1/3 High-resolution mapping of cell type-specific DNA (hydroxy)methylation in the human brain during postnatal development and in psychiatric disease.

1/3 出生后发育和精神疾病期间人脑中细胞类型特异性 DNA（羟基）甲基化的高分辨率图谱。

• 批准号: 10360523
• 负责人: Chunyu Liu
• 金额: $ 16.12万
• 依托单位: UPSTATE MEDICAL UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-05-01 至 2025-02-28
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10360523
• 关键词: Aberrant DNA Methylation; Adolescence; Adult; Affect; Alleles; Attention; Autopsy; Base Pairing; Binding Sites; Bipolar Disorder; Brain; Brain region; Cell Nucleus; Cells; Childhood; Complement; DNA; DNA Methylation; Data; Data Set; Development; Disease; Enhancers; Epigenetic Process; Etiology; Fluorescence; Functional disorder; Gene Expression; Gene Expression Profile; Gene Expression Regulation; Genetic; Genetic Risk; Genetic Transcription; Genome; Glutamates; Histones; Human; Interneurons; Link; Maps; Measures; Mediating; Mental disorders; Methods; Methylation; Minor Lymphocyte Stimulatory Loci; Modification; Molecular; Neuroglia; Neurons; Nuclear; Nucleic Acid Regulatory Sequences; Nucleotides; Patients; Population; Prefrontal Cortex; Process; Quantitative Trait Loci; Regulator Genes; Regulatory Element; Reporting; Resolution; Role; Sampling; Schizophrenia; Sex Bias; Site; Sorting - Cell Movement; Specimen; Techniques; Testing; Time; Tissues; Untranslated RNA; Variant; Work; base; bisulfite sequencing; brain cell; case control; cell type; disorder control; disorder risk; epigenome; epigenomics; excitatory neuron; gamma-Aminobutyric Acid; genetic association; genetic variant; genome wide association study; histone modification; individual patient; inhibitory neuron; insertion/deletion mutation; methylome; neuropsychiatric disorder; postnatal; postnatal development; promoter; recruit; relating to nervous system; risk variant; sex; spatiotemporal; transcription factor; transcriptome; transcriptome sequencing

Project Summary: Most genetic variants associated with disease in genome-wide association studies (GWAS) lie in non-coding gene regulatory elements (GRE; e.g., promoters and enhancers). GREs are tissue- and cell type-specific and are identified through their epigenomic signatures, including low DNA methylation (DNAm), DNA accessibility and certain histone modifications. The PsychENCODE Consortium has characterized brain GREs across brain regions and developmental time points, as well as in the brains of psychiatric patients using mostly DNA accessibility and histone modification marks. These marks, however, identify large regions of enrichment (~300-2,000bp), providing only low resolution coverage of the important regulatory nucleotides, e.g., transcription factor binding sites. DNAm (especially cell type-specific DNAm) has received less attention, although it has been linked to psychiatric disorders, including schizophrenia (SZ) and bipolar disorder (BD). In the adult human brain, ~80% of CG and 1.5% of non-CG (CH) sites are methylated, and can be converted to hydroxymethylcytosine (hmC) and further demethylated. In postmitotic neuronal genomes, mCH and hmC accumulate to a significantly higher level than in other tissues--a distinct feature of the brain's epigenome. Bisulfite sequencing (BS)-based approaches that are used to measure (h)mC can pinpoint GREs with single base resolution, presenting a unique opportunity to refine the gene regulatory landscape of the brain cell types. Here we aim to create reference DNAm maps [mC and hmC, using BS and oxidative (ox)BS sequencing] and transcriptional profiles (using RNA-seq) in two major subtypes of neurons in the human dorsolateral prefrontal cortex (DLPFC), namely excitatory glutamatergic (Glu) and inhibitory GABA-ergic neurons. The proposed work is based on fluorescence-activated nuclear sorting (FANS) methods that we recently developed to separate nuclei of different cell types from autopsied human brain, and on our recent findings that showed unexpected relationships between DNA(h)m, GREs, and gene expression in the DLPFC Glu and GABA neurons. We will perform these studies at key time points of postnatal brain development and adulthood to map DNA(h)m within active neuron subtype-specific GREs that may be vulnerable to disruption during childhood and adolescence periods that coincide with the critical processes of brain maturation and circuit refinement (Aim 1). This work will be complemented with single nucleus mC profiling, which will allow us to define the developmental trajectories of mC in discrete subpopulations of Glu and GABA neurons (Aim2). Finally, we will profile Glu and GABA neurons in 150 autopsied DLPFC samples obtained from controls and cases of SZ and BD, and will then map neuron subtype-specific gene expression and (hydroxy)methylation quantitative trait loci (eQTL, mQTLS, hmQTLs) (Aim3). We will integrate QTL, transcriptome, and DNA(h)m data with the results of SZ and BP GWAS to reveal DNA(h)m and gene expression-mediated causal risk variants and genes, and to distinguish specific neuronal subtype(s) that are critical in the etiology of these disorders.

项目摘要：在全基因组关联研究（GWAS）中，大多数与疾病相关的遗传变异 位于非编码基因调节元件（GRE；例如启动子和增强子）。 GRE是组织和细胞 特定于类型的特异性，并通过其表观基因组特征（包括低DNA甲基化（DNAM））来鉴定 DNA可及性和某些组蛋白修饰。心理代码财团已经表征了大脑 跨大脑区域和发育时间点以及精神病患者的大脑 主要是DNA可及性和组蛋白修饰标记。但是，这些标记确定了很大的区域 富集（〜300-2,000bp），仅提供重要调节核苷酸的低分辨率覆盖范围，例如 转录因子结合位点。 DNAM（尤其是细胞类型特异性DNAM）受到了较少的关注， 尽管它与精神病疾病有关，包括精神分裂症（SZ）和躁郁症（BD）。 在成年人的大脑中，约有80％的CG和1.5％的非CG（CH）位点是甲基化的，可以转化 到羟基胞嘧啶（HMC）并进一步去甲基化。在有丝分裂后神经元基因组中，MCH和HMC 与其他组织相比，积累的水平明显高得多，这是大脑表观基因组的独特特征。 用来测量（H）MC可以用单个GRE的基于硫甘硫酸盐测序（BS）的方法 基础分辨率，提供了一个独特的机会，可以完善脑细胞类型的基因调节景观。 在这里，我们旨在创建参考DNAM地图[MC和HMC，使用BS和氧化（OX）BS测序] 在人背外侧的两个主要亚型中的转录曲线（使用RNA-Seq）（使用RNA-Seq） 前额叶皮层（DLPFC），即兴奋性谷氨酸能（GLU）和抑制性GABA - 凝胶神经元。这 拟议的工作基于我们最近开发的荧光激活的核分子（风扇）方法 将不同细胞类型的核与尸检的人脑分开，以及我们最近的发现 DNA（H）M，GRE和基因表达之间的意外关系中的DLPFC GLU和GABA神经元之间的意外关系。 我们将在产后大脑发育和成年期的关键时间点进行这些研究 活性神经元亚型特异性GR中的DNA（H）M可能在儿童时期容易受到干扰和 青春期与大脑成熟和电路细化的关键过程相吻合（AIM 1）。 这项工作将与单核MC分析相辅相成，这将使我们能够定义发展 MC在GLU和GABA神经元离散亚群中的MC轨迹（AIM2）。 最后，我们将在150个从对照组中获得的150个载体DLPFC样品中介绍GLU和GABA神经元 SZ和BD的病例，然后将绘制神经元亚型特异性基因表达和（羟基）甲基化 定量性状基因座（EQTL，MQTL，HMQTLS）（AIM3）。我们将整合QTL，转录组和DNA（H）M数据 通过SZ和BP GWA的结果显示DNA（H）M以及基因表达介导的因果风险变异和 基因，并区分这些疾病病因至关重要的特定神经元亚型。