請用此 Handle URI 來引用此文件：
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/77259完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 鄭石通 | zh_TW |
| dc.contributor.author | 謝誌紘 | zh_TW |
| dc.contributor.author | Chih-Hung Hsieh | en |
| dc.date.accessioned | 2021-07-10T21:53:05Z | - |
| dc.date.available | 2024-08-15 | - |
| dc.date.copyright | 2019-08-19 | - |
| dc.date.issued | 2019 | - |
| dc.date.submitted | 2002-01-01 | - |
| dc.identifier.citation | 吳明璁 (2015.) 水稻過氧化氫調節之微小核糖核酸。國立台灣大學植物科學所博士論文。
吳宇凡 (2015.) 甘藷中受一氧化碳調控之嶄新miRNA-tag202參與MAPK訊息傳遞路徑。國立台灣大學植物科學碩士論文。 謝若微 (2017.) 新穎miRNA-tag292在甘藷傷害反應之探討。國立台灣大學植物科學碩士論文。 黃俊瑋 (2019.) 水稻過氧化氫相關之微小核糖核酸miR535研究。國立台灣大學植物科學所博士論文。 Addo-Quaye, C., Miller, W., and Axtell, M.J. (2009). CleaveLand: a pipeline for using degradome data to find cleaved small RNA targets. Bioinformatics 25: 130-131. Alves, C.S., Vicentini, R., Duarte, G.T., Pinoti, V.F., Vincentz, M., and Nogueira, F.T. (2017). Genome-wide identification and characterization of tRNA-derived RNA fragments in land plants. Plant Mol. Biol. 93: 35-48. Ambros, V. (2004). The functions of animal microRNAs. Nature 431: 350-355. Andrews, S. (2014). FastQC A Quality Control tool for High Throughput Sequence Data http://www.bioinformatics.babraham.ac.uk/projects/fastqc/. Balatti, V., Pekarsky, Y., and Croce, C.M. (2017). Role of the tRNA-Derived Small RNAs in Cancer: New Potential Biomarkers and Target for Therapy. In Adv Cancer Res, pp. 173-187. Berruezo, F., de Souza, F.S.J., Picca, P.I., Nemirovsky, S.I., Martínez Tosar, L., Rivero, M., Mentaberry, A.N., and Zelada, A.M. (2017). Sequencing of small RNAs of the fern Pleopeltis minima (Polypodiaceae) offers insight into the evolution of the microrna repertoire in land plants. PLoS One 12: e0177573. Bienert, G.P., Schjoerring, J.K., and Jahn, T.P. (2006). Membrane transport of hydrogen peroxide. Biochim. Biophys. Acta-Biomembr. 1758: 994-1003. Bolger, A.M., Lohse, M., and Usadel, B. (2014). Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30: 2114-2120. Bologna, N.G., Schapire, A.L., and Palatnik, J.F. (2012). Processing of plant microRNA precursors. Brief. Funct. Genomics 12: 37-45. Chan, P.P., and Lowe, T.M. (2016). GtRNAdb 2.0: an expanded database of transfer RNA genes identified in complete and draft genomes. Nucleic Acids Res. 44: D184-189. Cristodero, M., and Polacek, N.J.N.-c.R.I. (2017). The multifaceted regulatory potential of tRNA-derived fragments. Non-coding RNA Investigation 1. Dai, H.-P., Jia, G., and Shan, C. (2015). Jasmonic acid-induced hydrogen peroxide activates MEK1/2 in upregulating the redox states of ascorbate and glutathione in wheat leaves. Acta Physiol. Plant. 37. Dai, X., and Zhao, P.X. (2011). psRNATarget: a plant small RNA target analysis server. Nucleic Acids Res. 39: W155-159. Dai, X., Zhuang, Z., and Zhao, P.X. (2018). psRNATarget: a plant small RNA target analysis server (2017 release). Nucleic Acids Res. 46: W49-W54. Das, K., and Roychoudhury, A. (2014). Reactive oxygen species (ROS) and response of antioxidants as ROS-scavengers during environmental stress in plants. Front. Environ. Sci. 2. Dhahbi, J.M. (2015). 5' tRNA Halves: The Next Generation of Immune Signaling Molecules. Front. Immunol. 6: 74. Garnier, L., Simon-Plas, F., Thuleau, P., Agnel, J.-P., Blein, J.-P., Ranjeva, R., and Montillet, J.-L. (2006). Cadmium affects tobacco cells by a series of three waves of reactive oxygen species that contribute to cytotoxicity. Plant Cell Environ. 29: 1956-1969. Ge, Y., Han, J., Zhou, G., Xu, Y., Ding, Y., Shi, M., Guo, C., and Wu, G. (2018). Silencing of miR156 confers enhanced resistance to brown planthopper in rice. Planta 248: 813-826. Gechev, T.S., and Hille, J. (2005). Hydrogen peroxide as a signal controlling plant programmed cell death. J. Cell Biol. 168: 17-20. Guo, Q., Yoshida, Y., Major, I.T., Wang, K., Sugimoto, K., Kapali, G., Havko, N.E., Benning, C., and Howe, G.A. (2018). JAZ repressors of metabolic defense promote growth and reproductive fitness in <em>Arabidopsis</em>. Proc. Natl. Acad. Sci. U. S. A. 115: E10768. Hakata, M., Kuroda, M., Ohsumi, A., Hirose, T., Nakamura, H., Muramatsu, M., Ichikawa, H., and Yamakawa, H. (2012). Overexpression of a Rice TIFY Gene Increases Grain Size through Enhanced Accumulation of Carbohydrates in the Stem. Biosci. Biotechnol. Biochem. 76. Hakata, M., Muramatsu, M., Nakamura, H., Hara, N., Kishimoto, M., Iida-Okada, K., Kajikawa, M., Imai-Toki, N., Toki, S., Nagamura, Y., Yamakawa, H., and Ichikawa, H. (2017). Overexpression of TIFY genes promotes plant growth in rice through jasmonate signaling. Biosci. Biotechnol. Biochem. 81: 906-913. Hsieh, L.-C., Lin, S.-I., Shih, A.C.-C., Chen, J.-W., Lin, W.-Y., Tseng, C.-Y., Li, W.-H., and Chiou, T.-J. (2009). Uncovering Small RNA-Mediated Responses to Phosphate Deficiency in Arabidopsis by Deep Sequencing. Plant Physiol. 151: 2120-2132. Hung, S.-H., Yu, C.-W., and Ho Lin, C. (2005). Hydrogen peroxide functions as a stress signal in plants. Botanical Bulletin of Academia Sinica 46. Hunt, S.E., McLaren, W., Gil, L., Thormann, A., Schuilenburg, H., Sheppard, D., Parton, A., Armean, I.M., Trevanion, S.J., Flicek, P., and Cunningham, F. (2018). Ensembl variation resources. Database 2018. Ishimaru, T., Horigane, A.K., Ida, M., Iwasawa, N., San-oh, Y.A., Nakazono, M., Nishizawa, N.K., Masumura, T., Kondo, M., and Yoshida, M. (2009). Formation of grain chalkiness and changes in water distribution in developing rice caryopses grown under high-temperature stress. J. Cereal Sci. 50: 166-174. Izawa, T., and Shimamoto, K. (1996). Becoming a model plant: The importance of rice to plant science. Trends in Plant Sci. 1: 95-99. Jackson, S.A. (2016). Rice: The First Crop Genome. Rice 9: 14. Jiao, Y., Wang, Y., Xue, D., Wang, J., Yan, M., Liu, G., Dong, G., Zeng, D., Lu, Z., Zhu, X., Qian, Q., and Li, J. (2010). Regulation of OsSPL14 by OsmiR156 defines ideal plant architecture in rice. Nature Genet. 42: 541. Kalvari, I., Argasinska, J., Quinones-Olvera, N., Nawrocki, E.P., Rivas, E., Eddy, S.R., Bateman, A., Finn, R.D., and Petrov, A.I. (2017). Rfam 13.0: shifting to a genome-centric resource for non-coding RNA families. Nucleic Acids Res. 46: D335-D342. Kao, C.-H. (2014). Role of hydrogen peroxide in rice plants. Crop, Environ. Bioinform. 11: 1-10. Katsir, L., Schilmiller, A.L., Staswick, P.E., He, S.Y., and Howe, G.A. (2008). COI1 is a critical component of a receptor for jasmonate and the bacterial virulence factor coronatine. Proc. Natl. Acad. Sci. U. S. A. 105: 7100-7105. Kolde, R. (2019). pheatmap: Pretty Heatmaps. R package version 1.0.12. https://CRAN.R-project.org/package=pheatmap. Kozomara, A., Birgaoanu, M., and Griffiths-Jones, S. (2019). miRBase: from microRNA sequences to function. Nucleic Acids Res. 47: D155-D162. Krishnan, P., Ramakrishnan, B., Reddy, K.R., and Reddy, V.R. (2011). Chapter three - High-Temperature Effects on Rice Growth, Yield, and Grain Quality. In Advances in Agronomy, D.L. Sparks, ed (Academic Press), pp. 87-206. Kuo, Y.-W., Lin, J.-S., Li, Y.-C., Jhu, M.-Y., King, Y.-C., and Jeng, S.-T. (2018). MicroR408 regulates defense response upon wounding in sweet potato. J. Exp. Bot. 70: 469-483. Langmead, B., Trapnell, C., Pop, M., and Salzberg, S.L. (2009). Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol. 10: R25. Li, S., Xu, Z., and Sheng, J. (2018). tRNA-Derived Small RNA: A Novel Regulatory Small Non-Coding RNA. Genes 9: 246. Li, X. (2011). Infiltration of Nicotiana benthamiana Protocol for Transient Expression via Agrobacterium. Bio-protocol 1: e95. Lin, J.-S., Lin, C.-C., Lin, H.-H., Chen, Y.-C., and Jeng, S.-T. (2012). MicroR828 regulates lignin and H2O2 accumulation in sweet potato on wounding. New Phytol. 196: 427-440. Major, I.T., Yoshida, Y., Campos, M.L., Kapali, G., Xin, X.-F., Sugimoto, K., de Oliveira Ferreira, D., He, S.Y., and Howe, G.A. (2017). Regulation of growth–defense balance by the JASMONATE ZIM-DOMAIN (JAZ)-MYC transcriptional module. New Phytol. 215: 1533-1547. Mao, Y.-B., Liu, Y.-Q., Chen, D.-Y., Chen, F.-Y., Fang, X., Hong, G.-J., Wang, L.-J., Wang, J.-W., and Chen, X.-Y. (2017). Jasmonate response decay and defense metabolite accumulation contributes to age-regulated dynamics of plant insect resistance. Nat. Commun. 8: 13925. Martinez, G. (2018). tRNA-derived small RNAs: New players in genome protection against retrotransposons. RNA Biol. 15: 170-175. Martinez, G., Choudury, S.G., and Slotkin, R.K. (2017). tRNA-derived small RNAs target transposable element transcripts. Nucleic Acids Res. 45: 5142-5152. Meltzer, S.D.a.P. (2007). GEOquery: a bridge between the Gene Expression Omnibus (GEO) and BioConductor. Bioinformatics 14: 1846--1847. Millar, A.A., and Waterhouse, P.M. (2005). Plant and animal microRNAs: similarities and differences. Funct. Integr. Genomics 5: 129-135. Mittal, D., Madhyastha, D.A., and Grover, A. (2012). Genome-wide transcriptional profiles during temperature and oxidative stress reveal coordinated expression patterns and overlapping regulons in rice. PLoS One 7: e40899. Mittler, R. (2017). ROS Are Good. Trends in Plant Sci. 22: 11-19. Mohammed, A.R., and Tarpley, L. (2011). High night temperature and plant growth regulator effects on spikelet sterility, grain characteristics and yield of rice (Oryza sativa L.) plants. Can. J. Plant Sci. 91: 283-291. Morea, E., Silva, E., Silva, G., Valente, G., Barrera, C., Vincentz, M., and Nogueira, F. (2016). Functional and evolutionary analyses of the miR156 and miR529 families in land plants. BMC Plant Biol. 16. Nobuta, K., Lu, C., Shrivastava, R., Pillay, M., De Paoli, E., Accerbi, M., Arteaga-Vazquez, M., Sidorenko, L., Jeong, D.-H., Yen, Y., Green, P.J., Chandler, V.L., and Meyers, B.C. (2008). Distinct size distribution of endogenous siRNAs in maize: Evidence from deep sequencing in the <em>mop1-1</em> mutant. Proc. Natl. Acad. Sci. U. S. A. 105: 14958. Oliveros, J.C. (2007). VENNY. An interactive tool for comparing lists with Venn Diagrams. http://bioinfogp.cnb.csic.es/tools/venny/index.html. Ouyang, S., Zhu, W., Hamilton, J., Lin, H., Campbell, M., Childs, K., Thibaud-Nissen, F., Malek, R.L., Lee, Y., Zheng, L., Orvis, J., Haas, B., Wortman, J., and Buell, C.R. (2007). The TIGR Rice Genome Annotation Resource: improvements and new features. Nucleic Acids Res. 35: D883-D887. Pauwels, L., and Goossens, A. (2011). The JAZ Proteins: A Crucial Interface in the Jasmonate Signaling Cascade. Plant Cell 23: 3089-3100. Prasad, T.K. (1996). Mechanisms of chilling-induced oxidative stress injury and tolerance in developing maize seedlings: changes in antioxidant system, oxidation of proteins and lipids, and protease activities. Plant J. 10: 1017-1026. Preston, J.C., and Hileman, L.C. (2013). Functional Evolution in the Plant SQUAMOSA-PROMOTER BINDING PROTEIN-LIKE (SPL) Gene Family. Front. Plant Sci. 4: 80. Ritchie, M.E., Phipson, B., Wu, D., Hu, Y., Law, C.W., Shi, W., and Smyth, G.K. (2015). limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 43: e47. Rogers, K., and Chen, X. (2013). Biogenesis, turnover, and mode of action of plant microRNAs. Plant Cell 25: 2383-2399. Ryan, C.A. (2000). The systemin signaling pathway: differential activation of plant defensive genes. Biochim. Biophys. Acta-Protein Struct. Molec. Enzym. 1477: 112-121. S.D, K., Katsantonis, D., D.A, N., and Lupotto, E. (2009). The effect of blast disease on rice growth, yield and quality in the field. Turk. J. Agric. For. 33: 487-494. Sasaki, T., and International Rice Genome Sequencing, P. (2005). The map-based sequence of the rice genome. Nature 436: 793-800. Schorn, A.J., Gutbrod, M.J., LeBlanc, C., and Martienssen, R. (2017). LTR-Retrotransposon Control by tRNA-Derived Small RNAs. Cell 170: 61-71 e11. Shao, Y., Zhou, H.Z., Wu, Y., Zhang, H., Lin, J., Jiang, X., He, Q., Zhu, J., Li, Y., Yu, H., and Mao, C. (2019). OsSPL3, an SBP-Domain Protein, Regulates Crown Root Development in Rice. Plant Cell 31: 1257-1275. Sharma, M., Gupta, S., Deeba, F., and Pandey, V. (2017). Effects of Reactive Oxygen Species on Crop Productivity: an Overview, pp. 117-134. Shi, J., Ko, E.A., Sanders, K.M., Chen, Q., and Zhou, T. (2018). SPORTS1.0: A Tool for Annotating and Profiling Non-coding RNAs Optimized for rRNA- and tRNA-derived Small RNAs. Genom. Proteomics Bioinformatics 16: 144-151. Spriggs, K.A., Bushell, M., and Willis, A.E. (2010). Translational regulation of gene expression during conditions of cell stress. Mol. Cell 40: 228-237. Tang, J., and Chu, C. (2017). MicroRNAs in crop improvement: fine-tuners for complex traits. Nat. Plants 3: 17077. United Nations, D.o.E.a.S.A., Population Division. (2017). World Population Prospects: The 2017 Revision, Data Booklet. : ST/ESA/SER.A/401. Valin, H., Sands, R.D., van der Mensbrugghe, D., Nelson, G.C., Ahammad, H., Blanc, E., Bodirsky, B., Fujimori, S., Hasegawa, T., Havlik, P., Heyhoe, E., Kyle, P., Mason-D'Croz, D., Paltsev, S., Rolinski, S., Tabeau, A., van Meijl, H., von Lampe, M., and Willenbockel, D. (2014). The future of food demand: understanding differences in global economic models. Agricultural Economics 45: 51-67. Varkonyi-Gasic, E., Wu, R., Wood, M., Walton, E.F., and Hellens, R.P. (2007). Protocol: a highly sensitive RT-PCR method for detection and quantification of microRNAs. Plant Methods 3: 12. Vlk, D., and Repková, J. (2017). Application of next-generation sequencing in plant breeding. Czech J. Genet. Plant Breed. 53. Wang, J., Wu, D., Wang, Y., and Xie, D. (2019). Jasmonate action in plant defense against insects. J. Exp. Bot. Wang, S., Wu, K., Yuan, Q., Liu, X., Liu, Z., Lin, X., Zeng, R., Zhu, H., Dong, G., Qian, Q., Zhang, G., and Fu, X. (2012). Control of grain size, shape and quality by OsSPL16 in rice. Nature Genetics 44: 950. Wasternack, C., and Hause, B. (2013). Jasmonates: biosynthesis, perception, signal transduction and action in plant stress response, growth and development. An update to the 2007 review in Annals of Botany. Ann. Bot. 111: 1021-1058. Wojtaszek, P. (1997). Oxidative burst: an early plant response to pathogen infection. Biochemical j. 322 ( Pt 3): 681-692. Wu, G., Park, M.Y., Conway, S.R., Wang, J.-W., Weigel, D., and Poethig, R.S. (2009a). The Sequential Action of miR156 and miR172 Regulates Developmental Timing in Arabidopsis. Cell 138: 750-759. Wu, H.-P., Wei, F.-J., Wu, C.-C., Lo, S.-F., Chen, L.-J., Fan, M.-J., Chen, S., Wen, I.-C., Yu, S.-M., Ho, T.-H.D., Lai, M.-H., and Hsing, Y.-i.C. (2017). Large-scale phenomics analysis of a T-DNA tagged mutant population. GigaScience 6. Wu, L., Zhang, Q., Zhou, H., Ni, F., Wu, X., and Qi, Y. (2009b). Rice MicroRNA effector complexes and targets. Plant Cell 21: 3421-3435. Wu, L., Zhou, H., Zhang, Q., Zhang, J., Ni, F., Liu, C., and Qi, Y. (2010). DNA Methylation Mediated by a MicroRNA Pathway. Molecular Cell 38: 465-475. Xie, K., Wu, C., and Xiong, L. (2006). Genomic organization, differential expression, and interaction of SQUAMOSA promoter-binding-like transcription factors and microRNA156 in rice. Plant Physiol. 142: 280-293. Xie, K., Shen, J., Hou, X., Yao, J., Li, X., Xiao, J., and Xiong, L. (2012a). Gradual increase of miR156 regulates temporal expression changes of numerous genes during leaf development in rice. Plant Physiol. 158: 1382-1394. Xie, K., Shen, J., Hou, X., Yao, J., Li, X., Xiao, J., and Xiong, L. (2012b). Gradual increase of miR156 regulates temporal expression changes of numerous genes during leaf development in rice. Plant Physiol. 158: 1382-1394. Yang, L.-h., Wang, S.-l., Tang, L.-l., Liu, B., Ye, W.-l., Wang, L.-l., Wang, Z.-y., Zhou, M.-t., and Chen, B.-c. (2015). Universal Stem-Loop Primer Method for Screening and Quantification of MicroRNA. PLoS One 9: e115293. Ye, H., Du, H., Tang, N., Li, X., and Xiong, L. (2009). Identification and expression profiling analysis of TIFY family genes involved in stress and phytohormone responses in rice. Plant Mol. Biol. 71: 291-305. Yoshida, S. (1976). Routine procedures for growing rice plants in culture solution. Laboratory Manual for Physiological Studies of Rice: 61-66. Zhang, H., Zhang, J., Yan, J., Gou, F., Mao, Y., Tang, G., Botella, J.R., and Zhu, J.-K. (2017). Short tandem target mimic rice lines uncover functions of miRNAs in regulating important agronomic traits. Proc. Natl. Acad. Sci. U. S. A. 114: 5277-5282. Zhao, Y.F., Peng, T., Sun, H.Z., Teotia, S., Wen, H.L., Du, Y.X., Zhang, J., Li, J.Z., Tang, G.L., Xue, H.W., and Zhao, Q.Z. (2019). miR1432-OsACOT (Acyl-CoA thioesterase) module determines grain yield via enhancing grain filling rate in rice. Plant Biotechnol. J. 17: 712-723. Zheng, Y., Li, Y.F., Sunkar, R., and Zhang, W. (2012). SeqTar: an effective method for identifying microRNA guided cleavage sites from degradome of polyadenylated transcripts in plants. Nucleic Acids Res. 40: e28. | - |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/77259 | - |
| dc.description.abstract | 在植物體內，過氧化氫為一種強的氧化劑，其通常是受到生物性與非生物性逆境的誘導而產生。過去的研究也認為過氧化氫可以作為二次的訊息傳遞物質以調控植物的生長與逆境的防禦反應。小分子核醣核酸是一種長度約20到24個核苷酸大小的小片段非編碼核糖核酸，利用後轉錄調控機制影響植物的生理功能。然而，我們對於受到過氧化氫調控的小分子核醣核酸與其調控何種下游目標基因仍未明朗，因此本研究主要使用生物資訊方法闡明與探索過氧化氫可能調控的分子機制。本研究使用小RNA定序法與已發表之AGO1蛋白免疫共沉澱定序法所產生的序列資料分析受過氧化氫調控的小分子核醣核酸。並且使用psRNAtarget軟體與已發表的微陣列資料預測受小分子核醣核酸調控的目標基因，從中我們成功預測出377個小分子核醣核酸與其目標基因的調控路徑。為了更進一步確認小分子核醣核酸與其預測之目標基因是否存在真實的調控關係，我們開發了一個嶄新的分析軟體Pycleave對於水稻降解組進行分析，此軟體整合了psRNATarget 及 CleaveLand 。我們確認了64個mRNA在過氧化氫處理之下，可能受到小分子核醣核酸所調控。其中我們發現miR156受到過氧化氫所影響，而其目標基因為一個參與茉莉酸訊息調控的重要基因OsTIFY11b。此調控路徑我們使用即時定量聚合酶鏈鎖反應、農桿菌滲入短暫共表現法、已發表的miR156大量表現微陣列資料、轉基因植物法進行驗證。我們的結果闡明了一個嶄新的小分子核醣核酸與其目標基因的調控網絡。另一方面，我們亦對於小RNA定序法發現的轉運核糖核酸衍生之小核醣核酸進行分析。我們的結果顯示了由轉運核糖核酸衍生之小核醣核酸可能受到氧化逆境所累積。此外，轉運核糖核酸衍生之小核醣核酸可能不是RNA降解的副產物。總體而言，過氧化氫廣泛的調控小核醣核酸。其分子機制值得進一步探討。 | zh_TW |
| dc.description.abstract | Hydrogen peroxide (H2O2) is a strong oxidizer, whose production is commonly enhanced by abiotic and biotic stresses in plants. It has also been considered as a signal messenger involved in regulating growth and defense in plants. MicroRNAs (miRNAs) are 20-24 nucleotides non-coding RNAs playing crucial roles in biotic and abiotic responses by post-transcriptional regulation. However, the underlying mechanism for the regulation of H2O2-related miRNA and its targets remains unclear. In this study, differentially expressed miRNAs via small RNA sequencings and AGO1 immunoprecipitation-sequencings were discovered. Program psRNAtarget was used to predict miRNA target and the predicted targets were also analyzed by the published cDNA microarray data from rice treated with H2O2. Herein, 377 predicted miRNA-targets were discovered. In order to gain insight into the cleavage site of miRNA-target, a new program Pycleave was developed to analyze degradome data. The combination of psRNATarget and CleaveLand indicated that 64 mRNAs may be regulated by miRNAs. Among them, miR156 was regulated by H2O2. the predicted target gene of miR156 was OsTIFY11b, which is a member of JAZ protein, and may be involved in jasmonic acid signal transduction. This miRNA-target module was validated by real-time RT-PCR, agroinfiltration, microarray data from rice overexpressing miR156, and transgenic approaches. Our results may reveal a new miRNA and regulatory framework involved in H2O2 signal transduction. On the other hand, tRNA-derived small RNAs (tsRNAs) were also investigated in this study. Our results suggested tsRNAs were accumulated during oxidative stress. Moreover, tsRNAs might not be the byproducts from RNA degradation. Overall, H2O2 controlled small RNAs widely. The underlying molecular mechanisms for small RNAs regulated by H2O2 is worth for further study. | en |
| dc.description.provenance | Made available in DSpace on 2021-07-10T21:53:05Z (GMT). No. of bitstreams: 1 ntu-108-R06b42001-1.pdf: 3907063 bytes, checksum: 0904f3fc7f7408a34dfd7e02a9d2bcdd (MD5) Previous issue date: 2019 | en |
| dc.description.tableofcontents | 誌謝 i
中文摘要 ii Abstract iii Contents v List of Tables and Figures vii Appendixes ix Introduction 1 1. Rice is a major food crop in the world. 1 2. Role of Hydrogen peroxide in plants 3 3. Biosynthesis and function of miRNAs 5 4. Function of miR156 in plant 7 5. Jasmonic acid in plant defense and growth 9 6. tRNA-derived small RNA is a new star in small RNA research 11 7. Research motivations 13 Materials and Methods 14 Bioinformatic analysis of NGS data 14 1. Small RNA sequencing data pre-processing 14 2. Small RNA annotation and visualization 15 3. miRNA target prediction, microarray analysis and visualization 16 4. Degradome data analysis 17 Experimental methods 18 A. Detecting the expression levels of miRNAs and mRNAs in response to oxidative stress. 18 1. Plant materials and treatments. 18 1.1 Rice (Oryza sativa) 18 1.2 Tobacco (Nicotiana benthamiana) 19 2. RNA extraction 19 3. DNase treatment 20 4. Reverse transcription (RT) and stem-loop RT 20 5. Polymerase chain reaction (PCR) 22 6. DNA Gel electrophoresis 23 7. Quantitative real-time PCR (qPCR) 23 B. Validating the interaction between miRNA and its target. 25 1. Gel elution 25 2. DNA ligation 26 3. E.coli transformation 26 4. Plasmid DNA mini extraction 27 5. Restriction enzyme digestion 28 6. DNA sequencing 29 7. Agrobacterium transformation 29 8. Agrobacterium-mediated transient co-expression assay in tobacco 30 Results 32 1. Processing the raw data from small RNA sequencing 32 2. Small RNA annotation by SPORT1.0 and normalization 33 3. Identification of functional miRNAs 35 4. Predicting miRNA-targets 37 5. Pycleave, a new program for degradome analysis 39 6. Validating miRNA in rice responding to oxidative stress 41 7. Functional study of miR156-OsTIFY11b module 42 8. tRNA-derived small RNA 45 Discussion 47 1. Bioinformatic analyses of microRNAs responding to oxidative stress 47 2. New software for degradome sequencing analysis 49 3. Role of miR156 and its novel target: OsTIFY11b responding to oxidative stress 51 4. Interaction between miR156 and OsTIFY11b 53 5. New tRNA-derived small RNA 55 6. Conclusion 57 References 100 | - |
| dc.language.iso | en | - |
| dc.subject | 水稻 | zh_TW |
| dc.subject | 過氧化氫 | zh_TW |
| dc.subject | 小核醣核酸 | zh_TW |
| dc.subject | 次世代定序 | zh_TW |
| dc.subject | miR156 | zh_TW |
| dc.subject | OsTIFY11b | zh_TW |
| dc.subject | 轉運核糖核酸衍生之小核醣核酸 | zh_TW |
| dc.subject | Next generation sequencing | en |
| dc.subject | small RNAs | en |
| dc.subject | tRNA-derived small RNAs | en |
| dc.subject | OsTIFY11b | en |
| dc.subject | miR156 | en |
| dc.subject | Rice | en |
| dc.subject | Hydrogen peroxide | en |
| dc.title | 利用生物資訊方法探討在水稻中受過氧化氫調控的小核醣核酸 | zh_TW |
| dc.title | Exploring small RNAs in rice responding to hydrogen peroxide using bioinformatic analysis | en |
| dc.type | Thesis | - |
| dc.date.schoolyear | 107-2 | - |
| dc.description.degree | 碩士 | - |
| dc.contributor.oralexamcommittee | 邱子珍;黃浩仁;林振祥 | zh_TW |
| dc.contributor.oralexamcommittee | ;; | en |
| dc.subject.keyword | 水稻,過氧化氫,小核醣核酸,次世代定序,miR156,OsTIFY11b,轉運核糖核酸衍生之小核醣核酸, | zh_TW |
| dc.subject.keyword | Rice,Hydrogen peroxide,small RNAs,Next generation sequencing,miR156,OsTIFY11b,tRNA-derived small RNAs, | en |
| dc.relation.page | 106 | - |
| dc.identifier.doi | 10.6342/NTU201902718 | - |
| dc.rights.note | 未授權 | - |
| dc.date.accepted | 2019-08-13 | - |
| dc.contributor.author-college | 生命科學院 | - |
| dc.contributor.author-dept | 植物科學研究所 | - |
| 顯示於系所單位： | 植物科學研究所 | |
文件中的檔案：
| 檔案 | 大小 | 格式 | |
|---|---|---|---|
| ntu-107-2.pdf 未授權公開取用 | 3.82 MB | Adobe PDF |
系統中的文件，除了特別指名其著作權條款之外，均受到著作權保護，並且保留所有的權利。