CAREER: Delineate context-specific gene regulation in 3D chromatin space

基因组是成千上万个基因的家园，它们的活动由许多生物分子开启和关闭。基因控制系统的正常运作深刻地影响着生命的各个方面，例如不同组织的形成，不同物种的进化以及对环境刺激的反应。然而，基因组不是简单的一维实体，而是具有复杂的三维（3D）结构，其在促进生物分子之间的相互作用中起着基础作用。该项目的总体目标是开发严格的计算方法，通过整合3D基因组结构信息来发现基因的控制机制。这个问题的答案对于揭示生命的潜在规则至关重要，这将使我们有能力将复杂的基因组与生物系统的变化联系起来。该项目将产生开源软件和大规模资源，在细胞生物学，生物工程，疾病诊断，作物改良和生态学中具有广泛的应用和影响。暑期研究体验、公众科学素养在线资源和高中生教育模块等活动将极大地激励下一代学生进行跨学科学习和研究。该项目将开发一套先进的概率模型和高效的推理算法，通过系统整合3D染色质结构信息来描绘复杂的基因调控。本计画的第一个目标是发展一种基于贝叶斯图模型的细胞类型特异性转录因子结合位点预测算法。第二个目标是设计一个有效的搜索算法，以确定结构的转录因子参与特定的基因表达的调控电路。基于这些方法的发展，第三个目标是开发一种新的基于调控网络的算法来预测不同扰动引起的基因表达变化。该项目生成的算法和软件将成为实验和计算生物学家分析大规模多组学数据集的工具，以获得可解释的预测，并了解复杂的基因调控系统如何在3D染色质空间中协调。为了激励和吸引学生，特别是代表性不足的少数民族本科生，进入生物和计算科学，新颖的虚拟现实可视化YouTube视频和Youtube笔记本教学材料将沿着参与国家妇女工程计划和NSF REU计划。 该项目的成果，包括开发的计算基础设施和教育材料，可以在www.example.com上找到https://cmse.msu.edu/directory/faculty/jianrong-wang/.This奖项反映了NSF的法定使命，并被认为值得通过使用基金会的知识价值和更广泛的影响审查标准进行评估来支持。

The genome is home to thousands of genes, whose activities are turned on and off by many biological molecules. The proper functioning of gene control systems profoundly influences all aspects of life, such as the formation of diverse tissues, evolution of different species, and response to environmental stimuli. However, the genome is not simply a one-dimensional entity but takes on complex three-dimensional (3D) structure, which plays a fundamental role to facilitate interactions among biological molecules. The overarching goal of this project is to develop rigorous computational methods to discover the control mechanisms of genes by integrating 3D genome structure information. The answer to this question is crucial for revealing the underlying rules of life which will provide us the capacity to link complex genome to changes in a biological system. This project will generate open-source software and large-scale resources with wide applications and impacts in cell biology, bioengineering, disease diagnostics, crop improvement and ecology. Activities, such as summer research experiences, online resources for public scientific literacy, and education modules for high-school students, will greatly motivate next generation students to pursue interdisciplinary study and research.This project will develop a suite of advanced probabilistic models and efficient inference algorithms to delineate complex gene regulation by systematically integrating the 3D chromatin structure information. The first goal of this project is to develop a predictive algorithm of cell-type specific transcription factor binding site based on a novel Bayesian graphical model. The second goal is to design an efficient search algorithm to identify structures of regulatory circuitry of transcription factors involved in context-specific gene expression. Building upon these methodological developments, the third goal is to develop a new regulatory network-based algorithm to predict gene expression changes induced by different perturbations. The algorithms and software generated by this project will be tools for both experimental and computational biologists to analyze large-scale multi-omics datasets, to derive interpretable predictions, and to understand how complex gene regulatory systems are coordinated in 3D chromatin space. To motivate and engage students, especially underrepresented minority undergraduates, into biological and computational science, novel virtual reality visualization Youtube videos and Jupyter notebooks teaching materials will be disseminated along with participation in national Women in Engineering Program and NSF REU program. Results of this project, including the developed computational infrastructure and education materials, can be found at https://cmse.msu.edu/directory/faculty/jianrong-wang/.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.