Research Summary

The completion of the human genome project (HGP) in the beginning of this century and the application of affordable high-throughput sequencing technologies in the past decade have led life science researches to the post-genome era. The resulting wealth of deep-sequencing datasets at genome (including epi-genome) and transcriptome (including epi-transcriptome) levels challenges us to fully understand how functional genomic elements are transcribed and regulated, thus leading to human health and/or diseases. Importantly, the advent of novel genome editing technologies provides us powerful methods to change genetic information at desired target sites at single nucleotide resolution, which benefits not only basic research aiming to decipher how different genotypes result in distinct phenotypes but also pre-clinical study potential to cure human diseases caused by genetic mutations.

Since established in 2011, my lab has continuously developed and applied computational strategies, including the-state-of-the-art machine learning and deep learning approaches, together with deep-sequencing technologies and diverse biochemical methods,

• to dissect complex expression, novel function and potential application of long noncoding RNAs (lncRNAs) and circular RNAs (circRNAs) from back-splicing;
• to achieve precise genetic changes in the application of biomedical research and therapeutics by the invention of novel genome base editing systems;
• to uncover previously-underappreciated modes of RNA regulation, such as alternative polyadenylation and subcellular localization, at single-cell resolution.

Research Achievements

1. Genome-wide profiling and characterization of functional circRNAs
2. Nucleotide editing modification and genome base editing technologies
3. Novel machine/deep learning approaches for the understanding of RNA regulation