Pilot of New Technologies to Increase the Genomic Diagnosis of Undiagnosed Disease Network (UDN) Patients

新技术试点以提高未确诊疾病网络 (UDN) 患者的基因组诊断

• 批准号: 10377756
• 负责人: Carlos A. Bacino
• 金额: $ 14.99万
• 依托单位: BAYLOR COLLEGE OF MEDICINE
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-07-01 至 2022-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10377756
• 关键词: Administrative Supplement; Alleles; Award; Biological Assay; Complement; DNA; Data; Diagnosis; Diagnostic; Disease; Epigenetic Process; Exons; Genes; Genomics; Goals; Health; Hi-C; Investigation; Laboratories; Modeling; Molecular Diagnosis; Nucleotides; Parents; Patients; Phase; Protein Isoforms; Research; Sampling; Sequence Analysis; Structure; Technology; Transcript; Untranslated RNA; Variant; clinical research site; epigenomics; exome sequencing; genetic variant; genome sequencing; genomic data; improved; insertion/deletion mutation; new technology; parent grant; programs; sequencing platform; success; transcriptome; transcriptome sequencing; transcriptomics; whole genome; Administrative Supplement; Alleles; Award; Biological Assay; Complement; DNA; Data; Diagnosis; Diagnostic; Disease; Epigenetic Process; Exons; Genes; Genomics; Goals; Health; Hi-C; Investigation; Laboratories; Modeling; Molecular Diagnosis; Nucleotides; Parents; Patients; Phase; Protein Isoforms; Research; Sampling; Sequence Analysis; Structure; Technology; Transcript; Untranslated RNA; Variant; clinical research site; epigenomics; exome sequencing; genetic variant; genome sequencing; genomic data; improved; insertion/deletion mutation; new technology; parent grant; programs; sequencing platform; success; transcriptome; transcriptome sequencing; transcriptomics; whole genome

Abstract: Despite the diagnostic successes of the UDN program, a significant number of patients remain genetically undiagnosed after exome sequencing, genome sequencing, and transcriptome analyses. We hypothesize that longer-range data from complementary sequence analysis platforms will enhance diagnostic yield in the UDN by identifying structural variants with phasing that remain undetected using traditional short- read sequencing platforms. We propose that longer-range sequencing technologies, such as Hi-C Whole Genome Sequencing (WGS) and long-read RNAseq, will facilitate the allele-specific characterization of variants (single nucleotide, indel, and structural variants), allow transcript isoform analysis in addition to phasing of cis vs. trans variants, provide information about epigenetic and nucleomic features such as domains, loops and compartments, that will enable additional integrated analysis of all forms of noncoding variants to improve the diagnostic yield. To do this we will pilot two additional data types for UDN patient assessment: Hi-C WGS, and long-read RNAseq. This will complement established technologies in the UDN including short-read WGS and short-RNAseq, as well as add to our current investigations on long-read WGS.

抽象的： 尽管UDN计划取得了诊断成功，但仍有大量患者 外显子测序，基因组测序和转录组分析后，遗传上未诊断。我们 假设来自互补序列分析平台的较长范围数据将增强诊断 通过识别使用传统短暂的阶段的结构变体，在UDN中的产量 阅读测序平台。我们提出了更长的测序技术，例如Hi-C整体 基因组测序（WGS）和长阅读RNASEQ将有助于特定于等位基因的特异性表征 变体（单核苷酸，indel和结构变体），允许成绩单同工型分析除了 顺式和跨性别变体的相位，提供有关表观遗传学和核心成分特征的信息，例如 域，循环和隔室，将对所有形式的非编码进行其他集成分析 改善诊断产量的变体。为此，我们将为UDN患者试用两种其他数据类型 评估：HI-C WGS和长阅读RNASEQ。这将补充UDN中已建立的技术 包括短阅读的WGS和短RNASEQ，以及我们目前对长阅读WGS的调查。