Research |
Yinqing Li, Ph.D.

Yinqing Li joined Tsinghua faculty in 2018 and is currently an associate professor in the School of Pharmaceutical Sciences. He received his B.S. in microelectronics from Fudan University in 2008 and his S.M. and PhD in electrical engineering and computer science from Massachusetts Institute of Technology in 2012 and 2016, where he worked with Dr. Feng Zhang and Dr. Aviv Regev. He then performed postdoctoral research with Dr. Guoping Feng in the Broad Institute of Harvard and MIT and Stanley Center for Psychiatric Research. During the course of his doctoral and postdoctoral research, Yinqing pioneered the engineering and characterization of cell and gene editing tools, co-invented single-nucleus transcriptome profiling technologies, and broadened these tools to systematically interrogate cortical-thalamic circuity function and in disease models.

Research Interests

Dr. Yinqing Li's research focuses on the molecular and cellular changes that drive the onset and progression of complex diseases. The crucial aspect of his approach is to discern which molecules and cells undergo pivotal changes at specific time points during disease development, and to determine how these changes affect cellular functionality and interactions. This understanding is critical for developing effective diagnostic and therapeutic strategies, including targeting and modifying these essential molecules and cells to manage diseases.

His main research efforts are categorized into three primary areas:

Single-cell Characterization Technologies: Developing single-cell multi-omics techniques to capture dynamic changes in the epigenome, transcriptome, and signaling pathways. These methods allow for analysis at very rapid temporal and precise spatial scales, providing a detailed view of molecular and cellular interactions.

Gene Editing Technologies: Exploring novel gene editing systems for accurate gene replacement and epigenetic control, enabling holistic regulation of cellular states at the genetic level.

Bioinformatics: Advancing and applying statistical inference and machine learning algorithms to analyze high-throughput data in depth, discovering new genomic phenomena and modalities.

Scientific Contributions

1.Transcriptional condensates in precise expression control and stability (Cell 2024)
2.Graded neuronal heterogeneity in cortical-thalamic circuity regulation (Nature 2020)
3.Single nucleus omics in tracing adult neural stem cell (Science 2016)
4.Genome editing and chromatin modulation systems
5.Systems biology and gene circuit

Honors and awards
2019       MIT Technology Review, 35 under 35, China
2016       Extraordinary Potential Prize of 2016 Chinese Government Award for Students Abroad
2016       Wenner-Gren Fellowship
2013       McGovern Institute Fellowship

Selected Publications

1.He J*, Huo X*, Pei G*, Jia Z*, Yan Y, Yu J, Qu H, Xie Y, Yuan J, Zheng Y, Hu Y, Shi M, You K, Li T, Ma T, Zha ng MQ, Ding S, Li P#, Li Y#. Dual-role transcription factors stabilize intermediate expression levels. Cell. 2024 Apr 10:S0092-8674(24)00314-3.

2.Li Y, Lopez-Huerta VG, Adiconis X, Levandowski K, Choi S, Simmons SK, Arias-Garcia MA, Guo B, Yao AY, Blosser TR, Wimmer RD, Aida T, Atamian A, Naik T, Sun X, Bi D, Malhotra D, Hession CC, Shema R, Gomes M, Li T, Hwang E, Krol A, Kowalczyk M, Peça J, Pan G, Halassa MM, Levin JZ#, Fu Z#, Feng G#. Distinct subnetworks of the thalamic reticular nucleus. Nature. 2020, 583(7818):819-824.

3.Habib N*, Li Y*, Heidenreich M, Swiech L, Avraham-Davidi I, Trombetta JJ, Hession C, Zhang F#, Regev A#. Div-Seq: Single-nucleus RNA-Seq reveals dynamics of rare adult newborn neurons. SCIENCE. 2016, 353(6302):925-8.

4.Li Y*, Jiang Y*, Chen H*, Liao W, Li Z, Weiss R#, Xie Z#. Modular construction of mammalian gene circuits using TALE transcriptional repressors. NATURE CHEMICAL BIOLOGY. 2015, 11(3):207-13.

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