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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 鄭石通(Shih-Tong Jeng) | |
dc.contributor.author | Min-Yao Jhu | en |
dc.contributor.author | 朱敏瑤 | zh_TW |
dc.date.accessioned | 2021-06-08T01:19:08Z | - |
dc.date.copyright | 2014-09-04 | |
dc.date.issued | 2014 | |
dc.date.submitted | 2014-08-11 | |
dc.identifier.citation | Bartel, D.P. (2004). MicroRNAs: genomics, biogenesis, mechanism, and function. Cell 116, 281-297.
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dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/18682 | - |
dc.description.abstract | 植物的microRNA (miRNA)為由20至24個核苷酸所組成的一段小分子非編碼RNA。近年來許多研究發現,miRNA不論是在植物的生長發育方面或是面對生物和非生物逆境的反應方面,都扮演著重要的基因表現調控角色。在植物遭受的各種逆境中,傷害逆境對植物的影響尤為嚴重,甚至會妨害植物的生長與發育並造成作物產量損失。然而,現今研究對於植物在遭受傷害逆境下所產生的miRNA調控反應所知仍然十分有限,尤其在甘藷這項重要的糧食作物上,保守miRNA與傷害反應miRNA相關的研究非常缺乏。在本篇研究中,我們使用次世代高通量小分子RNA定序的方式,結合生物資訊分析,經過篩選及比對miRNA資料庫(miRBase 16版)後,找出83個在甘藷中與其他植物物種序列保守的miRNA,其中有15個miRNA在傷害後表現受到誘導而上升;以及有24個miRNA在傷害後表現受到抑制而下降。根據比對之預測結果,針對傷害誘導的其中兩個miRNA:miR2111和miR894更進一步地研究。進行其作用目標基因搜尋、釣取與功能預測,miR2111的目標基因為PUT-169a- 10214 和 TC6582,其中TC6582與其他植物物種的retinoblastoma -associated protein胺基酸序列相似度高,暗示其功能可能與調控細胞增生已修復傷口等功能相關。而miR894的目標基因為TC8064/ PUT-169a-2721,此基因具有calmodulin binding保守區域,屬於calmodulin binding protein家族且可能參與在植物傷害反應的訊息路徑中。更進一步,欲了解miR2111和miR894的上游訊息分子傳遞路徑,我們也偵測在處理各種訊息、賀爾蒙藥劑或抑制劑之後miR2111和miR894的表現量。實驗結果顯示茉莉酸甲酯(methyl jasmonate, MeJA)、水楊酸(salicylic acid, SA)、過氧化氫(H2O2)、乙烯、鈣離子皆可能參與在上游傷害訊息活化miR2111的表現。另一方面,只有MeJA、SA、H2O2可能部分參與在上游傷害訊息活化miR894,換言之,miR894的表現可能需要多種傷害訊息同時誘導。而隨著次世代定序的科技日新月異,被發現的miRNA數量持續增加。近日miRBase 第21版更新發表,其中更包含有8496個 miRNA分布在73種植物之中。為取得最新且更完整的保守miRNA檔案,我們發展了新的分析平台(the Mir Pipeline),並結合新的分析策略與miRBase 第21版以比對保守miRNA。從小分子RNA定序的資料中,總共找到159個保守的miRNA,其中27個為傷害誘導miRNA,49個為傷害抑制miRNA。此外,我們進行次世代高通量RNA定序,以建立甘藷的轉錄組資料庫。為了能更準確的預測miRNA的作用目標基因與mimic,我們亦根據新的條件發展預測程式(the Mir Score),並以此程式從甘藷的轉錄組片段預測所有保守miRNA的目標基因。其中也包含得到miR2111高度可信的5個目標基因以及miR894高度可信的7個目標基因。本實驗的研究成果開拓現今仍充滿未知的甘藷保守miRNA與傷害反應miRNA研究領域,並發展出可靠的新分析平台,提供未來進一步miRNA相關研究與預測應用。 | zh_TW |
dc.description.abstract | Plant microRNAs (miRNAs), which are 20-24 nucleotides small non-coding RNAs, play crucial roles not only in various developmental processes but also in responses to biotic and abiotic stresses. One of the most severe stresses is wounding, which affects plant growth and development and causes food production lost. However, few studies have been conducted to investigate the conserved miRNAs and the wounding-responsive miRNAs in sweet potato. In this study, 83 conserved miRNAs were identified, 15 of which are wounding-induced miRNAs and 24 of which are wounding-repressed miRNAs, in sweet potato from small RNA sequencing by matching with miRBase 16. According to this prediction, two of the most significantly wounding-induced miRNAs were miR2111 and miR894. The target genes of miR2111 were predicted to be PUT-169a-10214 and TC6582, which is highly similar to that of retinoblastoma-associated proteins and may regulate plant cell proliferation for healing the open wound. The target gene of miR894 was predicted to be TC8064/PUT-169a-2721, which is homologous to calmodulin-binding protein and may be involved in plant defense response. The expression patterns of miR2111and miR894 after applying different signal donors or inhibitors were detected in order to understand the upstream signaling transduction of miR2111 and miR894. Results indicated that MeJA, ethylene, SA, H2O2, and calcium ion were all involved in the upstream wounding signals that activate miR2111. On the other hand, only MeJA, SA and H2O2 were partially involved in miR894 expression. In other words, wounding responsive miR894 may need more than one wound signals to turn on. As the discovery about miRNAs is expanding at an astonishing rate, the miRBase 21 was released with 8,496 miRNAs in 73 plant species. To obtain the comprehensive and up-to-date conserved miRNA profiles, a novel pipeline, the Mir Pipeline, was developed, and the new strategies for conserved miRNA matching (miRBase 21) were used. In the small RNA sequencing data, 159 conserved miRNAs were identified, 27 of which are wounding-induced miRNAs and 49 of which are wounding-repressed miRNAs. In addition, by performing RNA-Seq, a sweet potato transcriptome database was built. For more precisely miRNA target genes and miRNA mimics prediction, a prediction program, the Mir Score, with new criteria was designed. With this pipeline, target predictions of all of the conserved miRNAs have been conducted. Among them, 5 highly confident targets of miR2111 were identified; 8 highly confident targets of miR894 were also identified from transcriptome contigs. These results shed light on the poorly understood field of conserved wounding-responsive miRNAs in sweet potato. These newly developed pipelines can be the reliable tools for miRNA research and prediction. | en |
dc.description.provenance | Made available in DSpace on 2021-06-08T01:19:08Z (GMT). No. of bitstreams: 1 ntu-103-R01b42002-1.pdf: 9121280 bytes, checksum: fc43d89a9fe1e85606cd8362bbbe0ccb (MD5) Previous issue date: 2014 | en |
dc.description.tableofcontents | 摘要 I
Abstract III Table of Contents VI List of Figures IX List of Tables XII List of Supplemental Data XIII Chapter 1: Introduction 1 Wounding Stress 1 Wounding Stress and Plant Wounding Responses 1 Wounding Signaling and Regulatory Mechanism 2 microRNA 4 The Discovery of miRNA 4 miRNA database: the miRBase 5 Plant miRNAs 7 Plant miRNAs Biogenesis and Function 7 The Roles of miRNA in Plant 8 The Roles of miRNA in Plant Growth and Development 8 The Roles of miRNA in Plant Stress Responses 8 Research Motivations and Objectives 11 Chapter 2: Materials and Methods 12 Plant materials and treatments 12 Small RNA Sequencing and RNA Sequencing 13 Small RNA sequence data processing and analysis 14 RNA sequence data processing and de novo transcriptome assembly 14 Small RNA blot assay 15 Quantitative real-time PCR (qPCR) assay and mature miRNA qPCR assay 17 Isolation and secondary structure prediction of miRNA precursors 17 Prediction and isolation of miRNA target genes 18 Construction of IbRDRs-RNAi, IbDCLs-RNAi and transgenic sweet potatos 19 Chapter 3: Results 21 Small RNA sequencing by NGS high-throughput analysis 21 Profile of conserved miRNAs and identification of wounding responsive miRNA in sweet potato 22 miR2111 24 Sequence, expression level, and secondary structure of miR2111 precursor 24 PUT-169a- 10214 and TC6582 are putative targets of miR2111 26 Functional prediction of TC6582 as a retinoblastoma-associated protein 27 Secondary messenger Ca2+ participates in miR2111 expression 28 Methyl jasmonate, ethylene, salicylic acid and H2O2 are involved in miR2111 expression 30 The sizes of mature miR894s are 16~21 nucleotides 31 Sequence and secondary structure of miR894 precursor 31 TC8064/ PUT-169a-2721 is a putative target of miR894 32 Functional prediction of TC8064/ PUT-169a-2721 as calmodulin binding protein 33 Secondary messenger Ca2+ does not participate in miR894 expression 34 Methyl jasmonate, salicylic acid and H2O2 are partially involved in miR894 expression 35 Up-to-date conserved miRNA prediction with new strategies 36 RNA-Seq data analysis and prediction of miRNA targets, mimics, precursors 37 Chapter 4: Discussion 41 Diverse sizes of mature miR894s 41 Identify the conserved miRNA in different plant species by different strategies and database versions 42 Diverse wounding responsive miRNAs 43 More potential target genes of miR2111 and miR894 45 Sweet potato transformation system improvement 46 Chapter 5: Conclusion 49 Chapter 6: Perspective 51 Figures 52 Tables 98 Supplemental Data 113 References 131 | |
dc.language.iso | en | |
dc.title | 甘藷傷害反應miRNA之篩選鑑定與功能分析 | zh_TW |
dc.title | Identification and functional characterization of wounding-responsive miRNAs in sweet potato (Ipomoea batatas cv. Tainung 57) | en |
dc.type | Thesis | |
dc.date.schoolyear | 102-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 靳宗洛(Tsung-Luo Jinn),林詩舜(Shih-Shun Lin),林淑怡(Shu-I Lin) | |
dc.subject.keyword | 甘藷,傷害,保守miRNA,miR2111,miR894,次世代定序資料分析, | zh_TW |
dc.subject.keyword | sweet potato,wounding,conserved miRNA,miR2111,miR894,next generation sequencing data analysis, | en |
dc.relation.page | 137 | |
dc.rights.note | 未授權 | |
dc.date.accepted | 2014-08-11 | |
dc.contributor.author-college | 生命科學院 | zh_TW |
dc.contributor.author-dept | 植物科學研究所 | zh_TW |
顯示於系所單位: | 植物科學研究所 |
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檔案 | 大小 | 格式 | |
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ntu-103-1.pdf 目前未授權公開取用 | 8.91 MB | Adobe PDF |
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