title: Multiple Factors Drive Replicating Strand Composition Bias in Bacterial Genomes.
abstract: Composition bias from Chargaff's second parity rule (PR2) has long been found in sequenced genomes, and is believed to relate strongly with the replication process in microbial genomes. However, some disagreement on the underlying reason for strand composition bias remains. We performed an integrative analysis of various genomic features that might influence composition bias using a large-scale dataset of 1111 genomes. Our results indicate (1) the bias was stronger in obligate intracellular bacteria than in other free-living species (p-value=0.0305); (2) Fusobacteria and Firmicutes had the highest average bias among the 24 microbial phyla analyzed; (3) the strength of selected codon usage bias and generation times were not observably related to strand composition bias (p-value=0.3247); (4) significant negative relationships were found between GC content, genome size, rearrangement frequency, Clusters of Orthologous Groups (COG) functional subcategories A, C, I, Q, and composition bias (p-values<1.0×10(-8)); (5) gene density and COG functional subcategories D, F, J, L, and V were positively related with composition bias (p-value<2.2×10(-16)); and (6) gene density made the most important contribution to composition bias, indicating transcriptional bias was associated strongly with strand composition bias. Therefore, strand composition bias was found to be influenced by multiple factors with varying weights.
authors.affiliation: Center of Bioinformatics, Key Laboratory for NeuroInformation of the Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China. biohellen@gmail.com.|Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu 610054, China. biohellen@gmail.com.
authors.forename: Hai-Long
authors.initials: HL
authors.lastname: Zhao
authors.affiliation: Center of Bioinformatics, Key Laboratory for NeuroInformation of the Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China. xiazhk@163.com.|Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu 610054, China. xiazhk@163.com.
authors.forename: Zhong-Kui
authors.initials: ZK
authors.lastname: Xia
authors.affiliation: Center of Bioinformatics, Key Laboratory for NeuroInformation of the Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China. fzzhang@cefg.cn.|Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu 610054, China. fzzhang@cefg.cn.
authors.forename: Fa-Zhan
authors.initials: FZ
authors.lastname: Zhang
authors.affiliation: Center of Bioinformatics, Key Laboratory for NeuroInformation of the Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China. ynye@cefg.cn.|Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu 610054, China. ynye@cefg.cn.
authors.forename: Yuan-Nong
authors.initials: YN
authors.lastname: Ye
authors.affiliation: Center of Bioinformatics, Key Laboratory for NeuroInformation of the Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China. fbguo@uestc.edu.cn.|Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu 610054, China. fbguo@uestc.edu.cn.
authors.forename: Feng-Biao
authors.initials: FB
authors.lastname: Guo
mesh_terms: D001419:Bacteria / Q000235:genetics*; D001482:Base Composition; D018628:Gene Dosage; D005798:Genes, Bacterial; D016680:Genome, Bacterial; D025341:Principal Component Analysis; D011995:Recombination, Genetic
keywords: COG functional category; gene density; genomic features; multiple factors; obligate intracellular bacteria; strand composition bias