Mycobiology

The Korean Society of Mycology (한국균학회)
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Genomic Insights into the Rice Blast Fungus through Estimation of Gene Emergence Time in Phylogenetic Context

  • Choi, Jaeyoung (Convergence Research Center for Smart Farm Solution, Korea Institute of Science and Technology) ;
  • Lee, Jong-Joon (Department of Biotechnology, College of Life and Applied Sciences, Yeungnam University) ;
  • Jeon, Junhyun (Department of Biotechnology, College of Life and Applied Sciences, Yeungnam University)
  • Received : 2018.08.03
  • Accepted : 2018.10.17
  • Published : 2018.12.31
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Abstract

The rice blast fungus, Magnaporthe oryzae, is an important pathogen of rice plants. It is well known that genes encoded in the genome have different evolutionary histories that are related to their functions. Phylostratigraphy is a method that correlates the evolutionary origin of genes with evolutionary transitions. Here we applied phylostratigraphy to partition total gene content of M. oryzae into distinct classes (phylostrata), which we designated PS1 to PS7, based on estimation of their emergence time. Genes in individual phylostrata did not show significant biases in their global distribution among seven chromosomes, but at the local level, clustering of genes belonging to the same phylostratum was observed. Our phylostrata-wide analysis of genes revealed that genes in the same phylostratum tend to be similar in many physical and functional characteristics such as gene length and structure, GC contents, codon adaptation index, and level of transcription, which correlates with biological functions in evolutionary context. We also found that a significant proportion of genes in the genome are orphans, for which no orthologs can be detected in the database. Among them, we narrowed down to seven orphan genes having transcriptional and translational evidences, and showed that one of them is implicated in asexual reproduction and virulence, suggesting ongoing evolution in this fungus through lineage-specific genes. Our results provide genomic basis for linking functions of pathogenicity factors and gene emergence time.

Keywords

References

  1. Talbot NJ. On the trail of a cereal killer: exploring the biology of Magnaporthe grisea. Annu Rev Microbiol. 2003;57:177-202. https://doi.org/10.1146/annurev.micro.57.030502.090957
  2. Dean R, Van Kan JA, Pretorius ZA, et al. The top 10 fungal pathogens in molecular plant pathology. Mol Plant Pathol. 2012;13:414-430. https://doi.org/10.1111/j.1364-3703.2011.00783.x
  3. Wilson RA, Talbot NJ. Under pressure: investigating the biology of plant infection by Magnaporthe oryzae. Nat Rev Micro. 2009;7:185-195. https://doi.org/10.1038/nrmicro2032
  4. Howard RJ, Valent B. Breaking and entering: host penetration by the fungal rice blast pathogen Magnaporthe grisea. Annu Rev Microbiol. 1996;50:491-512. https://doi.org/10.1146/annurev.micro.50.1.491
  5. Kankanala P, Czymmek K, Valent B. Roles for rice membrane dynamics and plasmodesmata during biotrophic invasion by the blast fungus. Plant Cell. 2007;19:706-724. https://doi.org/10.1105/tpc.106.046300
  6. Gladieux P, Condon B, Ravel S, et al. Gene flow between divergent cereal- and grass-specific lineages of the rice blast fungus Magnaporthe oryzae. mBio. 2018;9:e01219-17.
  7. Xue M, Yang J, Li Z, et al. Comparative analysis of the genomes of two field isolates of the rice blast fungus Magnaporthe oryzae. PLoS Genet. 2012;8:e1002869. https://doi.org/10.1371/journal.pgen.1002869
  8. Urban M, Cuzick A, Rutherford K, et al. PHI-base: a new interface and further additions for the multi-species pathogen-host interactions database. Nucleic Acids Res. 2017;45:D604-DD10. https://doi.org/10.1093/nar/gkw1089
  9. Urban M, Irvine AG, Cuzick A, et al. Using the pathogen-host interactions database (PHI-base) to investigate plant pathogen genomes and genes implicated in virulence. Front Plant Sci. 2015;6:605.
  10. Domazet-Loso T, Brajkovic J, Tautz D. A phylostratigraphy approach to uncover the genomic history of major adaptations in metazoan lineages. Trends Genet. 2007;23:533-539. https://doi.org/10.1016/j.tig.2007.08.014
  11. Neme R, Tautz D. Phylogenetic patterns of emergence of new genes support a model of frequent de novo evolution. BMC Genomics. 2013;14:117 https://doi.org/10.1186/1471-2164-14-117
  12. Domazet-Loso T, Tautz D. Phylostratigraphic tracking of cancer genes suggests a link to the emergence of multicellularity in metazoa. BMC Biol. 2010;8:66 https://doi.org/10.1186/1741-7007-8-66
  13. Moyers BA, Zhang J. Evaluating phylostratigraphic evidence for widespread De Novo gene birth in genome evolution. Mol Biol Evol. 2016;33:1245-1256. https://doi.org/10.1093/molbev/msw008
  14. Sipos G, Prasanna AN, Walter MC, et al. Genome expansion and lineage-specific genetic innovations in the forest pathogenic fungi Armillaria. Nat Ecol Evol. 2017;1:1931-1941. https://doi.org/10.1038/s41559-017-0347-8
  15. Conant GC, Wolfe KH. Turning a hobby into a job: How duplicated genes find new functions. Nat Rev Genet. 2008;9:938-950. https://doi.org/10.1038/nrg2482
  16. Tautz D, Domazet-Loso T. The evolutionary origin of orphan genes. Nat Rev Genet. 2011;12:692-702.
  17. Domazet-Loso T, Tautz D. An evolutionary analysis of orphan genes in Drosophila. Genome Res. 2003;13:2213-2219. https://doi.org/10.1101/gr.1311003
  18. Grigoriev IV, Nikitin R, Haridas S, et al. MycoCosm portal: gearing up for 1000 fungal genomes. Nucl Acids Res. 2014;42:D699-D704. https://doi.org/10.1093/nar/gkt1183
  19. Altschul SF, Gish W, Miller W, et al. Basic local alignment search tool. J Mol Biol. 1990;215:403-410. https://doi.org/10.1016/S0022-2836(05)80360-2
  20. Coordinators NR. Database resources of the National Center for Biotechnology Information. Nucleic Acids Res. 2018;46:D8-D13. https://doi.org/10.1093/nar/gkx1095
  21. Team RC. R: A language and environment for statistical computing. Vienna: R Foundation for Statistical Computing; 2015.
  22. Jeon J, Choi J, Lee GW, et al. Genome-wide profiling of DNA methylation provides insights into epigenetic regulation of fungal development in a plant pathogenic fungus. Magnaporthe oryzae. Sci Rep. 2015;5:8567. https://doi.org/10.1038/srep08567
  23. Choi J, Park J, Kim D, et al. Fungal secretome database: integrated platform for annotation of fungal secretomes. BMC Genomics. 2010;11:105. https://doi.org/10.1186/1471-2164-11-105
  24. Alba MM, Castresana J. On homology searches by protein blast and the characterization of the age of genes. BMC Evol Biol. 2007;7:53 https://doi.org/10.1186/1471-2148-7-53
  25. Postberg J, Forcob S, Chang WJ, et al. The evolutionary history of histone H3 suggests a deep eukaryotic root of chromatin modifying mechanisms. BMC Evol Biol. 2010;10:259. https://doi.org/10.1186/1471-2148-10-259
  26. Brosch G, Loidl P, Graessle S. Histone modifications and chromatin dynamics: a focus on filamentous fungi. FEMS Microbiol Rev. 2008;32:409-439. https://doi.org/10.1111/j.1574-6976.2007.00100.x
  27. Chi MH, Park SY, Kim S, et al. A novel pathogenicity gene is required in the rice blast fungus to suppress the basal defenses of the host. PLoS Pathog. 2009;5:e1000401 https://doi.org/10.1371/journal.ppat.1000401
  28. Okagaki LH, Nunes CC, Sailsbery J, et al. Genome sequences of three phytopathogenic species of the Magnaporthaceae family of fungi. G3 (Bethesda). 2015;5:2539-2545.
  29. Sadat A, Jeon J, Mir AA, et al. Analysis of in planta expressed orphan genes in the rice blast fungus Magnaporthe oryzae. Plant Pathol J. 2014;30:367-374. https://doi.org/10.5423/PPJ.OA.08.2014.0072
  30. Park J, Park B, Jung K, et al. CFGP: a web-based, comparative fungal genomics platform. Nucleic Acids Res. 2007;36:D562-D571. https://doi.org/10.1093/nar/gkm758
  31. Kim KT, Jeon J, Choi J, et al. Kingdom-wide analysis of fungal small secreted proteins (SSPs) reveals their potential role in host association. Front Plant Sci. 2016;7:186.
  32. Fox JM, Erill I. Relative codon adaptation: a generic codon bias index for prediction of gene expression. DNA Res. 2010;17:185-196. https://doi.org/10.1093/dnares/dsq012
  33. Jeon J, Park SY, Chi MH, et al. Genome-wide functional analysis of pathogenicity genes in the rice blast fungus. Nat Genet. 2007;39:561-565. https://doi.org/10.1038/ng2002
  34. Franck WL, Gokce E, Oh Y, et al. Temporal analysis of the Magnaporthe oryzae proteome during conidial germination and cyclic AMP (cAMP)-mediated appressorium formation. Mol Cell Proteomics. 2013;12:2249-2265. https://doi.org/10.1074/mcp.M112.025874
  35. Gokce E, Franck WL, Oh Y, et al. In-depth analysis of the Magnaporthe oryzae conidial proteome. J Proteome Res. 2012;11:5827-5835. https://doi.org/10.1021/pr300604s
  36. Kim ST, Yu S, Kim SG, et al. Proteome analysis of rice blast fungus (Magnaporthe grisea) proteome during appressorium formation. Proteomics. 2004;4:3579-3587. https://doi.org/10.1002/pmic.200400969
  37. Bhadauria V, Wang LX, Peng YL. Proteomic changes associated with deletion of the Magnaporthe oryzae conidial morphology-regulating gene COM1. Biol Direct. 2010;5:61. https://doi.org/10.1186/1745-6150-5-61

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