Evidence map›Paper›PMID 35879667›Full record

ArticleBMC plant biology2022

Transcriptome-based gene regulatory network analyses of differential cold tolerance of two tobacco cultivars.

Zhenyu Luo, Zhicheng Zhou, Yangyang Li, Shentong Tao, Zheng-Rong Hu, Jia-Shuo Yang, Xuejiao Cheng, Risheng Hu, Wenli Zhang

Open access · goldAbstract read
In one paragraph

Article in BMC plant biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
5.3field-weighted citation impact, top 5% of its field
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

14 citing papers in PubMed, 28 citations in OpenAlex.

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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

9 authors at 2 institutions in 1 country.

Zhenyu Luo *State Key Laboratory for Crop Genetics and Germplasm Enhancement, CIC-MCP, Nanjing Agricultural University, No.1 Weigang, Nanjing, 210095, Jiangsu, China.
Zhicheng Zhou *Hunan Tobacco Research Institute, Changsha, 410128, Hunan, China.
Yangyang Li *Hunan Tobacco Research Institute, Changsha, 410128, Hunan, China.
Shentong TaoState Key Laboratory for Crop Genetics and Germplasm Enhancement, CIC-MCP, Nanjing Agricultural University, No.1 Weigang, Nanjing, 210095, Jiangsu, China.
Zheng-Rong HuHunan Tobacco Research Institute, Changsha, 410128, Hunan, China.
Jia-Shuo YangHunan Tobacco Research Institute, Changsha, 410128, Hunan, China.
Xuejiao ChengState Key Laboratory for Crop Genetics and Germplasm Enhancement, CIC-MCP, Nanjing Agricultural University, No.1 Weigang, Nanjing, 210095, Jiangsu, China. xuejiaocheng@njau.edu.cn.
Risheng HuHunan Tobacco Research Institute, Changsha, 410128, Hunan, China. 495298768@qq.com.
Wenli ZhangState Key Laboratory for Crop Genetics and Germplasm Enhancement, CIC-MCP, Nanjing Agricultural University, No.1 Weigang, Nanjing, 210095, Jiangsu, China. wzhang25@njau.edu.cn.
Tobacco Research Institute · CNNanjing Agricultural University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCold is one of the main abiotic stresses that severely affect plant growth and development, and crop productivity as well. Transcriptional changes during cold stress have already been intensively studied in various plant species. However, the gene networks involved in the regulation of differential cold tolerance between tobacco varieties with contrasting cold resistance are quite limited.

resultsHere, we conducted multiple time-point transcriptomic analyses using Tai tobacco (TT, cold susceptibility) and Yan tobacco (YT, cold resistance) with contrasting cold responses. We identified similar DEGs in both cultivars after comparing with the corresponding control (without cold treatment), which were mainly involved in response to abiotic stimuli, metabolic processes, kinase activities. Through comparison of the two cultivars at each time point, in contrast to TT, YT had higher expression levels of the genes responsible for environmental stresses. By applying Weighted Gene Co-Expression Network Analysis (WGCNA), we identified two main modules: the pink module was similar while the brown module was distinct between the two cultivars. Moreover, we obtained 100 hub genes, including 11 important transcription factors (TFs) potentially involved in cold stress, 3 key TFs in the brown module and 8 key TFs in the pink module. More importantly, according to the genetic regulatory networks (GRNs) between TFs and other genes or TFs by using GENIE3, we identified 3 TFs (ABI3/VP1, ARR-B and WRKY) mainly functioning in differential cold responses between two cultivars, and 3 key TFs (GRAS, AP2-EREBP and C2H2) primarily involved in cold responses.

conclusionCollectively, our study provides valuable resources for transcriptome- based gene network studies of cold responses in tobacco. It helps to reveal how key cold responsive TFs or other genes are regulated through network. It also helps to identify the potential key cold responsive genes for the genetic manipulation of tobacco cultivars with enhanced cold tolerance in the future.

Indexed as

Gene Regulatory NetworksNicotianaCold-Shock ResponseGene Expression ProfilingGene Expression Regulation, PlantStress, PhysiologicalTranscriptomeCo-expression networkCold treatmentDifferential gene expressionTobaccoTranscriptome

Identifiers

PMID35879667
PMCPMC9316383
OpenAlexW4287831689

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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 OpenQuestion graph.