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 创建先进的多祖先资源和工具，用于短串联重复序列分析， AoURP研究员工作台 摘要 AoURP研究人员工作台提供了一个无与伦比的机会，研究多祖先 人类基因组大规模变异，有望造福所有人的健康和疾病 美国的人。一种特殊类型的变异，直到最近才适合生物信息学 由于软件开发和长读测序的突破，分析是串联的 重复序列（TR）。TRs，当不稳定和扩大时，与疾病有关，它被广泛应用于 预计它们将在未来的健康和疾病方面发挥更大的作用。我们有 一直在开发TR资源，基于机器学习的工具（RExPRT），并发现了新的 在过去5年中发表在Nature Genetics和NEJM上的致病TR。合作伙伴 该提案的一部分最近作为AoURP长阅读工作组的一部分， 来自1，027名AoURP参与者的超过35亿个TR等位基因的调用集使用PacBio HiFi测序 使用新开发的TRGT工具读取。这项拨款申请旨在描述 最近建立的AoURP数据资源，通过开发新的分析工具， 串联重复序列长度、基序和侧翼变异的相互关联模式， 详细除了这种基于长读的数据资源之外，我们还将描述 然而，由AoURP产生的> 250，000个Illumina短读全基因组的更大队列， 在不太详细的情况下，使用诸如ExpansionHunter之类的工具。这项工作的产品将提供 以规范数据库、工具、笔记本和脚本的形式提供给所有工作台用户， 加速在健康记录数据背景下的TR研究。我们相信这项工作将 使致病TR基因座的优先级，并导致更好地了解TR生物学 这对新疗法的发展至关重要。