Cell Epigenotype Specific Maps in the Brain

描述（由申请人提供）：这是一项发展两种新技术的提案，以消除大脑精神疾病研究中细胞异质性的混淆效应。该项目将利用一位经验丰富的DNA甲基组研究人员、一位富有创造力的生物信息学家和一位三联体形成DNA化学专家的才能。我们希望共同开发有用的生物信息学和分子生物学工具，并将其直接应用于现有和未来的精神病学表观基因组研究数据集，并最终为细胞类型特异性疾病研究的新范式奠定基础。表观遗传修饰如DNA甲基化是基因组功能的重要调控因子，其调控不当可能对精神疾病具有病因学意义。然而，第一轮精神病学表观基因组研究的成功受到限制，相关疾病表观遗传差异显示出看似生物学上微不足道的影响。对这些发现的一种直观的解释是，与疾病相关的表观遗传差异被大脑中不同细胞类型的细胞类型特异性表观遗传贡献所产生的噪音稀释或扭曲。为了克服这些混杂因素，在目标1中，我们建议鉴定神经元和胶质细胞的细胞类型特异性表观遗传标记，以生成细胞表观遗传类型特异性（CETS）图谱，从而实现基于混杂因素的细胞异质性的生物信息学消除。我们将在Illumina Infinium 450K微阵列平台上对死后皮层组织和来自MDD （N=20）和对照（N=20）样本的FACs分离的神经元和胶质细胞进行全基因组DNA甲基化分析。cts标记将使用与疾病无关的神经元和胶质甲基化特征的不配对测试来生成。在Aim 2中，将使用焦磷酸测序验证顶级CETS标记物的DNA甲基化特征，并测试基于CETS标记物的模型对不同比例混合神经元和胶质DNA的归一化能力。在此过程中，我们将生成与重性抑郁症（MDD）的表观遗传贡献相关的试点数据，并证明cts模型在病变组织中的纠正能力。在目标3中，我们建议开发一种新的工具，允许DNA的序列和甲基化特异性纯化，可以根据cts标记DNA甲基化信号使用，从混合DNA池中捕获神经元或胶质DNA。这项工作的结果将为更详细地绘制一系列大脑区域的神经元细胞类型提供原理证明，并可能确定与MDD相关的表观遗传变化，代表预后生物标志物或表观遗传治疗的新靶点。基于CETs模型的归一化将大大减少精神病学表观遗传学研究中基于组织的细胞异质性，从而获得更有力的发现。已确定的脑细胞类型特异性表观遗传标记与基于TFO的亲和捕获相结合，将为精神病学表观遗传学社区研究小细胞群体的基因组调控和使用其现有DNA储备测试细胞类型特异性假设创造一个强大的工具。

DESCRIPTION (provided by applicant): This is a proposal to develop two novel techniques to eliminate the confounding effects of cellular heterogeneity in the study of psychiatric diseases in the brain. The project will take advantage of the talents of a highly experienced DNA methylome researcher, a creative bioinformatician, and a specialist in triplex forming DNA chemistry. Together, we hope to produce useful bioinformatic and molecular biology tools with immediate applications to existing and future datasets in psychiatric epigenomic research and to ultimately to lay the foundation for a new paradigm of cell type specific disease study. Epigenetic modifications such as DNA methylation are important regulators of genomic function and their misregulation may have etiological significance to psychiatric disease. However, the success of the first round of psychiatric epigenomic studies has been limited with associated disease epigenetic differences displaying seemingly biologically insignificant effects. An intuitive explanation for these findings is that disease relevant epigenetic differences are diluted or skewed by the noise created by cell type specific epigenetic contributions of differing cell types in the brain. To overcome these confounders, in Aim 1 we propose to identify cell type specific epigenetic markers of neurons and glia in order to generate Cell EpigenoType-Specific (CETS) maps enabling the bioinformatic elimination of cell heterogeneity based confounders. We will perform genome wide DNA methylation profiling on the Illumina Infinium 450K microarray platform on post mortem cortex tissue and in FACs separated neurons and glia from MDD (N=20) and control (N=20) samples. CETS markers will be generated using a disease independent unpaired test of neuronal and glial methylation signatures. In Aim 2, the DNA methylation signature of top CETS markers will be validated using pyrosequencing and CETS marker based models will be tested for their ability to normalize varying proportions of mixed neuronal and glial DNA. In the process, we will generate pilot data relevant to the epigenetic contribution to major depressive disorder (MDD) and demonstrate the corrective capability of CETS models in diseased tissue. In Aim 3, we propose to develop a novel tool allowing the sequence and methylation specific purification of DNA that can be used in accordance with CETS marker DNA methylation signals to capture neuronal or glial DNA from a mixed DNA pool. The results of this work will serve as a proof of principle for a more detailed mapping of neuronal cell types over a range of brain regions and may identify epigenetic changes associated with MDD representing prognostic biomarkers or novel targets for epigenetic treatment. CETs model based normalization will greatly reduce the tissue based cellular heterogeneity in psychiatric epigenetic studies, leading to more robust findings. Identified brain cell type specific epigenetic markers in conjunction with TFO based affinity capture will create a powerful tool for the psychiatric epigenetics community to study genomic regulation in small cell populations and to test cell type specific hypotheses using their existing DNA stocks.