Genome-wide Investigation of cis-splicing between Adjacent Genes NOSI Admin Supplement

相邻基因之间顺式剪接的全基因组研究 NOSI Admin Supplement

基本信息

批准号：
10658934
负责人：
HUI LI
金额：
$ 11.86万
依托单位：
UNIVERSITY OF VIRGINIA
依托单位国家：
美国
项目类别：
财政年份：
2019
资助国家：
美国
起止时间：
2019-09-03 至 2024-07-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10658934
关键词：
Acute African ancestry All of Us Research Program Alternative Splicing Base Sequence Bioinformatics Biological Biological Markers Bypass Catalogs Cells Cerebrovascular Disorders Characteristics Chromosomal Rearrangement Clinical Clinical Data Complex DNA Data Data Set Detection Disease Exhibits Gastrointestinal Hemorrhage Gene Expression Regulation Gene Fusion Genes Genetic Polymorphism Genetic Transcription Genotype Genotype-Tissue Expression Project Goals Haplotypes Homeostasis Individual Investigation Lead Lymphocyte Malignant Neoplasms Mediating Medicine Messenger RNA Methods Molecular Biology NF1 gene Neurofibromatosis 1 Normal Cell Normal tissue morphology Patients Phenotype Physiological Population Population Heterogeneity Prevalence Publishing RNA RNA Splicing Recurrence Research Project Summaries Resolution Role Sampling Tissues Trans-Splicing Transcript Variant Whole Blood biobank clinical investigation cohort diagnostic biomarker ethnic diversity genetic variant genome-wide genome-wide analysis genomic data insight mRNA Precursor microdeletion novel personalized medicine therapeutic target

项目摘要

PROJECT SUMMARY Research on structural variants (SVs) has elucidated their importance to medicine and molecular biology, establishing their roles in regulation of gene expression, implications in diseases, and ethnic diversity. While large-scale studies of SVs have catalogued extensive variation in global populations, those found are often of unknown consequence in terms of what products they produce and what potential biological effects they may cause. In parallel, we and others have discovered a large number of chimeric RNAs in diseased and normal physiological tissues and cells. A subset of these RNA fusions are a consequence of SVs, which we call them canonical chimeric RNAS differentiating from the non-canonical chimeric RNAs made by intergenic splicing. We have therefore developed a bottom-up approach, using chimeric RNAs found in the GTEx dataset, to the identify SVs which produce gene fusion transcripts. These are therefore enriched for functionality and phenotypic impacts over traditional SV prediction methods, which catalogue SVs as polymorphisms. Each can be used as basis for PheWAS to find associated clinical variables or patient characteristics, and can serve as easily detectable biomarkers for personalized medicine. In our preliminary study, we uncovered over 90 such chimeric RNAs and their associated SVs, 42 of which have been predicted in whole blood or lymphocytes, which further supports their accessibility as biomarkers. One such chimeric RNA], SUZ12P1-CRLF3, is the result of a complex rearrangement on 17q11.2 and presents in individuals with African ancestry. The parental genes lie within a region deleted in a subset of type 1 neurofibromatosis (NF1) patients, and the rearrangement itself, intersects with known breakpoint deletions. We have observed from our limited clinical data that this chimeric RNA (and SV) is associated with acute cerebrovascular disease and smaller stature, and also exhibits a weaker association with gastrointestinal hemorrhage, all of which are indications of NF1. We plan to leverage the rich set of genomic and clinical data in All Of US program to achieve the following two goals. Aim1, Utilize the All of Us cohort to assess associations of the SUZ12P1-CRLF3 chiRNA with donor phenotypes, including NF1 and other clinical parameters. Aim2, Perform PheWAS on the remaining 92 canonical chimeric RNAs and their associated SVs. The findings will not only validate our bottom-up approach in identifying functional SVs, but also lead to novel clinical insights on a large number of novel SVs.

项目概要对结构变异（SV）的研究阐明了它们对医学和分子生物学的重要性，确定它们在基因表达调控、疾病影响和种族多样性方面的作用。尽管对 SV 的大规模研究已经对全球人群中的广泛差异进行了分类，这些发现通常是未知的后果，即它们生产的产品以及它们可能产生的潜在生物效应原因。与此同时，我们和其他人在患病和正常人体内发现了大量嵌合RNA 生理组织和细胞。这些 RNA 融合的一个子集是 SV 的结果，我们称之为规范嵌合RNA与通过基因间剪接产生的非规范嵌合RNA不同。我们因此，我们开发了一种自下而上的方法，使用 GTEx 数据集中发现的嵌合 RNA 来识别产生基因融合转录本的SV。因此，它们的功能和表型得到了丰富对传统 SV 预测方法的影响，传统 SV 预测方法将 SV 分类为多态性。每个都可以用作 PheWAS 是查找相关临床变量或患者特征的基础，并且可以轻松用作用于个性化医疗的可检测生物标志物。在我们的初步研究中，我们发现了超过 90 个这样的嵌合体 RNA 及其相关的 SV，其中 42 个已在全血或淋巴细胞中预测，这进一步支持它们作为生物标志物的可及性。一种这样的嵌合RNA]，SUZ12P1-CRLF3，是一个复合物的结果 17q11.2 上的重排并出现在具有非洲血统的个体中。亲本基因位于在 1 型神经纤维瘤病 (NF1) 患者的子集中删除的区域，以及重排本身，相交具有已知的断点删除。我们从有限的临床数据中观察到，这种嵌合 RNA（和 SV）与急性脑血管疾病和身材矮小有关，而且关联性也较弱胃肠道出血，这些都是 NF1 的指征。我们计划利用丰富的基因组 All Of US 计划中的临床数据和临床数据旨在实现以下两个目标。目标1，利用我们所有人的力量评估 SUZ12P1-CRLF3 chiRNA 与供体表型的关联，包括 NF1 和其他临床表型参数。目标2，对剩余的 92 个典型嵌合 RNA 及其相关的 SV 执行 PheWAS。这些发现不仅验证了我们自下而上识别功能性 SV 的方法，而且还带来了新颖的方法对大量新型 SV 的临床见解。