本文選題：基因組島　切入點(diǎn)：必需基因　出處：《天津大學(xué)》2016年碩士論文

【摘要】：原核生物包括細(xì)菌和古菌,涉及健康、醫(yī)藥、環(huán)境、能源等諸多領(lǐng)域,與人類生活休戚相關(guān)�；蚪M島是原核生物中水平轉(zhuǎn)移來的一簇外源基因,經(jīng)研究發(fā)現(xiàn)這些基因與原核生物的致病、耐藥、分泌、抗菌和代謝等密切相關(guān)。基于基因組島上出現(xiàn)的某些序列特征或?qū)Σ煌锓N間的基因組進(jìn)行序列比較,國內(nèi)外科研人員已經(jīng)研發(fā)出了大量識別基因組島的工具,比如基于序列組成的識別基因組島的方法IslandPath,SIGI-HMM,Zisland Explorer和基于比較基因組的方法Island-Pick和MobilomeFINDER。面對種類繁多的基因組島預(yù)測方法,如何選擇合適的方法就顯得尤為重要。本文的前半部分工作著重對原核生物基因組島預(yù)測結(jié)果進(jìn)行比較。文中先介紹了基因組島的功能類型和序列特性,其次介紹了目前常用的基因組島識別工具和網(wǎng)絡(luò)資源,最后我們用多種代表性的識別方法預(yù)測了28個原核生物的基因組島。通過與實(shí)驗(yàn)預(yù)測基因組島的比較,我們發(fā)現(xiàn)了不同基因組島識別方法在預(yù)測結(jié)果上的差異。基于比較可信的原核生物基因組島預(yù)測結(jié)果,科研人員逐漸把目光轉(zhuǎn)向了基因組島上的功能和成分分析,比如通過研究其中的耐藥基因,可以進(jìn)一步分析原核生物耐藥機(jī)理,從而為研制新的抗生素和耐藥靶點(diǎn)提供依據(jù)。在本文的后半部分,我們研究了原核生物基因組島中的必需基因,并對島內(nèi)外必需基因進(jìn)行了統(tǒng)計(jì)分析。必需基因是指對細(xì)胞生存起關(guān)鍵作用的基因,所編碼的蛋白質(zhì)能夠維持細(xì)胞存活的基本功能。文中先介紹了必需基因的實(shí)驗(yàn)識別方法和相關(guān)數(shù)據(jù)庫。其次,通過統(tǒng)計(jì)學(xué)方法進(jìn)一步分析了28個原核生物島內(nèi)和島外必需基因的比例,結(jié)果發(fā)現(xiàn)必需基因在島內(nèi)要比島外顯著地少。最后,通過BLAST比對基因組島上362個必需基因與VFDB和PHAST兩個數(shù)據(jù)庫,我們發(fā)現(xiàn)某些基因組島中的必需基因編碼了與毒素相關(guān)的蛋白質(zhì)和抑制子。該研究將有助于必需基因預(yù)測算法的設(shè)計(jì),還會對基因組島的功能性研究(如必需性)提供線索。
[Abstract]:Prokaryotes, including bacteria and ancient bacteria, are involved in many fields, such as health, medicine, environment, energy and so on, and are closely related to human life. Genome island is a cluster of exogenous genes transferred horizontally in prokaryotes. It has been found that these genes are closely related to the pathogenicity, drug resistance, secretion, antimicrobial activity and metabolism of prokaryotes. Researchers at home and abroad have developed a large number of tools to identify genomic islands, such as the method of identifying genomic islands based on sequence composition, the method of identifying genomic islands based on sequence, the method of identifying genomic islands based on SIGI-HMMMM-Zisland Explorer, and the methods based on comparative genomes, Island-Pick and MobilomeFINDER.faced with a wide variety of methods for predicting genomic islands, It is very important to choose suitable methods. In the first half of this paper, the prediction results of prokaryote genomic islands are compared. The functional types and sequence characteristics of genome islands are introduced in this paper. Secondly, the common tools and network resources of genome island identification are introduced. Finally, we predict the genome islands of 28 prokaryotes by using a variety of representative identification methods. We found differences in the prediction results of different genomic island recognition methods. Based on the more credible prediction results of the prokaryote genome island, researchers gradually turned their attention to the functional and component analysis of the genome island. For example, by studying the drug resistance genes, we can further analyze the drug resistance mechanism of prokaryotes, so as to provide the basis for the development of new antibiotics and drug resistance targets. We have studied the essential genes in the genome island of prokaryotes and analyzed the essential genes in and out of the island. The essential genes are the genes that play a key role in cell survival. The encoded protein can maintain the basic function of cell survival. This paper first introduces the experimental recognition method of essential genes and related databases. The proportion of essential genes in and out of the island of 28 prokaryotes is further analyzed by statistical method. The results show that the proportion of essential genes in the island is significantly less than that outside the island. BLAST was used to compare 362 essential genes with two databases, VFDB and PHAST. We find that the essential genes in some genomic islands encode proteins and suppressor associated with toxins. This study will be helpful to the design of necessary gene prediction algorithms and will provide clues to the functional studies of genomic islands such as necessity.
【學(xué)位授予單位】：天津大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2016
【分類號】：Q78

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本文編號：1671945