系統識別號 U0026-1408201416110500
論文名稱(中文) 有系統地在具有蛋白質交互作用的基因上分析調控特性
論文名稱(英文) A systematic analysis on regulatory characteristics of genes with protein-protein interactions
校院名稱 成功大學
系所名稱(中) 電機工程學系
系所名稱(英) Department of Electrical Engineering
學年度 102
學期 2
出版年 103
研究生(中文) 張紹庭
研究生(英文) Shao-Ting Jang
學號 N26011542
學位類別 碩士
語文別 中文
論文頁數 42頁
口試委員 指導教授-張天豪
中文關鍵字 蛋白質  蛋白間交互作用 
英文關鍵字 protein  Protein interactions 
中文摘要 蛋白質與蛋白質交互作用(Protein-Protein Interactions),簡稱PPI,是指兩種或兩種以上的蛋白質結合在一起,來執行生物中的部分機能。另外,在蛋白質的轉錄合成反應中,轉錄因子(TF)、TATA盒與核小體和DNA彎曲度…等,決定了基因的轉錄調控,進而影響蛋白質的生成。因此,了解這些調控元素和PPI之間的關係對於研究或是預測PPI是一個很重要的課題。目前已有許多的研究和資料庫探討PPI,然而,現有的研究和資料庫著重於蛋白質本質上的探討,包括蛋白質序列、結構、功能…等,而缺乏探討基因調控特徵和PPI之間的關係。有鑒於此,本論文整合了八種與轉錄調控相關的啟動區域特徵,包含啟動區域序列、轉錄起始點、5端非轉譯區和3端非轉譯區、基因之間的距離、TATA盒、轉錄因子結合位置、DNA彎曲度、核小體占有率、轉錄因子結合證據、轉錄因子調控證據,並將有利用這八種啟動區域特徵來分析PPI的有無。
英文摘要 Biological functions involve various protein–protein interactions (PPIs). For example, signals from the exterior of a cell are mediated to the interior of that cell involves PPIs of the signaling molecules. Understanding PPIs and their causes is important in systems biology. Many studies have been presented to analyze the relation between two genes with PPIs. However, these studies focused on intrinsic features such as protein sequences, structures, functions and so on. This study conducted a systematic analysis on regulatory characteristics of two genes with PPIs. If two genes have similar regulatory behaviors, they are supposed to be simultaneously regulated and thus their protein products, from the point of evolution, are probably related. This study analyzed nine regulatory features: gene’ transcription boundaries-transcription start sites (TSSs), five prime untranslated regions (5’-UTRs) and three prime untranslated regions (3’-UTRs), TATA boxes, transcription factor binding sites (TFBSs), nucleosome occupancy, DNA bendability, transcription factor (TF) binding, TF knockout expression and TF-TF physical interaction. The analytic results show that the genomic distance of two genes and the number common regulator influences their interactions. An interesting observation is that the distance of a considerable amount of gene pairs that have PPIs fell into the range of 50000-60000 base pairs. This suggests an unknown regulatory mechanism that involves such a large scale genomic region.
論文目次 目錄 1
表目錄 3
圖目錄 4
Chapter 1. 緒論 6
Chapter 2. 相關研究 8
2.1 介紹蛋白質交互作用 8
2.2 基因上各個位置的涵義 8
2.2.1 起始密碼子(start codon)與終止密碼子(stop codon) 9
2.2.2 轉錄因子與啟動子(promoter) 9
2.2.3 介紹TATA盒 9
2.2.4 介紹DNA彎曲度 10
2.2.5 介紹核小體的佔有率 10
2.3轉錄因子結合基因證據與調控證據 11
2.4酵母菌啟動區域相關研究 12
2.3.1酵母菌啟動區域的核小體與基因調控行為 12
2.3.2轉錄因子結合位置在酵母菌啟動區域的空間分佈 12
2.3.3酵母菌啟動區域彎曲度與TATA盒 13
2.5統計工具介紹 13
2.5.1費雪精確性檢定(Fisher's exact test)和卡方測定(Chi-square test) 13
2.5.2 T檢驗(T Test) 14
2.5.3等級和檢定(Mann–Whitney U test) 15
2.5.4柯爾莫諾夫-斯米爾諾夫檢驗(Kolmogorov–Smirnov test) 15
2.5.5 箱形圖 15
2.6 相關資料庫 16
Chapter 3. 資料收集與分析方法 18
3.1 資料收集 18
3.2資料處理 19
3.3趨勢線和數量長條圖 21
Chapter 4. 實驗結果與討論分析 23
4.1特定基因開放閱讀框(ORF)大小差距對影響PPI的形成 23
4.2有PPI的基因對距離會分佈在某個特定的區間 25
4.3有PPI的基因對傾向有較少的TATA盒 27
4.4核小體的佔有傾向低比較容易產生PPI 28
4.5 DNA的可彎曲度低比較容易產生PPI 31
4.6相似的轉錄因子結合位置比較會產生PPI 34
4.7有PPI的基因對會有較相同的轉錄因子結合 35
4.8有PPI的基因對會有較相同的轉錄因子破壞證據 37
Chapter 5. 結論與未來展望 39
5.1 結論 39
5.2 未來展望 39
參考文獻 40
參考文獻 1. Alberts, B., The cell as a collection of protein machines: preparing the next generation of molecular biologists. Cell, 1998. 92(3): p. 291-4.
2. Jones, S. and J.M. Thornton, Principles of protein-protein interactions. Proc Natl Acad Sci U S A, 1996. 93(1): p. 13-20.
3. Choo, K.H., T.W. Tan, and S. Ranganathan, SPdb--a signal peptide database. BMC Bioinformatics, 2005. 6: p. 249.
4. Ashburner, M., et al., Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat Genet, 2000. 25(1): p. 25-9.
5. Fields, S. and O.K. Song, A Novel Genetic System to Detect Protein Protein Interactions. Nature, 1989. 340(6230): p. 245-246.
6. Ito, T., et al., A comprehensive two-hybrid analysis to explore the yeast protein interactome. Proceedings of the National Academy of Sciences of the United States of America, 2001. 98(8): p. 4569-4574.
7. Gavin, A.C., et al., Functional organization of the yeast proteome by systematic analysis of protein complexes. Nature, 2002. 415(6868): p. 141-147.
8. Ho, Y., et al., Systematic identification of protein complexes in Saccharomyces cerevisiae by mass spectrometry. Nature, 2002. 415(6868): p. 180-183.
9. Gavin, A.C., et al., Proteome survey reveals modularity of the yeast cell machinery. Nature, 2006. 440(7084): p. 631-636.
10. Zhu, H., et al., Global analysis of protein activities using proteome chips. Science, 2001. 293(5537): p. 2101-2105.
11. Tong, A.H.Y., et al., A combined experimental and computational strategy to define protein interaction networks for peptide recognition modules. Science, 2002. 295(5553): p. 321-324.
12. Lodish, ed. Molecular Cell Biology (5th ed.). 2002.
13. Gu, S., Biological basis for restriction of microRNA targets to the 3' untranslated region in mammalian mRNAs. Nature Structural & Molecular Biology, 2009. 16: p. 144 - 150.
14. Grosschedl R, B.M., Identification of regulatory sequences in the prelude sequences of an H2A histone gene by the study of specific deletion mutants in vivo. Proc. Natl. Acad. Sci. USA, 1980. 77(3): p. 1432-1436.
15. Wasylyk B, D.R., Guy A, Molko D, Roget A, Téoule R, Chambon P, Specific in vitro transcription of conalbumin gene is drastically decreased by single-point mutation in T-A-T-A box homology sequence. Proc Natl Acad Sci U S A, 1980. 77(12): p. 7024-7028.
16. Grosveld GC, S.C., Jat P, Flavell RA, Localization of DNA sequences necessary for transcription of the rabbit beta-globin gene in vitro. Cell, 1981. 25(1): p. 215-226.
17. Green MR, T.R., Maniatis T, Transcriptional activation of cloned human beta-globin genes by viral immediate-early gene products. Cell, 1983. 35(1): p. 137-148.
18. Wu L, R.D., Schmidt MC, Berk A, A TATA box implicated in ElA transcriptional activation of a simple adenovirus 2 promoter. Nature, 1987. 326(6112): p. 512-515.
19. Simon MC, F.T., Benecke BJ, Nevins JR, Heintz N, Definition of multiple, functionally distinct TATA elements, one of which is a target in the hsp70 promoter for E1A regulation. Cell, 1988. 52(5): p. 723-729.
20. Boyer TG, K.J., Maquat LE, Transcriptional regulatory sequences of the housekeeping gene for human triosephosphate isomerase. J. Biol. Chem, 1989. 264(9): p. 5177-5187.
21. Williams GT, M.T., Morimoto RI, Ela transactivation of the human HSP70 promoter is mediated through the basal transcriptional complex. Mol Cell Biol, 1989. 9(6): p. 2574-2587.
22. Brukner, I., Sa´ nchez,R., Suck,D. and Pongor,S, Sequence-dependent bending propensity of DNA as revealed by DNase I: parameters for trinucleotides. EMBO 1995. 14: p. 1812-1818.
23. Barkai, I.T.a.N., Two strategies for gene regulation by promoter nucleosomes. Genome Research, 2008. 18(1084-1901).
24. Noam Kaplan, I.K.M., Yvonne Fondufe-Mittendorf, Andrea J. Gossett, Desiree Tillo, Yair Field1, Emily M. LeProust, Timothy R. Hughes, Jason D. Lieb, Jonathan Widom and Eran Segal, The DNA-encoded nucleosome organization of a eukaryotic genome. Nature, 2009. 458: p. 362-366.
25. Lee TI, Y.R., Transcription of eukaryotic protein-coding genes. Annual Review of Genetics, 2000. 34: p. 77-137.
26. Kenzie D MacIsaac, T.W., D Benjamin Gordon, David K Gifford, Gary D Stormo and Ernest Fraenkel, An improved map of conserved regulatory sites for Saccharomyces cerevisiae. BMC Bioinformatics, 2006. 7: p. 113.
27. Miguel C. Teixeira, P.M., Pooja Jain, Sandra Tenreiro,Alexandra R. Fernandes, Nuno P. Mira, Marta Alenquer, Ana T. Freitas, Arlindo L. Oliveira and Isabel Sa´-Correia, The YEASTRACT database: a tool for the analysis of transcription regulatory associations in Saccharomyces cerevisiae. Nucleic Acids Research, 2006. 34: p. D446-D451.
28. Lin, Z., Wu,W.S., Liang,H., Woo,Y. and Li,W.H., The spatial distribution of cis regulatory elements in yeast promotersand its implications for transcriptional regulation. BMC Genomics, 2010. 11: p. 581.
29. J. Michael Cherry*, C.A., Catherine Ball, Stephen A. Chervitz, Selina S. Dwight, Erich T. Hester, Yankai Jia, Gail Juvik, TaiYun Roe, Mark Schroeder, Shuai Weng and David Botstein SGD: Saccharomyces Genome Database. Nucleic Acids Research, 1998. 26: p. 73-79.
30. Stark C, B.B., Reguly T, Boucher L, Breitkreutz A, Tyers M, BioGRID: a general repository for interaction datasets. Nucleic Acids Res., 2006. 34(Database): p. 535-539.
31. Chang, D.T., et al., YPA: an integrated repository of promoter features in Saccharomyces cerevisiae. Nucleic Acids Res, 2011. 39(Database issue): p. D647-52.
32. Garten, Y., S. Kaplan, and Y. Pilpel, Extraction of transcription regulatory signals from genome-wide DNA–protein interaction data. Nucleic Acids Research, 2005. 33(2): p. 605-615.
33. Kim, R.S., H. Ji, and W.H. Wong, An improved distance measure between the expression profiles linking co-expression and co-regulation in mouse. BMC Bioinformatics, 2006. 7(1): p. 44.
34. Veerla, S. and M. Höglund, Analysis of promoter regions of co-expressed genes identified by microarray analysis. BMC Bioinformatics, 2006. 7(1): p. 384.
35. Shalgi, R., et al., Global and local architecture of the mammalian microRNA-transcription factor regulatory network. PLoS Comput Biol, 2007. 3(7): p. e131.
  • 同意授權校內瀏覽/列印電子全文服務,於2019-08-27起公開。

  • 如您有疑問,請聯絡圖書館