Alternating Inverse Modulation of Xylem K+/NO3 - Loading by HY5 and PIF Facilitates Diurnal Regulation of Root-to-shoot Water and Nutrient Transport.
NEW PHYTOLOGIST(2025)
Abstract
Diurnal light-dark cycles regulate nutrient uptake and transport; however, the underlying molecular mechanisms remain largely unknown. Transcription factor MYB59 and ion transporter NPF7.3 participate in root-to-shoot K+/NO3 - translocation in Arabidopsis. In this study, transcriptional analyses and western blotting experiments revealed the diurnal expression of the MYB59-NPF7.3 module. ChIP-qPCR and EMSA showed that transcription factors HY5 and PIF directly bind to the MYB59 promoter. Phenotype analyses and ion content measurement indicated that HY5 and PIF antagonistically control root-to-shoot K+/NO3 - translocation through the MYB59-NPF7.3 module. We found HY5 proteins accumulate in roots and repress MYB59 transcription during daytime, while PIF proteins promote MYB59 transcription in the dark. The expression levels of the NPF7.3 transcript and protein are gradually decreased during daytime, but increased at night. The enhancement of K+/NO3 - loading into the xylem mediated by NPF7.3 could increase root pressure at night, which maintained the root-to-shoot water/nutrient translocation. This study reveals a synergistic mechanism between light signaling and nutrient transport in plants, and defines a diurnal molecular switch of driving forces for root-to-shoot water/nutrient translocation.
MoreTranslated text
Key words
light signal,nitrate,nutrient transport,potassium,transcriptional regulation
求助PDF
上传PDF
View via Publisher
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
- Pretraining has recently greatly promoted the development of natural language processing (NLP)
- We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
- We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
- The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
- Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example

Generate MRT to find the research sequence of this paper
Related Papers
2008
被引用303 | 浏览
2007
被引用980 | 浏览
2009
被引用24 | 浏览
2004
被引用338 | 浏览
2006
被引用57 | 浏览
2008
被引用513 | 浏览
2008
被引用524 | 浏览
2010
被引用288 | 浏览
1997
被引用444 | 浏览
1980
被引用42 | 浏览
2000
被引用44 | 浏览
2017
被引用195 | 浏览
2017
被引用67 | 浏览
2017
被引用138 | 浏览
2019
被引用57 | 浏览
2019
被引用92 | 浏览
2016
被引用170 | 浏览
2004
被引用192 | 浏览
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper