌和卵巢癌 (HBOC)。然而，只有大约 35% 的 HBOC 病例符合分子检测的临床标准，可能与所述 HBOC 基因的致病突变有关。令人惊讶的是，在包括许多受影响个体在内的大量大家庭中以及在疾病非常早期发病的病例中也获得了阴性检测结果。此外，最近的分子研究表明存在基因组结构突变，例如。已知和未知 HBOC 基因的调控区域，无法通过短读长测序方法检测到。基于以下观察结果：(i) 确定的 HBOC 相关基因仅解释了约 35% 患者的家族风险，以及 (ii) 目前识别新型 HBOC 易感基因（即大群患者中的 WES）致病突变的策略并不是很成功，我们新成立的下萨克森联盟开发了一种创新的新策略，用于识别新基因和新分子机制 在HBOC。假设从头突变或隐性突变在极早发病 HBOC 的分子发病机制中发挥着重要的致病作用，我们将在四个选定的三人组（母亲、父亲、HBOC 指数 [所有已知 HBOC 基因均为阴性]）中进行低覆盖率长读长（Pacific Biosciences）全基因组测序（WGS）和高覆盖率短读长（Illumina）全基因组测序（WGS），这些三人组是早期发病的乳腺癌（<28 岁）。 年龄）和阴性家族史。长读长全基因组测序旨在检测结构变异，短读长全基因组测序将检测致病性单核苷酸变异。除了这种三重奏方法之外，我们还选择了四个大型 HBOC 基因阴性家族，其中有不同世代的数名受影响个体，我们的目标是通过结合 PacBio 和 Illumina-WGS 来识别新的致病突变和基因。这两件事都将由四个家庭中不同世代的两个人完成。生物信息学分析将由杜塞尔多夫和科隆的团队提供，其中还包括在科学合作的基础上使用 SMRT Link 管道进行二次分析。为了确保成功地解释 WGS 数据集的变异，我们位于哥廷根人类遗传学研究所的 MutationMining (MM) 团队将参与该项目。 MM 团队是一个独特的团队，由 21 名具有不同专业知识的临床医生和科学家组成，例如：临床遗传学、分子遗传学、分子生物学、生物化学和生物信息学，并在基于NGS的基因鉴定研究方面拥有长期的经验。随后将在更大的 HBOC 队列中测试新的 HBOC 相关基因和突变谱，以确定突变的频率和相对风险。