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Cross-ecosystem transcriptomics identifies distinct genetic modules for nutrient acquisition in maize

Sugimura, Y.; Kawahara, A.; Maruyama, H.; Ezawa, T.

2020-09-03 plant biology
10.1101/2020.09.02.269407 bioRxiv
Show abstract

Plants have evolved diverse strategies for the acquisition of the macro-nutrients phosphorus and nitrogen; e.g., mycorrhizal formation, root development, and secretion of chelators/hydrolases to liberate inorganic phosphate. Despite the extensive studies on the individual strategies, there is little information about how plants regulate these strategies in response to fluctuating environment. We approached this issue via profiling transcriptomes of plants grown in large environmental gradients. Roots, leaves, and root-zone soils of 251 maize plants were collected across the US Corn Belt and Japan. RNA was extracted from the roots and sequenced, and the leaves and soils were analyzed. Nineteen genetic modules were defined by weighted gene coexpression network analysis and functionally characterized according to gene ontology analysis, by which we found three modules that are directly involved in nutrient acquisition: mycorrhizal formation, phosphate-starvation response (PSR), and root development. Correlation analysis with soil and plant factors revealed that both phosphorus and nitrogen deficiencies upregulated the mycorrhizal module, whereas the PSR module was upregulated mainly by deficiency in phosphorus relative to nitrogen. Expression levels of the root development module were negatively correlated with those of the mycorrhizal module, suggesting that nutrient acquisition through the two pathways, mycorrhizas and roots, are opposite strategies that are employed under nutrient-deficient and -enriched conditions, respectively. The identification of the soil and plant factors that drive the modules has implications for sustainable agriculture; activation/optimization of the strategies is feasible via manipulating the factors. Overall, our study opens a new window for understanding plant response to complex environments.

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