GmGSTU13 Is Related to the Development of Mosaic Symptoms in Soybean Plants Infected with Soybean Mosaic Virus

文献类型： 外文期刊

第一作者： Zhang, Kai

作者： Zhang, Kai;Shen, Yingchao;Wang, Tao;Xue, Song;Luan, Hexiang;Wang, Liqun;Li, Kai;Zhi, Haijian;Zhang, Kai;Wang, Yu;Wang, Tao;Guo, Dongquan

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关键词： GmGSTU13; proteomics; soybean; soybean mosaic virus; symptom; virus-induced gene silencing

期刊名称：PHYTOPATHOLOGY （ 影响因子：4.01； 五年影响因子：4.457 ）

ISSN： 0031-949X

年卷期： 2022 年 112 卷 2 期

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收录情况： SCI

摘要： The leaves of soybean cultivar ZheA8901 show various symptoms (necrosis, mosaic, and symptomless) when infected with different strains of soybean mosaic virus (SMV). Based on a proteomic analysis performed with tandem mass tags (TMT), 736 proteins were differentially expressed from soybean samples that showed asymptomatic, mosaic, and necrosis symptoms induced by SMV strains SC3, SC7, and SC15, respectively. Among these, GmGSTU13 and ascorbate peroxidase (APX) were only upregulated in mosaic and symptomless leaves, respectively. The protein level of GmGSTU13 determined by western blot analysis was consistent with TMT analysis, and quantitative reverse transcriptase PCR analysis showed that GmGSTU13 mRNA levels in mosaic plants were 5.26- and 3.75-fold higher than those in necrotic and symptomless plants, respectively. Additionally, the expression of the viral coat protein (CP) gene was increased, and serious mosaic symptoms were observed in GmGSTU13-overexpressing plants inoculated with all three SMV strains. These results showed that GmGSTU13 is associated with the development of SMV-induced mosaic symptoms in soybean and that APX is upregulated in symptomless leaves at both the transcriptional and protein levels. In APX gene-silenced soybean plants, the relative expression of the viral CP gene was 1.50, 7.59, and 1.30 times higher than in positive control plants inoculated with the three SMV strains, suggesting that the upregulation of APX may be associated with lack of symptoms in soybean infected with SMV. This work provides a useful dataset for identifying key proteins responsible for symptom development in soybean infected with different SMV strains.

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