Project 3 Topological mapping of chromatin architectures for hormone-independent gene transcription

摘要/概要-项目3 染色体非依赖性基因转录的染色质结构拓扑图 ER β/AR结合的增强子和启动子之间的长距离染色质相互作用是必需的， 协调乳腺癌和前列腺癌细胞的基因调控。这些相互作用通过形成 3D染色质结构，使增强子和转录因子复合物与 靶基因为了解码这种复杂的调节，我们和其他研究人员先前使用Hi-C绘制了 拓扑相关结构域（TADs）在不同的细胞类型。在进一步的研究中，我们发现了一种癌症- 染色体17 q23上的特异性转录因子，其可以被分配到ER β调节的转录枢纽中。 其靶基因的一致性上调被发现与一个肿瘤患者的短无病生存期相关。 ER β阳性乳腺癌患者的亚组，无论他们的抗激素治疗。新兴 证据还表明AR特异性TADs存在于前列腺癌细胞基因组中。所以我们 假设1）频繁激素（即，雌激素或雄激素）刺激导致 ER β/AR相关TADs动态调节多个基因的转录，导致细胞异常增殖， 乳腺癌和前列腺癌细胞，和2）在拮抗剂存在下，这些染色质结构域的子集， 本文称为过渡TADs，继续通过染色质重新部署用于激素- 独立转录。而大多数ER β/AR相关的TADs在功能上被抑制， 拮抗剂，过渡TADs可以部分逃脱这种封锁基因转录的组成性调节。 为了验证这些假设，我们将使用一种改进的Hi-C方法，称为拴系构象捕获（TCC）， 研究暴露于抗肿瘤药物敏感和耐药肿瘤细胞系中的细胞结构的动态变化 激动剂或拮抗剂（目的1）。抑制性、活性和基因体组蛋白标记的ChIP-seq和CTCF 绝缘体也将在该细胞系面板中传导。将采集MNase-seq和MBDCap-seq数据集 以绘制常染色质化和异染色质化的TAD。为了整合omics-seq数据，我们将开发一个 计算模型PRAM 3D，它应用泊松随机效应架构模型（PRAM）， 概括3D染色质结构（Aim 2）。贝叶斯分层模型将预测假定的过渡 TADs一致性调节靶基因的非依赖性转录。此外，我们将使用 核小体密度方法将过渡金属亚结构域分类为不同的调节类别，即， 活性、抑制性或二价转录中心。关键染色质区域的CRISPR/Cas9基因组编辑 可能在功能上分解这些TAD相关枢纽的时空组织（目标3）。增殖 并且侵袭/迁移测定将确定这种基因组编辑是否部分地使癌细胞重新敏感， 抗激素治疗我们还将询问组蛋白修饰和其他机制的贡献 表观遗传调节剂，用于建立过渡性神经元结构。计算机表达谱分析和 单细胞RNA测序将在TCGA组的原发肿瘤和癌细胞亚群中进行， 并确定TAD相关靶基因的一致性调节是否是内在的 乳腺癌或前列腺癌中激素抵抗的预测因子。

ABSTRACT/SUMMARY - Project 3 Topological mapping of chromatin architectures for hormone-independent gene transcription Long-range chromatin interactions between ER/AR-bound enhancers and promoters are necessary for coordinated gene regulation in breast and prostate cancer cells. These interactions occur via the formation of 3D chromatin architecture that brings enhancers and transcription factor complexes into close contact with target genes. To decode this complex regulation, we and other investigators have previously used Hi-C to map topologically associated domains (TADs) in different cell types. In a further study, we have identified a cancer- specific TAD on chromosome 17q23 that can be partitioned into an ER-regulated transcription hub. Concordant up-regulation of its target genes is found to be associated with short disease-free survival in a subgroup of ER-positive breast cancer patients, irrespective of their anti-hormone treatments. Emerging evidence has also shown AR-specific TADs are present in the prostate cancer cell genome. Therefore, we hypothesize that 1) frequent hormone (i.e., estrogen or androgen) stimulation leads to the formation of ER/AR-related TADs that dynamically regulate transcription of multiple genes for aberrant proliferation of breast and prostate cancer cells and 2) in the presence of antagonists, a subset of these chromatin domains, herein termed transition TADs, continue to be exploited through chromatin redeployment for hormone- independent transcription. Whereas the majority of ER/AR-related TADs are functionally suppressed by antagonists, transition TADs may partially escape this blockade for constitutive regulation of gene transcription. To test these hypotheses, we will use a modified Hi-C method, called tethered conformation capture (TCC), to investigate dynamic changes of TAD structures in hormone-sensitive and -resistant cancer cell lines exposed to agonists or antagonists (Aim 1). ChIP-seq of repressive, active, and gene-body histone marks and CTCF insulator will also be conducted in this cell line panel. MNase-seq and MBDCap-seq datasets will be acquired to map euchromatinized and heterochromatinized TADs. To integrate omics-seq data, we will develop a computational model, PRAM3D, which applies a Poisson Random effect Architecture Model (PRAM) to recapitulate 3D chromatin architectures (Aim 2). A Bayesian hierarchical model will predict putative transition TADs that concordantly regulate hormone-independent transcription of target genes. Furthermore, we will use a nucleosome density method to classify transition TAD subdomains into different regulatory categories, i.e., active, repressive, or bivalent transcription hubs. CRISPR/Cas9 genome-editing of critical chromatin regions may functionally disassemble spatiotemporal organization of these TAD-associated hubs (Aim 3). Proliferation and invasion/migration assays will determine whether this genome editing partially re-sensitizes cancer cells to anti-hormone treatments. We will also interrogate mechanistic contribution of histone modifications and other epigenetic modulators for the establishment of transition TAD structures. In silico expression profiling and single-cell RNA seq will be conducted in primary tumors of TCGA cohorts and in cancer cell subpopulations, respectively, and determine whether concordant regulation of TAD-associated target genes is intrinsic predictors of hormone resistance in breast or prostate cancer.