THE HUMAN BRAINOME III: EQTL REGULATION BY NATURAL ANTISENSE RNA IN ALZHEIMER S DISEASE

人类大脑 III：天然反义 RNA 对阿尔茨海默病的 EQTL 调节

• 批准号: 10651684
• 负责人: Amanda J Myers
• 金额: $ 75.56万
• 依托单位: UNIVERSITY OF MIAMI SCHOOL OF MEDICINE
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-15 至 2025-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10651684
• 关键词: Affect; Alleles; Alzheimer' s Disease; Alzheimer' s Disease Pathway; Alzheimer' s disease pathology; Amyloid beta-Protein; Antisense RNA; Archives; Binding; Biology; Brain; Cell Culture Techniques; Code; DNA; DNA mapping; Data; Data Collection; Disease; Genetic Transcription; Genomics; Genotype; Goals; Human; International; Investigation; Laboratories; Late Effects; Late Onset Alzheimer Disease; Length; Maps; Measures; Oligonucleotides; Outcome; Output; Pathogenicity; Pathologic; Pathway interactions; Peptides; Procedures; Process; Proteins; Proteomics; Quantitative Trait Loci; RNA; Regulation; Reproducibility; Resources; Risk; Sampling; Sequence Alignment; Series; Site; Specificity; Techniques; Technology; Testing; Time; Tissue Banks; Transcript; Translations; Untranslated RNA; Validation; Variant; Work; brain tissue; differential expression; experimental study; genome wide association study; genomic variation; innovation; interest; knock-down; neurogenomics; novel; overexpression; public database; risk variant; scaffold; single molecule; single molecule real time sequencing; tau Proteins; transcriptome sequencing; transcriptomics; web site

PROJECT SUMMARY Previously, we have taken an innovative approach (The Human Brainome; [1-6]) to mapping risk loci for late onset Alzheimer's disease (LOAD). Rather than looking at a single layer of information as in most genome- wide association (GWAS) studies, we have mapped genomic variation in the context of downstream transcriptomic and proteomic expression. This allows for mapping both the crucial variation involved in LOAD, as well as the downstream effects and their directions. Additionally, it allows for building networks of multiple players crucial for disease processes. One shortcoming of the current work is that we have mapped DNA-expression relationships that are subtly changed in Alzheimer's, but we have yet to fully understand why those DNA-expression relationships are altered. We know that expression is altered by specific alleles, but there must be added regulation given our mapped outputs. One target that can alter pathways are natural antisense transcripts (NATs), which can bind to oligonucleotide products and alter their expression and degradation. In our application, we propose to use long read sequencing technology (SMRT; Single Molecule, Real-Time) and fully profile RNA from our human brain bank samples. We will examine where these outputs are located and perform preliminary work to determine if any of these new hits can act on our existing results. We propose to follow these targets through 3 Aims. Aim 1 will involve following hits from public databases. Aim 2 will involve collecting additional RNA profiling data. Finally, Aim 3 will seek to validate and order all novel findings from Aims 1 and 2. It is important to use technologies appropriate to our hypothesis for the new data collection. The majority of non-coding RNA belongs to the class of transcripts called long non-coding RNA (lncRNA), which can span from 1000-10,000 bp [7]. Typical short-read RNA sequencing (SRS) technologies are based on the capture of short sequences of ~150 bp, and therefore, SRS has difficulty in capture and alignment of longer products. We are working with Robert Sebra at the Icahn Institute for Genomics and Multicale Biology, who is an expert in SMRT sequencing [8]. This technology offers longer read lengths and will be unique-in-field, since most human RNA profiling involves SRS. By the completion of these Aims, we will have 1. A map of novel long read sequencing in human brain tissues, which will be a significant add-to-field, given most technologies used to date are focused on short read sequencing, and there is limited profiling in pathologically defined human brain tissues, 2. An understanding of how these novel hits are affecting both the direct sense transcript of interest as well as the known LOAD pathologies, 3. Multi-level mapping of rigor and reproducibility of targets through the use of multiple capture techniques and 4. Validation of the effect of hits on the known LOAD pathogenic targets by measuring both expression and protein levels in cell culture.

项目概要 此前，我们采用了一种创新方法（人脑组；[1-6]）来绘制风险位点 迟发性阿尔茨海默病（LOAD）。而不是像大多数基因组那样查看单层信息- 广泛关联（GWAS）研究，我们在下游背景下绘制了基因组变异图 转录组和蛋白质组表达。这允许映射 LOAD 中涉及的关键变化， 以及下游影响及其方向。此外，它还允许构建多个网络 对疾病过程至关重要的参与者。 当前工作的一个缺点是我们绘制的 DNA 表达关系微妙地 阿尔茨海默氏症发生了变化，但我们尚未完全理解为什么这些 DNA 表达关系会发生变化 改变了。我们知道表达会被特定的等位基因改变，但考虑到我们的基因，必须有额外的调节 映射的输出。可以改变途径的一个目标是天然反义转录本 (NAT)，它可以结合 寡核苷酸产物并改变其表达和降解。在我们的应用中，我们建议使用 长读长测序技术（SMRT；单分子，实时）并全面分析人类 RNA 脑库样本。我们将检查这些输出的位置并开展初步工作 确定这些新的点击是否可以对我们现有的结果产生作用。 我们建议通过 3 个目标来实现这些目标。目标 1 将涉及公共数据库中的点击次数。 目标 2 将涉及收集额外的 RNA 分析数据。最后，Aim 3 将寻求验证和订购所有小说 目标 1 和 2 的发现。使用适合我们对新数据的假设的技术非常重要 收藏。大多数非编码 RNA 属于长非编码 RNA 转录本类别 (lncRNA)，其长度范围为 1000-10,000 bp [7]。典型的短读长RNA测序（SRS）技术 基于~150bp短序列的捕获，因此SRS难以捕获和捕获 较长产品的对齐。我们正在与伊坎基因组学研究所的 Robert Sebra 合作， Multicale Biology，SMRT测序专家[8]。该技术提供更长的读取长度，并将 在该领域是独一无二的，因为大多数人类 RNA 分析都涉及 SRS。 完成这些目标后，我们将拥有 1. 人脑中新型长读测序图谱 组织，这将是一个重要的补充领域，因为迄今为止使用的大多数技术都集中在短读上 测序，并且在病理学上确定的人脑组织中的分析有限，2. 了解 这些新颖的点击如何影响感兴趣的直接意义转录本以及已知的负载 病理学，3. 通过使用多重捕获对目标的严格性和可重复性进行多级映射 4. 通过测量两者来验证命中对已知 LOAD 致病靶点的影响 细胞培养物中的表达和蛋白质水平。