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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 許輔 | |
dc.contributor.author | Chih-Liang Hung | en |
dc.contributor.author | 洪志良 | zh_TW |
dc.date.accessioned | 2021-05-13T08:35:56Z | - |
dc.date.available | 2016-08-26 | |
dc.date.available | 2021-05-13T08:35:56Z | - |
dc.date.copyright | 2016-08-26 | |
dc.date.issued | 2016 | |
dc.date.submitted | 2016-08-19 | |
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dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/3685 | - |
dc.description.abstract | 對臺灣夏作甘藍生產來說,颱風過後所帶來的高溫淹水是一主要逆境。此逆境會造成嚴重之生理障害進而導致產量的損失。然而,高溫淹水逆境所造成的生理障害之分子機制尚未明瞭。本論文研究目的是釐清高溫淹水逆境如何影響甘藍轉錄,同時找出甘藍中有助於增加高溫淹水耐受性之基因組。首先,利用次世代定序技術來調查25或35°C有/無淹水處理的八週大之甘藍全轉錄體表現。其中2,040個基因被選作分析目標,並用其對數倍率變化來進行差異表現分析。透過階層式分群法,發現具高溫淹水逆境特異性之受 WRKY 誘導而向上調節的ACC氧化酶1,其可能為降低甘藍‘夏峰一號’逆境耐受性的關鍵因子之一。而透過基因本體富集分析,結果顯示在高溫處理組的基因本體富集詞彙與高溫淹水處理組接近,但在個別處理組中仍有獨特的基因本體詞彙。為了更進一步了解逆境下甘藍之共功能網路,以AraNet v2 預測高溫淹水逆境處理之甘藍的共表現網路模組。在預測出的7組共表現模組中,其中兩組與離層酸訊息傳遞及滲透壓逆境耐受性有關的模組表現向下調控,提供了甘藍‘夏峰一號’不耐高溫淹水逆境的證據。再者,利用次世代定序比較高溫淹水逆境處理之逆境耐性及逆境敏感甘藍栽培品種的轉錄體表現,預期將找到受高溫淹水逆境影響之代謝路徑及基因組。此研究植物材料使用了具高溫淹水耐受性的‘228’,及敏感性的‘Fuyudori’。逆境處理則是在生長箱中進行,取樣時間點為處理後0、6、12、及24小時。藉由時程試驗,並結合階層式分群法進行初級表現測量與權重共表現基因網路分析,透過兩種不同生物資訊學方法來進行數據分析。根據此方法,256個具有最顯著表現差異的基因被確認,並建構了13個與高溫淹水逆境相關之共表現模組。最後,結果顯示在‘228’中高溫淹水逆境耐受性與酚類化合物生合成高度相關,而失控的缺水逆境可能是造成‘Fuyudori’不耐受高溫淹水逆境的關鍵因子之一。這些數據顯示高溫淹水逆境對甘藍代謝及調節路徑之影響。數個具逆境特異性之模組能與次級代謝物的累積、離層酸訊息的傳遞、及熱逆境因子與熱休克蛋白的向上調控做連結。上述這些機制也許提供了甘藍在面對劇烈變化的高溫淹水逆境下適合的代謝適應力維持生理反應的靈活對策。 | zh_TW |
dc.description.abstract | Waterlogging at high temperature is a major stress after typhoon to the cabbage production during summer in Taiwan. This stress brings in serious physiological disorder and results in yield loss in cabbage. However, the molecular mechanisms of the physiological disorders under waterlogging stress at high temperature remain unclear. This thesis aims to identify how the waterlogging stress at high temperature (HWS) influences the cabbage transcriptome and to discover the gene sets which contribute to the tolerance of HWS in cabbage. First, RNA-seq was used to investigate the whole transcriptome of eight-week-old cabbage ‘Shia Feng No. 1’ treated with or without waterlogging both at 25 or 35°C. Log2 fold change value in selected 2,040 genes was used to discriminate differentially expressed genes (DEGs). By hierarchical clustering, WRKY-induced up-regulation of ACC oxidase 1 was specifically found in HWS treatment, which to be one of the key factors that caused decreased stress tolerance in cabbage ‘Shia Feng No.1’. According to gene ontology (GO) enrichment analysis, the enriched GO terms in heat treatment were close to HWS treatment; however, there were still unique GO terms enriching in each treatment. To further understand the co-functional networks in cabbages exposed to stress, AraNet v2 was used to predict co-expression network modules of HWS-treated cabbages. In the 7 predicted co-expression modules, the down-regulation of two modules related to ABA signaling and tolerance to osmotic stress in plants may provide the evidence about the HWS intolerance in cabbage. Next, next generation sequencing was employed to compare the transcriptome of stress-tolerant cultivar ‘228’ and stress–intolerant cultivar ‘Fuyudori’ under HWS, which were used to find HWS-influenced metabolic pathways and gene sets. Stress treatment was performed in growth chamber at 35°C for 24 h, and sampling was performed at 0, 6, 12, and 24 h after treatment. A time-course RNA-seq analysis was performed and combined two different bioinformatic methods, primary co-expression measure with hierarchical clustering and weighted correlation network analysis (WGCNA), for analyzing the transcriptome data. 256 most significantly changed genes were identified and 13 coexpression modules associate to HWS were constructed. Finally, comparative analysis showed HWS tolerance highly linked to phenolic biosynthesis in ‘228’, and uncontrollable water deprivation may be one of the key factors to cause HWS-affected in ‘Fuyudori’. These data show how HWS influences the metabolic and regulatory pathways in cabbages. Several stress tolerance-specific gene modules were linked to the accumulation of secondary metabolites, transduction of ABA signaling, and up-regulation of heat stress factors and heat shock proteins. These may provide cabbage a flexible strategy tolerant to cope with HWS by offering appropriate metabolic adaptability under the dramatically changing environment. | en |
dc.description.provenance | Made available in DSpace on 2021-05-13T08:35:56Z (GMT). No. of bitstreams: 1 ntu-105-D98628003-1.pdf: 5430870 bytes, checksum: db5be04a074ac7b669ab5fc2c0c0df9b (MD5) Previous issue date: 2016 | en |
dc.description.tableofcontents | 論文審定書 II
誌謝 III 摘要 IV Abstract VI Content IX List of tables XII List of Abbreviations XV Chapter 1 Introduction 1 1.1 Heat and waterlogging stresses in crop 1 1.2 RNA-seq in plant transcriptome 8 1.3 Overview of cabbage and its problem on production in Taiwan 11 1.4 Aims 12 Chapter 2 Transcriptome analysis of heat tolerant cabbage under high temperature and/or waterlogging stress using RNA-seq 15 2.1 Materials and Methods 15 2.1.1 Plant materials and growth conditions 15 2.1.2 RNA extraction, cDNA library preparation, and RNA-seq 16 2.1.3 De novo assembly, annotation, and differential gene expression analysis of RNA-seq data 17 2.1.3 Validation of RNA-seq data by qPCR 18 2.2 Results 20 2.2.1 De novo assembly and annotations 20 2.2.2 Identification of differentially expressed genes in stress treatments 22 2.2.3 Singular enrichment analysis of GO for DEGs 26 2.2.4 DEGs involved in responding to reactive oxygen species 29 2.2.5 DEGs involved in responding to water deprivation 30 2.2.6 Co-functional gene network of cabbages under HWS 32 2.2.7 Validation of RNA-seq results by real time quantitative PCR (qPCR) 36 2.3 Discussion 38 Chapter 3 Comparative analysis of HWS responses in cabbages by weighted gene co-expression network analysis (WGCNA) 44 3.1 Materials and Methods 44 3.1.1 Plant materials and growth conditions 44 3.1.2 RNA extraction, cDNA library preparation, and RNA-seq 45 3.1.3 De novo assembly, annotation, and differential gene expression analysis of RNA-seq data 46 3.1.4 Gene coexpression network construction and visualization 47 3.2 Results 48 3.2.1 Global analysis of RNA-seq data 48 3.2.2 Differentially gene expression identifies the changes in stress tolerance-associated genes 54 3.2.3 Weighted gene correlation network analysis identified three cultivar-specific modules 60 3.2.4 Identification and analysis of coexpression network hub gene sets 71 4.3 Discussion 84 Chapter 5 General conclusion and future directions 89 Reference 93 Supplementary information 106 | |
dc.language.iso | en | |
dc.title | 甘藍高溫淹水耐受性之 RNA-seq 轉錄體分析 | zh_TW |
dc.title | A transcriptome analysis using RNA-seq to investigate the tolerance of the cabbage (Brassica oleracea var. capitata L.) to high temperature and waterlogging stresses | en |
dc.type | Thesis | |
dc.date.schoolyear | 104-2 | |
dc.description.degree | 博士 | |
dc.contributor.coadvisor | 羅筱鳳 | |
dc.contributor.oralexamcommittee | 洪進雄,郭純德,王仕賢,林詩舜 | |
dc.subject.keyword | 次世代定序,轉錄體,甘藍(Brassica oleracea var. capitata L.),淹水,高溫,逆境,權重共表現基因網路分析, | zh_TW |
dc.subject.keyword | next generation sequencing,transcriptome,Brassica oleracea var. capitata L.,waterlogging,high temperature,stress,WGCNA, | en |
dc.relation.page | 113 | |
dc.identifier.doi | 10.6342/NTU201603060 | |
dc.rights.note | 同意授權(全球公開) | |
dc.date.accepted | 2016-08-19 | |
dc.contributor.author-college | 生物資源暨農學院 | zh_TW |
dc.contributor.author-dept | 園藝暨景觀學系 | zh_TW |
顯示於系所單位: | 園藝暨景觀學系 |
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