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Proteomic Dissection of the Rice-Fusarium Fujikuroi Interaction

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Proteomic Dissection of the Rice-Fusarium Fujikuroi Interaction Ji et al. BMC Genomics (2019) 20:91 https://doi.org/10.1186/s12864-019-5435-5 RESEARCHARTICLE Open Access Proteomic dissection of the rice-Fusarium fujikuroi interaction and the correlation between the proteome and transcriptome under disease stress Zhijuan Ji, Yuxiang Zeng, Yan Liang, Qian Qian* and Changdeng Yang* Abstract Background: Bakanae disease, caused by the fungus Fusarium fujikuroi, occurs widely throughout Asia and Europe and sporadically in other rice production areas. Recent changes in climate and cropping patterns have aggravated this disease. To gain a better understanding of the molecular mechanisms of rice bakanae disease resistance, we employed a 6-plex tandem mass tag approach for relative quantitative proteomic comparison of infected and uninfected rice seedlings 7 days post-inoculation with two genotypes: the resistant genotype 93–11 and the susceptible genotype Nipponbare. Results: In total, 123 (77.2% up-regulated, 22.8% down-regulated) and 91 (94.5% up-regulated, 5.5% down-regulated) differentially expressed proteins (DEPs) accumulated in 93–11 and Nipponbare, respectively. Only 11 DEPs were both shared by the two genotypes. Clustering results showed that the protein regulation trends for the two genotypes were highly contrasting, which suggested obviously different interaction mechanisms of the host and the pathogen between 93 and 11 and Nipponbare. Further analysis showed that a noticeable aquaporin, PIP2–2, was sharply upregulated with a fold change (FC) of 109.2 in 93–11, which might be related to pathogen defense and the execution of bakanae disease resistance. Certain antifungal proteins were regulated in both 93–11 and Nipponbare with moderate FCs. These proteins might participate in protecting the cellular integrity required for basic growth of the susceptible genotype. Correlation analysis between the transcriptome and proteome revealed that Pearson correlation coefficients of R = 0.677 (P = 0.0005) and R = − 0.097 (P = 0.702) were obtained for 93–11 and Nipponbare, respectively. Our findings raised an intriguing result that a significant positive correlation only in the resistant genotype, while no correlation was found in the susceptible genotype. The differences in codon usage was hypothesized for the cause of the result. Conclusions: Quantitative proteomic analysis of the rice genotypes 93-11and Nipponbare after F. fujikuroi infection revealed that the aquaporin protein PIP2–2mightexecutebakanaediseaseresistance.Thedifferenceinthecorrelation between the transcriptome and proteome might be due to the differences in codon usage between 93- 11and Nipponbare. Overall, the protein regulation trends observed under bakanae disease stress are highly contrasting, and the molecular mechanisms of disease defense are obviously different between 93 and 11 and Nipponbare. In summary, these findings deepen our understanding of the functions of proteins induced by bakanae disease and the mechanisms of rice bakanae disease resistance. Keywords: Rice, Bakanae disease, Proteomic dissection, Transcript, Correlation * Correspondence: [email protected]; [email protected] State Key Laboratory of Rice Biology, China National Rice Research Institute, No.359 Tiyuchang Road, Hangzhou 310006, People’s Republic of China © The Author(s). 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Ji et al. BMC Genomics (2019) 20:91 Page 2 of 11 Background In addition, RNA sequencing (RNA-seq) has been Rice (Oryza sativa L.) is one of the world’s most important used to illustrate the molecular mechanism of the inter- food crops, serving as a staple for more than 50% of the action between F. fujikuroi and rice plants. Different ex- world population. In China, rice is a staple food crop that pression patterns were identified for the resistant feeds more than 60% of the population and contributes genotype 93–11 and the susceptible genotype Nippon- nearly 40% of the total calorie intake [1]. Under diverse bare through comparative transcriptome analysis [9]. ecological conditions, rice is frequently exposed to a var- The results revealed that certain WRKYs, WAK and iety of biotic and abiotic stresses [2]. Among biotic MAP3Ks were responsible for the bakanae disease resist- stresses, many diseases play an important role in deter- ance of 93-11and showed that the defense-related genes mining the yield and cost of food. Rice bakanae disease, (WRKYs and MARKs) on chromosome 1 that are modu- caused by the fungus Fusarium fujikuroi, is an important lated in 93–11 upon infection might play a crucial role disease in rice. That can be soilborne or seedborne and re- in the rice-F. fujikuroi interaction. Matić S et al. [10] sults in characteristic symptoms of excessively elongated found that PR1, germin-like proteins, glycoside hydro- seedlings with chlorotic stems and leaves. Bakanae disease lases, MAP kinases, and WRKY transcriptional factors occurs widely throughout Asia and Europe, and sporadic- were up-regulated in the resistant genotype Selenio upon ally in other areas of rice production [3, 4]. Recent infection with F. fujikuroi, whereas up-regulation of chit- changes in climate and in cropping patterns have aggra- inases and down-regulation of MAP kinases and WRKY vated the disease. Although bakanae disease can be man- transcription factors were found in the susceptible culti- aged to a certain extent using chemical fungicides [5] var Dorell. Pathways including the response to chitin, through seed treatment and soil amendment, a more effi- JA-dependent signalling and the hypersensitive response cient, sustainable and environmentally friendly solution is were found to be involved in bakanae resistance. to explore genetic resources that are resistant to the dis- In addition to QTL mapping and transcriptome ease and breed additional high-resistance genotypes. analysis of rice bakanae disease resistance, other tech- Several studies have made progress in identifying nologies and methods are needed to further dissect quantitative trait loci (QTLs) governing resistance resistance to bakanae disease. With the completion of against bakanae in rice [2, 6, 7]. Yang et al. [6] first ob- rice genome sequencing in 2002, proteomics is be- tained two QTLs, qB1 and qB10, associated with more coming an increasingly powerful tool for the investi- than 13% of expressed variance for resistance to bakanae gation of complex cellular processes and has also disease, via artificial inoculation at the seedling stage been successfully used for genetic and physiological using a japonica/indica double haploid (DH) population studies [11]. Proteomic technology is also playing a derived from Chunjiang 06 and TN1. Hur et al. [7] re- key role in developing an inventory of proteins that ported a major QTL for bakanae disease resistance, are responsive to biotic and abiotic stresses and in qBK1, which explained 65% of the total phenotypic vari- dissecting rice defense pathways [12]. In rice breed- ation in near-isogenic lines (NILs) obtained from a cross ing, proteomics is usually applied to detect between the resistant donor YR24982–9-1 and the sus- stress-responsive proteins through comparisons ceptible parent Ilpum. Fiyaz et al. [2] identified three among stressed plants. Further identification of candi- QTLs (qBK1.1, qBK1.2 and qBK1.3, which accounted for date proteins may reveal that some of these proteins 4.76, 24.74 and 6.49% of phenotypic variation, respect- have functions that are clearly consistent with the ively) using a recombinant inbred line (RIL) population stress-tolerance trait [13]. derived from the indica rice parents Pusa 1342 and Pusa A comparative proteomics study of rice genotypes that Basmati 1121. qBK1.1 is likely the same as qBK1 identi- are resistant and susceptible to bakanae disease has yet fied by Hur et al. [7], but the associated phenotypic vari- not to be reported, nor has the correlation between the ations were extremely different because different proteome and transcriptome under disease stress. In this mapping populations were used; thus, these QTLs are study, the tandem mass tag (TMT) technique was ap- far from application in marker-assisted introgression of plied to compare the differences in the proteomic pat- bakanae resistance in rice breeding. Recent research [8] tern associated with the bakanae disease response using using a GWAS approach to screen a japonica rice germ- the resistant genotype 93–11 and the susceptible geno- plasm collection revealed two new genomic regions that type Nipponbare. On the basis of our previous study of were highly associated with the observed phenotypic the disease response at different transcriptome levels be- variation for the response to bakanae infection on the tween the two genotypes [9], correlation analysis was short arm of chromosome 1 (designated qBK1_628091) conducted between proteomic data and the transcrip- and the long arm of chromosome 4 (designated tomic data. The molecular mechanism of rice resistance qBK4_31750955), representing new genomic
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