New PhytologistPlant BiologyPeer-reviewed journal article
Plant genetic and root-associated microbial diversity modulate Lactuca sativa responsiveness to a soil inoculum under phosphate deficiency
Arianna CapparottoiD, Alessandro Ciampanelli, Paolo Salvucci, Johannes HerpelliD, Guillaume ChesneauiD, Simone SelloiD, Cristina Sudiro, Pieter ClauwiD, Adriano AltissimoiD, Stéphane HacquardiD, Francesco Vuolo, Marco GiovannettiiD
Abstract
O_LIMicrobial-based approaches have been proposed as a solution to decrease the use of chemical fertilizers in agriculture. Among these, the most promising candidates are arbuscular mycorrhizal fungi (AMF), with their ability to extend the root surface and absorb phosphate, and phosphate solubilizing bacteria (PSB), but their effectiveness has been shown to depend on plant genetic diversity. C_LIO_LIWith the aim of identifying genetic markers explaining plant differential responses to soil-beneficial microbes, we monitored a panel of 128 fully sequenced varieties of Lactuca sativa under controlled P starvation conditions, treated with AMF and PSB. C_LIO_LIResults showed a strong effect of the lettuce genetic variation on the plant physiological and morphological response to the inoculum. Through genome-wide association studies, we identified specific genetic regions associated with variations in leaf phosphate and shoot biomass in response to the treatment. C_LIO_LIBeyond genetic factors, we detected changes in fungal {beta}-diversity and increases in bacterial -diversity associated with phenotypic variation, and we identified 44 ASVs linked to variation in agriculturally important traits. Among these, we experimentally validated the role of six bacterial strains through both in vitro and pot experiments, in affecting the leaf phosphate concentration and plant shoot biomass. C_LIO_LIIn conclusion, we highlighted key genetic and physiological mechanisms that could play a crucial role in enhancing microbial treatments for optimizing plant phosphate management. C_LI
- organism: plant (other)
- assay: bulk RNA-seq
- research focus: gene regulatory network inference
- approach: statistical model
- Citations
- 1
- FWCI
- 3.68
- Field percentile
- top 14%
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