Dataset Information

Comparison of different sequencing strategies for assembling chromosome-level genomes of extremophiles with variable GC content.

ABSTRACT: In this study, six bacterial isolates with variable GC, including Escherichia coli as mesophilic reference strain, were selected to compare hybrid assembly strategies based on next-generation sequencing (NGS) of short reads, single-tube long-fragment reads (stLFR) sequencing, and Oxford Nanopore Technologies (ONT) sequencing platforms. We obtained the complete genomes using the hybrid assembler Unicycler based on the NGS and ONT reads; others were de novo assembled using NGS, stLFR, and ONT reads by using different strategies. The contiguity, accuracy, completeness, sequencing costs, and DNA material requirements of the investigated strategies were compared systematically. Although all sequencing data could be assembled into accurate whole-genome sequences, the stLFR sequencing data yield a scaffold with more contiguity with more completeness of gene function than NGS sequencing assemblies. Our research provides a low-cost chromosome-level genome assembly strategy for large-scale sequencing of extremophile genomes with different GC contents.

SUBMITTER: Zhang Z

PROVIDER: S-EPMC7961107 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Comparison of different sequencing strategies for assembling chromosome-level genomes of extremophiles with variable GC content.

Zhang Zhidong Z Liu Guilin G Chen Yao Y Xue Weizhen W Ji Qianyue Q Xu Qiwu Q Zhang He H Fan Guangyi G Huang He H Jiang Ling L Chen Jianwei J

iScience 20210220 3

In this study, six bacterial isolates with variable GC, including <i>Escherichia coli</i> as mesophilic reference strain, were selected to compare hybrid assembly strategies based on next-generation sequencing (NGS) of short reads, single-tube long-fragment reads (stLFR) sequencing, and Oxford Nanopore Technologies (ONT) sequencing platforms. We obtained the complete genomes using the hybrid assembler Unicycler based on the NGS and ONT reads; others were <i>de novo</i> assembled using NGS, stLFR ...[more]

PMID: 33748707

Similar Datasets

Project description:BackgroundAs 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.ResultsMutator 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.ConclusionOur studies provide several lines of evidence indicating that DNA polymerase III ? 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.

Project description:The characterization of functional elements in genomes relies on the identification of the footprints of natural selection. In this quest, taking into account neutral evolutionary processes such as mutation and genetic drift is crucial because these forces can generate patterns that may obscure or mimic signatures of selection. In mammals, and probably in many eukaryotes, another such confounding factor called GC-Biased Gene Conversion (gBGC) has been documented. This mechanism generates patterns identical to what is expected under selection for higher GC-content, specifically in highly recombining genomic regions. Recent results have suggested that a mysterious selective force favouring higher GC-content exists in Bacteria but the possibility that it could be gBGC has been excluded. Here, we show that gBGC is probably at work in most if not all bacterial species. First we find a consistent positive relationship between the GC-content of a gene and evidence of intra-genic recombination throughout a broad spectrum of bacterial clades. Second, we show that the evolutionary force responsible for this pattern is acting independently from selection on codon usage, and could potentially interfere with selection in favor of optimal AU-ending codons. A comparison with data from human populations shows that the intensity of gBGC in Bacteria is comparable to what has been reported in mammals. We propose that gBGC is not restricted to sexual Eukaryotes but also widespread among Bacteria and could therefore be an ancestral feature of cellular organisms. We argue that if gBGC occurs in bacteria, it can account for previously unexplained observations, such as the apparent non-equilibrium of base substitution patterns and the heterogeneity of gene composition within bacterial genomes. Because gBGC produces patterns similar to positive selection, it is essential to take this process into account when studying the evolutionary forces at work in bacterial genomes.

Project description:BackgroundThe 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.ResultsWe 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.ConclusionNot 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.

Dataset Information

Comparison of different sequencing strategies for assembling chromosome-level genomes of extremophiles with variable GC content.

Publications

Comparison of different sequencing strategies for assembling chromosome-level genomes of extremophiles with variable GC content.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets