A research team led by Professor Zhang Xiaoyu from the College of Science's High-Dimensional Modeling Innovation Team recently published a groundbreaking study in Theoretical and Applied Genetics (IF: 4.4). Their paper, titled 'Exploiting Light Energy Utilization Strategies in Populus simonii through Multitrait-GWAS: Insights from Stochastic Differential Models,' reveals novel insights into plant photosynthesis efficiency.

The photosynthetic phenotype of trees undergoes changes and interactions that reflect their abilities to exploit light energy. Environmental disturbances and genetic factors have been recognized as influencing these changes and interactions, yet our understanding of the underlying biological mechanisms remains limited, particularly in stochastic environments. Here, we developed a high-dimensional stochastic differential framework (HDSD) for the genome-wide mapping of quantitative trait loci (QTLs) that regulate competition or cooperation in environment-dependent phenotypes. The framework incorporates random disturbances into system mapping, a dynamic model that views multiple traits as a system. Not only does this framework describe how QTLs regulate a single phenotype, but also how they regulate multiple phenotypes and how they interact with each other to influence phenotypic variations. To validate the proposed model, we conducted mapping experiments using chlorophyll fluorescence phenotype data from Populus simonii. Through this analysis, we identified several significant QTLs that may play a crucial role in photosynthesis in stochastic environments, in which 76 significant QTLs have already been reported to encode proteins or enzymes involved in photosynthesis through functional annotation. The constructed genetic regulatory network allows for a more comprehensive analysis of the internal genetic interactions of the photosynthesis process by visualizing the relationships between SNPs. This study shows a new way to understand the genetic mechanisms that govern the photosynthetic phenotype of trees, focusing on how environmental stochasticity and genetic variation interact to shape their light energy utilization strategies.

Junze Jiang, a Master's student at the College of Science, served as the paper's first author. The corresponding authors were Professor Zhang Xiaoyu from the College of Science and Professor Song Yuepeng from the School of Biological Science and Biotechnology. The research team also included Professor Zhang Deqiang from the School of Biological Science and Technology, Professor Fang Qing from Yamagata University, Japan, Master's students Lu Kaiyan and Zhou Ziyang from the College of Science, and doctoral student Gong Huiying from the School of Biological Science and Biotechnology.

This research was supported by the following projects: The 2023 Guiding Project of the College of Science, Beijing Forestry University(No: 2023BJFULXYYD-16), the National Science and Technology Major Special Project on New Drug Development(No.: 2019HXFWLIXY001), the National Natural Science Foundation of China(No.: 61802009) and the horizontal project (No.: 2017HXKFLIXY001).

Link: https://doi.org/10.1007/s00122-024-04775-x

Written by Zhang Xiaoyu
Translated and edited by Song He
Reviewed by Yu Yangyang