Genome-wide analysis of family-1 UDP glycosyltransferases (UGT) and identification of  UGT  genes for FHB resistance in wheat ( Triticum aestivum  L.)

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Abstract

Background

Fusarium head blight (FHB), a devastating disease in wheat worldwide, results in yield loses and mycotoxin, such as deoxynivalenol (DON), accumulation in infected grains. DON also facilitates the pathogen colonization and spread of FHB symptoms during disease development. UDP-glycosyltransferase enzymes (UGTs) are known to contribute to detoxification and enhance FHB resistance by glycosylating DON into DON-3-glucoside (D3G) in wheat. However, a comprehensive investigation of wheat ( Triticum aestivum) UGT genes is still lacking.

Results

In this study, we carried out a genome-wide analysis of family-1 UDP glycosyltransferases in wheat based on the PSPG conserved box that resulted in the identification of 179 putative UGT genes. The identified genes were clustered into 16 major phylogenetic groups with a lack of phylogenetic group K. The UGT genes were invariably distributed among all the chromosomes of the 3 genomes. At least 10 intron insertion events were found in the UGT sequences, where intron 4 was observed as the most conserved intron. The expression analysis of the wheat UGT genes using both online microarray data and quantitative real-time PCR verification suggested the distinct role of UGT genes in different tissues and developmental stages. The expression of many UGT genes was up-regulated after Fusarium graminearum inoculation, and six of the genes were further verified by RT-qPCR.

Conclusion

We identified 179 UGT genes from wheat using the available sequenced wheat genome. This study provides useful insight into the phylogenetic structure, distribution, and expression patterns of family-1 UDP glycosyltransferases in wheat. The results also offer a foundation for future work aimed at elucidating the molecular mechanisms underlying the resistance to FHB and DON accumulation.

Electronic supplementary material

The online version of this article (10.1186/s12870-018-1286-5) contains supplementary material, which is available to authorized users.

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Most cited references 46

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Prediction of protein subcellular localization.

Chin-Sheng Yu, Yu-Ching Chen, Chih-Hao Lu … (2006)

Because the protein's function is usually related to its subcellular localization, the ability to predict subcellular localization directly from protein sequences will be useful for inferring protein functions. Recent years have seen a surging interest in the development of novel computational tools to predict subcellular localization. At present, these approaches, based on a wide range of algorithms, have achieved varying degrees of success for specific organisms and for certain localization categories. A number of authors have noticed that sequence similarity is useful in predicting subcellular localization. For example, Nair and Rost (Protein Sci 2002;11:2836-2847) have carried out extensive analysis of the relation between sequence similarity and identity in subcellular localization, and have found a close relationship between them above a certain similarity threshold. However, many existing benchmark data sets used for the prediction accuracy assessment contain highly homologous sequences-some data sets comprising sequences up to 80-90% sequence identity. Using these benchmark test data will surely lead to overestimation of the performance of the methods considered. Here, we develop an approach based on a two-level support vector machine (SVM) system: the first level comprises a number of SVM classifiers, each based on a specific type of feature vectors derived from sequences; the second level SVM classifier functions as the jury machine to generate the probability distribution of decisions for possible localizations. We compare our approach with a global sequence alignment approach and other existing approaches for two benchmark data sets-one comprising prokaryotic sequences and the other eukaryotic sequences. Furthermore, we carried out all-against-all sequence alignment for several data sets to investigate the relationship between sequence homology and subcellular localization. Our results, which are consistent with previous studies, indicate that the homology search approach performs well down to 30% sequence identity, although its performance deteriorates considerably for sequences sharing lower sequence identity. A data set of high homology levels will undoubtedly lead to biased assessment of the performances of the predictive approaches-especially those relying on homology search or sequence annotations. Our two-level classification system based on SVM does not rely on homology search; therefore, its performance remains relatively unaffected by sequence homology. When compared with other approaches, our approach performed significantly better. Furthermore, we also develop a practical hybrid method, which combines the two-level SVM classifier and the homology search method, as a general tool for the sequence annotation of subcellular localization.

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QTL mapping and marker-assisted selection forFusariumhead blight resistance in wheat: a review

H Buerstmayr, T. Ban, J. Anderson (2009)

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Detoxification of the Fusarium mycotoxin deoxynivalenol by a UDP-glucosyltransferase from Arabidopsis thaliana.

Brigitte Poppenberger, Franz Berthiller, Doris Lucyshyn … (2003)

Plant pathogenic fungi of the genus Fusarium cause agriculturally important diseases of small grain cereals and maize. Trichothecenes are a class of mycotoxins produced by different Fusarium species that inhibit eukaryotic protein biosynthesis and presumably interfere with the expression of genes induced during the defense response of the plants. One of its members, deoxynivalenol, most likely acts as a virulence factor during fungal pathogenesis and frequently accumulates in grain to levels posing a threat to human and animal health. We report the isolation and characterization of a gene from Arabidopsis thaliana encoding a UDP-glycosyltransferase that is able to detoxify deoxynivalenol. The enzyme, previously assigned the identifier UGT73C5, catalyzes the transfer of glucose from UDP-glucose to the hydroxyl group at carbon 3 of deoxynivalenol. Using a wheat germ extract-coupled transcription/translation system we have shown that this enzymatic reaction inactivates the mycotoxin. This deoxynivalenol-glucosyltransferase (DOGT1) was also found to detoxify the acetylated derivative 15-acetyl-deoxynivalenol, whereas no protective activity was observed against the structurally similar nivalenol. Expression of the glucosyltransferase is developmentally regulated and induced by deoxynivalenol as well as salicylic acid, ethylene, and jasmonic acid. Constitutive overexpression in Arabidopsis leads to enhanced tolerance against deoxynivalenol.

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Author and article information

Contributors

Yi He: heyi_yihe@163.com

Dawood Ahmad: dawood@aup.edu.pk

Xu Zhang: xuzhang@jaas.ac.cn

Yu Zhang: zhangyu2005.8@163.com

Lei Wu: wulei686@sina.com

Peng Jiang: hmjp2005@163.com

Hongxiang Ma:

ORCID: http://orcid.org/0000-0002-7860-3608

hongxiangma@163.com

Journal

Journal ID (nlm-ta): BMC Plant Biol

Journal ID (iso-abbrev): BMC Plant Biol

Title: BMC Plant Biology

Publisher: BioMed Central (London )

ISSN (Electronic): 1471-2229

Publication date (Electronic): 19 April 2018

Publication date PMC-release: 19 April 2018

Publication date Collection: 2018

Volume: 18

Electronic Location Identifier: 67

Affiliations

[1 ]ISNI 0000 0000 9750 7019, GRID grid.27871.3b, Institute of Food Crops, Jiangsu Academy of Agricultural Sciences / Jiangsu Collaborative Innovation Center for Modern Crop Production, ; Nanjing, China

[2 ]ISNI 0000 0000 8577 8102, GRID grid.412298.4, Institute of Biotechnology and Genetic Engineering, , The University of Agriculture, ; Peshawar, Pakistan

Author information

Hongxiang Ma http://orcid.org/0000-0002-7860-3608

Article

Publisher ID: 1286

DOI: 10.1186/s12870-018-1286-5

PMC ID: 5909277

PubMed ID: 29673318

SO-VID: 274ba212-c453-404f-b974-37a3445865a4

License:

Open AccessThis 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.

History

Date received : 27 November 2017

Date accepted : 10 April 2018

Funding

Funded by: European Union Horizon 2020 Mycokey project

Award ID: EU678781

Award Recipient : Hongxiang Ma

Funded by: National key project for the research and development of China

Award ID: 2016YFD0100500, 2016YFE0112900

Award Recipient : Hongxiang Ma

Funded by: China agricultural research system program

Award ID: CARS-03

Award Recipient : Hongxiang Ma

Funded by: FundRef http://dx.doi.org/10.13039/501100001809, National Natural Science Foundation of China;

Award ID: 31561143004

Award Recipient : Hongxiang Ma

Funded by: Natural science foundation of Jiangsu province, China

Award ID: BK20170605

Award Recipient : Yi He

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ScienceOpen disciplines: Plant science & Botany

Keywords: udp-glycosyltransferase,fusarium head blight,wheat,expression pattern,phylogeny,deoxynivalenol

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ScienceOpen disciplines: Plant science & Botany

Keywords: udp-glycosyltransferase, fusarium head blight, wheat, expression pattern, phylogeny, deoxynivalenol

Genome-wide analysis of family-1 UDP glycosyltransferases (UGT) and identification of UGT genes for FHB resistance in wheat ( Triticum aestivum L.)

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Most cited references 46

Prediction of protein subcellular localization.

QTL mapping and marker-assisted selection forFusariumhead blight resistance in wheat: a review

Detoxification of the Fusarium mycotoxin deoxynivalenol by a UDP-glucosyltransferase from Arabidopsis thaliana.

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