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Characterization of the Rosellinia necatrix Transcriptome and Genes Related to Pathogenesis by Single-Molecule mRNA Sequencing

  • Kim, Hyeongmin (Department of Biology, Chungbuk National University) ;
  • Lee, Seung Jae (Bioinformatics Team, DNA Link, Inc.) ;
  • Jo, Ick-Hyun (Department of Herbal Crop Research, National Institute of Horticultural and Herbal Science, Rural Development Administration) ;
  • Lee, Jinsu (Department of Biology, Chungbuk National University) ;
  • Bae, Wonsil (Department of Biology, Chungbuk National University) ;
  • Kim, Hyemin (Department of Biology, Chungbuk National University) ;
  • Won, Kyungho (Pear Research Institute, National Institute of Horticultural & Herbal Science, Rural Development Administration) ;
  • Hyun, Tae Kyung (Department of Industrial Plant Science and Technology, Chungbuk National University) ;
  • Ryu, Hojin (Department of Biology, Chungbuk National University)
  • Received : 2017.03.05
  • Accepted : 2017.04.09
  • Published : 2017.08.01

Abstract

White root rot disease, caused by the pathogen Rosellinia necatrix, is one of the world's most devastating plant fungal diseases and affects several commercially important species of fruit trees and crops. Recent global outbreaks of R. necatrix and advances in molecular techniques have both increased interest in this pathogen. However, the lack of information regarding the genomic structure and transcriptome of R. necatrix has been a barrier to the progress of functional genomic research and the control of this harmful pathogen. Here, we identified 10,616 novel full-length transcripts from the filamentous hyphal tissue of R. necatrix (KACC 40445 strain) using PacBio single-molecule sequencing technology. After annotation of the unigene sets, we selected 14 cell cycle-related genes, which are likely either positively or negatively involved in hyphal growth by cell cycle control. The expression of the selected genes was further compared between two strains that displayed different growth rates on nutritional media. Furthermore, we predicted pathogen-related effector genes and cell wall-degrading enzymes from the annotated gene sets. These results provide the most comprehensive transcriptomal resources for R. necatrix, and could facilitate functional genomics and further analyses of this important phytopathogen.

Keywords

References

  1. Ashburner, M., Ball, C. A., Blake, J. A., Botstein, D., Butler, H., Cherry, J. M., Davis, A. P., Dolinski, K., Dwight, S. S., Eppig, J. T., Harris, M. A., Hill, D. P., Issel-Tarver, L., Kasarskis, A., Lewis, S., Matese, J. C., Richardson, J. E., Ringwald, M., Rubin, G. M. and Sherlock, G. 2000. Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat. Genet. 25:25-29.
  2. Cantarel, B. L., Korf, I., Robb, S. M., Parra, G., Ross, E., Moore, B., Holt, C., Sanchez Alvarado, A. and Yandell, M. 2008. MAKER: an easy-to-use annotation pipeline designed for emerging model organism genomes. Genome Res. 18:188-196.
  3. Chatnaparat, T., Prathuangwong, S. and Lindow, S. E. 2016. Global pattern of gene expression of Xanthomonas axonopodis pv. glycines within soybean leaves. Mol. Plant-Microbe Interact. 29:508-522. https://doi.org/10.1094/MPMI-01-16-0007-R
  4. Conesa, A. and Gotz, S. 2008. Blast2GO: a comprehensive suite for functional analysis in plant genomics. Int. J. Plant Genom. 2008:619832.
  5. Costa, T. R., Felisberto-Rodrigues, C., Meir, A., Prevost, M. S., Redzej, A., Trokte, M. and Waksman, G. 2015. Secretion systems in Gram-negative bacteria: structural and mechanistic insights. Nat. Rev. Microbiol. 13:343-359. https://doi.org/10.1038/nrmicro3456
  6. Dou, D. and Zhou, J. M. 2012. Phytopathogen effectors subverting host immunity: different foes, similar battleground. Cell Host Microbe 12:484-495. https://doi.org/10.1016/j.chom.2012.09.003
  7. Eguchi, N., Kondo, K. and Yamagishi, N. 2009. Bait twig method for soil detection of Rosellinia necatrix, causal agent of white root rot of Japanese pear and apple, at an early stage of tree infection. J. Gen. Plant Pathol. 75:325. https://doi.org/10.1007/s10327-009-0179-8
  8. Goodwin, S., McPherson, J. D. and McCombie, W. R. 2016. Coming of age: ten years of next-generation sequencing technologies. Nat. Rev. Genet. 17:333-351.
  9. Gordon, S. P., Tseng, E., Salamov, A., Zhang, J., Meng, X., Zhao, Z., Kang, D., Underwood, J., Grigoriev, I. V., Figueroa, M., Schilling, J. S., Chen, F. and Wang, Z. 2015. Widespread polycistronic transcripts in fungi revealed by single-molecule mRNA sequencing. PLoS One 10:e0132628. https://doi.org/10.1371/journal.pone.0132628
  10. Holt, C. and Yandell, M. 2011. MAKER2: an annotation pipeline and genome-database management tool for secondgeneration genome projects. BMC Bioinformatics 12:491. https://doi.org/10.1186/1471-2105-12-491
  11. Jones, P., Binns, D., Chang, H. Y., Fraser, M., Li, W., McAnulla, C., McWilliam, H., Maslen, J., Mitchell, A., Nuka, G., Pesseat, S., Quinn, A. F., Sangrador-Vegas, A., Scheremetjew, M., Yong, S. Y., Lopez, R. and Hunter, S. 2014. InterProScan 5: genome-scale protein function classification. Bioinformatics 30:1236-1240. https://doi.org/10.1093/bioinformatics/btu031
  12. Kanehisa, M., Sato, Y., Kawashima, M., Furumichi, M. and Tanabe, M. 2016. KEGG as a reference resource for gene and protein annotation. Nucleic Acids Res. 44:D457-D462. https://doi.org/10.1093/nar/gkv1070
  13. Kondo, H., Kanematsu, S. and Suzuki, N. 2013. Viruses of the white root rot fungus, Rosellinia necatrix. Adv. Virus Res. 86:177-214.
  14. Korf, I. 2004. Gene finding in novel genomes. BMC Bioinformatics 5:59. https://doi.org/10.1186/1471-2105-5-59
  15. Kubicek, C. P., Starr, T. L. and Glass, N. L. 2014. Plant cell wall-degrading enzymes and their secretion in plant-pathogenic fungi. Annu. Rev. Phytopathol. 52:427-451. https://doi.org/10.1146/annurev-phyto-102313-045831
  16. Lo Presti, L., Lanver, D., Schweizer, G., Tanaka, S., Liang, L., Tollot, M., Zuccaro, A., Reissmann, S. and Kahmann, R. 2015. Fungal effectors and plant susceptibility. Annu. Rev. Plant Biol. 66:513-545. https://doi.org/10.1146/annurev-arplant-043014-114623
  17. Macheleidt, J., Mattern, D. J., Fischer, J., Netzker, T., Weber, J., Schroeckh, V., Valiante, V. and Brakhage, A. A. 2016. Regulation and role of fungal secondary metabolites. Annu. Rev. Genet. 50:371-392. https://doi.org/10.1146/annurev-genet-120215-035203
  18. Oses-Ruiz, M., Sakulkoo, W., Littlejohn, G. R., Martin-Urdiroz, M. and Talbot, N. J. 2017. Two independent S-phase checkpoints regulate appressorium-mediated plant infection by the rice blast fungus Magnaporthe oryzae. Proc. Natl. Acad. Sci. U.S.A. 114:E237-E244. https://doi.org/10.1073/pnas.1611307114
  19. Pliego, C., Kanematsu, S., Ruano-Rosa, D., de Vicente, A., Lopez-Herrera, C., Cazorla, F. M. and Ramos, C. 2009. GFP sheds light on the infection process of avocado roots by Rosellinia necatrix. Fungal Genet. Biol. 46:137-145. https://doi.org/10.1016/j.fgb.2008.11.009
  20. Pliego, C., Lopez-Herrera, C., Ramos, C. and Cazorla, F. M. 2012. Developing tools to unravel the biological secrets of Rosellinia necatrix, an emergent threat to woody crops. Mol. Plant Pathol. 13:226-239. https://doi.org/10.1111/j.1364-3703.2011.00753.x
  21. Quoc, N. B. and Chau, N. N. 2016. The role of cell wall degrading enzymes in pathogenesis of Magnaporthe oryzae. Curr. Protein Pept. Sci. doi: 10.2174/1389203717666160813164955. [Epub ahead of print]
  22. Saunders, D. G., Aves, S. J. and Talbot, N. J. 2010. Cell cyclemediated regulation of plant infection by the rice blast fungus. Plant Cell 22:497-507. https://doi.org/10.1105/tpc.109.072447
  23. Sonah, H., Deshmukh, R. K. and Belanger, R. R. 2016. Computational prediction of effector proteins in fungi: opportunities and challenges. Front. Plant Sci. 7:126.
  24. Sperschneider, J., Gardiner, D. M., Dodds, P. N., Tini, F., Covarelli, L., Singh, K. B., Manners, J. M. and Taylor, J. M. 2016. EffectorP: predicting fungal effector proteins from secretomes using machine learning. New Phytol. 210:743-761. https://doi.org/10.1111/nph.13794
  25. Stanke, M., Schoffmann, O., Morgenstern, B. and Waack, S. 2006. Gene prediction in eukaryotes with a generalized hid-den Markov model that uses hints from external sources. BMC Bioinformatics 7:62. https://doi.org/10.1186/1471-2105-7-62
  26. ten Hoopen, G. M. and Krauss, U. 2006. Biology and control of Rosellinia bunodes, Rosellinia necatrix and Rosellinia pepo: a review. Crop Prot. 25:89-107. https://doi.org/10.1016/j.cropro.2005.03.009
  27. Tilgner, H., Grubert, F., Sharon, D. and Snyder, M. P. 2014. Defining a personal, allele-specific, and single-molecule longread transcriptome. Proc. Natl. Acad. Sci. U.S.A. 111:9869-9874. https://doi.org/10.1073/pnas.1400447111
  28. Tseng, T. T., Tyler, B. M. and Setubal, J. C. 2009. Protein secretion systems in bacterial-host associations, and their description in the Gene Ontology. BMC Microbiol. 9 Suppl 1:S2. https://doi.org/10.1186/1471-2180-9-S1-S2
  29. Urban, M., Cuzic, A., Rutherford, K., Irvine, A., Pedro, H., Pant, R., Sadanadan, V., Khamari, L., Billal, S., Mohanty, S. and Hammond-Kosack, K. E. 2017. PHI-base: a new interface and further additions for the multi-species pathogenhost interactions database. Nucleic Acids Res. 45:D604-D610. https://doi.org/10.1093/nar/gkw1089
  30. Yarullina, L. G., Akhatova, A. R. and Kasimova, I. 2016. Hydrolytic enzymes and their proteinaceous inhibitors in regulation of plant-pathogen interactions. Russ. J. Plant Physiol. 63:193-203. https://doi.org/10.1134/S1021443716020151