肝纖維化細胞與動物模型以轉錄體資料分析比較

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許偉恩(Wei-En Hsu) 查詢紙本館藏

畢業系所

系統生物與生物資訊研究所

論文名稱

肝纖維化細胞與動物模型以轉錄體資料分析比較
(Transcriptomic Data Analysis of Liver Fibrosis Cells and Animal Models)

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摘要(中)

纖維化是一段組織修復的過程，會由於修復過程中的失調而導致難以逆轉，在肝組織中會受到慢性炎症影響而發展纖維化。而纖維化的過程相當複雜，牽涉許多化學因子、機械應力調控，並會與許多疾病同時發展。此篇研究使用藉由物理刺激和化學刺激的細胞、小鼠及大鼠模型轉錄組數據進行分析，經由免疫組成分析確認模型內的免疫特徵，將差異表現基因以| log2FC| > 1的條件進行篩選並用於路徑分析，發現了許多細胞週期調控、免疫調控、組織修復、ECM結構變化等與纖維化相關的路徑，同時也觀察到使用不同方法刺激的模型有明顯參與不同路徑結果。在各個模型中，所顯現的特徵有所不同，在各階段的分析中，也有提出可能參與調控的因子，這些數據可於不同纖維化模型的建立時，提出可參考的資訊來選擇較適合的方法。

摘要(英)

Fibrosis is a process of tissue repair that can be difficult to reverse due to dysregulation during the repair process. It develops in liver tissue as a result of chronic inflammation. The process of fibrosis is highly complex, involving various chemical factors and mechanical stress regulation, and it often occurs concomitantly with many diseases. In this study, transcriptomic data from cell cultures, as well as mouse and rat models, stimulated by physical and chemical stimuli, were analyzed. In this study, transcriptomic data from cell cultures, as well as mouse and rat models, stimulated by physical and chemical stimuli, were analyzed. Immuno composition analysis was performed to confirm the immune characteristics within the models. Differential expression genes were filtered based on the condition of |log2FC| > 1 and used for pathway analysis. Many pathways related to fibrosis, such as cell cycle regulation, immune regulation, tissue repair, ECM structural changes, and others, were discovered. Additionally, it was observed that models stimulated using different methods significantly participated in different pathways. The features displayed in various models differ, and potential regulatory factors have been proposed in the analysis of different stages. These data can provide valuable information for selecting a suitable approach when constructing different fibrosis models.

關鍵字(中)

★ 纖維化
★ 轉錄體
★ 肝臟

關鍵字(英)

★ Fibrosis
★ Transcriptom
★ Liver

論文目次

中文摘要 i
Abstract ii
目錄 iii
圖目錄 vi
表目錄 viii
一、緒論 1
1-1. 纖維化 1
1-2. 纖維化模型 4
1-2-1. 細胞纖維化模型 4
1-2-1-1. 標準纖維化模型 4
1-2-1-2. 動態仿生模型 5
1-2-1-3. 三維培養模型 6
1-2-1-4. 四維培養模型 6
1-2-2. 動物纖維化模型 7
1-3. 次世代定序 8
1-4. 轉錄體學分析 8
1-5. 研究動機及目的 9
二、材料及方法 10
2-1. 纖維化模型建構 10
2-1-1. 細胞模型 10
2-1-1-1. 細胞培養 10
2-1-1-2. 標準纖維化細胞模型 10
2-1-1-3. 二維動態纖維化細胞模型 10
2-1-1-4. 三維動態纖維化細胞模型 11
2-1-2. 動物纖維化模型 11
2-1-2-1. 小鼠肝纖維化模型 11
2-1-2-2. 大鼠肝纖維化模型 12
2-2. RNA萃取 12
2-3. 核醣核酸定序 (RNA sequencing, RNA-seq) 13
2-4. 數據分析 14
2-4-1. 分析環境及套件 14
2-4-2. 數據來源 15
2-4-3. 數據處理 15
2-4-4. 免疫組成分分析 17
2-4-5. 轉錄體數據視覺化 18
2-4-5-1. 主成分分析 (Principal components analysis, PCA) 18
2-4-5-2. 相關係數矩陣 (Correlation matrix) 19
2-4-5-3. 聚類熱圖 (Heatmap) 20
2-4-5-4. 文氏圖 (Venn diagram) 20
2-4-5-5. 氣泡圖 (Bubble plot) 20
2-4-6. 路徑分析 21
2-4-6-1. 基因本體論 (GO) 21
2-4-6-2. 京都基因與基因組百科全書 (KEGG) 22
2-4-6-3. IPA 23
三、實驗流程 24
四、實驗結果 25
4-1. 各組模型的轉錄組數據處理 25
4-2. 各組模型的纖維化標誌物表現情況 26
4-3. 各組模型的免疫組成分分析結果 28
4-4. 各組模型的免疫因子表現情況 41
4-5. 各組模型的主成分分析結果 44
4-6. 各組模型的相關性矩陣結果 44
4-7. 各組模型的差異表現基因聚類熱圖 48
4-8. 各組模型中具有交集的差異表現基因 48
4-9. 各組模型的路徑分析結果 53
4-10. 各組模型的基質調節因子表現情況 57
五、討論與結論 61
5-1. 免疫組成分析 61
5-2. 差異表現基因篩選 63
5-3. GO-BP路徑分析結果 64
5-4. KEGG路徑分析結果 65
5-5. IPA路徑分析結果 66
5-6. 肝細胞株的差異 66
5-7. 結論 67
參考資料 68

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指導教授

許藝瓊(Yi-Chiung Hsu)

審核日期

2023-8-10

推文