Compartment-specific core microbiomes in potato tubers are associated with plant health across genotypes, soils, and years
Qiao, Y.; Qiao, J.; Berendsen, R.; Cheng, X.; Pieterse, C.; Song, Y.
Show abstract
Harnessing plant microbiomes for sustainable agriculture requires understanding not only whether they can boost crop performance, but also how they assemble, persist, and support plant growth and health across environments. While we previously showed that seed tuber microbiomes can predict potato vigour using machine learning, it remained unclear how ecological processes shape tuber microbiome stability and functionality across host genotypes, tuber compartments, soil types, and years. Here, we analyzed the national-scale dataset of 240 field-collected potato seedlots, spanning six genotypes, two soil types, and two growing years, with a focus on the spatially distinct heel and eye compartments of the potato tuber. By profiling over 1,200 bacterial and fungal communities and linking microbiome composition to plant performance using leaf area as a health proxy, we show that plant genotype and tuber compartment are the strongest determinants of microbial diversity and composition. Compartment-specific enrichment of functional traits was observed, with organic compound conversion and nitrogen cycling dominant in the heel, and energy metabolism enriched in the eye. Using a macroecological abundance-occupancy framework, we identified a stable core microbiome of bacterial and fungal taxa that persisted across environments and years. Core members were more strongly associated with plant performance than non-core taxa, and pathogen-suppressive functions were spatially structured, with distinct protective taxa dominating in the heel versus the eye. Together, our findings demonstrate that tuber compartments act as selective microbial filters, shaping persistent microbiomes with specialized functions. By providing an ecological and functional framework for compartment-resolved, stable core microbiomes, this study complements our predictive modelling work and highlights persistent microbial partners as promising targets for improving potato resilience and productivity.
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