Hit-and-Run transcription: The impact of transient interactions in dynamic gene regulatory networks that mediate rapid nutrient signaling

打了就跑的转录：介导快速营养信号传导的动态基因调控网络中瞬时相互作用的影响

• 批准号: 9886986
• 负责人: Gloria CORUZZI
• 金额: $ 42.97万
• 依托单位: NEW YORK UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-01 至 2024-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9886986
• 关键词: Affect; Affinity; Agriculture; Arabidopsis; Binding; Biological Assay; Biology; Biotin; Biotinylation; Cells; Complex; Computer software; DNA; DNA Binding; DNA Methylation; Data; Data Set; Databases; Dimensions; Drosophila genus; Environment; Eukaryota; Event; Family; Fertilizers; Fingerprint; Future; Gene Expression; Gene Expression Regulation; Gene Targeting; Genes; Genetic Transcription; Goals; Grant; Health; Health Benefit; Human; Influentials; Internet; Intervention; Knowledge; Mediating; Medicine; Messenger RNA; Methods; Modeling; Nitrogen; Nuclear; Nutrient; Pathway interactions; Phenotype; Plants; Prevalence; Process; Protein Methyltransferases; Publishing; Regulation; Regulator Genes; Reporter Genes; Resolution; Role; Running; Sampling; Sensitivity and Specificity; Series; Signal Transduction; System; Systems Biology; Testing; Thinking; Time; Transcript; Validation; Walking; Work; Yeasts; base; embryonic stem cell; gene discovery; genome-wide; in vivo; innovation; network models; random forest; recruit; response; scale up; stem cells; time use; tool; trait; transcription factor; transcription factor S-II; transcriptome sequencing

Project Summary: This grant exploits TIME - the 4th and largely unexplored dimension of transcription - to capture transient interactions in gene regulatory networks (GRNs) that are important, but missed, in vivo. This is because genome- scale methods to capture transcription factor (TF) target interactions favor stable binding, and reporter gene studies which detect transient TF-target interactions in seconds, miss global responses needed for GRN models. We aim to fill the time-gap in our collective knowledge of dynamic GRNs by experimentally capturing transient TF-target interactions globally using a cell-based temporal TF perturbation assay (Aims 1 & 2), and evaluate their importance in forecasting gene expression at future time-points (Aim 3), a main goal of systems biology. We model temporal GRNs controlling nitrogen (N)-signaling in plants, but our approaches are broadly applicable. We exploit a cell-based assay for temporal TF perturbation, TARGET, which captures transient TF-target interactions genome-wide; i) by TF-mediated gene regulation even in the absence of detectable TF-binding, ii) within minutes of controlled TF nuclear entry, and iii) identifies highly transient TF-binding leading to sustained transcription by affinity-capture of de novo mRNAs. We discovered that i) a single TF can stably or transiently bind to, and induce or repress, distinct sets of targets depending on their cis-context, ii) that transient TF-targets captured only in cells control early N-responses in planta, for two master TFs in our GRNs (bZIP1 & NLP7). This genome-wide data supports a Hit-and-Run transcription model, where a TF Hit can initiate a stable transcriptional complex, including recruitment of TF partners, enabling transcription to continue after the initiating TF is no longer bound, the Run. This could allow a small number of TF molecules to rapidly affect a large number of target genes by acting catalytically. Our studies have been cited and influenced thinking of transient transcription mechanisms across yeast, stems cells, and were invoked to explain the new discovery of transient binding of Zelda/Bicoid to a reporter gene in Drosophila. Herein, we deploy experimental and computational innovations to test the pervasiveness and in vivo significance of a conceptual innovation - transient Hit-and- Run interactions in GRNs. Our experimental innovations include; i) Assays for Hit-and-Run activity across all 70 TF families in Arabidopsis, using a higher throughput version of the cell-based TARGET assay we recently published, ii) new methods to capture TF-target interactions using time-series biotin-ChIP and DamID, which leaves DNA methylation marks on transient TF-target interactions, supported by preliminary data (Aims 1 & 2). Our computational innovations include: i) ConnectTF, a platform to integrate TF-DNA binding and RNA-seq data and identify candidate Hit-and-Run TFs, and approaches to assess the in planta relevance of transient TF- target interactions in GRNs, such as ii) our newly published Network Walking method, and iii) OutPredict, a new time-based method to forecast gene expression at future time-points (Aim 3). Our experimental & computational approaches are broadly applicable and our results are relevant to environmental N-use affecting human health.

项目概要： 这项资助利用时间（转录的第四个且很大程度上未被探索的维度）来捕获瞬态 基因调控网络（GRN）中的相互作用在体内很重要，但被忽视了。这是因为基因组- 捕获转录因子 (TF) 靶标相互作用的规模方法有利于稳定结合，报告基因 在几秒钟内检测瞬时 TF-目标相互作用的研究错过了 GRN 模型所需的全局响应。 我们的目标是通过实验捕获瞬态来填补动态 GRN 集体知识中的时间空白 使用基于细胞的时间 TF 扰动测定（目标 1 和 2）在全球范围内进行 TF 与目标相互作用，并评估 它们在预测未来时间点基因表达（目标 3）方面的重要性，这是系统生物学的主要目标。 我们对控制植物中氮 (N) 信号传导的时间 GRN 进行建模，但我们的方法具有广泛的适用性。 我们利用基于细胞的时间 TF 扰动分析 TARGET，它捕获瞬态 TF 目标 全基因组相互作用； i) 即使在没有可检测到的 TF 结合的情况下，也可以通过 TF 介导的基因调控，ii) 在受控 TF 核进入几分钟内，以及 iii) 识别高度瞬时的 TF 结合，从而导致持续的 通过 de novo mRNA 的亲和捕获进行转录。我们发现 i) 单个 TF 可以稳定或短暂地 根据顺式上下文，结合并诱导或抑制不同的目标组，ii) 瞬时 TF 目标 仅在控制植物早期 N 反应的细胞中捕获，对于我们的 GRN 中的两个主 TF（bZIP1 和 NLP7）。这 全基因组数据支持 Hit-and-Run 转录模型，其中 TF Hit 可以启动稳定的转录 转录复合体，包括招募转录因子伙伴，使转录在启动后继续进行 TF不再束缚，快跑。这可以让少量的 TF 分子迅速影响大量的 TF 分子。 通过催化作用来改变靶基因。我们的研究被引用并影响了瞬态思维 跨酵母、干细胞的转录机制，并被用来解释瞬态的新发现 Zelda/Bicoid 与果蝇报告基因的结合。在这里，我们部署了实验和计算 创新来测试概念创新的普遍性和体内意义 - 瞬态的点击和 - 在 GRN 中运行交互。我们的实验性创新包括： i) 对所有肇事逃逸活动的分析 拟南芥中的 70 个 TF 家族，使用我们最近基于细胞的 TARGET 检测的更高通量版本 发表，ii) 使用时间序列生物素 ChIP 和 DamID 捕获 TF-靶标相互作用的新方法，其中 在短暂的 TF-靶标相互作用上留下 DNA 甲基化标记，并得到初步数据的支持（目标 1 和 2）。 我们的计算创新包括： i) ConnectTF，一个集成 TF-DNA 结合和 RNA-seq 的平台 数据并识别候选的 Hit-and-Run TF，以及评估瞬态 TF 的植物相关性的方法 GRN 中的目标交互，例如 ii) 我们新发布的 Network Walking 方法，以及 iii) OutPredict，一种新的 基于时间的方法来预测未来时间点的基因表达（目标 3）。我们的实验和计算 这些方法具有广泛的适用性，我们的结果与影响人类健康的环境氮利用相关。