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

标题 创建用于短串联重复分析的高级多祖先资源和工具 AoURP研究员工作台 摘要 AoURP研究员工作台提供了研究多个祖先的无与伦比的机会 人类基因组的大规模变异，有望造福所有人的健康和疾病 在美国的人们。一种特殊类型的变异，直到最近才服从于生物信息学 由于软件开发和长时间测序的突破，分析是齐头并进的 重复(RR)。当TRS不稳定和扩张时，已经与疾病联系在一起，它被广泛地 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 我一直在开发基于机器学习的工具(RExPRT)，并发现了新的 过去5年发表在《自然遗传学》和《新英格兰医学杂志》上的致病受体。联合少年派的 最近作为AoURP Long Reads工作组的一部分，创建了一个 使用PacBio HiFi对1,027名AoURP参与者的超过35亿个TR等位基因进行测序的呼叫集 使用新开发的TRGT工具阅读。这项拨款申请建议将 最近通过开发新的分析工具来挖掘AoURP数据资源 史无前例的串联重复序列长度、基序和侧翼变异的相关模式 细节。除了这个基于长时间阅读的数据资源之外，我们还将在 然而，AoURP产生的更大的&gt；250,000个Illumina短读完整基因组队列 在不太详细的情况下，使用ExpansionHunter等工具。这项工作的产品将会上市 以标准化数据库、工具、笔记本和脚本的形式提供给所有工作台用户 在健康记录数据的背景下，加快研究TRs。我们相信这项工作将 能够确定致病基因座的优先顺序，并有助于更好地理解基因重组生物学 这将对新疗法的发展至关重要。

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.