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Published on: January 3, 2025
Engineering Wheat for Compound Climate Extremes: Molecular Trade-Offs, Stress Memory, and Precision Genome Editing
Xin Song1, Xixiong Hong1, Huaiyuan Wu1
1School of Life Science and Environmental Resources, Yichun University, Yichun 336000, China.
Abstract:
Bread wheat (Triticum aestivum L.) increasingly encounters combinations of abiotic stresses that interact in time and whose effects are not predictable from single-stress responses. We define yield-stable resilience as the capacity to maintain grain yield under compound climate extremes without a significant penalty in yield or quality under favourable conditions; both components are required, and a line that tolerates stress while losing yield potential does not satisfy the definition. This critical review addresses three dimensions: the temporal architecture of stress across development; the biological control layers that run from perception through recovery to stress memory; and the precision-engineering strategies enabled by genome editing. We argue that field-level yield stability is rarely achieved by constitutively overexpressing or deleting a single stress-response gene. Instead, stress-integration networks must be engineered in a context-dependent, dosage-aware manner. To explain why single-gene solutions fall short, we examine molecular and physiological trade-offs, including water conservation versus transpirational cooling, photoprotection versus carbon acquisition, and stay-green versus remobilization. Stress-memory mechanisms, which range from chromatin modifications to persistent signalling states, offer a route to primed protection, but causal validation in wheat remains largely absent. The hexaploid wheat genome affords distinctive engineering opportunities through homoeologue-dosage control, promoter tuning and tissue-specific regulation. We propose an evidence-gated pathway that proceeds from mechanism to calibrated editing, to biologically realistic stress testing, to multi-environment yield testing, and finally to equitable deployment, and we treat breeding integration, introgression, recurrent selection and precision editing as a single pipeline rather than as competing alternatives.
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