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1.  On the molecular mechanism of GC content variation among eubacterial genomes 
Biology Direct  2012;7:2.
Background
As a key parameter of genome sequence variation, the GC content of bacterial genomes has been investigated for over half a century, and many hypotheses have been put forward to explain this GC content variation and its relationship to other fundamental processes. Previously, we classified eubacteria into dnaE-based groups (the dimeric combination of DNA polymerase III alpha subunits), according to a hypothesis where GC content variation is essentially governed by genome replication and DNA repair mechanisms. Further investigation led to the discovery that two major mutator genes, polC and dnaE2, may be responsible for genomic GC content variation. Consequently, an in-depth analysis was conducted to evaluate various potential intrinsic and extrinsic factors in association with GC content variation among eubacterial genomes.
Results
Mutator genes, especially those with dominant effects on the mutation spectra, are biased towards either GC or AT richness, and they alter genomic GC content in the two opposite directions. Increased bacterial genome size (or gene number) appears to rely on increased genomic GC content; however, it is unclear whether the changes are directly related to certain environmental pressures. Certain environmental and bacteriological features are related to GC content variation, but their trends are more obvious when analyzed under the dnaE-based grouping scheme. Most terrestrial, plant-associated, and nitrogen-fixing bacteria are members of the dnaE1|dnaE2 group, whereas most pathogenic or symbiotic bacteria in insects, and those dwelling in aquatic environments, are largely members of the dnaE1|polV group.
Conclusion
Our studies provide several lines of evidence indicating that DNA polymerase III α subunit and its isoforms participating in either replication (such as polC) or SOS mutagenesis/translesion synthesis (such as dnaE2), play dominant roles in determining GC variability. Other environmental or bacteriological factors, such as genome size, temperature, oxygen requirement, and habitat, either play subsidiary roles or rely indirectly on different mutator genes to fine-tune the GC content. These results provide a comprehensive insight into mechanisms of GC content variation and the robustness of eubacterial genomes in adapting their ever-changing environments over billions of years.
Reviewers
This paper was reviewed by Nicolas Galtier, Adam Eyre-Walker, and Eugene Koonin.
doi:10.1186/1745-6150-7-2
PMCID: PMC3274465  PMID: 22230424
2.  Nonsynonymous substitution rate (Ka) is a relatively consistent parameter for defining fast-evolving and slow-evolving protein-coding genes 
Biology Direct  2011;6:13.
Background
Mammalian genome sequence data are being acquired in large quantities and at enormous speeds. We now have a tremendous opportunity to better understand which genes are the most variable or conserved, and what their particular functions and evolutionary dynamics are, through comparative genomics.
Results
We chose human and eleven other high-coverage mammalian genome data–as well as an avian genome as an outgroup–to analyze orthologous protein-coding genes using nonsynonymous (Ka) and synonymous (Ks) substitution rates. After evaluating eight commonly-used methods of Ka and Ks calculation, we observed that these methods yielded a nearly uniform result when estimating Ka, but not Ks (or Ka/Ks). When sorting genes based on Ka, we noticed that fast-evolving and slow-evolving genes often belonged to different functional classes, with respect to species-specificity and lineage-specificity. In particular, we identified two functional classes of genes in the acquired immune system. Fast-evolving genes coded for signal-transducing proteins, such as receptors, ligands, cytokines, and CDs (cluster of differentiation, mostly surface proteins), whereas the slow-evolving genes were for function-modulating proteins, such as kinases and adaptor proteins. In addition, among slow-evolving genes that had functions related to the central nervous system, neurodegenerative disease-related pathways were enriched significantly in most mammalian species. We also confirmed that gene expression was negatively correlated with evolution rate, i.e. slow-evolving genes were expressed at higher levels than fast-evolving genes. Our results indicated that the functional specializations of the three major mammalian clades were: sensory perception and oncogenesis in primates, reproduction and hormone regulation in large mammals, and immunity and angiotensin in rodents.
Conclusion
Our study suggests that Ka calculation, which is less biased compared to Ks and Ka/Ks, can be used as a parameter to sort genes by evolution rate and can also provide a way to categorize common protein functions and define their interaction networks, either pair-wise or in defined lineages or subgroups. Evaluating gene evolution based on Ka and Ks calculations can be done with large datasets, such as mammalian genomes.
Reviewers
This article has been reviewed by Drs. Anamaria Necsulea (nominated by Nicolas Galtier), Subhajyoti De (nominated by Sarah Teichmann) and Claus O. Wilke.
doi:10.1186/1745-6150-6-13
PMCID: PMC3055854  PMID: 21342519
3.  Modeling compositional dynamics based on GC and purine contents of protein-coding sequences 
Biology Direct  2010;5:63.
Background
Understanding the compositional dynamics of genomes and their coding sequences is of great significance in gaining clues into molecular evolution and a large number of publically-available genome sequences have allowed us to quantitatively predict deviations of empirical data from their theoretical counterparts. However, the quantification of theoretical compositional variations for a wide diversity of genomes remains a major challenge.
Results
To model the compositional dynamics of protein-coding sequences, we propose two simple models that take into account both mutation and selection effects, which act differently at the three codon positions, and use both GC and purine contents as compositional parameters. The two models concern the theoretical composition of nucleotides, codons, and amino acids, with no prerequisite of homologous sequences or their alignments. We evaluated the two models by quantifying theoretical compositions of a large collection of protein-coding sequences (including 46 of Archaea, 686 of Bacteria, and 826 of Eukarya), yielding consistent theoretical compositions across all the collected sequences.
Conclusions
We show that the compositions of nucleotides, codons, and amino acids are largely determined by both GC and purine contents and suggest that deviations of the observed from the expected compositions may reflect compositional signatures that arise from a complex interplay between mutation and selection via DNA replication and repair mechanisms.
Reviewers
This article was reviewed by Zhaolei Zhang (nominated by Mark Gerstein), Guruprasad Ananda (nominated by Kateryna Makova), and Daniel Haft.
doi:10.1186/1745-6150-5-63
PMCID: PMC2989939  PMID: 21059261
4.  γ-MYN: a new algorithm for estimating Ka and Ks with consideration of variable substitution rates 
Biology Direct  2009;4:20.
Background
Over the past two decades, there have been several approximate methods that adopt different mutation models and used for estimating nonsynonymous and synonymous substitution rates (Ka and Ks) based on protein-coding sequences across species or even different evolutionary lineages. Among them, MYN method (a Modified version of Yang-Nielsen method) considers three major dynamic features of evolving DNA sequences–bias in transition/transversion rate, nucleotide frequency, and unequal transitional substitution but leaves out another important feature: unequal substitution rates among different sites or nucleotide positions.
Results
We incorporated a new feature for analyzing evolving DNA sequences–unequal substitution rates among different sites–into MYN method, and proposed a modified version, namely γ (gamma)-MYN, based on an assumption that the evolutionary rate at each site follows a mode of γ-distribution. We applied γ-MYN to analyze the key estimator of selective pressure ω (Ka/Ks) and other relevant parameters in comparison to two other related methods, YN and MYN, and found that neglecting the variation of substitution rates among different sites may lead to biased estimations of ω. Our new method appears to have minimal deviations when relevant parameters vary within normal ranges defined by empirical data.
Conclusion
Our results indicate that unequal substitution rates among different sites have variable influences on ω under different evolutionary rates while both transition/transversion rate ratio and unequal nucleotide frequencies affect Ka and Ks thus selective pressure ω.
Reviewers
This paper was reviewed by Kateryna Makova, David A. Liberles (nominated by David H Ardell), Zhaolei Zhang (nominated by Mark Gerstein), and Shamil Sunyaev.
doi:10.1186/1745-6150-4-20
PMCID: PMC2702329  PMID: 19531225

Results 1-4 (4)