Qingqing Wang (王晴晴), Ph.D.
Title: Professor
Address: Room 602, College of Agriculture,
South China Agricultural University, Guangzhou, China
Email: qingqing.wang@scau.edu.cn
RESEARCH INTEREST
Photoperiod, the length of day and night, is the most reliable seasonal signal. While previous studies mainly focused on photoperiodic flowering, we demonstrate that plants distinguish different photoperiods to independently control seasonal flowering and growth. By integrating biochemical, genetic, and multi-omics approaches, we aim to understand how photoperiod regulates growth rate in sensitive crops like soybean and rice. Our goal is to dissect photoperiodic response networks and provide insights for breeding crops with improved yield, quality, and regional adaptation.
EDUCATION
2011-2015 Ph.D. at School of Life Sciences, Sun Yat-sen University, Guangzhou
2008-2011 Master at Fisheries College, Ocean University of China
2004-2008 B.S. in Biology, Qufu Normal University, Shandong
EMPLOYMENT HISTORY
2025-Now Professor,
Collage of Agriculture, South China Agricultural University
2023-2024 Associate Research Scientist,
Department of Molecular, Cellular and Developmental Biology, Yale University
2018-2023 Postdoctoral Researcher,
Department of Molecular, Cellular and Developmental Biology, Yale University
2015-2016 Postdoctoral Fellow,
School of Life Science, Sun Yat-sen University, Guangzhou
AWARDS AND HONORS
2025-2027 Recipient of the Excellent Young Scientist Fund of NSFC (Overseas)
2021-2022 Elizabeth D. W. Brown Fund Endowed Fellowship (Yale University)
2020-2021 Forest B. H. Fellowship (Yale University)
PUBLICATIONS
1.Qingqing Wang, Wei Liu, Chun Chung Leung, Daniel A. Tarté, Joshua M. Gendron (2024) Plants distinguish different photoperiods to independently control seasonal flowering and growth, Science, 383(6683).
(Highlighted by Buckley and Haydon. (2024) Time for Growth. Science 383(6683):589)
2.Chun Chung Leung, Daniel A. Tarté, Lilijana S. Oliver, Qingqing Wang, Joshua M. Gendron (2023) Systematic characterization of photoperiodic gene expression patterns reveals diverse seasonal transcriptional systems in Arabidopsis, PLoS Biol., 21(9): e3002283.