1887

Abstract

Long non-coding RNAs (lncRNAs) are regulatory molecules interacting in a wide array of biological processes. lncRNAs in fungal pathogens can be responsive to stress and play roles in regulating growth and nutrient acquisition. Recent evidence suggests that lncRNAs may also play roles in virulence, such as regulating pathogenicity-associated enzymes and on-host reproductive cycles. Despite the importance of lncRNAs, only a few model fungi have well-documented inventories of lncRNA. In this study, we apply a recent computational pipeline to predict high-confidence lncRNA candidates in an important global pathogen of wheat impacting global food production. We analyse genomic features of lncRNAs and the most likely associated processes through analyses of expression over a host infection cycle. We find that lncRNAs are frequently expressed during early infection, before the switch to necrotrophic growth. They are mostly located in facultative heterochromatic regions, which are known to contain many genes associated with pathogenicity. Furthermore, we find that lncRNAs are frequently co-expressed with genes that may be involved in responding to host defence signals, such as oxidative stress. Finally, we assess pangenome features of lncRNAs using four additional reference-quality genomes. We find evidence that the repertoire of expressed lncRNAs varies substantially between individuals, even though lncRNA loci tend to be shared at the genomic level. Overall, this study provides a repertoire and putative functions of lncRNAs in enabling future molecular genetics and functional analyses in an important pathogen.

Funding
This study was supported by the:
  • Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (Award 205401)
    • Principle Award Recipient: DanielCroll
  • This is an open-access article distributed under the terms of the Creative Commons Attribution License.
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2023-11-22
2024-04-27
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References

  1. Guttman M, Rinn JL. Modular regulatory principles of large non-coding RNAs. Nature 2012; 482:339–346 [View Article] [PubMed]
    [Google Scholar]
  2. Ard R, Tong P, Allshire RC. Long non-coding RNA-mediated transcriptional interference of a permease gene confers drug tolerance in fission yeast. Nat Commun 2014; 5:5576 [View Article] [PubMed]
    [Google Scholar]
  3. Robinson EK, Covarrubias S, Carpenter S. The how and why of lncRNA function: an innate immune perspective. Biochim Biophys Acta Gene Regul Mech 2020; 1863:194419 [View Article] [PubMed]
    [Google Scholar]
  4. Wang C, Wang L, Ding Y, Lu X, Zhang G et al. LncRNA structural characteristics in epigenetic regulation. IJMS 2017; 18:2659 [View Article]
    [Google Scholar]
  5. Yao R-W, Wang Y, Chen L-L. Cellular functions of long noncoding RNAs. Nat Cell Biol 2019; 21:542–551 [View Article] [PubMed]
    [Google Scholar]
  6. Romero-Barrios N, Legascue MF, Benhamed M, Ariel F, Crespi M. Splicing regulation by long noncoding RNAs. Nucleic Acids Res 2018; 46:2169–2184 [View Article] [PubMed]
    [Google Scholar]
  7. Iaccarino I, Klapper W. LncRNA as cancer biomarkers. In Navarro A. eds Long Non-Coding RNAs in Cancer New York, NY: Springer US; pp 27–41 [View Article]
    [Google Scholar]
  8. Abdi E, Latifi-Navid S, Latifi-Navid H. LncRNA polymorphisms and breast cancer risk. Pathol Res Pract 2022; 229:153729 [View Article] [PubMed]
    [Google Scholar]
  9. Sun T-T, He J, Liang Q, Ren L-L, Yan T-T et al. LncRNA GClnc1 promotes gastric carcinogenesis and May act as a modular scaffold of WDR5 and KAT2A complexes to specify the histone modification pattern. Cancer Discov 2016; 6:784–801 [View Article] [PubMed]
    [Google Scholar]
  10. Guo F, Li Y, Liu Y, Wang J, Li Y et al. Inhibition of metastasis-associated lung adenocarcinoma transcript 1 in CaSki human cervical cancer cells suppresses cell proliferation and invasion. Acta Biochim Biophys Sin 2010; 42:224–229 [View Article] [PubMed]
    [Google Scholar]
  11. Liu B, Xiang W, Liu J, Tang J, Wang J et al. The regulatory role of antisense lncRNAs in cancer. Cancer Cell Int 2021; 21:459 [View Article] [PubMed]
    [Google Scholar]
  12. Rapicavoli NA, Qu K, Zhang J, Mikhail M, Laberge R-M et al. A mammalian pseudogene lncRNA at the interface of inflammation and anti-inflammatory therapeutics. Elife 2013; 2:e00762 [View Article] [PubMed]
    [Google Scholar]
  13. Atianand MK, Hu W, Satpathy AT, Shen Y, Ricci EP et al. A long noncoding RNA lincRNA-EPS acts as a transcriptional brake to restrain inflammation. Cell 2016; 165:1672–1685 [View Article] [PubMed]
    [Google Scholar]
  14. Castellanos-Rubio A, Fernandez-Jimenez N, Kratchmarov R, Luo X, Bhagat G et al. A long noncoding RNA associated with susceptibility to celiac disease. Science 2016; 352:91–95 [View Article] [PubMed]
    [Google Scholar]
  15. Zhang D-D, Wang W-T, Xiong J, Xie X-M, Cui S-S et al. Long noncoding RNA LINC00305 promotes inflammation by activating the AHRR-NF-κB pathway in human monocytes. Sci Rep 2017; 7:46204 [View Article] [PubMed]
    [Google Scholar]
  16. Xu Q, Song Z, Zhu C, Tao C, Kang L et al. Systematic comparison of lncRNAs with protein coding mRNAs in population expression and their response to environmental change. BMC Plant Biol 2017; 17:42 [View Article]
    [Google Scholar]
  17. Lv Y, Liang Z, Ge M, Qi W, Zhang T et al. Genome-wide identification and functional prediction of nitrogen-responsive intergenic and intronic long non-coding RNAs in maize (Zea mays L.). BMC Genomics 2016; 17:350 [View Article]
    [Google Scholar]
  18. Garg A, Sanchez AM, Shuman S, Schwer B. A long noncoding (lnc)RNA governs expression of the phosphate transporter Pho84 in fission yeast and has cascading effects on the flanking prt lncRNA and pho1 genes. J Biol Chem 2018; 293:4456–4467 [View Article] [PubMed]
    [Google Scholar]
  19. Marquardt S, Raitskin O, Wu Z, Liu F, Sun Q et al. Functional consequences of splicing of the antisense transcript COOLAIR on FLC transcription. Mol Cell 2014; 54:156–165 [View Article] [PubMed]
    [Google Scholar]
  20. Li S, Yu X, Lei N, Cheng Z, Zhao P et al. Genome-wide identification and functional prediction of cold and/or drought-responsive lncRNAs in cassava. Sci Rep 2017; 7:45981 [View Article]
    [Google Scholar]
  21. Zhang W, Han Z, Guo Q, Liu Y, Zheng Y et al. Identification of maize long non-coding RNAs responsive to drought stress. PLOS ONE 2014; 9:e98958 [View Article]
    [Google Scholar]
  22. Yuan C, He R-R, Zhao W-L, Chen Y-Q, Zhang Y-C. Insights into the roles of long noncoding RNAs in the communication between plants and the environment. Plant Genome 2022e20277 [View Article] [PubMed]
    [Google Scholar]
  23. Statello L, Guo C-J, Chen L-L, Huarte M. Gene regulation by long non-coding RNAs and its biological functions. Nat Rev Mol Cell Biol 2021; 22:96–118 [View Article]
    [Google Scholar]
  24. Hüttenhofer A, Schattner P, Polacek N. Non-coding RNAs: hope or hype?. Trends Genet 2005; 21:289–297 [View Article] [PubMed]
    [Google Scholar]
  25. Pang KC, Frith MC, Mattick JS. Rapid evolution of noncoding RNAs: lack of conservation does not mean lack of function. Trends Genet 2006; 22:1–5 [View Article] [PubMed]
    [Google Scholar]
  26. Gloss BS, Dinger ME. The specificity of long noncoding RNA expression. Biochim Biophys Acta BBA. Gene Regul Mech 2016; 1859:16–22 [View Article] [PubMed]
    [Google Scholar]
  27. Sims D, Sudbery I, Ilott NE, Heger A, Ponting CP. Sequencing depth and coverage: key considerations in genomic analyses. Nat Rev Genet 2014; 15:121–132 [View Article] [PubMed]
    [Google Scholar]
  28. Ghosh A, Chakrabarti R, Shukla PC. Inadvertent nucleotide sequence alterations during mutagenesis: highlighting the vulnerabilities in mouse transgenic technology. J Genet Eng Biotechnol 2021; 19:30 [View Article] [PubMed]
    [Google Scholar]
  29. Iwakiri J, Hamada M, Asai K. Bioinformatics tools for lncRNA research. Biochim Biophys Acta BBA. Gene Regul Mech 2016; 1859:23–30 [View Article] [PubMed]
    [Google Scholar]
  30. Till P, Mach RL, Mach-Aigner AR. A current view on long noncoding RNAs in yeast and filamentous fungi. Appl Microbiol Biotechnol 2018; 102:7319–7331 [View Article] [PubMed]
    [Google Scholar]
  31. Wang Z, Jiang Y, Wu H, Xie X, Huang B. Genome-wide identification and functional prediction of long non-coding RNAs involved in the heat stress response in Metarhizium robertsii. Front Microbiol 2019; 10:2336 [View Article] [PubMed]
    [Google Scholar]
  32. Chacko N, Zhao Y, Yang E, Wang L, Cai JJ et al. The lncRNA RZE1 controls cryptococcal morphological transition. PLOS Genet 2015; 11:e1005692 [View Article] [PubMed]
    [Google Scholar]
  33. Li Y, Baptista RP, Sateriale A, Striepen B, Kissinger JC. Analysis of long non-coding RNA in Cryptosporidium parvum reveals significant stage-specific antisense transcription. Front Cell Infect Microbiol 2020; 10:608298 [View Article] [PubMed]
    [Google Scholar]
  34. Gao J, Chow EWL, Wang H, Xu X, Cai C et al. LncRNA DINOR is a virulence factor and global regulator of stress responses in Candida auris. Nat Microbiol 2021; 6:842–851 [View Article] [PubMed]
    [Google Scholar]
  35. Tang J, Chen X, Yan Y, Huang J, Luo C et al. Comprehensive transcriptome profiling reveals abundant long non-coding RNAs associated with development of the rice false smut fungus, Ustilaginoidea virens. Environ Microbiol 2021; 23:4998–5013 [View Article] [PubMed]
    [Google Scholar]
  36. Till P, Pucher ME, Mach RL, Mach-Aigner AR. A long noncoding RNA promotes cellulase expression in Trichoderma reesei. Biotechnol Biofuels 2018; 11:78 [View Article] [PubMed]
    [Google Scholar]
  37. Liu N, Wang P, Li X, Pei Y, Sun Y et al. Long non-coding RNAs profiling in pathogenesis of Verticillium dahliae: New insights in the host-pathogen interaction. Plant Sci 2022; 314:111098 [View Article] [PubMed]
    [Google Scholar]
  38. Kalem MC, Panepinto JC. Long non-coding RNAs in Cryptococcus neoformans: insights into fungal pathogenesis. Front Cell Infect Microbiol 2022; 12:858317 [View Article] [PubMed]
    [Google Scholar]
  39. Wang J, Zeng W, Cheng J, Xie J, Fu Y et al. lncRsp1, a long noncoding RNA, influences Fgsp1 expression and sexual reproduction in Fusarium graminearum. Mol Plant Pathol 2022; 23:265–277 [View Article] [PubMed]
    [Google Scholar]
  40. O’Driscoll A, Kildea S, Doohan F, Spink J, Mullins E. The wheat-Septoria conflict: a new front opening up?. Trends Plant Sci 2014; 19:602–610 [View Article] [PubMed]
    [Google Scholar]
  41. Berraies S, Gharbi MS, Belzile F, Yahyaoui A, Hajlaoui MR et al. High genetic diversity of Mycospaherella graminicola (Zymoseptoria tritici) from a single wheat field in Tunisia as revealed by SSR markers. Afr J Biotechnol 2013; 12: [View Article]
    [Google Scholar]
  42. Feurtey A, Lorrain C, McDonald MC, Milgate A, Solomon PS et al. A thousand-genome panel retraces the global spread and adaptation of a major fungal crop pathogen. Nat Commun 2023; 14:1059 [View Article] [PubMed]
    [Google Scholar]
  43. Palma-Guerrero J, Ma X, Torriani SFF, Zala M, Francisco CS et al. Comparative transcriptome analyses in Zymoseptoria tritici reveal significant differences in gene expression among strains during plant infection. Mol Plant Microbe Interact 2017; 30:231–244 [View Article] [PubMed]
    [Google Scholar]
  44. Haueisen J, Möller M, Eschenbrenner CJ, Grandaubert J, Seybold H et al. Highly flexible infection programs in a specialized wheat pathogen. Ecol Evol 2019; 9:275–294 [View Article] [PubMed]
    [Google Scholar]
  45. Oggenfuss U, Badet T, Wicker T, Hartmann FE, Singh NK et al. A population-level invasion by transposable elements triggers genome expansion in a fungal pathogen. Elife 2021; 10:e69249 [View Article] [PubMed]
    [Google Scholar]
  46. Goodwin SB, M’barek SB, Dhillon B, Wittenberg AHJ, Crane CF et al. Finished genome of the fungal wheat pathogen Mycosphaerella graminicola reveals dispensome structure, chromosome plasticity, and stealth pathogenesis. PLoS Genet 2011; 7:e1002070 [View Article] [PubMed]
    [Google Scholar]
  47. Johnson R, Guigó R. The RIDL hypothesis: transposable elements as functional domains of long noncoding RNAs. RNA 2014; 20:959–976 [View Article] [PubMed]
    [Google Scholar]
  48. Francisco CS, Ma X, Zwyssig MM, McDonald BA, Palma-Guerrero J. Morphological changes in response to environmental stresses in the fungal plant pathogen Zymoseptoria tritici. Sci Rep 2019; 9:9642 [View Article] [PubMed]
    [Google Scholar]
  49. Fouché S, Badet T, Oggenfuss U, Plissonneau C, Francisco CS et al. Stress-driven transposable element de-repression dynamics and virulence evolution in a fungal pathogen. Mol Biol Evol 2020; 37:221–239 [View Article] [PubMed]
    [Google Scholar]
  50. Yang F. Genome-wide analysis of small RNAs in the wheat pathogenic fungus Zymoseptoria tritici. Fungal Biol 2015; 119:631–640 [View Article] [PubMed]
    [Google Scholar]
  51. Kettles GJ, Hofinger BJ, Hu P, Bayon C, Rudd JJ et al. sRNA profiling combined with gene function analysis reveals a lack of evidence for cross-Kingdom RNAi in the wheat - Zymoseptoria tritici pathosystem. Front Plant Sci 2019; 10:892 [View Article] [PubMed]
    [Google Scholar]
  52. Lapalu N, Lamothe L, Petit Y, Genissel A, Delude C et al. Improved gene annotation of the fungal wheat pathogen Zymoseptoria tritici based on combined Iso-Seq and RNA-Seq evidence. Genomics 2023; 2023 [View Article]
    [Google Scholar]
  53. Schmal M, Girod C, Yaver D, Mach RL, Mach-Aigner AR. A bioinformatic-assisted workflow for genome-wide identification of ncRNAs. NAR Genom Bioinform 2022; 4:lqac059 [View Article] [PubMed]
    [Google Scholar]
  54. Grandaubert J, Bhattacharyya A, Stukenbrock EH. RNA-seq-based gene annotation and comparative genomics of four fungal grass pathogens in the genus Zymoseptoria identify novel orphan genes and species-specific invasions of transposable elements. G3 2015; 5:1323–1333 [View Article] [PubMed]
    [Google Scholar]
  55. Pertea G, Pertea M. GFF utilities: gffread and gffcompare. F1000Res 2020; 9:304 [View Article]
    [Google Scholar]
  56. Kim D, Paggi JM, Park C, Bennett C, Salzberg SL. Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype. Nat Biotechnol 2019; 37:907–915 [View Article] [PubMed]
    [Google Scholar]
  57. Liao Y, Smyth GK, Shi W. featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics 2014; 30:923–930 [View Article]
    [Google Scholar]
  58. Kovaka S, Zimin AV, Pertea GM, Razaghi R, Salzberg SL et al. Transcriptome assembly from long-read RNA-seq alignments with StringTie2. Genome Biol 2019; 20:278 [View Article] [PubMed]
    [Google Scholar]
  59. Robinson MD, McCarthy DJ, Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 2010; 26:139–140 [View Article] [PubMed]
    [Google Scholar]
  60. R Core Team R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing; 2018 https://www.R-project.org/
  61. Plissonneau C, Hartmann FE, Croll D. Pangenome analyses of the wheat pathogen Zymoseptoria tritici reveal the structural basis of a highly plastic eukaryotic genome. BMC Biol 2018; 16:5 [View Article]
    [Google Scholar]
  62. Plissonneau C, Stürchler A, Croll D. The evolution of orphan regions in genomes of a fungal pathogen of wheat. mBio 2016; 7:e01231-16 [View Article] [PubMed]
    [Google Scholar]
  63. Meyer D, Dimitriadou E, Hornik K, Weingessel A, Leisch F. E1071: Misc Functions of the Department of Statistics, Probability Theory Group (Formerly: E1071), TU Wien; 2023 https://CRAN.R-project.org/package=e1071
  64. Schwämmle V, Jensen ON. A simple and fast method to determine the parameters for fuzzy c–means cluster analysis. Bioinformatics 2010; 26:2841–2848 [View Article]
    [Google Scholar]
  65. Gentleman R, Falcon S, Castelo R, Kumari S, Ndubi D et al. Gostats: Tools for Manipulating GO and Microarrays 2023
    [Google Scholar]
  66. Quinlan AR, Hall IM. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics 2010; 26:841–842 [View Article]
    [Google Scholar]
  67. Li J, Ma W, Zeng P, Wang J, Geng B et al. LncTar: a tool for predicting the RNA targets of long noncoding RNAs. Brief Bioinform 2015; 16:806–812 [View Article] [PubMed]
    [Google Scholar]
  68. Blin K, Shaw S, Augustijn HE, Reitz ZL, Biermann F et al. antiSMASH 7.0: new and improved predictions for detection, regulation, chemical structures and visualisation. Nucleic Acids Res 2023; 51:W46–W50 [View Article] [PubMed]
    [Google Scholar]
  69. Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 2014; 30:2114–2120 [View Article] [PubMed]
    [Google Scholar]
  70. Langmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2. Nat Methods 2012; 9:357–359 [View Article] [PubMed]
    [Google Scholar]
  71. Stovner EB, Sætrom P. epic2 efficiently finds diffuse domains in ChIP-seq data. Bioinformatics 2019; 35:4392–4393 [View Article] [PubMed]
    [Google Scholar]
  72. Slater GSC, Birney E. Automated generation of heuristics for biological sequence comparison. BMC Bioinformatics 2005; 6:31 [View Article] [PubMed]
    [Google Scholar]
  73. Badet T, Oggenfuss U, Abraham L, McDonald BA, Croll D. A 19-isolate reference-quality global pangenome for the fungal wheat pathogen Zymoseptoria tritici. BMC Biol 2020; 18:12 [View Article] [PubMed]
    [Google Scholar]
  74. Li W, Godzik A. Cd-hit: a fast program for clustering and comparing large sets of protein or nucleotide sequences. Bioinformatics 2006; 22:1658–1659 [View Article]
    [Google Scholar]
  75. Oksanen J, Simpson GL, Blanchet FG, Kindt R, Legendre P et al. vegan: community ecology package; 2023 https://github.com/vegandevs/vegan
  76. Wei T, Simko V. R package ‘corrplot’: visualization of a correlation matrix; 2021 https://github.com/taiyun/corrplot
  77. Wickham H. ggplot2. In Ggplot2: Elegant Graphics for Data Analysis Cham: Springer-Verlag; 2016 [View Article]
    [Google Scholar]
  78. Derrien T, Johnson R, Bussotti G, Tanzer A, Djebali S et al. The GENCODE v7 catalog of human long noncoding RNAs: analysis of their gene structure, evolution, and expression. Genome Res 2012; 22:1775–1789 [View Article] [PubMed]
    [Google Scholar]
  79. Conesa A, Madrigal P, Tarazona S, Gomez-Cabrero D, Cervera A et al. A survey of best practices for RNA-seq data analysis. Genome Biol 2016; 17:181 [View Article] [PubMed]
    [Google Scholar]
  80. Kornienko AE, Dotter CP, Guenzl PM, Gisslinger H, Gisslinger B et al. Long non-coding RNAs display higher natural expression variation than protein-coding genes in healthy humans. Genome Biol 2016; 17:14 [View Article] [PubMed]
    [Google Scholar]
  81. Andergassen D, Dotter CP, Wenzel D, Sigl V, Bammer PC et al. Mapping the mouse allelome reveals tissue-specific regulation of allelic expression. Elife 2017; 6:e25125 [View Article] [PubMed]
    [Google Scholar]
  82. Gil N, Ulitsky I. Regulation of gene expression by cis-acting long non-coding RNAs. Nat Rev Genet 2020; 21:102–117 [View Article] [PubMed]
    [Google Scholar]
  83. Gong C, Maquat LE. lncRNAs transactivate STAU1-mediated mRNA decay by duplexing with 3’ UTRs via Alu elements. Nature 2011; 470:284–288 [View Article] [PubMed]
    [Google Scholar]
  84. Pisignano G, Ladomery M. Epigenetic regulation of alternative splicing: how LncRNAs tailor the message. Noncoding RNA 2021; 7:21 [View Article] [PubMed]
    [Google Scholar]
  85. Umu SU, Gardner PP. A comprehensive benchmark of RNA-RNA interaction prediction tools for all domains of life. Bioinformatics 2017; 33:988–996 [View Article] [PubMed]
    [Google Scholar]
  86. Rudd JJ, Kanyuka K, Hassani-Pak K, Derbyshire M, Andongabo A et al. Transcriptome and metabolite profiling of the infection cycle of Zymoseptoria tritici on wheat reveals a biphasic interaction with plant immunity involving differential pathogen chromosomal contributions and a variation on the hemibiotrophic lifestyle definition. Plant Physiol 2015; 167:1158–1185 [View Article] [PubMed]
    [Google Scholar]
  87. Ben M’Barek S, Cordewener JHG, van der Lee TAJ, America AHP, Mirzadi Gohari A et al. Proteome catalog of Zymoseptoria tritici captured during pathogenesis in wheat. Fungal Genet Biol 2015; 79:42–53 [View Article] [PubMed]
    [Google Scholar]
  88. Yang F, Li W, Jørgensen HJL, Lee Y-H. Transcriptional reprogramming of wheat and the hemibiotrophic pathogen Septoria tritici during two phases of the compatible interaction. PLoS One 2013; 8:e81606 [View Article]
    [Google Scholar]
  89. Gohari A, Mehrabi R, De Wit P, Kema G. Functional Analysis of Catalase-Peroxidase Encoding Genes in the Fungal Wheat Pathogen Zymoseptoria Tritici 2013
    [Google Scholar]
  90. Jashni MK, Dols IHM, Iida Y, Boeren S, Beenen HG et al. Synergistic action of a metalloprotease and a serine protease from Fusarium oxysporum f. sp. lycopersici cleaves chitin-binding tomato chitinases, reduces their antifungal activity, and enhances fungal virulence. Mol Plant Microbe Interact 2015; 28:996–1008 [View Article] [PubMed]
    [Google Scholar]
  91. Muszewska A, Stepniewska-Dziubinska MM, Steczkiewicz K, Pawlowska J, Dziedzic A et al. Fungal lifestyle reflected in serine protease repertoire. Sci Rep 2017; 7:9147 [View Article] [PubMed]
    [Google Scholar]
  92. Rausch T, Wachter A. Sulfur metabolism: a versatile platform for launching defence operations. Trends Plant Sci 2005; 10:503–509 [View Article] [PubMed]
    [Google Scholar]
  93. Denslow SA, Walls AA, Daub ME. Regulation of biosynthetic genes and antioxidant properties of vitamin B6 vitamers during plant defense responses. Physiol Mol Plant Pathol 2005; 66:244–255 [View Article]
    [Google Scholar]
  94. Samsatly J, Copley TR, Jabaji SH. Antioxidant genes of plants and fungal pathogens are distinctly regulated during disease development in different Rhizoctonia solani pathosystems. PLoS One 2018; 13:e0192682 [View Article] [PubMed]
    [Google Scholar]
  95. Panaretou B, Zhai C. The heat shock proteins: their roles as multi-component machines for protein folding. Fungal Biol Rev 2008; 22:110–119 [View Article]
    [Google Scholar]
  96. Thiebaut C, Eve L, Poulard C, Le Romancer M. Structure, activity, and function of PRMT1. Life 2021; 11:1147 [View Article]
    [Google Scholar]
  97. Wang G, Wang C, Hou R, Zhou X, Li G et al. The AMT1 arginine methyltransferase gene is important for plant infection and normal hyphal growth in Fusarium graminearum. PLoS One 2012; 7:e38324 [View Article]
    [Google Scholar]
  98. Soyer JL, Grandaubert J, Haueisen J, Schotanus K, Stukenbrock EH. In planta chromatin immunoprecipitation in Zymoseptoria tritici reveals chromatin-based regulation of putative effector gene expression. bioRxiv [View Article]
    [Google Scholar]
  99. Schotanus K, Soyer JL, Connolly LR, Grandaubert J, Happel P et al. Histone modifications rather than the novel regional centromeres of Zymoseptoria tritici distinguish core and accessory chromosomes. Epigenetics Chromatin 2015; 8:41 [View Article] [PubMed]
    [Google Scholar]
  100. Singh NK, Karisto P, Croll D. Population-level deep sequencing reveals the interplay of clonal and sexual reproduction in the fungal wheat pathogen Zymoseptoria tritici. Microbial Genomics 2021; 7:000678 [View Article]
    [Google Scholar]
  101. Zhan J, Pettway RE, McDonald BA. The global genetic structure of the wheat pathogen Mycosphaerella graminicola is characterized by high nuclear diversity, low mitochondrial diversity, regular recombination, and gene flow. Fungal Genet Biol 2003; 38:286–297 [View Article] [PubMed]
    [Google Scholar]
  102. Chen H, King R, Smith D, Bayon C, Ashfield T et al. Combined pangenomics and transcriptomics reveals core and redundant virulence processes in a rapidly evolving fungal plant pathogen. BMC Biol 2023; 21:24 [View Article] [PubMed]
    [Google Scholar]
  103. Mattick JS, Amaral PP, Carninci P, Carpenter S, Chang HY et al. Long non-coding RNAs: definitions, functions, challenges and recommendations. Nat Rev Mol Cell Biol 2023; 24:430–447 [View Article] [PubMed]
    [Google Scholar]
  104. Jachowicz JW, Strehle M, Banerjee AK, Blanco MR, Thai J et al. Xist spatially amplifies SHARP/SPEN recruitment to balance chromosome-wide silencing and specificity to the X chromosome. Nat Struct Mol Biol 2022; 29:239–249 [View Article] [PubMed]
    [Google Scholar]
  105. Cemel IA, Ha N, Schermann G, Yonekawa S, Brunner M. The coding and noncoding transcriptome of Neurospora crassa. BMC Genomics 2017; 18:978 [View Article] [PubMed]
    [Google Scholar]
  106. Ouyang J, Zhong Y, Zhang Y, Yang L, Wu P et al. Long non-coding RNAs are involved in alternative splicing and promote cancer progression. Br J Cancer 2022; 126:1113–1124 [View Article] [PubMed]
    [Google Scholar]
  107. Khan MR, Wellinger RJ, Laurent B. Exploring the alternative splicing of long noncoding RNAs. Trends Genet 2021; 37:695–698 [View Article] [PubMed]
    [Google Scholar]
  108. Hadjiargyrou M, Delihas N. The intertwining of transposable elements and non-coding RNAs. IJMS 2013; 14:13307–13328 [View Article]
    [Google Scholar]
  109. Corley SM, MacKenzie KL, Beverdam A, Roddam LF, Wilkins MR. Differentially expressed genes from RNA-Seq and functional enrichment results are affected by the choice of single-end versus paired-end reads and stranded versus non-stranded protocols. BMC Genomics 2017; 18:399 [View Article]
    [Google Scholar]
  110. Dindhoria K, Monga I, Thind AS. Computational approaches and challenges for identification and annotation of non-coding RNAs using RNA-Seq. Funct Integr Genomics 2022; 22:1105–1112 [View Article]
    [Google Scholar]
  111. Choi G, Jeon J, Lee H, Zhou S, Lee Y-H. Genome-wide profiling of long non-coding RNA of the rice blast fungus Magnaporthe oryzae during infection. BMC Genomics 2022; 23:132 [View Article] [PubMed]
    [Google Scholar]
  112. Cohen AL, Jia S. Noncoding RNAs and the borders of heterochromatin. Wiley Interdiscip Rev RNA 2014; 5:835–847 [View Article] [PubMed]
    [Google Scholar]
  113. Torres MA, Jones JDG, Dangl JL. Reactive oxygen species signaling in response to pathogens. Plant Physiol 2006; 141:373–378 [View Article] [PubMed]
    [Google Scholar]
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