Journal of Zhejiang Agricultural Sciences ›› 2024, Vol. 65 ›› Issue (2): 395-400.DOI: 10.16178/j.issn.0528-9017.20221179

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PPI network analysis of differentially expressed mRNA in the roots of tobacco varieties resistant to Meloidogyne incongnita (Kofold&White) Chitwood

Xiaoxiang CHEN1(), Wenjun ZHANG2, Zhengguang ZHAI2, Zhiqiang XU1, Huabing LIU1, Yongjian ZHONG1, Zhimin JIANG1,*()   

  1. 1. Technology Development Branch, China Tobacco Zhejiang Industrial Co., Ltd., Hangzhou 310008, Zhejiang
    2. Changsha Branch of Hunan Provincial Tobacco Company, Changsha 410000, Hunan
  • Received:2022-11-18 Online:2024-02-11 Published:2024-02-28
  • Contact: Zhimin JIANG

Abstract:

Based on the differentially expressed genes among varieties, tobacco disease resistant variety K326 and susceptible variety Changbohuang were selected as experimental materials, and key genes related to infection resistance were screened using bioinformatics analysis methods, this article used Protein Protein Interaction (PPI) and Gene Ontology (GO) functional classification analysis (including Biological Process analysis and KEGG pathway analysis) to annotate the biological functions of differentially expressed genes, identify important genes and genes with consistent pathways in the PPI network, analyze these genes to clarify the resistance mechanism of tobacco varieties to Meloidogyne incongnita (Kofold&White) Chitwood, and provide theoretical basis for studying the molecular mechanism of tobacco resistance to Meloidogyne incongnita (Kofold&White) Chitwood. The results showed that differentially expressed genes were significantly enriched in 9 pathways related to anti-infection, including cell metabolism, intracellular transport, and RNA mediated gene silencing. Seven key factor genes that simultaneously formed the PPI network were identified, including Fab1b, Fab1c, Fab1d, Glu1, Dcl1, Dcl2 and Dcl4.

Key words: tobacco, Meloidogyne incongnita (Kofold&White) Chitwood, protein protein interaction, gene ontology (GO) functional classification analysis, key genes

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