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Decoding multifactorial stress responses in plants: lessons from omics integration
Laia Molinero-Domingo1, Lidia S Pascual1,2, Rosa M Rivero3
1Department of Biology, Biochemistry and Environmental Sciences, University Jaume I. Castelló de la Plana, 12071, Spain.
Plant responses to multiple simultaneous abiotic stresses are complex and non-additive. New integrative approaches are needed to predict plant resilience under multifactorial stress combination (MFSC) for crop improvement.
Area of Science:
- Plant Science
- Stress Biology
- Computational Biology
Background:
- Plants face simultaneous abiotic stresses, but research often uses reductionist single-stress models.
- Understanding combined stress effects is crucial as they differ significantly from individual stresses.
Purpose of the Study:
- To argue for integrative approaches in plant stress biology.
- To synthesize advances in understanding plant responses to multifactorial stress combination (MFSC).
Main Methods:
- Synthesizing recent research on signaling and metabolic rewiring under MFSC.
- Highlighting the role of multi-omics integration.
- Discussing computational frameworks like machine learning for predictive modeling.
Main Results:
- Plant responses to MFSC are non-additive, involving emergent states.
- Signaling and metabolic networks are rewired, exhibiting nonlinear behaviors.
- Multi-omics and machine learning can link molecular states to plant performance.
Conclusions:
- A shift towards integrative and predictive approaches is necessary for plant stress biology.
- Bridging the gap between controlled environments and field conditions is vital.
- Developing a predictive science of plant resilience is key for crop improvement under climate change.
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