CoreSimul: a forward-in-time simulator of genome evolution for prokaryotes modeling homologous recombination

Bobay, Louis‐Marie

doi:10.1186/s12859-020-03619-x

Cited by 15 publications

(20 citation statements)

References 37 publications

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“…Because homoplasies can be introduced by convergent mutations as well as by recombination, we conducted genome simulations using CoreSimul [ 42 ] to establish the frequency of shared polymorphisms expected to occur solely by mutational processes. For each core genome alignment, we built a phylogenetic tree in RAxML v8 using the GTR + GAMMA model, and we estimated the transition to transversion ratio κ.…”

Section: Methodsmentioning

confidence: 99%

Recombination events are concentrated in the spike protein region of Betacoronaviruses

2020

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The Betacoronaviruses comprise multiple subgenera whose members have been implicated in human disease. As with SARS, MERS and now SARS-CoV-2, the origin and emergence of new variants are often attributed to events of recombination that alter host tropism or disease severity. In most cases, recombination has been detected by searches for excessively similar genomic regions in divergent strains; however, such analyses are complicated by the high mutation rates of RNA viruses, which can produce sequence similarities in distant strains by convergent mutations. By applying a genome-wide approach that examines the source of individual polymorphisms and that can be tested against null models in which recombination is absent and homoplasies can arise only by convergent mutations, we examine the extent and limits of recombination in Betacoronaviruses. We find that recombination accounts for nearly 40% of the polymorphisms circulating in populations and that gene exchange occurs almost exclusively among strains belonging to the same subgenus. Although experimental studies have shown that recombinational exchanges occur at random along the coronaviral genome, in nature, they are vastly overrepresented in regions controlling viral interaction with host cells.

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Section: Methodsmentioning

confidence: 99%

Recombination events are concentrated in the spike protein region of Betacoronaviruses

2020

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“…1 ). Simulations were conducted with CoreSimul ( 53 ) either by introducing SNPs randomly along each sequence to test the impact of PCR artifacts or by introducing SNPs with different probabilities across codon positions to test the effect of purifying sequence on strain inference. The relative probability of substitutions across codon positions was defined empirically based on the distribution of observed SNPs across the distinct strains inferred by each marker: 0.12, 0.10, and 0.78 for guaA , 0.17, 0.04, and 0.79 for gluS , 0.14, 0.04, and 0.82 for pflA , and 0.20, 0.09, and 0.71 for rimM at the first, second, and third codon positions, respectively.…”

Section: Methodsmentioning

confidence: 99%

Strain Structure and Dynamics Revealed by Targeted Deep Sequencing of the Honey Bee Gut Microbiome

Bobay

Wissel

Raymann

2020

mSphere

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Host-associated microbiomes can be critical for the health and proper development of animals and plants. The answers to many fundamental questions regarding the modes of acquisition and microevolution of microbiome communities remain to be established. Deciphering strain-level dynamics is essential to fully understand how microbial communities evolve, but the forces shaping the strain-level dynamics of microbial communities remain largely unexplored, mostly because of methodological issues and cost. Here, we used targeted strain-level deep sequencing to uncover the strain dynamics within a host-associated microbial community using the honey bee gut microbiome as a model system. Our results revealed that amplicon sequencing of conserved protein-coding gene regions using species-specific primers is a cost-effective and accurate method for exploring strain-level diversity. In fact, using this method we were able to confirm strain-level results that have been obtained from whole-genome shotgun sequencing of the honey bee gut microbiome but with a much higher resolution. Importantly, our deep sequencing approach allowed us to explore the impact of low-frequency strains (i.e., cryptic strains) on microbiome dynamics. Results show that cryptic strain diversity is not responsible for the observed variations in microbiome composition across bees. Altogether, the findings revealed new fundamental insights regarding strain dynamics of host-associated microbiomes. IMPORTANCE The factors driving fine-scale composition and dynamics of gut microbial communities are poorly understood. In this study, we used metagenomic amplicon deep sequencing to decipher the strain dynamics of two key members of the honey bee gut microbiome. Using this high-throughput and cost-effective approach, we were able to confirm results from previous large-scale whole-genome shotgun (WGS) metagenomic sequencing studies while also gaining additional insights into the community dynamics of two core members of the honey bee gut microbiome. Moreover, we were able to show that cryptic strains are not responsible for the observed variations in microbiome composition across bees.

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“…However, these simulations were conducted by introducing exactly one recombination event at each informative site and it is di cult to compare this analysis to the actual levels of recombination occurring across prokaryote species. To assess the effect of recombination rate on our ability to reconstruct accurate phylogenies in prokaryotes, we simulated the evolution of core genomes with various levels of recombination using CoreSimul [40]. In order to mimic realistic conditions, we used a previously published set of 100 core genomes encompassing 13 major prokaryotic phyla (99 bacteria and one archaeon), different lifestyles (e.g.…”

Section: Impact Of Recombination Rate On Tree Inferencementioning

confidence: 99%

“…We conducted independent sets of simulations for each of the 100 core genome datasets using CoreSimul [40]. Simulations were initiated by generating a random circular genome composed of 100,000 nucleotides with the same nucleotide composition (i.e.…”

Section: Simulationsmentioning

confidence: 99%

“…The simulated genomes were then used to build phylogenetic trees (see above) and the topology of each these trees was compared to the topology of the tree built on the actual core genome of the corresponding species. The scripts used to run these simulations have been assembled into the CoreSimul program, which can be freely downloaded at https://github.com/lbobay/CoreSimul [40].…”

Section: Simulationsmentioning

confidence: 99%

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Impact of homologous recombination on core genome phylogenies

Stott

Bobay

2020

Preprint

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Background. Core genome phylogenies are widely used to build the evolutionary history of individual prokaryote species. By using hundreds or thousands of shared genes, these approaches are the gold standard to reconstruct the relationships of large sets of strains. However, there is growing evidence that bacterial strains exchange DNA through homologous recombination at rates that vary widely across prokaryote species, indicating that core genome phylogenies might not be able to reconstruct true phylogenies when recombination rate is high. Few attempts have been made to evaluate the robustness of core genome phylogenies to recombination, but some analyses suggest that reconstructed trees are not always accurate.Results. In this study, we tested the robustness of core genome phylogenies to various levels of recombination rates. By analyzing simulated and empirical data, we observed that core genome phylogenies are relatively robust to recombination rates; nevertheless, our results suggest that many reconstructed trees are not completely accurate even when bootstrap supports are high. We found that some core genome phylogenies are highly robust to recombination whereas others are strongly impacted by it, and we identified that the robustness of core genome phylogenies to recombination is highly linked to the levels of selective pressures acting on a species. Stronger selective pressures lead to less accurate tree reconstructions, presumably because selective pressures more strongly bias the routes of DNA transfers, thereby causing phylogenetic artifacts. Conclusions. Overall, these results have important implications for the application of core genome phylogenies in prokaryotes.

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CoreSimul: a forward-in-time simulator of genome evolution for prokaryotes modeling homologous recombination

Cited by 15 publications

References 37 publications

Recombination events are concentrated in the spike protein region of Betacoronaviruses

Recombination events are concentrated in the spike protein region of Betacoronaviruses

Strain Structure and Dynamics Revealed by Targeted Deep Sequencing of the Honey Bee Gut Microbiome

Impact of homologous recombination on core genome phylogenies

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