Understanding Cell Fate with Single-cell and Regulatory Genomics
We aim to understand how cell fate is determined and how gene regulatory mechanisms operate in development and disease. Using single-cell and spatial multi-omics as core technology platforms, we integrate functional perturbation experiments, epigenomic profiling, bioinformatics, and machine learning to systematically map regulatory networks underlying cell-state transitions, tissue and organ formation, and disease progression.
Embryonic development and cancer progression are deeply interconnected. Tumour cells often recapitulate developmental programs of cellular plasticity, lineage transition, and epigenetic regulation, while also hijacking regulatory mechanisms that normally operate during development to drive disease progression. To address these questions, we combine wet-lab and dry-lab approaches to develop new omics technologies and computational methods. Our goal is to reveal the key regulatory logic of development and cancer at genome-wide scale and single-cell resolution, providing a mechanistic foundation for precision tumour stratification, personalised therapy, and the discovery of new therapeutic targets.
我们课题组的工作希望能解析发育与疾病中的细胞命运决定及其基因调控机制。以单细胞与空间多组学为核心技术平台，结合功能扰动实验、表观基因组测序、生物信息学和机器学习方法，系统描绘细胞状态转变、组织器官形成以及疾病进展中的调控网络。
胚胎发育与癌症发生发展存在深层联系。肿瘤细胞常常重现胚胎发育过程中的细胞可塑性、谱系转换和表观遗传程序，并劫持正常发育中的调控机制以促进疾病进展。围绕这一核心问题，我们通过“湿实验—干实验”紧密结合的研究体系，发展新的组学技术与计算方法，在全基因组层面和单细胞分辨率揭示发育和癌症中的关键调控逻辑，为肿瘤精准分层、个体化治疗和新靶点发现提供机制基础。
Highlights
RegVelo
GRN-informed 单细胞动态建模框架，将 RNA velocity 与调控网络连接起来，用于轨迹推断、latent time 和 perturbation effect 预测。
Cranial neural crest regulatory circuits
整合单细胞 multiome、空间转录组与系统扰动，解析 cranial neural crest migration 与 fate plasticity 的调控网络。
Low-input methylome methods
开发 TEMPT 与 FINE-EM-seq 等低输入甲基化测序方法，用于 EV-DNA 和早期胚胎甲基组研究。