The research goal of our laboratory is to understand the fundamental principles of plant genetics, development, and evolution through deep learning techniques, genome editing and synthesis technologies, high-throughput experimental methods, and associated bioinformatics tools. By generating and interpreting big biological data, we design and optimize plant genetic elements to enhance crop quality and yield, and to modify wild plant populations. Specifically, our research includes the following areas:

1. Plant Protein Optimization: Using directed evolution techniques and deep learning, we optimize sequences of target plant proteins and attempt to understand the evolutionary processes guided by the relationship between genotypes and phenotypes (fitness landscape).

2. Cell Lineage Tracing: Employing dynamic gene editing tools in conjunction with single-cell technologies, we trace the processes of plant cell division and differentiation. This helps us uncover the basic principles of plant growth, development, and organ formation, and to replicate trait innovation in plants through evolutionary processes.

3. Gene Drive Design: We explore genetic modification and population control of wild plant species using gene drive technology, aiming to achieve sustainable development in ecological management and agricultural production.

Together, these directions form a comprehensive framework for the design and synthesis of plant genetic elements, providing innovative solutions for modern agriculture and ecological conservation.