Low-temperature stress restricts plant growth, geographic distribution, and crop productivity. Plants mitigate this threat through cold acclimation, a process involving the activation of protective genes and physiological responses. The ICE1-CBF-COR signaling pathway has long been recognized as a central regulator of cold tolerance, while photoreceptors and light-responsive transcription factors are known to influence plant development and stress adaptation. Increasing evidence suggests that temperature responses are also shaped by photoperiod and light quality. However, previous studies have generally examined individual genes or isolated pathways, leaving the dynamic transcriptional network connecting light perception with cold signaling insufficiently understood.
A study (DOI: 10.48130/els-0026-0007) published in Engineering in Life Sciences on 12 August 2026 by Ai-Sheng Xiong's team, Nanjing Agricultural University, presents a computational model that reproduces observed cold-responsive gene-expression dynamics and identifies phytochromes and the SlPIF4-SlGAI4 feedback loop as important regulatory hubs.
The researchers constructed a system of ordinary differential equations integrating three experimentally supported regulatory modules: the ICE1-CBF-COR cold-response pathway, the light-regulated COP1-HY5-MYB15 cascade, and the phytochrome-PIF4-GAI4 pathway responsible for sensing light quality. Environmental inputs included temperature, light-dark cycles, and the ratio of red to far-red light. Transcriptional regulation was represented using Hill functions, while translation, protein activation, and degradation were modeled through mass-action, Michaelis-Menten, or first-order kinetics. The model was parameterized using published tomato expression data for SlHY5 and SlMYB15 under cold treatment and different genetic backgrounds. It was then validated against independent datasets for SlCBF1 and SlCOR413 under contrasting photoperiods and continuous light. Simulations closely matched experimental observations: coefficients of determination ranged from 0.836 to 0.918 for the training genes and from 0.843 to 0.986 for the validation genes. The model reproduced cold-induced SlHY5 expression, genotype-dependent SlMYB15 activity, rapid induction of SlCBF1, and the sustained response of SlCOR413. It further predicted that short days and low red-to-far-red light conditions increase SlPHYA accumulation, reduce SlPHYB levels, and produce stronger SlCBF1 expression during cold exposure. Simulations also suggested that cold treatment enhances the stability of both phyA and phyB proteins. Analysis of the SlPIF4-SlGAI4 negative feedback loop produced sustained oscillations in SlPIF4 expression with a period of 23.82 hours; removing the feedback abolished this rhythmic behavior. In additional simulations, repeated warm-cold cycles induced persistent oscillations in SlCOR413, with longer temperature cycles producing longer periods and larger amplitudes. Sensitivity analysis identified transcriptional activation and protein synthesis parameters as especially influential, highlighting regulatory processes that require more precise experimental measurement.
Overall, the study demonstrates how mathematical modeling can connect fragmented molecular evidence into a coherent picture of light-cold signaling in tomato. By identifying phytochrome activity and the SlPIF4-SlGAI4 feedback circuit as potential control points, the framework offers testable hypotheses for improving crop cold tolerance. Because the predicted oscillations of SlCOR413 have not yet been experimentally confirmed, high-resolution time-series experiments will be essential before these findings can be translated into breeding or targeted genetic-engineering strategies.
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References
DOI
10.48130/els-0026-0007
Original Source URL
https://doi.org/10.48130/els-0026-0007
Funding information
This work was supported by the Primary Research and Development Plan (Modern Agriculture) of Jiangsu Province (BE2023350) and the Priority Academic Program Development of Jiangsu Higher Education Institutions Project (PAPD).
About Engineering in Life Sciences
Engineering in Life Sciences (e-ISSN 1618-2863; p-ISSN 1618-0240) is an international source on bioengineering principles and innovations in life sciences and biotechnology, spanning biochemical engineering, process engineering, industrial chemistry. As a fully open access journal, we aim to promote global relationships among biologists, biotechnologists and bioengineers.