4.7 Article

Strigolactones shape the rhizomicrobiome in rice (Oryza sativa)

Journal

PLANT SCIENCE
Volume 286, Issue -, Pages 118-133

Publisher

ELSEVIER IRELAND LTD
DOI: 10.1016/j.plantsci.2019.05.016

Keywords

Oryza sativa; Rhizomicrobiome; RNA-sequencing; Strigolactones; Metabolic pathways

Funding

  1. Science Foundation of Chinese Academy of Sciences [XDB15030103]
  2. National Key Research and Development Program of China [2016YFC0501202]
  3. Key Research Project of the Chinese Academy of Sciences [KFZD-SW-112]
  4. National Natural Science Foundation of China [41571255, 31370144]
  5. Key Laboratory Foundation of Mollisols Agroecology [2016ZKHT-05]
  6. Key Technology Research and Development Program of CAS [Y6H2043001]
  7. Science and Technology Development Project of Jilin Province of China [20180519002JH]

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The rhizomicrobiome helps the host plant to better adapt to environmental stresses. In contrast, plant-derived metabolic substances, including phytohormones, play an active role in structuring rhizomicrobiome. Although strigolactones (SLs), a group of phytohormones, serve as potential rhizosphere signaling molecules, their contributions in shaping the rice (Oryza sativa) rhizomicrobiome remain elusive. To address this issue, we compared the rhizomicrobiome of rice mutants defective in either SL biosynthesis or signaling and wild-type (WT) plants. To understand whether SL-regulated metabolic pathways shape the rhizomicrobiome, a correlation network analysis was conducted among the metabolic pathway-related genes and the rhizomicrobiome of rice. Compared to WT, higher bacterial richness (evidenced by the operational taxonomic unit richness) and lower fungal diversity (evidenced by the Shannon index) were observed in both SL deficient dwarf17 (d17) and signaling (d14) mutants. Additionally, remarkable differences were observed in the composition of a large number of bacterial communities than the fungal communities in the d17 and d14 mutants with respect to the WT. The abundance of certain beneficial bacterial taxa, including Nitrosomonadaceae and Rhodanobacter, were significantly decreased in both mutants relative to the WT. Correlation network analysis between SL-regulated metabolic pathway-associated genes and rhizomicrobiome proposed a role for SL-dependent metabolic pathways in shaping rhizomicrobiome composition. Taken together, our study suggests that SL biosynthesis and signaling play a key role in determining the rice rhizomicrobiome, directly or indirectly, through the mediation of distinct metabolic pathways. Based on our findings, the genetic modulation of rice SL biosynthesis and/or signaling pathways may help to recruit/increase the abundance of the desired rhizomicrobiome, which may assist in the stress resilience of rice.

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