Center for Genomics and Systems Biology, Department of Biology, New York University, New York, NY, 10003, USA.
Courant Institute for Mathematical Sciences, New York University, New York, NY, 10012, USA.
Nat Commun. 2019 Apr 5;10(1):1569. doi: 10.1038/s41467-019-09522-1.
Charting a temporal path in gene networks requires linking early transcription factor (TF)-triggered events to downstream effects. We scale-up a cell-based TF-perturbation assay to identify direct regulated targets of 33 nitrogen (N)-early response TFs encompassing 88% of N-responsive Arabidopsis genes. We uncover a duality where each TF is an inducer and repressor, and in vitro cis-motifs are typically specific to regulation directionality. Validated TF-targets (71,836) are used to refine precision of a time-inferred root network, connecting 145 N-responsive TFs and 311 targets. These data are used to chart network paths from direct TF-regulated targets identified in cells to indirect targets responding only in planta via Network Walking. We uncover network paths from TGA1 and CRF4 to direct TF targets, which in turn regulate 76% and 87% of TF indirect targets in planta, respectively. These results have implications for N-use and the approach can reveal temporal networks for any biological system.
绘制基因网络的时程路径需要将早期转录因子 (TF) 触发的事件与下游效应联系起来。我们扩展了基于细胞的 TF 扰动测定法，以鉴定涵盖 88%氮响应拟南芥基因的 33 个氮早期响应 TF 的直接调控靶标。我们揭示了一种二元性，即每个 TF 既是诱导剂又是抑制剂，体外顺式基序通常特定于调控方向性。经过验证的 TF-靶标（71836）用于细化时间推断根网络的精度，连接 145 个氮响应 TF 和 311 个靶标。这些数据用于通过网络行走从细胞中鉴定的直接 TF 调控靶标到仅在植物中响应的间接靶标绘制网络路径。我们揭示了 TGA1 和 CRF4 到直接 TF 靶标的网络路径，它们分别在植物中调节 76%和 87%的 TF 间接靶标。这些结果对氮利用具有影响，并且该方法可以揭示任何生物系统的时间网络。
