Journal
NEW PHYTOLOGIST
Volume 227, Issue 5, Pages 1434-1452Publisher
WILEY
DOI: 10.1111/nph.16627
Keywords
coexpression; gene regulatory network; genome editing; machine learning; nitrogen; rice; systems biology; transcription factor
Categories
Funding
- CREST, JST [JPMJCR15O5, JPMJCR15O2]
- JSPS KAKENHI [18H03940, 18J01554]
- Grants-in-Aid for Scientific Research [18J01554, 18H03940] Funding Source: KAKEN
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Increase in the nitrogen (N)-use efficiency and optimization of N response in crop species are urgently needed. Although transcription factor-based genetic engineering is a promising approach for achieving these goals, transcription factors that play key roles in the response to N deficiency have not been studied extensively. Here, we performed RNA-seq analysis of root samples of 20 Asian rice (Oryza sativa) accessions with differential nutrient uptake. Data obtained from plants exposed to N-replete and N-deficient conditions were subjected to coexpression analysis and machine learning-based pathway inference to dissect the gene regulatory network required for the response to N deficiency. Four transcription factors, including members of the G2-like and bZIP families, were predicted to function as key regulators of gene transcription within the network in response to N deficiency. Cotransfection assays validated inferred novel regulatory pathways, and further analyses using genome-edited knockout lines suggested that these transcription factors are important for N-deficiency responses in planta. Many of the N deficiency-responsive genes, including those encoding key regulators within the network, were coordinately regulated by transcription factors belonging to different families. Transcription factors identified in this study could be valuable for the modification of N response and metabolism.
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