原核生物基因组岛预测结果比较及岛内必需基因分析

发布时间：2018-03-27 14:40

本文选题：基因组岛　切入点：必需基因　出处：《天津大学》2016年硕士论文

【摘要】：原核生物包括细菌和古菌,涉及健康、医药、环境、能源等诸多领域,与人类生活休戚相关。基因组岛是原核生物中水平转移来的一簇外源基因,经研究发现这些基因与原核生物的致病、耐药、分泌、抗菌和代谢等密切相关。基于基因组岛上出现的某些序列特征或对不同物种间的基因组进行序列比较,国内外科研人员已经研发出了大量识别基因组岛的工具,比如基于序列组成的识别基因组岛的方法IslandPath,SIGI-HMM,Zisland Explorer和基于比较基因组的方法Island-Pick和MobilomeFINDER。面对种类繁多的基因组岛预测方法,如何选择合适的方法就显得尤为重要。本文的前半部分工作着重对原核生物基因组岛预测结果进行比较。文中先介绍了基因组岛的功能类型和序列特性,其次介绍了目前常用的基因组岛识别工具和网络资源,最后我们用多种代表性的识别方法预测了28个原核生物的基因组岛。通过与实验预测基因组岛的比较,我们发现了不同基因组岛识别方法在预测结果上的差异。基于比较可信的原核生物基因组岛预测结果,科研人员逐渐把目光转向了基因组岛上的功能和成分分析,比如通过研究其中的耐药基因,可以进一步分析原核生物耐药机理,从而为研制新的抗生素和耐药靶点提供依据。在本文的后半部分,我们研究了原核生物基因组岛中的必需基因,并对岛内外必需基因进行了统计分析。必需基因是指对细胞生存起关键作用的基因,所编码的蛋白质能够维持细胞存活的基本功能。文中先介绍了必需基因的实验识别方法和相关数据库。其次,通过统计学方法进一步分析了28个原核生物岛内和岛外必需基因的比例,结果发现必需基因在岛内要比岛外显著地少。最后,通过BLAST比对基因组岛上362个必需基因与VFDB和PHAST两个数据库,我们发现某些基因组岛中的必需基因编码了与毒素相关的蛋白质和抑制子。该研究将有助于必需基因预测算法的设计,还会对基因组岛的功能性研究(如必需性)提供线索。
[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.
【学位授予单位】：天津大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：Q78

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