Zhiyong Wang was appointed acting director of Department of Plant Biology in 2018.

Wang’s research aims to understand how plant growth is controlled by environmental and endogenous signals. Being sessile, plants respond environmental changes by altering their growth behavior. As such, plants display high developmental plasticity and their growth is highly sensitive to environmental conditions. Plants have evolved many hormones that function as growth regulators, and growth is also responsive to the availability of nutrients and energy (photosynthates).

To understand how plant cells perceive and transduce various regulatory signals, and how combinations of complex information are processed into growth decisions, such as shoot cell elongation and root growth, by the cellular circuitry, the Wang lab uses a wide range of cutting-edge technologies in proteomics and genomics, as well as traditional genetic and molecular approaches, and both model systems and crops.

The Wang lab has spent years dissecting the signaling pathway of one major class of plant hormones, brassinosteroids, making it one of the best-studied signal transduction pathways in plants. Brassinosteroids play important roles in a wide array of functions, including cell elongation, photomorphogenesis, and reproductive development, with major effects on plant size and biomass accumulation. Brassinosteroids also have impacts on the response to environmental stresses and resistance to pathogens.

In recent years, research by the Wang lab has uncovered a central growth-regulation network that integrates all major signals that control shoot cell elongation, including brassinosteroids, auxin, gibberellin, light, temperature, the circadian clock, sugar, and pathogen signals. Wang believes that this central growth network will be a major target for genetically engineering high-yield crops.

A major current effort of Wang lab is to map the protein networks using proteomic approaches. Both protein-protein interactions and posttranslational modifications are studies at large scale using mass spectrometry in combination with affinity enrichment, proximity labelling, crosslinking, and synthetic protein interactions. The aim is to establish complete protein and gene networks and to engineer the networks to achieve improved traits.

Wang received his B.S. in plant physiology from Lanzhou University, China, his M.S. from the Institute of Botany, Chinese Academy of Sciences, and his Ph. D. in molecular, cell and developmental biology at UCLA. For more see http://dpb.carnegiescience.edu/labs/wang-lab

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Photo of flowering Arabidopsis thaliana purchased from Shutterstock.
February 11, 2021

Palo Alto, CA— Understanding how plants respond to stressful environmental conditions is crucial to developing effective strategies for protecting important agricultural crops from a changing climate. New research led by Carnegie’s Zhiyong Wang, Shouling Xu, and Yang Bi reveals an important process by which plants switch between amplified and dampened stress responses. Their work is published by Nature Communications.

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Senna tora photo courtesy of Shutterstock.
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PolyP courtesy of Arthur Grossman and Emanuel Sanz-Luque
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Revolutionary progress in understanding plant biology is being driven through advances in DNA sequencing technology. Carnegie plant scientists have played a key role in the sequencing and genome annotation efforts of the model plant Arabidopsis thaliana and the soil alga Chlamydomonas reinhardtii. Now that many genomes from algae to mosses and trees are publicly available, this information can be mined using bioinformatics to build models to understand gene function and ultimately for designing plants for a wide spectrum of applications.

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Evolutionary geneticist Moises Exposito-Alonso joined the Department of Plant Biology as a staff associate in September 2019. He investigates whether and how plants will evolve to keep pace with climate change by conducting large-scale ecological and genome sequencing experiments. He also develops computational methods to derive fundamental principles of evolution, such as how fast natural populations acquire new mutations and how past climates shaped continental-scale biodiversity patterns. His goal is to use these first principles and computational approaches to forecast evolutionary outcomes of populations under climate change to anticipate potential future