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Modeling of the GC content of the substituted bases in bacterial core genomes

Overview of attention for article published in BMC Genomics, August 2018
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Title
Modeling of the GC content of the substituted bases in bacterial core genomes
Published in
BMC Genomics, August 2018
DOI 10.1186/s12864-018-4984-3
Pubmed ID
Authors

Jon Bohlin, Vegard Eldholm, Ola Brynildsrud, John H.-O. Petterson, Kristian Alfsnes

Abstract

The purpose of the present study was to examine the GC content of substituted bases (sbGC) in the core genomes of 35 bacterial species. Each species, or core genome, constituted genomes from at least 10 strains. We also wanted to explore whether sbGC for each strain was associated with the corresponding species' core genome GC content (cgGC). We present a simple mathematical model that estimates sbGC from cgGC. The model assumes only that the estimated sbGC is a function of cgGC proportional to fixed AT→GC (α) and GC → AT (β) mutation rates. Non-linear regression was used to estimate parameters α and β from the empirical data described above. We found that sbGC for each strain showed a non-linear association with the corresponding cgGC with a bias towards higher GC content for most core genomes (66.3% of the strains), assuming as a null-hypothesis that sbGC should be approximately equal to cgGC. The most GC rich core genomes (i.e. approximately %GC > 60), on the other hand, exhibited slightly less GC-biased sbGC than expected. The best fitted regression model indicates that GC → AT mutation rates β = (1.91 ± 0.13) p < 0.001 are approximately (1.91/0.79) = 2.42 times as high, on average, as AT→GC α = (- 0.79 ± 0.25) p < 0.001 mutation rates. Whether the observed sbGC GC-bias for all but the most GC-rich prokaryotic species is due to selection, compensating for the GC → AT mutation bias, and/or selective neutral processes is currently debated. Residual standard error was found to be σ = 0.076 indicating estimated errors of sbGC to be approximately within ±15.2% GC (95% confidence interval) for the strains of all species in the study. Not only did our mathematical model give reasonable estimates of sbGC it also provides further support to previous observations that mutation rates in prokaryotes exhibit a universal GC → AT bias that appears to be remarkably consistent between taxa.

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Mendeley readers

The data shown below were compiled from readership statistics for 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 21 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 24%
Student > Master 3 14%
Researcher 3 14%
Professor 2 10%
Student > Bachelor 2 10%
Other 2 10%
Unknown 4 19%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 8 38%
Computer Science 3 14%
Agricultural and Biological Sciences 3 14%
Chemical Engineering 1 5%
Social Sciences 1 5%
Other 2 10%
Unknown 3 14%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 07 August 2018.
All research outputs
#10,617,813
of 13,337,884 outputs
Outputs from BMC Genomics
#6,042
of 7,838 outputs
Outputs of similar age
#200,020
of 267,789 outputs
Outputs of similar age from BMC Genomics
#11
of 15 outputs
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