Dr. Jing Li joined Sun Yat-sen University Cancer Center (SYSUCC) in November 2019. Currently, she is an associate professor at the department of experimental research with the support of “the 100 Top Talents Program” of Sun Yat-sen University. Dr. Li obtained her Bachelor degree in biological science at Nanjing University in 2009. She continued her PhD training in Nanjing University under the advisement of Dr. Dacheng Tian and got her PhD degree in 2014. During that time, she applied both wet lab and bioinformatics approaches to understand the basic questions in genetics and molecular evolution, including the evolution of plant resistant genes and the influence of GC-content on amino acid usages. After that, she moved to Nice (France) to continue the training as postdoc with the fellowship from Fondation ARC pour la Recherche sur le Cancer. During her postdoc from 2014 to 2019, she worked with Dr. Gianni Liti at Centre National de la Recherche Scientifique (CNRS), Institute for Research on Cancer and Aging, Nice (IRCAN) and tried to understand the mechanisms of how cells getting adapted to drugs, briefly, how drug resistance occurring  and evolving by pre-existing genetic variation and de novo mutations. At SYSUCC, Dr. Li is setting up multiple experimental systems and bioinformatics pipelines to understand evolutionary dynamics of cancer development and the underlying mechanisms of drug persistence and resistance.

Dr. Jing Li has broad interest in genetics, genomics and evolution, especially fascinated by the open question “how organisms respond to the changing environments by adaptive evolution”. The use of drugs is one of the most important approaches to treat cancer. However, “smart” cancer cells respond to the changing environments and evolve to search for various ways to escape the drug treatment, resulting in drug resistance. In order to overcome drug resistance, it is of great significance to understand the dynamics of how resistance arises. By experimental evolution and high-throughput approaches, we are able to track and investigate the detailed changes (e.g. genomic alterations, epigenetic modifications, transcriptome regulation) of cancer cells during adaptive evolution. On the other hand, once the cancer cells acquire drug resistance, they must have fitness costs (evolutionary trap). By high-throughput functional screen and phenotyping, we are able to identify such costs, which provide the potential targets to overcome resistance.

2014.8-2019.9 
Postdoctoral fellow, Centre National de la Recherche Scientifique (CNRS), Institute for Research on Cancer and Aging, Nice (IRCAN), France. Advised by Dr. Gianni Liti.

2009.9-2014.6 
Ph.D. in Biology, School of Life Sciences, Nanjing University, China. Advised by Dr. Dacheng Tian.

2005.9-2009.6 
B.Sc. in Biological Science, School of Life Sciences, Nanjing University, China.

Selected publications

Shared Molecular Targets Confer Resistance over Short and Long Evolutionary Timescales. Li, J., Vázquez-García, I., Persson, K., González, A., Yue, J.-X., Barré, B., Hall, M.N., Long, A., Warringer, J., Mustonen, V., Liti, G.*. Mol. Biol. Evol. 36, 691–708, 2019.

Identifying a large number of high-yield genes in rice by pedigree analysis, whole-genome sequencing, and CRISPR-Cas9 gene knockout. Huang, J.#, Li, J.#, Zhou, J., Wang, L., Yang, S., Hurst, L.D.*, Li, W.-H.*, Tian, D.*. Proc. Natl. Acad. Sci. U. S. A. 115, E7559–E7567, 2018

Contrasting evolutionary genome dynamics between domesticated and wild yeasts. Yue, J.-X., Li, J., Aigrain, L., Hallin, J., Persson, K., Oliver, K., Bergström, A., Coupland, P., Warringer, J., Lagomarsino, M.C., Fischer, G., Durbin, R., Liti, G.*. Nat. Genet. 49, 913–924, 2017

GC-Content of Synonymous Codons Profoundly Influences Amino Acid Usage. Li, J.#, Zhou, J.#*, Wu, Y., Yang, S., Tian, D.*. G3 Bethesda Md 5, 2027–2036, 2015

Rapidly evolving R genes in diverse grass species confer resistance to rice blast disease. Yang, S.#, Li, J.#, Zhang, X.#, Zhang, Q., Huang, J., Chen, J.-Q., Hartl, D.L.*, Tian, D.*. Proc. Natl. Acad. Sci. U. S. A. 110, 18572–18577, 2013

Unique evolutionary pattern of numbers of gramineous NBS–LRR genes. Li, J.#, Ding, J.#, Zhang, W., Zhang, Y., Tang, P., Chen, J.-Q., Tian, D.*, Yang, S.*. Mol. Genet. Genomics 283, 427–438, 2010

Last updated: April 2020 by International Office, Sun Yat-sen University Cancer Center