基于共表达网络和蛋白互作分析挖掘小麦赤霉病抗性相关核心蛋白

doi:10.19586/j.2095-2341.2021.0117

生物技术进展 ›› 2021, Vol. 11 ›› Issue (5): 628-633.DOI: 10.19586/j.2095-2341.2021.0117

• 寄主-病原菌互作及其抗性机制 • 上一篇下一篇

基于共表达网络和蛋白互作分析挖掘小麦赤霉病抗性相关核心蛋白

刘家俊(), 陈琛, 温明星, 郭瑞, 姚维成, 李东升()

江苏丘陵地区镇江农业科学研究所，江苏句容 212400

收稿日期:2021-06-15 接受日期:2021-07-27 出版日期:2021-09-25 发布日期:2021-10-08
通讯作者: 李东升
作者简介:刘家俊 E-mail：divergent9304@hotmail.com；
基金资助:
镇江市农业科学院青年基金项目(QNJJ2020001);句容市科技项目(NY202009);扬州大学开放课题项目(PL202008)

Combining WGCNA and PPI Network for Identifying Hub Proteins Associated with Fusarium Head Blight Responses in Wheat

Jiajun LIU(), Chen CHEN, Mingxing WEN, Rui GUO, Weicheng YAO, Dongsheng LI()

Zhenjiang Institute of Agricultural Science of Hilly Regions，Jiangsu Jurong 212400，China

Received:2021-06-15 Accepted:2021-07-27 Online:2021-09-25 Published:2021-10-08
Contact: Dongsheng LI

摘要/Abstract

摘要：

高通量蛋白组学技术能够鉴定小麦特定组织的蛋白表达水平，对小麦穗轴混池蛋白组学分析得到的632个差异表达蛋白数据进行共表达网络分析，同时筛选显著表达模块进行蛋白质互作分析，以期挖掘出与小麦赤霉病抗性相关的蛋白。WGCNA分析结果共构建了12个表达模块，其中模块6与赤霉病抗病呈极显著相关，模块8显著相关。蛋白互作网络分析筛选到7个候选蛋白，分别为参与毒素降解的GST （glutathione S?transferase）和AdoMet?MTase（S?adenosylmethionine?dependent methyltransferase），参与光合作用的IM30（membrane?associated 30 Da, chloroplastic）、PnsL2（photosynthetic NDH subcomplex L 2）和PPL1（PsbP?like protein 1）,以及抗逆相关的UCHL（ubiquitin carboxyl?terminal hydrolase）和MetAP2（methionine aminopeptidase 2）。这些蛋白可能在赤霉病抗、感病响应中具有重要作用，值得进一步研究。

关键词: 小麦, 赤霉病, 蛋白组学, WGCNA, 蛋白互作

Abstract:

High?throughput proteomics enables the identification and quantitation of protein expression profiles of a specific tissue in wheat. Based on a previous proteomics study on bulked rachides post inoculation with Fusarium graminearum， the current study employed 632 differentially accumulated proteins for co?expression network construction， and the highly correlated modules was proceeded with protein?protein interaction （PPI） analysis， aiming at exploring potential proteins associated with Fusarium head blight （FHB） resistance. Weighted correlation network analysis （WGCNA） constructed a total of 12 modules， module 6 and module 8 were significantly correlated with FHB. The PPI identified seven candidates， and these proteins were connected to detoxification， such as glutathione S?transferase （GST） and S?adenosylmethionine?dependent methyltransferase （AdoMet?MTase）， photosynthesis， such as membrane?associated 30 kD， chloroplastic （IM30）， photosynthetic NDH subcomplex L 2 （PnsL2） and PsbP?like protein 1 （PPL1）， defense response， such as ubiquitin carboxyl?terminal hydrolase （UCHL） and methionine aminopeptidase 2 （MetAP2）. These proteins may play crucial roles in host resistance to FHB， and are worth further explorations.

Key words: wheat, Fusarium head blight, proteomics, WGCNA, protein?protein interaction

中图分类号:

S435.121.4+5

刘家俊, 陈琛, 温明星, 郭瑞, 姚维成, 李东升. 基于共表达网络和蛋白互作分析挖掘小麦赤霉病抗性相关核心蛋白[J]. 生物技术进展, 2021, 11(5): 628-633.

Jiajun LIU, Chen CHEN, Mingxing WEN, Rui GUO, Weicheng YAO, Dongsheng LI. Combining WGCNA and PPI Network for Identifying Hub Proteins Associated with Fusarium Head Blight Responses in Wheat[J]. Current Biotechnology, 2021, 11(5): 628-633.

图/表 3

图1 WGCNA共表达模块分析注：A：样品聚类；B：不同软阈值对应的R2值以及平均连通性；C：蛋白聚类及模块划分；D：模块与性状相关性热图；E：模块蛋白多维尺度变换图；F：蛋白与模块显著性散图。

Fig.1 The WGCNA analysis results

图2 蛋白与蛋白互作网络图

Fig.2 Protein?protein interaction network

图3 候选蛋白表达热图

Fig.3 Candidates protein expression heatmap

参考文献 22

1	BAI G, SHANER G. Management and resistance in wheat and barley toFusarium head blight [J]. Annu. Rev. Phytopathol., 2004, 42(1): 135-161.
2	刘永杰. 小麦赤霉病的危害及防治措施[J]. 现代农村科技, 2012(15): 31.
3	程顺和, 张勇, 别同德, 等. 中国小麦赤霉病的危害及抗性遗传改良[J]. 江苏农业学报, 2012, 28(05): 938-942.
4	YANG M, WANG X, DONG J, et al.. Proteomics reveals the changes that contribute to Fusarium head blight resistance in wheat[J]. Phytopathology, 2021, 111(2): 386-397.
5	ELDAKAK M, DAS A, ZHUANG Y, et al.. A quantitative proteomics view on the function of Qfhb1, a major QTL for Fusarium head blight resistance in wheat[J/OL]. Pathogens, 2018, 7(3): 58[2021-07-27]. .
6	FABRE F, URBACH S, ROCHE S, et al.. Proteomics-based data integration of wheat cultivars facing Fusariumgraminearum strains revealed a core-responsive pattern controlling Fusarium head blight[J]. Front. Plant Sci., 2021, 12: 644810.
7	XU M, OUYANG T, LV K, et al.. Integrated WGCNA and PPI Network to screen hub genes signatures for infantile hemangioma[J/OL]. Front. Genet., 2021, 11: 614195[2021-07-27]. .
8	PEI G, CHEN L, ZHANG W. WGCNA application to proteomic and metabolomic data analysis[J]. Methods Enzymol., 2017, 585: 135-158.
9	LIU J, LI L, FOROUD N A, et al.. Proteomics of bulked rachides combined with documented QTL uncovers genotype nonspecific players of the Fusarium head blight responses in wheat[J]. Phytopathology, 2019, 109(1): 111-119.
10	LANGFELDER P, HORVATH S. WGCNA: an R package for weighted gene co-expression network analysis[J/OL]. BMC Bioinform., 2008, 9(1): 559[2021-07-27]. .
11	SHANNON, P. Cytoscape: A software environment for integrated models of biomolecular interaction networks[J]. Genome Res., 2003, 13(11): 2498-2504.
12	CHIN C H, CHEN S H, WU H H, et al.. cytoHubba: identifying hub objects and sub-networks from complex interactome[J/OL]. BMC Syst. Biol., 2014, 8 (4): S11[2021-07-27]. .
13	BADER G D, HOGUE C W. An automated method for finding molecular complexes in large protein interaction networks[J/OL]. BMC Bioinform., 2003, 4: 2[2021-07-27]. .
14	JUNGLAS B, SCHNEIDER D. What is Vipp1 good for?[J]. Mol. Microbiol, 2018, 108(1): 1-5.
15	MCDONALD C, JOVANOVIC G, WALLACE B A, et al.. Structure and function of PspA and Vipp1 N-terminal peptides: Insights into the membrane stress sensing and mitigation[J]. Biochim. Biophys. Acta Biomembr., 2017, 1859(1): 28-39.
16	THUROTTE A, SCHNEIDER D. The fusion activity of IM30 rings involves controlled unmasking of the fusogenic core[J/OL]. Front. Plant Sci., 2019, 10: 108[2021-07-27]. .
17	ROOSE J L, WEGENER K M, PAKRASI H B. The extrinsic proteins of photosystem II[J]. Photosynth. Res., 2007, 92(3): 369-387.
18	DING L, XU H, YI H, et al.. Resistance to hemi-biotrophic F. graminearum infection is associated with coordinated and ordered expression of diverse defense signaling pathways[J/OL]. PLoS ONE, 2011, 6(4): e19008[2021-07-27]. .
19	WANG H, SUN S, GE W, et al.. Horizontal gene transfer of Fhb7 from fungus underlies Fusarium head blight resistance in wheat[J/OL]. Science, 2020, 368(6493): eaba5435[2021-07-27]. .
20	SCHUBERT H L, BLUMENTHAL R M, CHENG X. Many paths to methyltransfer: a chronicle of convergence[J]. Trends Biochem. Sci., 2003, 28(6): 329-335.
21	SCHUBERT H L, BLUMENTHAL R M, CHENG X. Protein methyltransferases: their distribution among the five structural classes of AdoMet-dependent methyltransferases[J]. Enzymes, 2006, 24: 3-28.
22	WANG W L, CHAI S C, YE Q Z. Synthesis and structure-function analysis of Fe(II)-form-selective antibacterial inhibitors of Escherichia coli methionine aminopeptidase[J]. Bioorg. Med. Chem. Lett., 2009, 19(4): 1080-1083.

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基于共表达网络和蛋白互作分析挖掘小麦赤霉病抗性相关核心蛋白

Combining WGCNA and PPI Network for Identifying Hub Proteins Associated with Fusarium Head Blight Responses in Wheat

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