I aim at improving the specificity and fidelity of genome editing procedures by testing different donor DNA structures and programmable “nickases”. Such “nickases” are promising tools for precise genome editing as, in contrast to double-stranded DNA breaks, nicks are normally not engaged by mutagenic NHEJ while, albeit at low efficiency, they are still capable of triggering homology-directed gene targeting in mammalian cells. According to previous results from our group, coordinated nicking of target and donor DNA templates (in trans paired nicking) yields efficient and non-mutagenic genome editing in human cells, including pluripotent stem cells. My current research activities are focused on exploring this new genome strategy and investigating its underlying mechanisms.
From 2014 to 2017, I performed my M.Sc. studies under the supervision of Prof. Dr. Kai Li in the Laboratory of Molecular Medicine, Soochow University, China and worked on an experimental thesis about the application of a Blue-White Colony Assay for the off-target evaluation of CRISPR-Cas9 activity. In 2017, I was awarded a CSC scholarship to support my Ph.D. studies in the group of Dr. Manuel Gonçalves in the department of Cell and Chemical biology at the LUMC. My current research is mainly focused on investigating new strategies to improve the specificity and fidelity of genome editing based on testing different donor DNA structures and engineered programmable nucleases.
Advances in the engineering of the gene editing enzymes and the genomes: understanding and handling the off-target effects of CRISPR/Cas9
Yin Y, Wang Q, Xiao L, Wang F, Song Z, Zhou C, Liu X, Xing C, He N, Li K, Feng Y, Zhang J. J.
Biomed. Nanotechnol. 14, 456-476 (2018). doi: 10.1166/jbn.2018.2537.
Comparison of the off-target effects among one-base to three-base mismatched targets of gRNA using a blue to white assay.
Wang Q, Xiao L, Zhou L, Sun W, Xing C, Li K, He N.
J. Nanosci. Nanotechnol. 18, 1594-1598 (2018) doi: 10.1166/jnn.2018.13813.
A mutation-sensitive switch assay to detect five clinically significant epidermal growth factor receptor mutations.
Liu B, Zhou L, Wang Q, Li K.
Genet. Test. Mol. Biomarkers 19, 316-323 (2015). doi: 10.1089/gtmb.2014.0329.