Journal
PLANT PHYSIOLOGY AND BIOCHEMISTRY
Volume 143, Issue -, Pages 1-10Publisher
ELSEVIER FRANCE-EDITIONS SCIENTIFIQUES MEDICALES ELSEVIER
DOI: 10.1016/j.plaphy.2019.08.014
Keywords
Nitrogen transport; Organic nitrogen cycling; Nitrate/peptide transporter family; Nitrogen stress; Source-sink interactions
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Funding
- Plant Imaging Consortium, AR, United States - AR/MO NSF EPSCoR Track 2 award [IIA-1430427, IIA-1430428]
- USDA National Institute of Food and Agriculture, McIntire-Stennis Program, United States [1009319]
- Laboratory Directed Research and Development grant from Brookhaven National Laboratory, United States
- Brookhaven Science Associates, LLC [DE-AC02-98CH10886]
- U.S. Department of Energy, United States
- Arkansas Biosciences Institute, United States
- NIFA [1009319, 913238] Funding Source: Federal RePORTER
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Internal nitrogen (N) cycling is crucial to N use efficiency. For example, N may be remobilized from older, shaded leaves to young leaves near the apex that receive more direct sunlight, where the N can be used more effectively for photosynthesis. Yet our understanding of the mechanisms and regulation of N transport is limited. To identify relevant transporters in Arabidopsis, fifteen transporter knockout mutants were screened for defects in leaf N export using nitrogen-13 (N-13) administered as (NH3)-N-13 gas to leaves. We found that three nitrate/peptide transporter family (NPF) genes were necessary for normal leaf N export under low N but not adequate soil N availability, including AtNPF7.1, which has not been previously characterized. High-throughput phenotyping revealed altered leaf area and chlorophyll fluorescence relative to wild-type plants. High AtNPF7.1 expression in flowers and large flower stalks of Atnpf7.1 mutants in low N suggests that AtNPF7.1 influences leaf N export via sink-to-source feedback, perhaps via a role in sensing plant internal N-status. We also identified previously unreported phenotypes for the mutants of the other two NPF transporters that indicate possible roles in N sensing networks.
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