Revealing new short tandem repeat variation in the human population across sequencing technologies: towards rare disease diagnosis and discovery

跨测序技术揭示人群中新的短串联重复变异：迈向罕见病诊断和发现

• 批准号: 10572951
• 负责人: Harriet Dashnow
• 金额: $ 18.54万
• 依托单位: UNIVERSITY OF UTAH
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-02-01 至 2025-01-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10572951
• 关键词: Address; Alleles; Catalogs; Child; Communities; DNA Sequence; Data; Data Set; Databases; Detection; Diagnosis; Disease; Dropout; Exclusion; Frequencies; Funding; Future; Gene Expression; Gene Frequency; Gene Order; Genetic Diseases; Genome; Genomics; Genotype; Hospitals; Human; Human Genome; Incidence; Individual; Investigation; Medical Research; Methods; Mutation; National Human Genome Research Institute; Pathogenicity; Patients; Phenotype; Population; Population Heterogeneity; Rare Diseases; Repetitive Sequence; Research; Research Personnel; Resources; Scheme; Short Tandem Repeat; Single Nucleotide Polymorphism; Stretching; Stuttering; Technology; Trans-Omics for Precision Medicine; Underserved Population; Universities; Untranslated RNA; Variant; Washington; Work; cohort; contig; detection method; disease diagnosis; empowerment; experience; genetic disorder diagnosis; genome sequencing; genome-wide; human disease; innovation; insertion/deletion mutation; nanopore; novel; rare genetic disorder; whole genome

Abstract Short tandem repeats (STRs) are 1–6 bp repetitive and highly polymorphic DNA sequences. Expansions in dozens of STRs are associated with genetic disease. However, STRs are challenging to sequence and interpret, meaning that individuals with STR disease often go undiagnosed. In rare disease studies, it is now standard to prioritize candidate pathogenic SNVs, indels and SVs by excluding variants that have high allele frequencies in population-scale databases such as gnomAD. However, there is no such genome-wide database available for large STR expansions. I will produce a publicly available STR variation community resource, stratified by ancestry, to enable prioritization of candidate pathogenic STR expansions. Long-read sequencing technologies from PacBio and Nanopore have been heralded as the solution to accurately genotype long repeats because their reads can span the repetitive region. However, there are several challenges when genotyping STRS in long-reads that are not adequately addressed by existing approaches. I will develop a method to genotype STRs from long-read Oxford Nanopore sequencing data. It will discover informative reads using a combination of alignment and identifying repetitive regions in reads. It will then infer the genotype by integrating evidence from multiple reads, informed by my investigation of biases in these technologies. Drawing together new short and long-read computational approaches to calling STR expansions, and my population-scale STR catalog, with an emphasis on diverse and under-served populations, this proposal will establish a genetic diagnosis for hundreds of patients, while searching for new STR disease loci. I will analyze patient cohorts enriched for phenotypes associated with STRs from the UDN, University of Washington, Harry Perkins Institute of Medical Research and Children’s Mercy Hospital to solve cases and discover new disease- associated STRs in both short and long-read sequencing.

摘要 短串联重复序列(STR)是1-6个碱基重复的高度多态的DNA序列。中的扩展 数十种短串联重复序列与遗传病有关。然而，短串联重复序列很难测序和解释， 这意味着患有STR疾病的人往往没有得到诊断。在罕见疾病研究中，现在的标准是 优先考虑候选致病SNV、INDELS和SVS，排除等位基因频率较高的变异 人口规模的数据库，如gnomAD。然而，目前还没有这样的全基因组数据库可用于 大规模的STR扩展。我将制作一个公开可用的STR变体社区资源，按以下方式分层 祖先，以实现候选致病STR扩展的优先顺序。 PacBio和Nanopore的长读测序技术已被誉为准确的解决方案 基因长重复是因为它们的读数可以跨越重复区域。然而，也有几个挑战 在对现有方法不能充分解决的长读数中的STR进行基因分型时。我会发展的 一种从长时间读取的牛津纳米孔测序数据中对STR进行分型的方法。它将发现信息量大的阅读 使用比对和识别读出中的重复区域的组合。然后，它将通过以下方式推断基因 整合来自多次阅读的证据，这是我对这些技术中的偏见的调查得出的信息。 收集新的短文和长文计算方法来调用STR扩展，以及我的 人口规模的STR目录，重点是多样化和服务不足的人口，这项提议将 在寻找新的STR疾病基因座的同时，为数百名患者建立基因诊断。我会分析一下 从华盛顿大学哈里分校获得的与STR相关的表型丰富的患者队列 珀金斯医学研究所和儿童慈悲医院解决病例并发现新疾病- 短读和长读测序中的相关STR。