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: 10673969
• 负责人: Gloria CORUZZI
• 金额: $ 42.95万
• 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 2025-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10673969
• 关键词: 4-thiouracil; Affect; Affinity; Agriculture; Animals; Arabidopsis; Binding; Biological Assay; Biology; Biotin; Biotinylation; Cells; Classification; 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; Intervention; Knowledge; Mediating; Medicine; Messenger RNA; Methods; Methylation; Modeling; Nitrogen; Nuclear; Nutrient; Pathway interactions; Peptide Initiation Factors; Phenotype; Plants; Prevalence; Process; Protein Methyltransferases; Publishing; Regulation; Reporter Genes; Repression; Resolution; Role; Running; Sampling; Sensitivity and Specificity; Series; Signal Transduction; System; Systems Biology; Testing; Thinking; Time; Transcript; Transcription Initiation; Validation; Walking; Work; Yeasts; candidate identification; chromatin immunoprecipitation; data integration; embryonic stem cell; gene discovery; gene regulatory network; genome-wide; in vivo; innovation; network models; random forest; recruit; response; scale up; stem cells; time use; trait; transcription factor; transcriptome sequencing; web-based tool

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.

项目摘要： 该赠款利用了时间 - 第四和很大程度上未开发的转录维度 - 捕获瞬态 体内重要但错过的基因调节网络（GRN）的相互作用。这是因为基因组 - 捕获转录因子（TF）目标相互作用的比例方法有利于稳定的结合和报告基因 在几秒钟内检测瞬态TF目标相互作用的研究，错过了GRN模型所需的全局响应。 我们旨在通过实验捕获瞬态来填补我们对动态GRN的集体知识的时差 使用基于细胞的时间TF扰动测定法（AIMS 1＆2），全球TF目标相互作用，并评估 它们在未来时间点的预测基因表达方面的重要性（AIM 3），这是系统生物学的主要目标。 我们对植物中控制氮（N）信号的时间grns进行建模，但我们的方法广泛适用。 我们利用基于细胞的分析用于时间TF扰动，捕获瞬态TF-TARGET 相互作用全基因组； i）通过TF介导的基因调节，即使没有可检测到的TF结合，II） 在受控的TF核进入的几分钟内，iii）确定高度瞬态的TF结合，导致持续 从头mRNA的亲和力捕获的转录。我们发现我）一个TF可以稳定或瞬时 根据其顺式粘合，绑定并诱导或抑制不同的目标集，ii）瞬态TF目标 仅在细胞中捕获的planta早期N-子弹，用于我们的GRN中的两个主TF（BZIP1和NLP7）。这 全基因组数据支持撞击转录模型，其中TF命中可以启动稳定 转录复合物，包括招募TF合作伙伴，使转录在启动后继续 TF不再绑定，运行。这可能会使少数TF分子迅速影响大量 靶基因的作用。我们的研究被引用并影响了对瞬态的思维 跨酵母，茎细胞的转录机制，并被调用以解释新的瞬态发现 Zelda/Bicoid与果蝇中的报告基因的结合。本文中，我们部署了实验和计算 测试概念创新的普遍性和体内意义的创新 - 短暂的命中和 在GRN中运行互动。我们的实验创新包括： i）所有人进行击球活动的测定 70个拟南芥中的70个TF家族，使用较高的基于细胞的靶标测定的较高吞吐量。 发表，ii）使用时间序列生物素芯片和Damid捕获TF目标互动的新方法， 在初步数据支持的瞬态TF-TARGET相互作用上留下DNA甲基化标记（AIMS 1和2）。 我们的计算创新包括：i）ConnectTF，一个集成TF-DNA绑定和RNA-Seq的平台 数据并确定候选撞击TF，以及评估瞬态TF-植物相关性的方法 GRN中的目标互动，例如ii）我们新发布的网络步行方法，以及iii）Everpredict，一个新的 基于时间的方法在未来时间点预测基因表达（AIM 3）。我们的实验和计算 方法广泛适用，我们的结果与影响人类健康的环境N使用有关。

项目成果

DamID-seq: A Genome-Wide DNA Methylation Method that Captures Both Transient and Stable TF-DNA Interactions in Plant Cells.

DamID-seq：一种全基因组 DNA 甲基化方法，可捕获植物细胞中瞬时和稳定的 TF-DNA 相互作用。

• DOI: 10.1007/978-1-0716-3354-0_7
• 发表时间: 2023
• 期刊: Methods in molecular biology (Clifton, N.J.)
• 作者: Alvarez,JoséM;Hinckley,WillE;Leonelli,Lauriebeth;Brooks,MatthewD;Coruzzi,GloriaM
• 通讯作者: Coruzzi,GloriaM

The TARGET System: Rapid Identification of Direct Targets of Transcription Factors by Gene Regulation in Plant Cells.

TARGET 系统：通过植物细胞中的基因调控快速识别转录因子的直接靶标。

• DOI: 10.1007/978-1-0716-2815-7_1
• 发表时间: 2023
• 期刊: Methods in molecular biology (Clifton, N.J.)
• 作者: Brooks,MatthewD;Reed,KelseyM;Krouk,Gabriel;Coruzzi,GloriaM;Bargmann,BastiaanOR
• 通讯作者: Bargmann,BastiaanOR

EnsInfer: a simple ensemble approach to network inference outperforms any single method.

• DOI: 10.1186/s12859-023-05231-1
• 发表时间: 2023-03-24
• 期刊: BMC bioinformatics
• 影响因子: 3

Building High-Confidence Gene Regulatory Networks by Integrating Validated TF-Target Gene Interactions Using ConnecTF.

使用 ConnecTF 集成经过验证的 TF-目标基因相互作用，构建高可信度的基因调控网络。

• DOI: 10.1007/978-1-0716-3354-0_13
• 发表时间: 2023
• 期刊: Methods in molecular biology (Clifton, N.J.)
• 作者: Huang,Ji;Katari,ManpreetS;Juang,Che-Lun;Coruzzi,GloriaM;Brooks,MatthewD
• 通讯作者: Brooks,MatthewD

Author Correction: OutPredict: multiple datasets can improve prediction of expression and inference of causality.

作者更正：OutPredict：多个数据集可以提高表达的预测和因果关系的推断。

• DOI: 10.1038/s41598-020-69883-2
• 发表时间: 2020
• 期刊: Scientific reports
• 影响因子: 4.6
• 作者: Cirrone,Jacopo;Brooks,MatthewD;Bonneau,Richard;Coruzzi,GloriaM;Shasha,DennisE
• 通讯作者: Shasha,DennisE