基因组时代的计算微生物学  

Computational microbiology in genomic era

作　　者：左光宏[1] 郝柏林[1,2] ZUO GuangHong HAO BaiLin(Department of Physics and T-Life Research Center, Fudan University, Shanghai 200433, China Institute of Theoretical Physics, Academia Sinica, Beijing 100190, China)

机构地区：[1]复旦大学物理系,理论生命科学研究中心,上海200433 [2]中国科学院理论物理研究所,北京100190

出　　处：《中国科学：生命科学》2017年第2期159-170,共12页Scientia Sinica(Vitae)

基　　金：国家重大科学研究计划(批准号:2007CB814800,2013CB834100)资助

摘　　要：微生物基因组和RNA序列构成生物学数据的重要部分.从基因组出发而且不用序列联配的CVTree和基于16S rRNA序列联配的LVTree,是两套原始数据和计算过程相互独立的构建原核生物亲缘树和分类系统的途径.这两套途径的自动化,使亲缘关系和分类系统成为大数据分析的副产品,可以帮助后继乏人的分类学摆脱困境.特别是基于基因组的CVTree,既提供了大范围研究的工具,又在种以下具有16SrRNA序列分析所不能企及的高分辨力,可以提出和解决一批新问题,开辟若干新方向.本文是相关研究工作的扼要综述.Microbial genomes and RNA sequences comprise an important part of biological big data.CVTree is a whole-genome based and alignment-free method whereas LVTree is based on alignment of 16 S rRNA sequences.They provide two independent ways to construct phylogenetic trees and to extract taxonomic information for prokaryotes.The automation of these two approaches make the study of prokaryotic phytogeny and classification by-product of big data analysis and come as a rescue to the declining discipline of taxonomy.Especially,the whole-genome based CVTree not only provides a tool for large-scale study but also possesses high resolution power at the species level and below,a distinctive feature beyond the reach of 16 S rRNA sequence analysis.These methods taken together may open new directions in microbiological research.This paper is a brief review of our recent work.

关 键 词：原核生物 亲缘树 分类系统 不用序列联配的基因组比较 CVTree LVTree 

分 类 号：Q811.4[生物学—生物工程]