昼夜节律磷酸化参与季节性情绪调节的生物信息学研究

多组学数据整合是生物信息学领域的重大挑战，蛋白质磷酸化是重要的生物大分子动态修饰之一，昼夜节律参与季节性情绪调节是重要的科学问题。本项目中，我们拟基于已有的研究基础，围绕第一个在人类个体中发现的、参与季节性情绪调节的生物钟基因PERIOD3 (PER3)，以携带人类野生型PER3和变异PER3小鼠为主要模型，结合不同光周期的实验条件，收集小鼠脑组织开展多维时序组学鉴定，设计生物信息学算法高效整合多组学数据，模拟联结昼夜节律和季节性情绪调节的潜在信号通路，预测并验证通路中重要蛋白激酶和磷酸化底物，揭示其与PER3的相互作用关系及其受到光调控的分子机制，初步阐明昼夜节律磷酸化参与季节性情绪调节的机理。研究结果不仅为翻译后修饰的组学数据整合与分析提供重要的计算方法，也为情感障碍的临床预防与诊疗提供坚实的理论基础。

Multi-omics data integration is a great challenge in bioinformatics. Protein phosphorylation is an important dynamic modification of biological macromolecules, whereas how circadian rhythm is involved in seasonal mood regulation has emerged to be an important scientific question. Based on our previous studies, we propose to focus on PERIOD3 (PER3), the first clock gene discovered to participate in seasonal mood regulation in human, using transgenic mice carrying human wild-type PER3 (hPER3-WT) and mutant PER3 (hPER3-P415A/H417R) as main models. We will collect mouse brain tissues under different photoperiods to conduct multi-dimensional time-course omics profilings, develop new bioinformatic algorithms to efficiently integrate the multi-omics data, and model the potential signaling pathways that connect circadian rhythm and seasonal mood regulation. Our goal is to identify new protein kinases and related substrates in this process which are direct or indirect targets of PER3, so as to unveil the molecular mechanisms of PER3 in mood regulation, as well as how photoperiod influences this process. These findings shall help elucidate the mechanism underlying how circadian phosphorylation participates in seasonal mood regulation. Our study will not only generate useful computational methods for the integration and analysis of the omics data for post-translational modifications, but also provide theoretical foundation for clinical prevention, diagnosis and treatment of affective disorders.