Comparing Mycobacterium tuberculosis genomes using genome topology networks

Jiang, Jianping, Gu, Jianlei, Zhang, Liang, Zhang, Chenyi, Deng, Xiao, Dou, Tonghai, Zhao, Guoping and Zhou, Yan (2015) Comparing Mycobacterium tuberculosis genomes using genome topology networks. BMC Genomics, 16 85: . doi:10.1186/s12864-015-1259-0


Author Jiang, Jianping
Gu, Jianlei
Zhang, Liang
Zhang, Chenyi
Deng, Xiao
Dou, Tonghai
Zhao, Guoping
Zhou, Yan
Title Comparing Mycobacterium tuberculosis genomes using genome topology networks
Journal name BMC Genomics   Check publisher's open access policy
ISSN 1471-2164
Publication date 2015-02-14
Year available 2015
Sub-type Article (original research)
DOI 10.1186/s12864-015-1259-0
Open Access Status DOI
Volume 16
Issue 85
Total pages 10
Place of publication London, United Kingdom
Publisher BioMed Central Ltd.
Language eng
Formatted 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/ webcite, 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.
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2016 Collection
School of Information Technology and Electrical Engineering Publications
 
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