Comparative cofactor screens reveal the influence of transactivation domains and core promoters on the mechanisms of transcription [ChIP-seq]

Eukaryotic transcription factors (TFs) activate gene expression by recruiting cofactors to promoters. However, the relationships between TFs, promoters and their associated cofactors remain poorly understood. Here, we combine GAL4-transactivation assays with comparative CRISPR-Cas9 screens to identify the cofactors required by nine different TFs in human cells. Using this dataset, we associate key TFs with their cofactors, classify cofactors as ubiquitous or specific, discover novel transcriptional co-dependencies and demonstrate that certain TFs use the tail 2 and kinase submodules of Mediator to potentiate transcriptional elongation. By employing a reductionistic and comparative approach, we demonstrate that TFs do not display discrete mechanisms of activation. Instead, each TF is dependent on a unique combination of cofactors, which influences distinct steps in the transcriptional process. We also extend our screens to nine different core promoters to explore how core promoter elements influence cofactor dependence. Our data suggest that different classes of promoter are constrained by either initiation or pause release, which influences their dynamic range of gene expression and compatibility with specific cofactors. Overall, our comparative cofactor screens uncover the interplay between TFs, cofactors and core promoters and reveal general principles by which they influence transcription. ChIP-seq to assess the effect of loss of various Mediator subunits and to assess the effect of loss of various cofactors on response to TNF treatment. Cells were harvested on D4 after infection with relevant sgRNAs. TNF treatment was performed for 6hrs prior to harvest at 25ng/ml. For all ChIP experiments, at least 20 million cells were crosslinked for 15 mins with 1% formaldehyde. Crosslinked material was sonicated to approximately 200-1000bp using the Covaris Ultrasonicator e220. Sonicated material was incubated overnight with each antibody, then incubated for 3hrs with Protein A magnetic beads. Beads were washed with low and high salt wash buffers, LiCl buffer and TE, before being eluted and de-crosslinked overnight. DNA was purified using Qiagen Minelute columns. All ChIP antibodies were used at ~10ug per IP and are listed under the antibodies section. Sequencing libraries were prepared from eluted DNA using Rubicon ThruPLEX DNA-seq kit. Libraries were size selected between 200-500bps and sequenced on the NextSeq500 using the 75bp single-end chemistry.

真核转录因子（Transcription Factors, TFs）通过将辅因子招募至启动子区域以激活基因表达。然而，转录因子、启动子及其关联辅因子之间的相互关系仍不甚明晰。在此研究中，我们将GAL4转录激活测定与比较性CRISPR-Cas9筛选相结合，以鉴定人类细胞中9种不同转录因子所需的辅因子。利用该数据集，我们将关键转录因子与其辅因子进行关联，将辅因子分为普遍型或特异型，发现了新的转录共依赖关系，并证实部分转录因子利用中介体（Mediator）的尾段2及激酶亚模块来增强转录延伸。通过采用还原论与比较性研究方法，我们证实转录因子并不具备离散的激活机制。相反，每种转录因子均依赖于独特的辅因子组合，而这些组合会影响转录过程中的不同步骤。我们还将筛选扩展至9种不同的核心启动子，以探究核心启动子元件如何影响辅因子依赖性。我们的数据表明，不同类别的启动子分别受限于转录起始或暂停释放，这会影响其基因表达的动态范围以及与特定辅因子的兼容性。总体而言，我们的比较性辅因子筛选揭示了转录因子、辅因子与核心启动子之间的相互作用，并阐明了它们影响转录的通用原则。我们采用染色质免疫沉淀测序（Chromatin Immunoprecipitation sequencing, ChIP-seq）来评估多种中介体亚基缺失的影响，以及多种辅因子缺失对肿瘤坏死因子（Tumor Necrosis Factor, TNF）处理应答的影响。用相关单向导RNA（single guide RNA, sgRNA）感染细胞后，于第4天收集细胞。TNF处理于收获前6小时进行，浓度为25ng/ml。所有ChIP实验中，至少收集2000万个细胞，用1%甲醛交联15分钟。交联后的样品使用Covaris Ultrasonicator e220超声破碎至约200-1000bp。将超声后的样品与对应抗体孵育过夜，随后与蛋白A磁珠孵育3小时。磁珠先后经低盐、高盐洗涤缓冲液、氯化锂（LiCl）缓冲液及TE缓冲液洗涤，之后进行洗脱并过夜去交联。使用Qiagen Minelute柱纯化DNA。所有ChIP实验所用抗体的用量约为每免疫沉淀（Immunoprecipitation, IP）反应10μg，抗体详情见抗体部分。使用Rubicon ThruPLEX DNA-seq试剂盒从洗脱得到的DNA中构建测序文库。文库在200-500bp范围内进行片段大小筛选，并使用NextSeq500测序平台采用75bp单端测序化学法进行测序。