Evidence map›Paper›PMID 40764913›Full record

ArticleBMC plant biology2025

Single-cell transcriptome sequencing reveals the sphingolipid metabolism pathway plays an important role in leaf senescence in tobacco.

Quan Sun, Bing Hou, Xinghui Liu, Langlang Zhang, Pingan Chang, Huimin Pang, Xiaohong He, Zexiang Huang, Jili Zhang, Guoxia Liu and 2 more

Abstract read
In one paragraph

Article in BMC plant biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Quan SunChongqing Key Laboratory of Big Data for Bio Intelligence, School of Life Health Information Science and Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China. sunquan@cqupt.edu.cn.
Bing HouChongqing Key Laboratory of Big Data for Bio Intelligence, School of Life Health Information Science and Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China.
Xinghui LiuChongqing Key Laboratory of Big Data for Bio Intelligence, School of Life Health Information Science and Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China.
Langlang ZhangChongqing Key Laboratory of Big Data for Bio Intelligence, School of Life Health Information Science and Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China.
Pingan ChangChongqing Key Laboratory of Big Data for Bio Intelligence, School of Life Health Information Science and Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China.
Huimin PangChongqing Key Laboratory of Big Data for Bio Intelligence, School of Life Health Information Science and Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China.
Xiaohong HeChongqing Key Laboratory of Big Data for Bio Intelligence, School of Life Health Information Science and Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China.
Zexiang HuangShandong branch of China National Tobacco Corporation, Jinan, China.
Jili ZhangChina Tobacco Guangxi Industry Co., Ltd., Nanning, China.
Guoxia LiuAnhui Wannan Tobacco Co., Ltd., Xuancheng, China.
Daping GongTobacco research institute, Chinese Academy of Agricultural Sciences, Qingdao, China.
Mingli ChenTobacco research institute, Chinese Academy of Agricultural Sciences, Qingdao, China. chenmingli@caas.cn.

Funding

China Tobacco Guangxi Industrial Co., LTD. "Investigation and implementation of production technology for the high-aroma concentrated yellowing leaf of the new K326 strain" 2023450000340047The Key Science and Technology Project of China National Tobacco Corporation 110202201007(JY-07)
6 · The paper itself

Abstract

Tobacco was an important cash crop and model plant, and the senescence (yellowing) of its leaves were essential markers of harvesting and secondary metabolite formation. However, the cellular senescence process and its regulatory mechanisms in tobacco leaves remain unknown. Therefore, we constructed single-cell transcriptome profiles using tobacco leaf tissues at the maturation and senescence stages to clarify the molecular mechanism of the process. We obtained 17,100 high-quality cells and sorted them into 15 clusters. Based on the marker genes of the leaf cells, we sorted the 15 clusters into 10 cell types, including palisade mesophyll, spongy mesophyll, epidermis, xylem, phloem, hydathode, companion, bundle sheath, guard, and trichome cells. Comparison of gene expression patterns in mature and senescent leaf cells revealed that senescence-related cells were mainly associated with palisade mesophyll, spongy mesophyll, epidermis, xylem, and phloem cells. Enrichment analysis indicated that the differentially expressed genes in various cells were mainly related to chlorophyll synthesis and photosynthesis. Interestingly, most genes tended to show downregulated expression during senescence, whereas genes in the sphingolipid metabolism pathway were significantly upregulated in the senescent samples. We hypothesized that genes such as SPT may regulate the senescence process of tobacco leaves through the sphingolipid metabolism pathway. To our knowledge, this is the first study to analyze single-cell transcriptomes in aging tobacco leaves. Our findings offer insights for future molecular and cellular studies on tobacco leaf senescence.

Indexed as

NicotianaPlant LeavesPlant SenescenceSphingolipidsTranscriptomeGene Expression ProfilingGene Expression Regulation, PlantSingle-Cell AnalysisSphingolipidsDevelopmentSenescenceSingle-cell RNA sequencingSphingolipid metabolismTobacco

Identifiers

PMID40764913
PMCPMC12326597

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.