课题组综合运用前沿生物技术与机器智能方法，重点开展以下研究：（1）开发适用于油菜群体组学的新技术与分析方法；（2）解析油菜重要性状的基因组学特征及其演化规律；（3）结合机器智能方法与实验研究，探究油菜性状调控机制与生命活动的基础过程；（4）开发油菜设计育种的关键技术。课题组致力于为油菜的设计育种提供理论支撑和优异基因资源，促进高产优质油菜品种的培育。
Our research group integrates cutting-edge biotechnology and machine intelligence methods to focus on the following areas: (1) developing new technologies and analytical methods tailored for rapeseed population genomics; (2) elucidating the genomic characteristics and evolutionary patterns of key traits in rapeseed; (3) exploring the regulatory mechanisms of rapeseed traits and fundamental biological processes by combining AI approaches with experimental studies; and (4) advancing key technologies for rapeseed design breeding. The group is dedicated to providing theoretical support and superior genetic resources for rapeseed design breeding, thereby promoting the development of high-yield and high-quality rapeseed varieties.
The lab connects genome-scale resources, field phenotyping, and computational models for rapeseed design breeding.
We develop and analyze rapeseed population genomic resources to understand diversity, evolution, and trait architecture.
We map loci and prioritize candidate genes for important agronomic traits, including seed oil content and fatty acid composition.
We integrate multi-omics data and AI methods to model regulatory mechanisms and support crop design breeding.
We build web servers, databases, tutorials, and data resources for the rapeseed research community.
Recent studies from the lab and collaborators.
Xu Han, Zhanxiang Zong, Weidong Ning, Yuting Zhang, Zengdong Tan, Yunhao Liu, Yukun Song, Qiyuan Long, Yuyan Xiang, Shaoping Lu, Xuan Yao, Hu Zhao, Liang Guo
DOI / ArticleBo Wang, Zhanxiang Zong, Shaochen Jia, Xu Han, Liang Guo, Hu Zhao
DOI / ArticleZhang Y, Liu Y, Zong Z, Guo L, Shen W, Zhao H.
DOI / ArticleRecent publications, lab activities, and research updates from RGMI Lab.
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