Cell Epigenotype Specific Maps in the Brain

描述(由申请人提供)：这是一项开发两种新技术的建议，以消除大脑中精神疾病研究中细胞异质性的混杂影响。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链形成DNA化学的专家的才华。总之，我们希望生产出有用的生物信息学和分子生物学工具，立即应用于精神病学表观基因组研究中现有和未来的数据集，并最终为细胞类型特定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节因素，它们的错误调节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是有限的，相关疾病的表观遗传学差异显示出似乎在生物学上微不足道的影响。对这些发现的一个直观解释是，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定表观遗传贡献所产生的噪音冲淡或扭曲。为了克服这些混杂因素，在目标1中，我们建议识别神经元和胶质细胞的细胞类型特异性表观遗传标记，以便生成细胞表观类型特异性(CETS)图，从而能够通过生物信息消除基于细胞异质性的混杂因素。我们将在Illumina Infinium450K微阵列平台上对死后皮质组织进行全基因组DNA甲基化分析，并在FACS中从MDD(N=20)和对照(N=20)样本中分离出神经元和胶质细胞。CETS标记将使用神经元和神经胶质甲基化签名的非配对疾病测试来生成。在目标2中，将使用焦磷酸测序验证顶级CETS标记的DNA甲基化签名，并将测试基于CETS标记的模型对不同比例的混合神经元和神经胶质DNA进行正常化的能力。在这个过程中，我们将生成与表观遗传学对严重抑郁障碍(MDD)的贡献相关的试点数据，并展示CETS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，允许根据CETS标记的DNA甲基化信号对DNA进行序列和甲基化特异性纯化，以从混合DNA池中捕获神经元或神经胶质DNA。这项工作的结果将为更详细地绘制一系列脑区的神经细胞类型提供原则证明，并可能识别与MDD相关的表观遗传学变化，这些变化代表预后生物标记物或表观遗传治疗的新靶点。基于CETS模型的标准化将大大降低精神病学表观遗传学研究中基于组织的细胞异质性，导致更可靠的结果。识别的脑细胞类型特异性表观遗传标记与基于TFO的亲和力捕获相结合，将为精神病学表观遗传学社区创建一个强大的工具，以研究小细胞群体中的基因组调控，并利用他们现有的DNA库存来测试细胞类型特异性假说。

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.