Creating an advanced multi-ancestral resource and tools for short tandem repeat analysis in the AOURP researcher workbench

在 AOURP 研究人员工作台中创建先进的多祖先资源和工具，用于短串联重复分析

• 批准号: 10798717
• 负责人: Matthew Christopher Danzi
• 金额: $ 42.21万
• 依托单位: UNIVERSITY OF MIAMI SCHOOL OF MEDICINE
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-15 至 2025-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10798717
• 关键词: Acceleration; Affect; African American; All of Us Research Program; Alleles; Applications Grants; Area; Bioinformatics; Biology; Biomedical Research; Catalogs; Collection; Complex; Data; Data Analyses; Databases; Development; Disease; Environment; Eye; Future; Gene Frequency; General Population; Genetic; Genetic Variation; Genome; Genomics; Genotype; Health; Health Benefit; Heritability; Heterogeneity; Human; Human Genome; Image; Individual; Leadership; Learning; Length; Link; Machine Learning; Maps; Measures; Minisatellite Repeats; Modeling; Nature; Nervous System; Participant; Pathogenicity; Patients; Pattern; Persons; Phenotype; Pilot Projects; Play; Prevalence; Principal Investigator; Publications; Publishing; Qualifying; Research Personnel; Resources; Role; Sampling; Short Tandem Repeat; Signal Transduction; Single Nucleotide Polymorphism; Software Tools; Standardization; Structure; Tandem Repeat Sequences; Technology; Training; Variant; Work; analytical tool; cohort; data curation; data resource; disease phenotype; empowerment; genetic analysis; guided inquiry; health record; improved; large datasets; member; next generation; novel; novel therapeutics; software development; tool; whole genome; working group

Title Creating an advanced multi-ancestral resource and tools for short tandem repeat analysis in the AoURP researcher workbench Abstract The AoURP researcher workbench provides an unparalleled opportunity to study multi-ancestral human genome variation at scale with the promise of benefitting health and diseases for all people in the USA. A particular type of variation, only recently amenable to bioinformatic analysis due to breakthroughs in software development and long-read sequencing, are tandem repeats (TRs). TRs, when unstable and expanded, have been linked to disease and it is widely expected that they will play a much larger role for health and disease going forward. We have been developing TR resources, machine learning based tools (RExPRT), and discovered novel disease-causing TRs published in Nature Genetics and NEJM in the past 5 years. The co-PI’s of this proposal recently worked as part of the AoURP Long Reads Working Group to create a call set of over 3.5 billion TR alleles from 1,027 AoURP participants sequenced with PacBio HiFi reads using the newly developed TRGT tool. This grant application proposes to characterize this recently established AoURP data resource by developing novel analytical tools to unearth interrelated patterns of tandem repeat length, motif, and flanking variation in unprecedented detail. In addition to this long-read based data resource, we will also characterize the TRs in the larger cohort of >250,000 Illumina short-read whole genomes produced by the AoURP, though in lesser detail, using tools such as ExpansionHunter. The product of this work will be available to all workbench users in the form of normative databases, tools, notebooks, and scripts to accelerate the study of TRs in the context of health records data. We believe this work will enable prioritization of disease-causing TR loci and lead to a better understanding of TR biology which will be vital to the development of new therapeutics.

标题 创建高级的多主管资源和工具，用于简短串联重复分析 AOURP研究员工作台 抽象的 AOURP研究人员的工作台提供了一个无与伦比的机会来研究多学业 人类基因组的大规模变异，有望使所有人受益于健康和疾病 在美国的人。一种特定类型的变化，直到最近才适应生物信息 由于软件开发和长阅读测序的突破而引起的分析是串联的 重复（TR）。当不稳定和扩展时，TR已与疾病联系在一起，并且广泛 预计他们将在健康和疾病中发挥更大的作用。我们有 正在开发TR资源，基于机器学习的工具（REXPRT），并发现了新颖 在过去的5年中，在自然遗传学和NEJM上发表的引起疾病的TR。 Co-Pi的 该提案最近是Aourp Long Reads工作组的一部分，以创建一个 与PACBIO HIFI测序的1,027个AOURP参与者的35亿TR等位基因的电话集超过35亿TR等位基因 使用新开发的TRGT工具读取。此赠款申请提案以表征 这是最近通过开发新的分析工具来发掘的AOURP数据资源 串联重复长度，基序和侧翼变化的相互关联模式 细节。除了这个基于长阅读的数据资源外，我们还将表征 较大的队列> 250,000个Illumina的简读整个基因组，但是AOURP产生 较小的详细信息，使用诸如ExpansionHunter之类的工具。这项工作的产品将可用 以普通数据库，工具，笔记本和脚本的形式向所有Workbench用户致 在健康记录数据的背景下加速TRS的研究。我们相信这项工作将会 可以优先考虑引起疾病的TR基因座，并更好地理解TR生物学 这对于新治疗学的发展至关重要。