Research
Our research decodes the dynamic information of biological systems, including epigenetic marks, RNA structures, and cell lineages. By developing and applying novel sequencing technologies, we aim to uncover how these dynamic layers govern development, disease, and evolution.
Research Interests
Sequencing Technology for Biological Dynamics
Our lab develops and optimizes high-throughput sequencing methods to study biological dynamics, including cell lineage tracing and RNA modifications (e.g., m6A, m5C, Ψ) at single-base resolution. We pioneer techniques such as CAM-seq, PUM-seq, and RAD-seq to push the boundaries of epitranscriptomics and single-cell analysis.[1]
Small RNA Targetome and RBP Footprinting
We develop and apply advanced sequencing technologies for RNA-binding protein (RBP) footprinting to map protein-RNA interactions across the transcriptome. Our research focuses on identifying small RNAs and non-coding RNAs, characterizing their targetomes, quantifying their abundance, and tracking their dynamic changes across different conditions.[2]
RNA and Protein Design
Our work focuses on innovative RNA and protein design strategies to unravel and engineer complex biological functions. This includes integrating AI-driven approaches and developing novel tools for cell lineage tracing such as SMALT to uncover how genetic and epigenetic networks evolve.[3]
Evolutionary and Systems Biology
We investigate developmental and evolutionary history by integrating multi-omics data. We also explore the role of epigenetic modifications in evolutionary processes. Using our advanced sequencing technologies for RBP footprinting and accessibility profiling, we aim to understand how RNA and DNA modifications contribute to adaptation and evolutionary fitness.[4]
Research Experience
Optimizing Bisulfite Sequencing for 5-Methylcytosine Detection in DNA and RNA
Building on our base-resolution toolkit, we pushed bisulfite chemistry to detect 5mC in both DNA and RNA with unprecedented speed and accuracy.
Developing Transcriptome-wide Pseudouridine Profiling Method at Base Resolution
In parallel, we tackled pseudouridine, the most abundant RNA modification, developing BID-seq and related methods to map it transcriptome-wide at single-base resolution.
Developing Single Base-Resolution Sequencing Methods for m6A
Around the same time, we pioneered quantitative m6A sequencing through m6A-SAC-seq and related approaches, achieving the single-base resolution that had long eluded the field.
Developing New Cell Lineage Tracing Strategy
These epitranscriptomic efforts grew out of our earlier work in cell lineage tracing, where we engineered CRISPR-based barcoding to record developmental histories in vivo.
Combining Lineage Tracing with Molecular Profiling
Extending the lineage tracing framework, we integrated it with molecular profiling to link cellular ancestry with functional states.
Assessing the Influence of Dietary History on Gut Microbiota
Early in the lab's trajectory, we explored how environmental factors such as diet shape microbial community dynamics, a theme that continues to inform our systems-level thinking.
References
- Ultrafast bisulfite sequencing for 5mC: Dai et al. 2024. Quantitative pseudouridine mapping with BID-seq: Dai et al. 2023. Quantitative m6A profiling with m6A-SAC-seq: Ge et al. 2023.
- RBP binding site profiling via in situ reverse transcription: Xiao et al. 2024. Transcriptome-wide 2'-O-methylation mapping with Nm-Mut-seq: Chen et al. 2023.
- Single-cell-resolution lineage tracing: Liu et al. 2021. Lineage recording in zebrafish embryogenesis: Chen et al. 2020.
- Multi-omics integration for cell phylogeny: Liu et al. 2021. Influence of dietary history on gut microbiota: Yang et al. 2019.