Comprehensive Human Expressed Sequences in Brain (CHESS-BRAIN) and their roles in neuropsychiatric illness

大脑中综合人类表达序列（CHESS-BRAIN）及其在神经精神疾病中的作用

• 批准号: 10541887
• 负责人: Steven L. Salzberg
• 金额: $ 61.81万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-03-02 至 2025-12-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10541887
• 关键词: Algorithm Design; Autopsy; Bipolar Disorder; Brain; Brain Diseases; Brain region; Catalogs; Code; Collection; Computer software; Computing Methodologies; Data; Data Set; Databases; Diagnosis; Disease; Event; Exons; Gene Expression; Genes; Genetic; Genetic Risk; Genetic Transcription; Genotype-Tissue Expression Project; Human; Human Genome; Learning; Libraries; Major Depressive Disorder; Maps; Measures; Mental Depression; Mental disorders; Methods; Post-Traumatic Stress Disorders; Preparation; Process; Protein Isoforms; Proteins; Quantitative Trait Loci; RNA; RNA Splicing; Regulation; Ribosomal RNA; Risk; Role; Sampling; Schizophrenia; Scientist; Site; Specificity; System; Techniques; Technology; Tissues; Transcript; Transcription Initiation Site; Untranslated RNA; Validation; Variant; Weight; Work; autism spectrum disorder; brain tissue; cell type; clinically relevant; differential expression; exon skipping; experimental study; genetic variant; genome wide association study; improved; neuropsychiatry; novel; statistics; transcription termination; transcriptome; transcriptome sequencing

Project Summary The widespread use of RNA sequencing technology over the past decade has allowed scientists to discover a far larger and richer repertoire of genes and transcripts encoded by the human genome than were known just a decade ago. At least 90% of human genes have multiple isoforms, including splicing variants, alternative sites of transcription initiation and termination, exon skipping events, and more. The number of human transcripts in standard gene databases has grown enormously, from ~40,000 in the late 2000s to over 200,000 today, but it is still likely far from complete. Our previous work using exon-exon splice junctions and other fragmentary transcripts has demonstrated the clinical relevance of unannotated but expressed genes in the human brain, including associations with schizophrenia and its genetic risk. This project will attempt to discover and characterize novel gene isoforms collected from both healthy and diseased brains, using the latest computational methods for transcriptome assembly and an extensive collection of brain RNA-seq datasets. The project is organized into three aims: first, we will develop new algorithms designed to assemble RNA-seq data from samples that have been sequenced using ribosomal RNA depletion, a technique that is widely used in human brain studies but that is not used in most other RNA-seq experiments, which instead use polyA+ enrichment. We will implement these methods as extensions to the HISAT and StringTie systems for RNA-seq alignment and assembly, both of which were developed in the PI's and co-PI's labs. We will then apply these improved methods to thousands of publicly available RNA-seq samples from human brain tissue to create a new "CHESS-BRAIN" (Comprehensive Human Expressed Sequences in Brain) gene annotation database. This effort will also determine which transcripts are tissue-specific and brain-region specific; i.e., expressed at significantly higher or lower levels in brain tissues and in various brain regions as compared to other tissues. In the second aim, we will use these methods to quantify gene expression levels in hundreds of post-mortem brain RNA-seq samples from subjects diagnosed with schizophrenia (SCZD), major depression (MDD), bipolar disorder (BPD), autism spectrum disorder (ASD), and post-traumatic stress disorder (PTSD), whom we will compare to matched controls to identify the contribution of unannotated transcription in these disorders. In our third aim we will perform expression quantitative trait loci (eQTL) mapping across the entire CHESS-brain dataset, both within and across brain regions and diagnoses, to identify genetic regulation of unannotated transcripts, including both coding and noncoding transcripts. This analysis will identify genes and transcripts whose expression levels change significantly in different tissues and diseases. We will combine these results to identify novel transcripts associated with genetic risk for each of the psychiatric disorders.

项目摘要 在过去的十年中，RNA测序技术的广泛使用使科学家发现了一个很远的 由人类基因组编码的基因和转录本的大，更丰富的曲目，远不闻 十年前。至少90％的人基因具有多种同工型，包括剪接变体，替代位点 转录启动和终止，外显子跳过事件等等。人类成绩单的数量 在标准基因数据库中，数据库的增长巨大，从2000年代后期的约40,000到今天超过200,000，但 它仍然可能远离完成。我们以前使用外显子剪接连接和其他碎片的工作 成绩单已经证明了人脑中未经注释但表达的基因的临床相关性， 包括与精神分裂症及其遗传风险的关联。该项目将尝试发现和 表征从健康和患病的大脑收集的新型基因同工型，使用最新 转录组组件的计算方法和大量脑RNA-seq数据集的集合。这 项目分为三个目标：首先，我们将开发旨在组装RNA-Seq数据的新算法 从已使用核糖体RNA耗竭测序的样品中，该技术广泛用于 人脑研究，但在大多数其他RNA-seq实验中都没有使用，这些实验使用Polya+ 丰富。我们将将这些方法实施为RNA-Seq的HISAT和StringTie系统的扩展 对齐和组装，这两者都是在PI和Co-Pi实验室中开发的。然后我们将应用这些 改进了来自人类脑组织的数千种公共可用的RNA-seq样品的方法 新的“国际象棋 - 脑”（全面的人类在大脑中表达的序列）基因注释数据库。这 努力还将确定哪些转录本是组织特异性和特定于大脑区域的；即表示 与其他组织相比，脑组织和各个大脑区域的水平明显更高或更低。在 第二个目的，我们将使用这些方法来量化数百个验尸大脑中的基因表达水平 来自诊断为精神分裂症（SCZD），严重抑郁症（MDD）的受试者的RNA-Seq样品，双极 障碍（BPD），自闭症谱系障碍（ASD）和创伤后应激障碍（PTSD），我们将 与匹配的控件相比，以确定这些疾病中未注释的转录的贡献。在 我们的第三个目标我们将在整个国际象棋中执行表达定量特质基因座（EQTL）映射 在大脑区域和诊断内部和诊断的数据集，以识别未注释的遗传调节 笔录，包括编码和非编码成绩单。该分析将确定基因和成绩单 其表达水平在不同的组织和疾病中发生了显着变化。我们将将这些结果结合在一起 确定与每种精神疾病的遗传风险相关的新成绩单。