Seed‐borne, endospheric and rhizospheric core microbiota as predictors of plant functional traits across rice cultivars are dominated by deterministic processes

Summary

This study used rice as a model to investigate how bacterial microbiota assemble across plant microhabitats (seed, root endosphere, rhizosphere) and their relationship to plant phenotypic traits. The research found that plant microhabitat, rather than cultivar subspecies, was the primary driver of microbial community structure, with assembly governed predominantly by deterministic host–microbe interactions. A core community of 15 generalist bacterial species persisted across microhabitats and their relative abundance profiles could predict plant functional traits, suggesting mechanistic links between plant-associated microbiota and host phenotype.

UK applicability

The findings on deterministic microbiota assembly mechanisms may inform strategies for optimising rice microbiota in temperate conditions, though direct UK applicability is limited given rice is not a major UK crop. The general principles regarding core microbiota and plant trait prediction could be transferable to other UK cereal crops if validated empirically.

Key measures

Bacterial community composition (16S rRNA sequencing), microbial assembly processes (deterministic vs stochastic), core microbiota identity and relative abundance, plant functional trait prediction accuracy via machine learning algorithms

Outcomes reported

The study characterised bacterial microbiota composition across seed, root endosphere and rhizosphere compartments in rice cultivars, and identified a core community of 15 generalist microbial species whose relative abundance could predict plant functional traits using machine learning.

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