MODELING THE EFFECTS OF STRUCTURAL VARIATION IN GTEX DATA AND MENDELIAN DISEASE

模拟 GTEX 数据结构变异和孟德尔疾病的影响

• 批准号: 8706981
• 负责人: DONALD F. CONRAD
• 金额: $ 38万
• 依托单位: WASHINGTON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-08-01 至 2016-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8706981
• 关键词: Affect; Base Sequence; Childhood; Chromosomal Rearrangement; Chromosome Structures; Classification; Code; Collaborations; Complex; Congenital Abnormality; Copy Number Polymorphism; Data; Data Set; Disease; Functional RNA; Gene Dosage; Gene Duplication; Gene Expression; Gene Family; Generic Drugs; Genes; Genetic Variation; Genomics; Glean; Human; Human Genetics; Intellectual functioning disability; Knowledge; Learning; Letters; Maps; Measurement; Methods; Modeling; Mutation; Nucleotides; Pathogenicity; Performance; Play; Point Mutation; Process; Regulation; Research Personnel; Role; Sampling; Testing; Tissues; Variant; Work; base; duplicate genes; human disease; human tissue; improved; innovation; insertion/deletion mutation; interest; novel; novel strategies; paralogous gene; public health relevance; repository; tool; transcription factor

DESCRIPTION (provided by applicant): A handful of mutation processes operate on the human germline to form small insertions and deletions (indels), large copy number variants (CNVs), inversions, translocations and more complex changes in chromosome structure. These diverse mutations are collectively referred to as structural variation (SV). Assessing the functional and pathogenic impact of singleton and rare structural variants in disease is one of the most pressing and understudied problems in human genetics today. Here we describe methodological innovations for integrating structural variation into eQTL studies, and then transforming knowledge learned from GTEx data into a probabilistic pathogenicity assessment tool that can be used by a wide range of researchers. We will pilot new approaches for integrating SVs and single nucleotide variants (SNVs) in a coherent framework. The centerpiece of this integrative effort will be a new model- based pathogenicity assessment method that will integrate (i) knowledge gleaned from GTEx analyses, (ii) recent breakthroughs in classification of Mendelian disease genes, and (iii) the rapidly expanding set of known disease mutations matriculating from array- and sequencing-based studies of severe Mendelian and other pediatric diseases. This method will be the first tool for generic functional assessment of both SVs and SNVs and will interpret variation affecting coding and/or non-coding regions.

描述（由申请人提供）：少数突变过程在人类生殖系上运行，形成小插入和缺失（indel）、大拷贝数变体（CNV）、倒位、易位和染色体结构中更复杂的变化。这些不同的突变统称为结构变异（SV）。评估疾病中单个和罕见结构变异的功能和致病影响是当今人类遗传学中最紧迫和研究不足的问题之一。在这里，我们描述了将结构变异整合到eQTL研究中的方法创新，然后将从GTEx数据中学到的知识转化为可供广泛研究人员使用的概率致病性评估工具。我们将试验新的方法，将SV和单核苷酸变异（SNV）整合到一个连贯的框架中。这种综合努力的核心将是一种新的基于模型的致病性评估方法，该方法将整合（i）从GTEx分析中收集的知识，（ii）孟德尔疾病基因分类的最新突破，以及（iii）从严重孟德尔和其他儿科疾病的基于阵列和测序的研究中获得的快速扩展的已知疾病突变集。该方法将是SV和SNV的通用功能评估的第一个工具，并将解释影响编码和/或非编码区的变异。