title: Comparing Mycobacterium tuberculosis genomes using genome topology networks.
abstract: BACKGROUND
  Over the last decade, emerging research methods, such as comparative genomic analysis and phylogenetic study, have yielded new insights into genotypes and phenotypes of closely related bacterial strains. Several findings have revealed that genomic structural variations (SVs), including gene gain/loss, gene duplication and genome rearrangement, can lead to different phenotypes among strains, and an investigation of genes affected by SVs may extend our knowledge of the relationships between SVs and phenotypes in microbes, especially in pathogenic bacteria.
  
  
  RESULTS
  In this work, we introduce a 'Genome Topology Network' (GTN) method based on gene homology and gene locations to analyze genomic SVs and perform phylogenetic analysis. Furthermore, the concept of 'unfixed ortholog' has been proposed, whose members are affected by SVs in genome topology among close species. To improve the precision of 'unfixed ortholog' recognition, a strategy to detect annotation differences and complete gene annotation was applied. To assess the GTN method, a set of thirteen complete M. tuberculosis genomes was analyzed as a case study. GTNs with two different gene homology-assigning methods were built, the Clusters of Orthologous Groups (COG) method and the orthoMCL clustering method, and two phylogenetic trees were constructed accordingly, which may provide additional insights into whole genome-based phylogenetic analysis. We obtained 24 unfixable COG groups, of which most members were related to immunogenicity and drug resistance, such as PPE-repeat proteins (COG5651) and transcriptional regulator TetR gene family members (COG1309).
  
  
  CONCLUSIONS
  The GTN method has been implemented in PERL and released on our website. The tool can be downloaded from http://homepage.fudan.edu.cn/zhouyan/gtn/ , and allows re-annotating the 'lost' genes among closely related genomes, analyzing genes affected by SVs, and performing phylogenetic analysis. With this tool, many immunogenic-related and drug resistance-related genes were found to be affected by SVs in M. tuberculosis genomes. We believe that the GTN method will be suitable for the exploration of genomic SVs in connection with biological features of bacterial strains, and that GTN-based phylogenetic analysis will provide additional insights into whole genome-based phylogenetic analysis.
authors.affiliation: State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, 200433, People's Republic of China. 11210700012@fudan.edu.cn.|Shanghai-MOST Key Laboratory of Health and Disease Genomics, Chinese National Human Genome Center at Shanghai, Shanghai, 201203, People's Republic of China. 11210700012@fudan.edu.cn.
authors.forename: Jianping
authors.initials: J
authors.lastname: Jiang
authors.affiliation: State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, 200433, People's Republic of China. jianleigu@gmail.com.|Shanghai-MOST Key Laboratory of Health and Disease Genomics, Chinese National Human Genome Center at Shanghai, Shanghai, 201203, People's Republic of China. jianleigu@gmail.com.
authors.forename: Jianlei
authors.initials: J
authors.lastname: Gu
authors.affiliation: Shanghai-MOST Key Laboratory of Health and Disease Genomics, Chinese National Human Genome Center at Shanghai, Shanghai, 201203, People's Republic of China. bright0000@gmail.com.
authors.forename: Liang
authors.initials: L
authors.lastname: Zhang
authors.affiliation: School of Information Technology and Electrical Engineering, The University of Queensland, St Lucia, QLD 4072, Australia. chenyi@uq.edu.au.
authors.forename: Chenyi
authors.initials: C
authors.lastname: Zhang
authors.affiliation: Institutes of Biology and Medical Sciences, Soochow University, Suzhou, 215123, People's Republic of China. dengxiaonothing@yeah.net.
authors.forename: Xiao
authors.initials: X
authors.lastname: Deng
authors.affiliation: State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, 200433, People's Republic of China. tonghaidou@fudan.edu.cn.
authors.forename: Tonghai
authors.initials: T
authors.lastname: Dou
authors.affiliation: State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, 200433, People's Republic of China. gpzhao@sibs.ac.cn.|Shanghai-MOST Key Laboratory of Health and Disease Genomics, Chinese National Human Genome Center at Shanghai, Shanghai, 201203, People's Republic of China. gpzhao@sibs.ac.cn.
authors.forename: Guoping
authors.initials: G
authors.lastname: Zhao
authors.affiliation: State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, 200433, People's Republic of China. zhouy@fudan.edu.cn.|Shanghai-MOST Key Laboratory of Health and Disease Genomics, Chinese National Human Genome Center at Shanghai, Shanghai, 201203, People's Republic of China. zhouy@fudan.edu.cn.
authors.forename: Yan
authors.initials: Y
authors.lastname: Zhou
mesh_terms: D019295:Computational Biology; D019143:Evolution, Molecular; D016680:Genome, Bacterial; D006801:Humans; D009169:Mycobacterium tuberculosis / Q000235:genetics* / Q000472:pathogenicity; D010802:Phylogeny; D014376:Tuberculosis / Q000235:genetics* / Q000382:microbiology