journal article·2022-10

Quantitative System Modeling Bridges the Gap between Macro‐ and Microscopic Stomatal Model

Mengmeng Rui, Yi Jing, Hangjin Jiang, Yizhou Wang

Advanced Biology· Volume 6· Issue 10
Publisher page

Abstract

Abstract An understanding of stomatal function is vital for the carbon and water cycle in nature. In the past decades, various stomatal models with different functions have been established to investigate and predict stomatal behavior and its association with plants’ responses to the changing climate, but with limited biological information provided. On the other hand, many stomatal models at the molecular level focus on simulating and predicting molecular practices and ignore the dynamic quantitative information. As a result, stomatal models are often divided between the microscopic and macroscopic scales. Quantitative systems analysis offers an effective in silico approach to explore the link between microscopic gene function and macroscopic physiological traits. As a first step, a systems model, OnGuard, is developed for the investigation of guard cell ion homeostasis and its relevance to the dynamic stomatal movements. The system model has already yielded a series of important predictions to guide molecular physiological studies in stomata. It also exhibits great potential in breeding practice, which represents a key step toward “Breeding by design” of improving plant carbon–water use efficiency. Here, the development of stomatal models is reviewed, and the future perspectives on stomatal modeling for agricultural and ecological applications are discussed.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Plant Stress Responses and Tolerance · Plant Water Relations and Carbon Dynamics · Plant nutrient uptake and metabolism

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Institute of Crop Science College of Agriculture and Biotechnology Zijingang Campus Zhejiang University Hangzhou 310058 P. R. China

BGI‐Sanya Sanya 572025 P. R. China

Center for Data Science Zhejiang University Hangzhou 310058 P. R. China

Hainan Yazhou Bay Seed Laboratory Sanya 572025 P. R. China

Zhejiang Provincial Key Laboratory of Crop Germplasm Zhejiang University Hangzhou 310058 P. R. China

Funding

National Natural Science Foundation of China

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