Guest Editors
Prof. Dr. Khalid Rehman Hakeem
Email: kur.hakeem@gmail.com
Affiliation: Department of Biological Sciences, Faculty of Science, King Abdulaziz University, Jeddah, 21589, Saudi Arabia
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Research Interests: plant eco-physiology, plant molecular biology, pollution research, environmental and agricultural studies, medicinal plant research, plant pathology, ecological and forestry studies
Dr. Vaseem Raja
Email: wrajamp2009@gmail.com
Affiliation: University Centre for Research and Development, Chandigarh University, Mohali, 140413, India
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Research Interests: plant stress, physiology phtochemistry, nano technology, molecular biology
Summary
Climate change driven extremes of temperature, drought, salinity, and pathogen outbreaks are jeopardizing global food security. Plants respond to these stresses through complex molecular, epigenetic, and microbial networks that determine their resilience. Recent studies highlight that epigenetic stress memory (DNA methylation, histone modifications, and small RNAs) can prime plants for faster recovery and confer heritable tolerance to future stress. Simultaneously, plant-associated microbiomes including plant growth–promoting rhizobacteria (PGPR) and endophytes enhance abiotic and biotic stress tolerance by modulating hormonal signaling and defense metabolism. However, the integration of epigenetic and microbiome-based priming remains largely unexplored, especially under combined stress conditions that mimic real agricultural environments. This proposal seeks to bridge that gap using multi-omics and machine-learning approaches to identify causal links between microbiome shifts, epigenetic reprogramming, and stress-resilient phenotypes.
· Crosstalk between plant epigenetic marks and microbial communities under combined abiotic (drought/salinity) and biotic (pathogen) stresses.
· Multi-omics biomarkers (microbial taxa, metabolites, methylation loci, transcripts) linked to stress resilience using interpretable machine-learning models.
· Evaluate transgenerational inheritance of primed states and resilience traits in progeny plants.
· Validate the efficacy of microbial epigenetic priming treatments in small-scale field trials under realistic stress conditions.
Keywords
epigenetics, microbial consortia, machine learning, DNA methylation, microbiome
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