Stanford Mendelian Genomics Research Center

斯坦福孟德尔基因组学研究中心

• 批准号: 10217842
• 负责人: Jonathan Bernstein
• 金额: $ 283.69万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-07-15 至 2026-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10217842
• 关键词: ATAC-seq; Biological Assay; CRISPR interference; CRISPR screen; Cell Line; Cells; Clinical; Clustered Regularly Interspaced Short Palindromic Repeats; Computing Methodologies; Coupled; DNA sequencing; Data; Data Set; Development; Diagnosis; Diagnostic; Disease; Engineering; Enrollment; Ethnic Origin; Evaluation; Family; Family Study; Family member; Fostering; Gene Expression; Genes; Genetic; Genomic approach; Genomics; In Vitro; Individual; Knowledge; Laboratories; Leadership; Literature; Mendelian disorder; Methods; Multiomic Data; Participant; Patients; Phase; Phenotype; Process; Rare Diseases; Reporter; Reporter Genes; Reproducibility; Research; Research Personnel; Research Support; Resources; Risk; Site; Techniques; Technology; Testing; Tissues; Triage; Validation; Variant; Work; base; biobank; causal variant; clinical care; clinical practice; cohort; computational pipelines; data integration; data sharing; disease diagnosis; epigenomics; exome; exome sequencing; frontier; functional genomics; gene discovery; genetic disorder diagnosis; genetic signature; genetic variant; genome sequencing; genomic data; high standard; improved; in vivo; induced pluripotent stem cell; innovation; insight; lipidomics; metabolomics; mouse model; multiple omics; novel; novel strategies; population based; public health relevance; rare genetic disorder; rare variant; recruit; sex; statistical learning; transcriptome sequencing; translational genomics; whole genome

Rapid advances in genomics have ushered in new opportunities for Mendelian disease discovery and diagnosis. In the last decade, exome and genome sequencing have moved from the research domain to clinical practice. These approaches have identified new disease genes and causative variants for ~30% of individuals suffering from a rare genetic disease. We believe that the systematic application of promising new genomics assays coupled with innovative computational approaches will foster discovery benefitting the 70% of symptomatic individuals without a genetic diagnosis. To this end we will apply long-read whole genome sequencing, RNA-sequencing, epigenomics assays, metabolomics and targeted in vitro and in vivo assays to evaluate a cohort of undiagnosed individuals suspected to have a Mendelian disorder. Our approach will be augmented through the development and application of computational strategies enabling improved gene and phenotype matching, integrative multi-omics analysis, and variant interpretation. This work is expected to establish a new frontier in Mendelian disease discovery. Our Mendelian Genomics Research Center (MRGC) team has developed key prior expertise and leadership in the use of diverse state-of-the-art experimental and computational methods for the diagnosis and discovery of Mendelian disorders. We hypothesize that the next phase of Mendelian genomics research will be defined by assessing and deploying the most effective ‘omics’ strategies. We propose that ongoing and iterative integration of functional genomics data into the translational genomics toolkit will significantly increase discovery of new gene and variant disease associations beyond the capabilities of DNA-sequencing assays alone. To facilitate this, we will comprehensively study 400 individuals and their immediate family members (N= 900 total) with Mendelian disease where exome sequencing has not yielded a genetic diagnosis. These represent a select cohort of hard to solve cases intractable to DNA sequencing to date. In Aim 1, individuals recruited into the study will undergo short-read and long-read whole genome sequencing, RNA-seq, ATAC-seq and MethylC-seq across multiple commonly used cell/tissue types as well as metabolomics and lipidomics assays. This dataset will define a holistic view of emerging genomics approaches for Mendelian disease diagnosis and facilitate evaluation of the relative merits of each approach. In Aim 2, we focus on computational innovations that will improve integration of these multi-omics data in gene and variant interpretation by integrating functional genomics outliers and advanced statistical learning approaches. These methods will be applicable broadly across the MGRC and the world. In Aim 3, we apply state-of-the-art targeted approaches including massively-parallel reporter assays, induced-pluripotent stem cell functional genomics, CRISPR screens for modifier genes and engineered mouse models to detect and validate novel causal variants and genes. Work at our site will potentiate the broad impact of the MGRC by providing a platform for functional genomics research, validation and diagnosis in Mendelian disease.

基因组学的快速发展为孟德尔疾病的发现带来了新的机会， 诊断.在过去的十年中，外显子组和基因组测序已经从研究领域转移到 临床实践这些方法已经确定了新的疾病基因和致病变异，约30%的 患有罕见遗传病的人。我们认为，系统地应用有前途的新技术， 基因组学分析加上创新的计算方法将促进发现，使70%的人受益。 没有基因诊断的有症状的个体。为此，我们将应用长读全基因组 测序、RNA测序、表观基因组学测定、代谢组学和靶向体外和体内测定， 评估一组未确诊的疑似患有孟德尔遗传病的个体。我们的做法会有所 通过开发和应用计算策略来增强，从而改善基因和 表型匹配、综合多组学分析和变体解释。这项工作预计将 在孟德尔疾病的发现中开辟了新的领域。我们的孟德尔基因组学研究中心（MRGC） 该团队在使用各种最先进的实验和 用于诊断和发现孟德尔疾病的计算方法。我们假设接下来 孟德尔基因组学研究的一个阶段将通过评估和部署最有效的“组学”来定义 战略布局我们建议将功能基因组学数据持续和迭代地整合到翻译中， 基因组学工具包将大大增加新基因和变异疾病的发现， 仅DNA测序分析的能力。为了促进这一点，我们将全面研究400个人， 及其直系亲属（共N= 900）患有孟德尔疾病，其中外显子组测序尚未 进行了基因诊断这些代表了一组难以解决的DNA难以解决的案件 排序到目前为止在目标1中，被招募到研究中的个体将接受短读和长读的整体测试。 跨多种常用细胞/组织类型的基因组测序、RNA-seq、ATAC-seq和MethylC-seq 以及代谢组学和脂质组学分析。该数据集将定义新兴基因组学的整体视图 孟德尔疾病的诊断方法，并促进每种方法的相对优点的评价。 在目标2中，我们专注于计算创新，这将改善基因组学中这些多组学数据的整合。 通过整合功能基因组学异常值和先进的统计学习， 接近。这些方法将广泛适用于整个MGRC和世界。在目标3中，我们应用 最先进的靶向方法，包括并行报告基因测定、诱导多能干细胞 功能基因组学，CRISPR筛选修饰基因和工程小鼠模型，以检测和验证 新的致病变体和基因。我们现场的工作将通过提供一个 孟德尔疾病的功能基因组学研究、验证和诊断平台。