Gene-coexpression network analysis identifies specific modules and hub genes related to cold stress in rice

被引:26
|
作者
Zeng, Zhichi [1 ,2 ]
Zhang, Sichen [1 ,2 ]
Li, Wenyan [1 ,2 ]
Chen, Baoshan [1 ,3 ]
Li, Wenlan [1 ,2 ]
机构
[1] Guangxi Univ, State Key Lab Conservat & Utilizat Subtrop Agrobi, Nanning, Peoples R China
[2] Guangxi Univ, Coll Life Sci & Technol, Nanning, Peoples R China
[3] Guangxi Univ, Coll Agr, Nanning, Peoples R China
基金
中国国家自然科学基金;
关键词
Cold stress; Transcriptome; WGCNA; Hub genes; LOW-TEMPERATURE; TRANSGENIC TOBACCO; DRAFT SEQUENCE; ABSCISIC-ACID; TOLERANCE; EXPRESSION; RESPONSES; PROTEIN; REVEALS; DROUGHT;
D O I
10.1186/s12864-022-08438-3
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
Background When plants are subjected to cold stress, they undergo a series of molecular and physiological changes to protect themselves from injury. Indica cultivars can usually withstand only mild cold stress in a relatively short period. Hormone-mediated defence response plays an important role in cold stress. Weighted gene co-expression network analysis (WGCNA) is a very useful tool for studying the correlation between genes, identifying modules with high phenotype correlation, and identifying Hub genes in different modules. Many studies have elucidated the molecular mechanisms of cold tolerance in different plants, but little information about the recovery process after cold stress is available. Results To understand the molecular mechanism of cold tolerance in rice, we performed comprehensive transcriptome analyses during cold treatment and recovery stage in two cultivars of near-isogenic lines (9311 and DC907). Twelve transcriptomes in two rice cultivars were determined. A total of 2509 new genes were predicted by fragment splicing and assembly, and 7506 differentially expressed genes were identified by pairwise comparison. A total of 26 modules were obtained by expression-network analysis, 12 of which were highly correlated with cold stress or recovery treatment. We further identified candidate Hub genes associated with specific modules and analysed their regulatory relationships based on coexpression data. Results showed that various plant-hormone regulatory genes acted together to protect plants from physiological damage under short-term low-temperature stress. We speculated that this may be common in rice. Under long-term cold stress, rice improved the tolerance to low-temperature stress by promoting autophagy, sugar synthesis, and metabolism. Conclusion Through WGCNA analysis at the transcriptome level, we provided a potential regulatory mechanism for the cold stress and recovery of rice cultivars and identified candidate central genes. Our findings provided an important reference for the future cultivation of rice strains with good tolerance.
引用
收藏
页数:18
相关论文
共 50 条
  • [1] Gene-coexpression network analysis identifies specific modules and hub genes related to cold stress in rice
    Zhichi Zeng
    Sichen Zhang
    Wenyan Li
    Baoshan Chen
    Wenlan Li
    BMC Genomics, 23
  • [2] Weighted Gene Coexpression Network Analysis Identifies Specific Modules and Hub Genes Related to Major Depression
    Zhang, Guangyin
    Xu, Shixin
    Yuan, Zhuo
    Shen, Li
    NEUROPSYCHIATRIC DISEASE AND TREATMENT, 2020, 16 : 703 - 713
  • [3] Weighted gene coexpression network analysis identifies specific transcriptional modules and hub genes related to intramuscular fat traits in chicken breast muscle
    Li, Guoxi
    Zhao, Yinli
    Li, Yuanfang
    Chen, Yi
    Jin, Wenjiao
    Sun, Guirong
    Han, Ruili
    Tian, Yadong
    Li, Hong
    Kang, Xiangtao
    JOURNAL OF CELLULAR BIOCHEMISTRY, 2019, 120 (08) : 13625 - 13639
  • [4] Weighted Gene Co-Expression Network Analysis Identifies Specific Modules and Hub Genes Related to Hyperlipidemia
    Miao, Liu
    Yin, Rui-Xing
    Pan, Shang-Ling
    Yang, Shuo
    Yang, De-Zhai
    Lin, Wei-Xiong
    CELLULAR PHYSIOLOGY AND BIOCHEMISTRY, 2018, 48 (03) : 1151 - 1163
  • [5] Weighted gene coexpression network analysis identifies hub genes related to KRAS mutant lung adenocarcinoma
    Dai, Dongjun
    Shi, Rongkai
    Han, Shuting
    Jin, Hongchuan
    Wang, Xian
    MEDICINE, 2020, 99 (32)
  • [6] A gene-coexpression network for global discovery of conserved genetic modules
    Stuart, JM
    Segal, E
    Koller, D
    Kim, SK
    SCIENCE, 2003, 302 (5643) : 249 - 255
  • [7] Identification of Key Modules and Hub Genes of Keloids with Weighted Gene Coexpression Network Analysis
    Liu, Wenhui
    Huang, Xiaolu
    Liang, Xiao
    Zhou, Yiwen
    Li, Haizhou
    Yu, Qingxiong
    Li, Qingfeng
    PLASTIC AND RECONSTRUCTIVE SURGERY, 2017, 139 (02) : 376 - 390
  • [8] Weighted Gene Co-expression Network Analysis Identifies Specific Modules and Hub Genes Related to Subacute Ruminal Acidosis
    Wang, Qiuju
    Gao, Bingnan
    Yue, Xueqing
    Cui, Yizhe
    Loor, Juan J.
    Dai, Xiaoxia
    Wei, Xu
    Xu, Chuang
    FRONTIERS IN VETERINARY SCIENCE, 2022, 9
  • [9] Weighted gene co-expression network analysis identifies specific modules and hub genes related to coronary artery disease
    Jing Liu
    Ling Jing
    Xilin Tu
    BMC Cardiovascular Disorders, 16
  • [10] Weighted gene co-expression network analysis identifies specific modules and hub genes related to coronary artery disease
    Zheng, Peng-Fei
    Chen, Lu-Zhu
    Guan, Yao-Zong
    Liu, Peng
    SCIENTIFIC REPORTS, 2021, 11 (01)