Stanford Mendelian Genomics Research Center

斯坦福孟德尔基因组学研究中心

基本信息

批准号：
10619619
负责人：
Jonathan Bernstein
金额：
$ 283.8万
依托单位：
STANFORD UNIVERSITY
依托单位国家：
美国
项目类别：
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/10619619
关键词：
ATAC-seq Acceleration 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 Pluripotent Stem Cells Process Rare Diseases Reporter Reporter Genes Reproducibility Research Research Personnel Research Support Resources Risk Site Techniques Technology Testing Tissues Triage Validation Variant Work 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 synergism transcriptome sequencing translational genomics whole genome

项目摘要

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和研究带来了新的机遇。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诊断领域。这些方法已经确定了大约 30% 的新疾病基因和致病变异。我们相信，对患有罕见遗传病的个体进行系统应用是有希望的新方法。基因组学检测与创新计算方法相结合将促进发现，使 70% 的人受益为此，我们将应用长读全基因组。测序、RNA 测序、表观基因组学测定、代谢组学以及靶向体外和体内测定评估一组疑似患有孟德尔疾病的未确诊个体。我们的方法是。通过计算策略的开发和应用来增强基因和这项工作预计将进行表型匹配、综合多组学分析和变异解释。建立孟德尔疾病发现的新领域。团队在使用各种最先进的实验和技术方面已经发展了关键的先前专业知识和领导力诊断和发现孟德尔疾病的计算方法。孟德尔基因组学研究的阶段将通过评估和部署最有效的“组学”来定义我们建议将功能基因组学数据持续迭代地整合到转化中。基因组学工具包将显着增加新基因和变异疾病关联的发现为了实现这一目标，我们将全面研究 400 个人。及其直系亲属（总共 N = 900）患有孟德尔病，但外显子组测序尚未发现这些代表了一组难以解决的 DNA 难以解决的病例。迄今为止，在目标 1 中，招募参与研究的个体将接受短读长和长读长测序。跨多种常用细胞/组织类型的基因组测序、RNA-seq、ATAC-seq 和 MmethylC-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。孟德尔疾病诊断方法并促进对每种方法优点的相对评估。在目标 2 中，我们专注于计算创新，以改善这些多组学数据在基因中的整合通过整合功能基因组学异常值和高级统计学习来解释变异这些方法将广泛适用于 MGRC 和全世界。最先进的靶向方法，包括大规模并行报告分析、诱导多能干细胞功能基因组学、CRISPR 筛选修饰基因并设计小鼠模型来检测和验证我们网站的工作将通过提供新的因果变异和基因来增强 MGRC 的广泛影响。孟德尔病功能基因组学研究、验证和诊断平台。