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研究生:陳虹瑋
研究生(外文):Hon-Wei Chen
論文名稱:以比較基因體學的方法鑑定遺失酵素功能的基因
論文名稱(外文):Computational identification of missing enzymatic gene based on conservation profile of correlated gene clusters
指導教授:劉德明劉德明引用關係
指導教授(外文):Der-Ming Liou
學位類別:碩士
校院名稱:國立陽明大學
系所名稱:衛生資訊與決策研究所
學門:醫藥衛生學門
學類:公共衛生學類
論文種類:學術論文
論文出版年:2004
畢業學年度:92
語文別:英文
論文頁數:48
中文關鍵詞:比較基因體學
外文關鍵詞:comparative genomicsmissing genegene clusterprofile
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大部分的基因功能的註解主要是透過生物醫學實驗來完成。但在後基因體時代,隨著越來越多經過完整定序與註解的基因體可取得,未知功能的基因可以藉由搜尋其他已註解完成的生物序列而自動地得到功能的註解。雖然數個搜尋序列相似度的工具如BLAST、FASTA等已經成功地應用在這方面,它們卻常常失敗在鑑定某些基因的功能且甚至導致不正確的基因功能的註解。這些參與代謝但是卻不知道功能或者功能被註解錯誤的基因會導致在代謝路徑上酵素的遺失。由於酵素遺失的影響,針對於某一生物所重建的代謝路徑將會缺乏準確性而且提供不完整的代謝知識給生物學家。以致於後續應用如不同生物間代謝路徑的比較或者代謝路徑的模擬會產生累加的錯誤。在傳統上、這些遺失酵素功能的基因可以透過進一步的實驗方式來找回其功能,但往往需要大量的實驗成本與時間上的花費。
為了解決代謝路徑上酵素遺失的問題,我們提出了一個計算方法來取得保留在多生物間基因叢集,而這些基因叢集同時在染色體上有著相似的基因排列以及在共同參與的代謝路徑上有著功能性的耦合。我們從日本京都大學的KEGG上取得157個生物的代謝路徑圖與基因體註解的資料。一些具有酵素功能的基因會群聚一起並且形成基因叢集,而條件是它們所製造的酵素會共享在所選擇的生物間以及其會座落在染色體上相鄰的位置。隨著基因體重新排列的可能性,一個同時存在不同生物且功能耦合的基因叢集裡,基因的順序可以允許不同的排列而且所有的基因都必須存在這些生物間。
這樣所保留在多生物的基因叢集可以自動取得且以圖形的方式同時呈現在染色體與代謝路徑圖上。它們可以被用於調查基因體的演化關係以及透過鑑定遺失酵素功能的基因而促進基因體註解的品質。
在這篇論文中,我們提供一個如何透過我們的系統來鑑定遺失酵素功能的基因例子。其結果將會呈現我們所發現的在bacillus cereus ATCC 14579的糖解代謝途徑中的兩個遺失酵素功能的基因。然而、這結果將可以補足這個生物不完整的功能註解。
Most of genome annotations primarily come from biochemical experimentation. But with the availability of increasing numbers of fully sequenced and annotated genomes, uncharacterized genes can be automatically assigned functions by sequence similarity search for well-characterized genes in other organisms. Although the sequence similarity-based tools [such as BLAST, FASTA] have most successes in functional assignment of genes, they fail to identify functions for many genes or even result in annotation errors. The genes which participate in metabolism but have no functions or incorrect functions bring the problem of missing enzymes in metabolic pathways. As a result of missing enzymes, the results from pathway reconstruction for a specific organism often lack of precision and provide incomplete pathway knowledge for biologists. So that the follow-up applications like pathway comparison in different organisms or pathway simulation will have progressive errors. The problem traditionally requires advanced experiments to be solved but therefore produce a large number of experimental efforts and time costs.
In order to solve the problem of missing enzymes in metabolism, we propose a computational approach to identify conservation profiles of gene clusters which both have similar chromosomal arrangements and are functionally-coupled in metabolic pathways shared among multiple organisms. Metabolic pathway diagrams and annotations of 157 prokaryotic genomes are obtained from KEGG (Kyoto Encyclopedia of Genes and Genomes). Enzymatic genes involved in a pathway shared by selected organisms and located at neighboring positions in chromosome are grouped together as a gene cluster. With the possibility of genome rearrangement, the gene order in each correlated gene cluster is allowed to be different for different organisms. The genes in each correlated gene cluster completely present in all organisms.
A conservation profile of the gene clusters shared among multiple organisms is automatically recognized and graphically presented on both chromosome and pathway maps. The profile can be used to investigate evolutionary genome dynamics and improve the quality of genome annotation by identifying missing enzymatic genes.
In this thesis, we present one case example how to identify missing enzymatic genes through our computational approach. The results will perform two missing enzymatic genes we discovered in glycolysis pathway for bacillus cereus ATCC 14579. Finally, the results can fill the incomplete annotation of this organism.
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