臺灣博碩士論文加值系統

microRNAs(miRNAs)是內源性短片斷的RNA，長度一般約為17-25個鹼基，在功能上卻具有影響基因表現的能力。目前人類在miRNA的資料庫(miRNA registry)約有三百多條被註冊。miRNAs 最明顯的特徵是由具有髮夾結構的pre-miRNAs演變而來，之後由Dicer這個切割酶將它切成雙股的RNA，其中一股隨之與其他的蛋白質結合形成一個引導沉默複合體(RISC)，這個複合體再與其互補的mRNA結合，若結合的程度是完全互補，則mRNA結構被切斷，此情形多發生於植物，若結合程度是部分互補，則mRNA被抑制轉譯，此情形多發生於動物。此次研究主要是探討miRNAs與exon skipping事件的關係，因為選擇性裁剪會造成不同的form，因而假設不同的form也影響了與miRNAs的結合，繼而研究兩種form與miRNAs結合的差異處，從這些差異區域處探討是否具有組織及癌性專一性，也判斷是否也有特定的miRNA結合於此處。
研究方法的資料來源為NCBI人類染色體序列資料、miRNA registry之人類miRNAs序列及AVATAR exon skipping資料。本研究採用John, B. et al.開發之miRanda軟體，分別尋找miRNAs與exon skipping事件兩種form結合之區域，我們稱中間之alternative exon未被裁剪之form為 form1，被裁剪之form為 form2，接著將每一個exon skipping事件中miRNAs只會結合於其中一種form之區域過濾出來，即miRNAs只會結合於form1或只會結合於form2，最後利用費雪精確檢驗法(Fisher's exact test)檢驗這些具有miRNAs form1或form2專一性之區域在某組織中是否與癌症相關，結果找出form1有37處在胃、肝、皮膚、腦、胎盤、胰臟及乳腺，form2有5處在皮膚、腦、胎盤及胰臟與癌症相關，最後亦將所有具有form1或form2專一性之資料分別予以分析統計，如位於那條染色體，位於那個基因及與miRNAs結合處是位於基因的3'未轉譯區、5'未轉譯區或編碼區，並將找到的基因使用基因本體論(Gene Ontology)做功能上的分析。
由於form1之序列長度較長於form2，因此我們認為form1與miRNAs結合之機率亦較高，而此研究之結果亦是如此。因為miRNAs會抑制基因之轉譯，因此我們也認為miRNAs 對form1之影響程度可能也較大。當然這些結果仍需實驗佐以證明，所以我們也將結果開發查詢網站，提供研究人員一個查詢資料的選擇。

MicroRNAs (miRNAs) are a new class of small, endogenous, non-coding RNAs. These single-stranded RNAs of ~17-25 nucleotides that regulate gene expression. Current now about 300 novel miRNAs were identified in miRNA registry. MiRNA most obvious characteristic is a hairpin structure(pre-miRNA), the mature pre-miRNAs are exported to the cytoplasm for further processing. In the cytoplasm, Dicer cleaves the pre-miRNA and produces double-stranded RNA. One of the unwound strands (mature miRNA) is subsequently incorporated into ribonucleoprotein complex, RNA-induced silencing complex (RISC) and binds target mRNA. In plants, miRNAs have perfect complementarity to their targets and cleave them, In animals, miRNAs bind mRNA with partial complementarity in the 3′ UTR of their targets and repress translation. This research explores association between miRNAs and exon skipping events, Because alternative splicing results in two isoforms, we hypothesize different forms may influence miRNAs binding, and try to find relationship between miRNAs and exon skipping events. According to the miRNAs bind with alternative splicing sites, may be found that miRNAs are expressed higher in some tissues and tumors.
Data source from this research are NCBI chromosome data、miRNA registry human miRNAs and AVATAR exon skipping data. This research applys miRanda software developed by John, B. et al., try to find two forms binding sites of exon skipping events. We name the alternative exon not be spliced form form1 and be spliced form form2, and filter the binding sites of miRNAs bind only form1 or form2 with every exon skipping event. The filtered binding sites are tested if each site is related with tissue or tumor specific or not by Fisher’s exact test. There are 37 sites in form1 associated with cancer, for example gastric carcinoma, hepatoma, melanoma, brain tumor, mastocarcinoma, pancreatic carcinoma, placenta carcinoma, and 5 sites in form2 involved brain tumor, melanoma, pancreatic carcinoma, placenta carcinoma. Finally, we also summarize and analyze the results, for example finding the target genes and binding site position(3′ UTR or 5′ UTR or coding regions) and functional analysis with Gene Ontology.
Because the length of form1 is larger than form2, so form1 binding probability is much higher than form2, and miRNAs can repress gene translation, so we think influence degree of form1 may be higher than form2, but the results will need be verified with experiment in the future. The results developed with a query tool for researchers to search interesting data.

Chapter 1 Introduction 1
1.1 microRNAs play an important role of gene regulation 1
1.2 Research background 2
1.3 Research purpose 3
Chapter 2 Related work 4
2.1 Methods of miRNAs target prediction 4
2.2 Association between miRNAs and human diseases 8
2.2.1 miRNAs related with cell growth, differentiation and disease 8 2.2.2 miRNAs associated with cancer 9
2.3 Tissue specific of miRNAs and miRNAs profiles 12
Chapter 3 Materials and methods 14
3.1 Data Source 14
3.2 Methods 15
3.3 Query tool 23
Chapter 4 Results and discussion 27
4.1 Degree of miRNAs influence 27
4.2 Tissue and Tissue-Tumor specific 28
4.3 miRNAs and target genes 30
Chapter 5 Conclusion and future work 37
5.1 Conclusion 37
5.2 Future work 37
Acknowledgements 39
Reference 40

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