ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2025
Unveiling Salt Tolerance Mechanisms in Plants: Integrating the KANMB Machine Learning Model With Metabolomic and Transcriptomic Analysis.
Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Early detection and genetic insights into salt tolerance in rice by linking physiology and spectral reflectance during seed germination.Plant phenomics (Washington, D.C.) · 2026Article
- AI-Augmented Multi-Omics for Abiotic Stress Responses: A New Frontier in Plant Hormone Systems Biology.Plants (Basel, Switzerland) · 2026Review
- Artificial intelligence in plant salt stress research: from predictive models to multi-omics integration.Journal of experimental botany · 2026Review
- Decoding plant physiology through systems biology: Integrative multi-omics and computational perspectives for next-generation crop design.Plant communications · 2026Review
- Review
- Evolutionary expansion of theFrontiers in plant science · 2026Article
- Omics landscapes in molecular mechanisms withFood chemistry. Molecular sciences · 2025Review
- Dual-Emission Carbon Dot Nanozymes Mitigate Salt Stress and Enhance Photosynthesis for Crop Germination and Growth.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Multiomics analysis revealed the temporally common and specific molecular changes in Arabidopsis thaliana (L.) under salt stress.BMC genomics · 2025Article
- Recent Advances and Application of Machine Learning for Protein-Protein Interaction Prediction in Rice: Challenges and Future Perspectives.Proteomes · 2025Review
- Combined effect of salt stress and high light in plants: from basic statistical approach to machine learning methods.BMC plant biology · 2025Article
- Progress in Transcriptomics and Metabolomics in Plant Responses to Abiotic Stresses.Current issues in molecular biology · 2025Review
- Unveiling Salt Tolerance Mechanisms in Plants: Integrating the KANMB Machine Learning Model With Metabolomic and Transcriptomic Analysis.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Characterization and expression analysis of transcription factors inFrontiers in plant science · 2025Article
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
Salt stress presents a substantial threat to cereal crop productivity, especially in coastal agricultural regions where salinity levels are high. Addressing this challenge requires innovative approaches to uncover genetic resources that support molecular breeding of salt-tolerant crops. In this study, a novel machine learning model, KANMB is introduced, designed to analyze integrated multi-omics data from the natural halophyte Spartina alterniflora under various NaCl concentrations. Using KANMB, 226 metabolic biomarkers significantly linked to salt stress responses, grounded in metabolomic and transcriptomic profiles are identified. These biomarkers correlate with metabolic pathways associated with salt tolerance, providing insight into the underlying biochemical mechanisms. A co-expression analysis further highlights the MYB gene SaMYB35 as a pivotal regulator in the flavonoid biosynthesis pathway under salt stress. When overexpressed SaMYB35 in rice (ZH11) grown under high salinity, it triggers the upregulation of key flavonoid biosynthetic genes, elevates flavonoid content, and enhances salt tolerance compared to wild-type plants. The findings from this study offer a valuable genetic toolkit for breeding salt-tolerant cereal varieties and demonstrate the power of machine learning in accelerating biomarker discovery for stress resilience in non-model plant species.
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