Comparative transcriptome analysis reveals stress-response pathways as key drivers of nitrogen use efficiency in tobacco under low-nitrogen conditions

Enhancing nitrogen use efficiency (NUE) is essential for sustainable agriculture. Stress response pathways play a significant role in regulating NUE across various growth stages and organs. Therefore, it is imperative to systematically investigate how these pathways contribute to improving NUE, particularly under low nitrogen (N) conditions. We conducted a comparative experiment using two tobacco cultivars, Hongda and K326, under low nitrogen conditions and investigated nitrogen and biomass accumulation from 25 days after transplantation (DAT) to 125 DAT. Additionally, a transcriptome analysis was performed at 50, 75, and 100 DAT in leaves, stems, and roots of both cultivars to examine their transcriptomic responses to low N conditions. Our results highlight that Hongda exhibits notably higher N and biomass accumulation than K326 under low N conditions, confirming its superior NUE. The transcriptome analysis revealed that Hongda’s stress response pathways were more robust in leaves, stems, and roots at 50, 75, and 100 DAT than in K326. Pathways such as unfolded protein binding (GO:0051082) and tubulin binding (GO:0015631) were more prominently enriched in Hongda than in K326. Furthermore, stress response pathways, including Phenylpropanoid biosynthesis (ko00940) and the MAPK signaling pathway–plant (ko04016), consistently displayed enhanced activity in Hongda compared to K326 across different stages. Moreover, analysis of gene expression profiles revealed 281 differentially expressed genes (DEGs) with consistent patterns across various organs and stages. Protein-protein interaction analysis of 281 DEGs suggests that protein processing in the endoplasmic reticulum (ER) process (ko04141) may be pivotal in determining Hongda’s superior NUE compared to K326. This includes functions related to the translocon, ribosome anchor, and protein recognition by luminal chaperones. We conclude that stress response pathways emerge as key determinants of the NUE difference between Hongda and K326, with Hongda exhibiting advantages across leaves, stems, and roots. Notably, the ER protein processing pathway (ko04141) appears to be a significant predictor of the increased NUE in Hongda.

Authors

Institutions

Publication Details

Journal
BMC Plant Biology
Published
2026-03-23
DOI
https://doi.org/10.1186/s12870-026-08558-y
Primary Topic
Plant nutrient uptake and metabolism
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Comparative transcriptome analysis reveals stress-response pathways as key drivers of nitrogen use efficiency in tobacco under low-nitrogen conditions

Fupeng Mei, Ting Yat Miu, Waqar Ahmed, Gang Chen et al.
BMC Plant Biology
Plant nutrient uptake and metabolism
article

Comparative transcriptome analysis reveals stress-response pathways as key drivers of nitrogen use efficiency in tobacco under low-nitrogen conditions

Fupeng Mei, Ting Yat Miu, Waqar Ahmed, Gang Chen, Linyuan YANG, Yingfen Yang, Shichen Li, Qu SHAN, Xiaoci Peng, Tao Jiang, Zhengxiong Zhao, Yan Gao, Tao Zhang
article en

Abstract

Enhancing nitrogen use efficiency (NUE) is essential for sustainable agriculture. Stress response pathways play a significant role in regulating NUE across various growth stages and organs. Therefore, it is imperative to systematically investigate how these pathways contribute to improving NUE, particularly under low nitrogen (N) conditions. We conducted a comparative experiment using two tobacco cultivars, Hongda and K326, under low nitrogen conditions and investigated nitrogen and biomass accumulation from 25 days after transplantation (DAT) to 125 DAT. Additionally, a transcriptome analysis was performed at 50, 75, and 100 DAT in leaves, stems, and roots of both cultivars to examine their transcriptomic responses to low N conditions. Our results highlight that Hongda exhibits notably higher N and biomass accumulation than K326 under low N conditions, confirming its superior NUE. The transcriptome analysis revealed that Hongda’s stress response pathways were more robust in leaves, stems, and roots at 50, 75, and 100 DAT than in K326. Pathways such as unfolded protein binding (GO:0051082) and tubulin binding (GO:0015631) were more prominently enriched in Hongda than in K326. Furthermore, stress response pathways, including Phenylpropanoid biosynthesis (ko00940) and the MAPK signaling pathway–plant (ko04016), consistently displayed enhanced activity in Hongda compared to K326 across different stages. Moreover, analysis of gene expression profiles revealed 281 differentially expressed genes (DEGs) with consistent patterns across various organs and stages. Protein-protein interaction analysis of 281 DEGs suggests that protein processing in the endoplasmic reticulum (ER) process (ko04141) may be pivotal in determining Hongda’s superior NUE compared to K326. This includes functions related to the translocon, ribosome anchor, and protein recognition by luminal chaperones. We conclude that stress response pathways emerge as key determinants of the NUE difference between Hongda and K326, with Hongda exhibiting advantages across leaves, stems, and roots. Notably, the ER protein processing pathway (ko04141) appears to be a significant predictor of the increased NUE in Hongda.

BMC Plant Biology
Yunnan Agricultural University (CN), China Tobacco (CN), Qujing Normal University (CN), Chuxiong Normal University (CN), Yunnan Environmental Protection Bureau (CN)
Zero hunger
Openalex Percentile: Top 12%
Plant nutrient uptake and metabolism
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.