Resources for Comparative Mendelian Disease Genomics

比较孟德尔疾病基因组学资源

• 批准号: 10404070
• 负责人: DAVID ERIC BERGSTROM
• 金额: $ 80.33万
• 依托单位: JACKSON LABORATORY
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-06-01 至 2024-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10404070
• 关键词: Affect; American; Animal Model; Biological Process; Bone Diseases; CRISPR/Cas technology; Candidate Disease Gene; Catalogs; Clinic; Clinical; Clustered Regularly Interspaced Short Palindromic Repeats; Communities; DNA Sequence Analysis; Data; Detection; Diagnosis; Disease; Disease model; Engineering; Etiology; Family; Funding; Generations; Genes; Genetic; Genetic Engineering; Genetic Heterogeneity; Genetic Processes; Genome; Genomics; Goals; Hereditary Malignant Neoplasm; Heritability; High-Throughput Nucleotide Sequencing; Human; Human Genetics; Inbred Strain; Inherited; Investigation; Laboratory mice; Link; Maps; Mendelian disorder; Minor; Molecular Diagnosis; Mus; Mutation; Neonatal; Online Systems; Partner in relationship; Pathogenicity; Pathology; Patients; Perinatal; Perinatal mortality demographics; Phenotype; Population; Public Health; Research; Research Personnel; Resources; Role; Source; Techniques; Technology; Translating; Validation; Variant; accurate diagnosis; base; causal variant; clinical application; comparative; computer framework; congenital heart disorder; consanguineous family; cost; data resource; design; disease phenotype; exome; exome sequencing; gene discovery; genome sequencing; genome-wide; improved; in vivo; model development; mouse genome; neonatal human; nervous system disorder; public health relevance; research study; reverse genetics; segregation; sequencing platform; skin disorder; success; tool; transcriptome sequencing; whole genome

PROJECT SUMMARY Approximately 20-30 million Americans are affected by Mendelian genetic disorders with broad clinical consequences including congenital heart disease, congenital bone diseases, inherited skin diseases, hereditary neurological disorders, hereditary cancers, and others. Over the last several years, high-throughput, whole-exome sequencing has been used for molecular diagnosis and as a research tool for discovery of new disease-causative gene(s). Since the first successful application of this technology six years ago, the fundamental genetic bases for over 100 Mendelian diseases have been identified. Despite these advances, the clinical yield for human Mendelian disease by whole-exome sequencing is less than 40%. In contrast to these clinical cases, the discovery of Mendelian disease genes in mice is powered by genetically defined inbred strain backgrounds, large consanguineous pedigrees for segregation analysis, and disease modeling through the use of exciting new CRISPR/Cas9 approaches and more traditional genetic engineering techniques. With these allied technologies, the application of whole-exome sequencing in recent years has increased the rate of mutation discovery in mouse by nearly ten-fold. Yet, the success rate for Mendelian disease gene discovery in the mouse is only slightly higher than 50 percent. Possible limitations of whole-exome sequencing for disease gene discovery in mouse include shortcomings of variant calling tools, insufficient data resources describing `normal' genome variation, and the likely existence of structural variants that escape detection by exome- sequencing. With the promise of exploring and surmounting these limitations, our long-term goal is to create genomic resources that will facilitate functionalization of naturally occurring variation by employing forward genetic discovery and reverse genetic validation. More specifically, the objectives of this project are to continue to tackle the problem of robust discovery and functional validation of variants that cause Mendelian disease phenotypes in mice with an emphasis on those variants that escape detection by exome sequencing. We will harness newly affordable, third-generation, long-read sequencing technologies for the discovery of structural variants (SVs); and further develop pipelines that integrate these new datatypes into a data-driven framework formouse variant interpretation and candidate gene prioritization that is available to the research community. Finally, we will take advantage of new high throughput in vivo, CRISPR-based engineering and phenotyping to prove disease-causation from among a subset of our most interesting and relevant candidate genes.

项目摘要 大约2000万至3000万美国人患有孟德尔遗传性疾病， 包括先天性心脏病、先天性骨病、遗传性皮肤病、 遗传性神经系统疾病、遗传性癌症和其他疾病。在过去的几年里，高通量， 全外显子组测序已用于分子诊断，并作为发现新的 致病基因。自六年前首次成功应用这项技术以来， 已经确定了100多种孟德尔疾病的基本遗传基础。尽管取得了这些进展， 通过全外显子组测序的人孟德尔氏病的临床产率小于40%。与此相反， 在临床病例中，小鼠中孟德尔疾病基因的发现是由遗传定义的近交系提供动力的。 菌株背景、用于分离分析的大的血缘谱系和通过 使用令人兴奋的新CRISPR/Cas9方法和更传统的基因工程技术。与 近年来，全外显子组测序的应用提高了 在小鼠中发现突变的几率提高了近十倍。然而，孟德尔遗传病基因发现的成功率， 老鼠只比50%稍高一点。疾病全外显子组测序的可能局限性 小鼠基因发现包括变异识别工具的缺陷，描述基因的数据资源不足， “正常”基因组变异，以及可能存在逃避外显子检测的结构变异- 测序随着探索和超越这些限制的承诺，我们的长期目标是创造 基因组资源，其将通过采用正向技术促进天然存在的变异的功能化， 基因发现和反向基因验证。更具体地说，该项目的目标是继续 以解决导致孟德尔疾病的变体的稳健发现和功能验证问题 表型，重点是那些逃避外显子组测序检测的变异。我们将 利用新的负担得起的，第三代，长读序测序技术， 变体（SV）;并进一步开发将这些新数据类型集成到数据驱动框架中的管道 形成小鼠变异解释和候选基因的优先顺序，可供研究界。 最后，我们将利用新的高通量体内、基于CRISPR的工程和表型分析技术， 从我们最感兴趣和最相关的候选基因的子集中证明致病性。