During plant terrestrialization (the process of moving from aquatic to terrestrial environments), plants face many terrestrial stressors, such as drought, high salinity, and drastic temperature shifts. The main goal of our research is to understand how land plants adapt to these unfavorable environments at the molecular level during the course of evolution. We are also interested in applying the knowledge we obtain from these studies to design stress-resilient crops for precision agriculture.
Multi-omics: By using bulk RNA-seq, single-cell RNA-seq, ATAC-seq, and proteomics, we can accurately measure and quantify changes in genes and/or proteins at a systems level. By harnessing the hidden information from this big data, it also allows us to infer hypotheses and answer new questions.
Multi-species: By combining experimental data from diverse model plant species, such as Arabidopsis thaliana (a dicot and vascular plant), Oryza sativa (a monocot and vascular plant), and Marchantia polymorpha (a bryophyte and non-vascular plant), we can study the molecular evolution of distinct or conserved gene regulatory networks (GRNs) and signaling networks in the green lineage.
Multi-networks: Integrated network analysis is crucial for accurately predicting regulatory circuits. Gene regulatory networks (GRNs) allow us to understand the dynamics and hierarchy of hundreds and thousands of regulators (e.g., transcription factors, TFs) and their targeted genes simultaneously. Similarly, signaling networks will provide us with a sophisticated understanding of kinase cascade dynamics upon environmental perturbations.
Understanding the chromatin accessibility dynamics and gene regulatory landscape of multiple abiotic stress responses during long-term plant evolution.
Understanding the global phosphorylation landscape across distant species in response to environmental perturbations.
Decoding plant abiotic response at the single cellular resolution during early land plant evolution.
Predictive modeling for plant stress tolerance