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Article|07 Jun 2022|OPEN
An eco-evo-devo genetic network model of stress response
Li Feng1 ,† , Tianyu Dong1 ,† , Peng Jiang1 ,† , Zhenyu Yang1 , Ang Dong1 , Shang-Qian Xie2 , Christopher H. Griffin3 and Rongling Wu,1,4 ,
1Center for Computational Biology, College of Biological Sciences and Technology, Beijing Forestry University, Beijing 100083, China
2Key Laboratory of Ministry of Education for Genetics and Germplasm Innovation of Tropical Special Trees and Ornamental Plants, College of Forestry, Hainan University, Haikou 570228, China
3Applied Research Laboratory, The Pennsylvania State University, University Park, PA 16802, USA
4Center for Statistical Genetics, Departments of Public Health Sciences and Statistics, The Pennsylvania State University, Hershey, PA 17033, USA
*Corresponding author. E-mail: rwu@phs.psu.edu
Li Feng,Tianyu Dong and Peng Jiang contributed equally to the study.

Horticulture Research 9,
Article number: uhac135 (2022)
doi: https://doi.org/10.1093/hr/uhac135
Views: 82

Received: 01 Mar 2022
Accepted: 04 Jun 2022
Published online: 07 Jun 2022

Abstract

The capacity of plants to resist abiotic stresses is of great importance to agricultural, ecological and environmental sustainability, but little is known about its genetic underpinnings. Existing genetic tools can identify individual genetic variants mediating biochemical, physiological, and cellular defenses, but fail to chart an overall genetic atlas behind stress resistance. We view stress response as an eco-evo-devo process by which plants adaptively respond to stress through complex interactions of developmental canalization, phenotypic plasticity, and phenotypic integration. As such, we define and quantify stress response as the developmental change of adaptive traits from stress-free to stress-exposed environments. We integrate composite functional mapping and evolutionary game theory to reconstruct omnigenic, information-flow interaction networks for stress response. Using desert-adapted Euphrates poplar as an example, we infer salt resistance-related genome-wide interactome networks and trace the roadmap of how each SNP acts and interacts with any other possible SNPs to mediate salt resistance. We characterize the previously unknown regulatory mechanisms driving trait variation; i.e. the significance of a SNP may be due to the promotion of positive regulators, whereas the insignificance of a SNP may result from the inhibition of negative regulators. The regulator-regulatee interactions detected are not only experimentally validated by two complementary experiments, but also biologically interpreted by their encoded protein–protein interactions. Our eco-evo-devo model of genetic interactome networks provides an approach to interrogate the genetic architecture of stress response and informs precise gene editing for improving plants’ capacity to live in stress environments.