Condition-Specific Modeling of Biophysical Parameters Advances Inference of Regulatory Networks.
Condition-Specific Modeling of Biophysical Parameters Advances Inference of Regulatory Networks.
复制标题
生物物理参数的特定条件建模促进了监管网络的推断。
DOI：
10.1016/j.celrep.2018.03.048
复制
发表时间：
2018
期刊：
影响因子：
8.8
通讯作者：
Bonneau,Richard
中科院分区：
文献类型：
--
作者：
Tchourine,Konstantine;Vogel,Christine;Bonneau,Richard
真核转录调控网络的大规模推断仍然具有挑战性。一个根本原因是现有算法通常忽略了关键的调控机制，例如 RNA 降解和转录后处理。在这里，我们描述了 InfereCLaDR，它结合了这些元素并推进了酿酒酵母的预测。首先，InfereCLaDR 采用高质量的黄金标准数据集，我们分别将其用作先验信息和模型验证。其次，InfereCLaDR 明确模拟转录因子活性和 RNA 半衰期。第三，它引入了表达子空间来导出每个基因的条件响应调控网络。 InfereCLaDR 的最终网络通过已知数据和趋势进行验证，并产生多种见解。例如，它预测作为蛋白酶体调节剂 Rpn4p 靶标的核酸代谢基因转录本和胞质伴侣蛋白复合体成员的半衰期较长。 InfereCLaDR 表明，更符合生物物理现实的调控网络模型可以提高真核生物和原核生物的预测准确性。
Large-scale inference of eukaryotic transcription-regulatory networks remains challenging. One underlying reason is that existing algorithms typically ignore crucial regulatory mechanisms, such as RNA degradation and post-transcriptional processing. Here, we describe InfereCLaDR, which incorporates such elements and advances prediction inSaccharomyces cerevisiae. First, InfereCLaDR employs a high-quality Gold Standard dataset that we use separately as prior information and for model validation. Second, InfereCLaDR explicitly models transcription factor activity and RNA half-lives. Third, it introduces expression subspaces to derive condition-responsive regulatory networks for every gene. InfereCLaDR's final network is validated by known data and trends and results in multiple insights. For example, it predicts long half-lives for transcripts of the nucleic acid metabolism genes and members of the cytosolic chaperonin complex as targets of the proteasome regulatorRpn4p. InfereCLaDR demonstrates that more biophysically realistic modeling of regulatory networks advances prediction accuracy both in eukaryotes and prokaryotes.