Genotype-specific transcriptomic response to drought stress in potato cultivars modulated by microbial biostimulants
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Background Drought is a major abiotic stress that significantly limits potato productivity and tuber quality. Microbial biostimulants have emerged as promising tools to improve crop resilience and promote sustainable agriculture. This study aimed to investigate the transcriptomic response to severe drought stress in three potato cultivars (Camelia, Cicero, and Agata) characterized by differing polyphenol content. In addition, the potential mitigating effects of a microorganism-based biostimulant mixture composed by two Trichoderma species, were evaluated. Results Severe drought stress led to a significant reduction in tuber yield in Camelia and Agata, whereas Cicero exhibited greater tolerance. Application of the microbial biostimulant slightly alleviated yield loss in Camelia but was associated with an increased proportion of non-commercial tubers. Polyphenol content varied according to genotype and treatment, Cicero displayed elevated polyphenol levels in the skin under drought, while Camelia showed increased levels in both skin and pulp when drought was combined with biostimulant application. Transcriptomic analysis revealed genotype-specific drought response strategies. Camelia exhibited enhanced proteostasis and osmoprotection via anthocyanin accumulation, while Cicero maintained photosynthetic activity, redox homeostasis, and genome stability. Trichoderma -based biostimulant treatment modulated these responses by enhancing endoplasmic reticulum protein quality control in Camelia, and promoting photosynthesis and sugar metabolism in Cicero. Conclusions Potato responses to drought are highly genotype-dependent and involve complex trade-offs among growth, stress defense, and metabolic reprogramming. Microbial biostimulants offer a promising approach to enhance drought resilience and tuber nutraceutical quality. However, their efficacy is genotype-specific and requires targeted application strategies for optimal results.
