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Comparative proteomics combined with analyses of transgenic plants reveal ZmREM1.3 mediates maize resistance to southern corn rust.

ABSTRACT: Southern corn rust (SCR), which is a destructive disease caused by Puccinia polysora Underw. (P. polysora), commonly occurs in warm-temperate and tropical regions. To identify candidate proteins related to SCR resistance and characterize the molecular mechanisms underlying the maize-P. polysora interaction, a comparative proteomic analysis of susceptible and resistant maize lines was performed. Statistical analyses revealed 1489 differentially abundant proteins in the resistant line, as well as 1035 differentially abundant proteins in the susceptible line. After the P. polysora infection, the abundance of one remorin protein (ZmREM1.3) increased in the resistant genotype, but decreased in the susceptible genotype. Plant-specific remorins are important for responses to microbial infections as well as plant signalling processes. In this study, transgenic maize plants overexpressing ZmREM1.3 exhibited enhanced resistance to the biotrophic P. polysora. In contrast, homozygous ZmREM1.3 UniformMu mutant plants were significantly more susceptible to P. polysora than wild-type plants. Additionally, the ZmREM1.3-overexpressing plants accumulated more salicylic acid (SA) and jasmonic acid (JA). Moreover, the expression levels of defence-related genes were higher in ZmREM1.3-overexpressing maize plants than in non-transgenic control plants in response to the P. polysora infection. Overall, our results provide evidence that ZmREM1.3 positively regulates maize defences against P. polysora likely via SA/JA-mediated defence signalling pathways. This study represents the first large-scale proteomic analysis of the molecular mechanisms underlying the maize-P. polysora interaction. This is also the first report confirming the remorin protein family affects plant resistance to SCR.

SUBMITTER: Wang S

PROVIDER: S-EPMC6790363 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature

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Comparative proteomics combined with analyses of transgenic plants reveal ZmREM1.3 mediates maize resistance to southern corn rust.

Wang Shunxi S Chen Zan Z Tian Lei L Ding Yezhang Y Zhang Jun J Zhou Jinlong J Liu Ping P Chen Yanhui Y Wu Liuji L

Plant biotechnology journal 20190423 11

Southern corn rust (SCR), which is a destructive disease caused by Puccinia polysora Underw. (P. polysora), commonly occurs in warm-temperate and tropical regions. To identify candidate proteins related to SCR resistance and characterize the molecular mechanisms underlying the maize-P. polysora interaction, a comparative proteomic analysis of susceptible and resistant maize lines was performed. Statistical analyses revealed 1489 differentially abundant proteins in the resistant line, as well as ...[more]

PMID: 30972847

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Project description:Southern corn rust (SCR), caused by Puccinia polysora Underw, is a destructive disease that can severely reduce grain yield in maize (Zea mays L.). Owing to P. polysora being multi-racial, it is very important to explore more resistance genes and develop more efficient selection approaches in maize breeding programs. Here, four Doubled Haploid (DH) populations with 384 accessions originated from selected parents and their 903 testcross hybrids were used to perform genome-wide association (GWAS). Three GWAS processes included the additive model in the DH panel, additive and dominant models in the hybrid panel. As a result, five loci were detected on chromosomes 1, 7, 8, 8, and 10, with P-values ranging from 4.83×10-7 to 2.46×10-41. In all association analyses, a highly significant locus on chromosome 10 was detected, which was tight chained with the known SCR resistance gene RPPC and RPPK. Genomic prediction (GP), has been proven to be effective in plant breeding. In our study, several models were performed to explore predictive ability in hybrid populations for SCR resistance, including extended GBLUP with different genetic matrices, maker based prediction models, and mixed models with QTL as fixed factors. For GBLUP models, the prediction accuracies ranged from 0.56-0.60. Compared with traditional prediction only with additive effect, prediction ability was significantly improved by adding additive-by-additive effect (P-value< 0.05). For maker based models, the accuracy of BayesA and BayesB was 0.65, 8% higher than other models (i.e., RRBLUP, BRR, BL, BayesC). Finally, by adding QTL into the mixed linear prediction model, the accuracy can be further improved to 0.67, especially for the G_A model, the prediction performance can be increased by 11.67%. The prediction accuracy of the BayesB model can be further improved significantly by adding QTL information (P-value< 0.05). This study will provide important valuable information for understanding the genetic architecture and the application of GP for SCR in maize breeding.

Dataset Information

Comparative proteomics combined with analyses of transgenic plants reveal ZmREM1.3 mediates maize resistance to southern corn rust.

Publications

Comparative proteomics combined with analyses of transgenic plants reveal ZmREM1.3 mediates maize resistance to southern corn rust.

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