本项目针对该重大计划指南中的（1）组织器官再生修复的新模型、新技术与新方法与（2）组织器官再生修复的多维网络信息解码等两个资助方法，突破染色质表观研究瓶颈，首次提出染色质修饰纳米环境的新概念、新观点，拟发展DNA邻近步行机器编码的识别新思路，论证DNA邻近编码扩增原理，建立再生修复模型组织样品的单细胞分辨染色质修饰纳米环境成像分析新方法。我们以某一种组蛋白PTM邻近纳米空间（半径约20 nm）内5mC、5hmC、5fC等DNA修饰为例。在该纳米环境内，我们的方法可循环识别PTM/5mC、PTM/5hmC、PTM/5fC三种组合修饰位点，并实现单位点灵敏的细胞或组织荧光成像。可获取染色质修饰纳米环境中的修饰种类、位点数、亚细胞分布等多维信息；再利用机器学习算法解析所得特征信息，绘制再生修复过程的相关分子调控网络；为阐释损伤组织器官再生修复障碍的病理基础与关键调控机制提供方法学基础。

During organ regeneration and repair, the chromatin modifications paly important regulatory functions. And the complex spatial co-existing and interaction of diverse chromatin modifications may imply unknown, complicated regulatory mechanisms, which is essential for revealing the key mechanisms of the differences in regeneration and repair capabilities between tissues. However, the current detection technology cannot meet the demand. In this project, we intends to develop a novel DNA proximity-encoded amplification strategy to image the nanoenvironments of chromatin modifications during organ regeneration/repair. We detect three DNA modifications (5mC, 5hmC, and 5fC) in the nanoenvironment of a histone PTM (with a radius of about 20 nm) as an example. In this nanoenvironment, our method can repeatedly recognize and identify the three combination modification sites (PTM/5mC, PTM/5hmC and PTM/5fC), and finally realize cell or tissue fluorescence imaging with single-site sensitivity. Finally, complex combinations and interactions in the chromatin modification nanoenvironment in single cells will be visualized. We can obtain multi-level information of chromatin signatures including modification types, numbers of modification sites, subcellular distributions and combination patterns. And machine learning algorithms are used to analyze these information, and the relevant molecular regulation network of the regeneration and repair process can be drawn. We will also explain the key regulatory mechanisms of the regeneration and repair of damaged tissues/organs.