不同侵染时间点稻粒黑粉病菌的转录组分析

doi:10.11686/cyxb2019505

草业学报 ›› 2020, Vol. 29 ›› Issue (9): 190-202.DOI: 10.11686/cyxb2019505

不同侵染时间点稻粒黑粉病菌的转录组分析

舒新月^1,2,**, 江波^3,**, 马丽^1,2, 郑爱萍^1,2,*

1.四川农业大学水稻研究所,四川温江 611130;
2.四川农业大学西南作物基因资源与遗传改良教育部重点实验室,四川雅安 625014;
3.长江师范学院生命科学与技术学院,重庆 408100

收稿日期:2019-11-20 修回日期:2020-01-22 出版日期:2020-09-20 发布日期:2020-09-20
通讯作者: E-mail: apzh0602@gmail.com
作者简介:舒新月(1995-),女,四川雅安人,在读硕士。E-mail: 1374055882@qq.com;江波(1974-),男,重庆涪陵人,副教授,硕士。E-mail: 543038089@qq.com。**共同第一作者These authors contributed equally to this work.
基金资助:
重庆市自然科学基金(cstc2018jcyjAX0594)和涪陵区科委项目(FLKW, 2017ABB1029)资助

Transcriptome analysis of Tilletia horrida at different infection time points

SHU Xin-yue^1,2,**, JIANG Bo^3,**, MA Li^1,2, ZHENG Ai-ping^1,2,*

1. Rice Research Institute, Sichuan Agricultural University, Wenjiang 611130, China;
2. Key Laboratory of South-west Crop Gene Research : Genetic Improvement of Ministry of Education, Sichuan Agricultural University, Ya'an 625014, China;
3. College of Life Science and Technology, Yangtz Normal University, Chongqing 408100, China

Received:2019-11-20 Revised:2020-01-22 Online:2020-09-20 Published:2020-09-20

摘要/Abstract

摘要： 由土传真菌稻粒黑粉菌引起的稻粒黑粉病是水稻杂交制种田中的主要病害之一。为初步解析稻粒黑粉病菌侵染过程中与寄主的互作分子机制,本研究用稻粒黑粉病菌强毒力菌株JY-521侵染感病不育系材料“9311A”,于侵染8、12、24、48和72 h 5个时间点取菌样进行转录组测序分析。结果表明,与未侵染对照组相比,在侵染8 h时,差异表达基因(DEGs)数最多,有337个DEGs;其中上调的DEGs有120个,下调的DEGs有217个。337个DEGs 的KEGG富集分析表明,脂肪酸代谢和过氧化物酶体可能是稻粒黑粉病菌侵染过程中的关键代谢途径。此外,对编码碳水化合物酶、分泌蛋白和宿主植物—病原互作蛋白的DEGs在5个侵染时间点的表达模式进行解析,结果表明,一些显著上调表达的DEGs可能是稻粒黑粉病菌侵染的关键致病因子。该研究结果为解析稻粒黑粉病菌的致病分子机制,进一步防控该病害奠定了理论基础。

关键词: 水稻, 稻粒黑粉病, 转录组, 致病机制

Abstract: Rice kernel smut (RSB) caused by Tilletia horrida, is one of the most important rice diseases in hybrid rice growing areas worldwide. In order to classify the mechanisms of pathogenicity, transcriptome analysis of the T. horrid strain JY-521 was conducted at different times post inoculation (8, 12, 24, 48, and 72 h) early in the infection. The highest number of differentially expressed genes (DEGs) occurred at 8 h post inoculation. Based on kyoto encyclopedia of genes and genomes (KEGG) pathway analysis of the DEGs, autophagy processes and lipid degradation were key pathways for T. horrida pathogenicity. The expression patterns of carbohydrate-active enzyme genes, pathogen-host interaction genes, and secreted protein genes were also analyzed at different times during the infection, and some DEGs that may play an important role in pathogenic progress of T. horrid were found. In summary, this research provides a new foundation for future study of the infection mechanism and control of this important rice disease.

Key words: rice, kernel smut of rice, transcriptome, pathogenic mechanism

舒新月, 江波, 马丽, 郑爱萍. 不同侵染时间点稻粒黑粉病菌的转录组分析[J]. 草业学报, 2020, 29(9): 190-202.

SHU Xin-yue, JIANG Bo, MA Li, ZHENG Ai-ping. Transcriptome analysis of Tilletia horrida at different infection time points[J]. Acta Prataculturae Sinica, 2020, 29(9): 190-202.

参考文献

[1] Zhu D F, Zhang Y P, Chen H Z, et al. Innovation and practice of high-yield rice cultivation technology in China. Scientia Agricultura Sinica, 2015, 48(17): 3404-3414.
朱德峰, 张玉屏, 陈惠哲, 等. 中国水稻高产栽培技术创新与实践. 中国农业科学, 2015, 48(17): 3404-3414.
[2] Chen S J, Wang Y L, Zhang Z, et al. Factors influencing teliospore germination of Neovossia horrida and screening of sporulation medium of N. horrida. Acta Agriculturae Zhejiangensis, 2011, 23(3): 572-576.
陈胜军, 王艳丽, 张震, 等. 稻粒黑粉菌冬孢子萌发影响因素及其产孢培养基的筛选. 浙江农业学报, 2011, 23(3): 572-576.
[3] Tao J F, Zhou K D, Zhu J Q.The process of rice sterile line infected by Tilletia horrida. Southwest China Journal of Agricultural Sciences, 1998, 11(2): 68-72.
陶家凤, 周开达, 朱建清. 稻粒黑粉菌对水稻不育系的侵染过程. 西南农业学报, 1998, 11(2): 68-72.
[4] Chen Y, Yang X, Liang Z R, et al. A rapid and simple extraction method for plant pathogenic fungi. Scientific Reports, 2016, 6: 1-8.
[5] Wang A J, Yin D S, Fu R, et al. Evaluation of resistance to rice kernel smut in seventy-eight species of rice sterile lines. Acta Phytopathologica Sinica, 2018, 48(2): 207-212.
王爱军, 殷得所, 富蓉, 等. 78个水稻不育系对稻粒黑粉病的抗性评价. 植物病理学报, 2018, 48(2): 207-212.
[6] Wang Z, Gerstein M, Snyder M.RNA-Seq: A revolutionary tool for transcriptomics. Nature Reviews Genetics, 2010, 10(1): 57-63.
[7] Tang C, Zhang H Y, Wang T, et al. Differentiating transcriptomic patterns and functional analysis of Hansenula anomala during cultivation. Food and Fermentation Industries, 2019, 45(4): 1-6.
唐朝, 张寒玉, 王婷, 等. 基于转录组测序的异常汉逊酵母菌不同发酵时期差异表达基因功能分析. 食品与发酵工业, 2019, 45(4): 1-6.
[8] Thatcher L F, Williams A H, Gary G, et al. Transcriptome analysis of the fungal pathogen Fusarium oxysporum f. sp. medicaginis during colonisation of resistant and susceptible Medicago truncatula hosts identifies differential pathogenicity profiles and novel candidate effectors. BMC Genomics, 2016, 17(1): 860.
[9] Han Y Q, Han Y H, Zhang C L, et al. Transcriptomic analysis of early interaction between rice young spikelets and Ustilaginoidea virens. Acta Phytopathological Sinica, 2019, 49(3): 296-305.
韩彦卿, 韩渊怀, 张春来, 等. 水稻幼穗与Ustilaginoidea virens互作早期的转录组分析. 植物病理学报, 2019, 49(3): 296-305.
[10] Xiao J, Jin X, Jia X, et al. Transcriptome-based discovery of pathways and genes related to resistance against Fusarium head blight in wheat landrace Wangshuibai. BMC Genomics, 2013, 14(1): 1-19.
[11] Guo C G, Li S G, Wei Z M, et al. A simple and high quality of total RNA extraction method for Pholiota adiposa. Acta Agriculturae Boreali-Sinica, 2016, 31(S1): 75-79.
[12] Wang A J, Pan L X, Wang N, et al. The pathogenic mechanism of Tilletia horrida as revealed by comparative and functional genomics. Scientific Reports, 2018, 8(1): 15413.
[13] Benjamini Y, Hochberg Y.Controlling the false discovery rate: A practical and powerful approach to multiple testing. Journal of the Royal Statal Society: Series B (Methodological), 1995, 57(1): 289-300.
[14] Benjamini Y, Yektieli D.The control of the false discovery rate in multiple testing under dependency. The Annals of Statistics, 2001, 29(4): 1165-1188.
[15] Ernst J, Bar-Joseph Z.STEM: A tool for the analysis of short time series gene expression data. BMC Bioinformatics, 2006, 7(1): 1-11.
[16] Wang L K, Feng Z X, Wang X, et al. DEGseq: An R package for identifying differentially expressed genes from RNA-seq data. Bioinformatics, 2010, 26: 136-138.
[17] Mao X, Cai T, Olyarchuk J G, et al. Automated genome annotation and pathway identification using the KEGG orthology (KO) as a controlled vocabulary. Bioinformatics, 2005, 21(19): 3787-3793.
[18] Wang L G, Li L, Peng Y H.Advance of research on pathogenicity genes of phytopathogenic fungi. Journal of South China Normal University (Natural Science), 2003, (1): 135-142.
王利国, 李玲, 彭永宏. 植物真菌致病基因的研究进展. 华南师范大学学报(自然科学版), 2003, (1): 135-142.
[19] Cantarel B L, Coutinho P M, Rancurel C, et al. The Carbohydrate-active enzymes database (CAZy): An expert resource for glycogenomics. Nucleic Acids Research, 2009, 37(Database Issue): 233-238.
[20] Liu X H, Lu J P, Zhang L, et al. Involvement of a Magnaporthe grisea serine/threonine kinase gene, MgATG1, in appressorium turgor and pathogenesis. Eukaryotic Cell, 2007, 6(6): 997-1005.
[21] Liu L P, Yan Y Q, Huang J B, et al. A novel MFS transporter gene ChMfs1 is important for hyphal morphology, conidiation, and pathogenicity in colletotrichum higginsianum. Frontiers in Microbiology, 2017, 8: 1953.
[22] Skamnioti P, Gurr S J.Cutinase and hydrophobin interplay. Plant Signaling : Behavior, 2008, 3(4): 248-250.
[23] Zhou X G, Su Y, Li C Y, et al. Pathogenicity analysis of secretory protein of the rice blast fungus under nitrogen starvation. Acta Phytopathologica Sinica, 2009, 39(5): 491-500.
周晓罡, 苏源, 李成云, 等. 氮胁迫条件下稻瘟病菌分泌蛋白致病性分析. 植物病理学报, 2009, 39(5): 491-500.
[24] Leuthner B, Aichinger C, Oehmen E, et al. A H₂O₂-producing glyoxal oxidase is required for filamentous growth and pathogenicity in Ustilago maydis. Molecular Genetics and Genomics, 2005, 272(6): 639-650.
[25] Peng C, Chen H L, Wang J W, et al. Cloning and expression analysis of a P-ATPase gene MoCTA3 in rice blast pathogen Magnaporthe oryzae. Jiangsu Journal of Agricultural Sciences, 2012, 28(3): 492-496.
彭陈, 陈洪亮, 王俊伟, 等. 稻瘟菌P-ATPase基因MoCTA3的克隆及表达分析. 江苏农业学报, 2012, 28(3): 492-496.
[26] Lin H C.Functional analysis of chitinase gene Pst_23943 in Puccinia striiformis f. sp. tritici. Xianyang: Northwest A : F University, 2019.
林颢丞. 小麦条锈菌几丁质酶基因Pst_23943的功能分析. 咸阳: 西北农林科技大学, 2019.
[27] Wang S, Chen G J, Zhang H Q, et al. Carbohydrate-active enzyme (CAZy) database and its new prospect. Chinese Journal of Bioprocess Engineering, 2014, 12(1): 102-108.
王帅, 陈冠军, 张怀强, 等. 碳水化合物活性酶数据库(CAZy)及其研究趋势. 生物加工过程, 2014, 12(1): 102-108.
[28] Martin-Udiroz M.Role of chitin synthase genes in Fusarium oxysporum. Microbiology, 2004, 150(10): 3175-3187.
[29] Kubo Y.Function of peroxisomes in plant-pathogen interactions. Sub-cellular Biochemistry, 2013, 69: 329-345.
[30] Kimura A.Peroxisomal metabolic function is required for appressorium-mediated plant infection by Colletotrichum lagenarium. Plant Cell, 2001, 13(8): 1945-1957.
[31] Ramos-Pamplona M, Naqvi N I.Host invasion during rice-blast disease requires carnitine-dependent transport of peroxisomal acetyl-CoA. Molecular Microbiology, 2006, 61(1): 61-75.
[32] Zheng A P, Lin R M, Zhang D H, et al. The evolution and pathogenic mechanisms of the rice sheath blight pathogen. Nature Communications, 2013, 4: 1424.
[33] Liu Y F, Chen Z Y, Yu W Y, et al. Primary study on effect of secreted proteins of Magnaporthe oryzae during infection. Chinese Journal of Rice Science, 2011, 25(4): 452-454.
刘永锋, 陈志谊, 俞文渊, 等. 稻瘟病菌分泌蛋白质在致病过程中的作用初探. 中国水稻科学, 2011, 25(4): 452-454.
[34] Ren W C, Zhang Z H, Shao W Y, et al. The autophagy-related gene BcATG1 is involved in fungal development and pathogenesis in Botrytis cinerea. Molecular Plant Pathology, 2017, 18(2): 238-248.
[35] Todd R B, Lockington R A, Kelly J M.The Aspergillus nidulans creC gene involved in carbon catabolite repression encodes a WD40 repeat protein. MGG-Molecular and General Genetics, 2000, 263(4): 561-570.
[36] Matar K A O, Chen X F, Chen D J, et al. WD40-repeat protein MoCreC is essential for carbon repression and is involved in conidiation, growth and pathogenicity of Magnaporthe oryzae. Current Genetics, 2016, 63(4): 685-696.

不同侵染时间点稻粒黑粉病菌的转录组分析

Transcriptome analysis of Tilletia horrida at different infection time points

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