The CoSMoS approach and pattern language has typically been used to guide the entire process of development and use of scientific simulators. The resulting CoSMoS components (domain, domain model, platform model, simulation platform and results models) provide an explicit framework for presenting and reasoning about both the engineering and scientific aspects of the simulator and its results. The flexibility of CoSMoS enables us to use the same patterns to reverse engineer CoSMoS model components from pre-existing simulators and associated research literature. We demonstrate this here by ap- plying the CoSMoS patterns to the Aevol (artificial evolution) simulator in order to extract an explicit Aevol domain model.
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Non-retroviral integrated RNA viruses (NIRVs) are genes of non-retroviral RNA viruses found in the genomes of many eukaryotic organisms. NIRVs are thought to sometimes confer virus resistance, meaning that they could impact spread of the virus in the host population. However, a NIRV that is expressed may also impact the evolution of virus populations within host organisms. Here, we experimentally addressed the evolution of a virus in a host expressing a NIRV using Tobacco etch virus, a plant RNA virus, and transgenic tobacco plants expressing its replicase, NIb. We found that a virus missing the NIb gene, TEV-ΔNIb, which is incapable of autonomous replication in wild-type plants, had a higher fitness than the full-length TEV in the transgenic plants. Moreover, when the full-length TEV was evolved by serial passages in transgenic plants we observed genomic deletions within NIb – and in some cases the adjacent cistrons – starting from the first passage. When we passaged TEV and TEV-ΔNIb in transgenic plants we found mutations in proteolytic sites, but these only occurred in TEV-ΔNIb lineages, suggesting the adaptation of polyprotein processing to altered NIb expression. These results raise the possibility that NIRV expression can indeed induce the deletion of the corresponding genes in the viral genome, resulting in the formation of viruses that are replication defective in hosts that do not express the same NIRV. Moreover, virus genome evolution was contingent upon the deletion of the viral replicase, suggesting NIRV expression could also alter patterns of virus evolution.
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Large-scale rearrangements may be important in evolution because they can alter chromosome organization and gene expression in ways not possible through point mutations. In a long-term evolution experiment, twelve Escherichia coli populations have been propagated in a glucose-limited environment for over 25 years. We used whole-genome mapping (optical mapping) combined with genome sequencing and PCR analysis to identify the large-scale chromosomal rearrangements in clones from each population after 40,000 generations. A total of 110 rearrangement events were detected, including 82 deletions, 19 inversions, and 9 duplications, with lineages having between 5 and 20 events. In three populations, successive rearrangements impacted particular regions. In five populations, rearrangements affected over a third of the chromosome. Most rearrangements involved recombination between insertion sequence (IS) elements, illustrating their importance in mediating genome plasticity. Two lines of evidence suggest that at least some of these rearrangements conferred higher fitness. First, parallel changes were observed across the independent populations, with ~65% of the rearrangements affecting the same loci in at least two populations. For example, the ribose-utilization operon and the manB-cpsG region were deleted in 12 and 10 populations, respectively, suggesting positive selection, and this inference was previously confirmed for the former case. Second, optical maps from clones sampled over time from one population showed that most rearrangements occurred early in the experiment, when fitness was increasing most rapidly. However, some rearrangements likely occur at high frequency and may have simply hitchhiked to fixation. In any case, large-scale rearrangements clearly influenced genomic evolution in these populations.
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We present a model for genome size evolution that takes into account both local mutations such as small insertions and small deletions, and large chromosomal rearrangements such as duplications and large deletions. We introduce the possibility of undergoing several mutations within one generation. The model, albeit minimalist, reveals a non-trivial spontaneous dynamics of genome size: in the absence of selection, an arbitrary large part of genomes remains beneath a finite size, even for a duplication rate 2.6-fold higher than the rate of large deletions, and even if there is also a systematic bias toward small insertions compared to small deletions. Specifically, we show that the condition of existence of an asymptotic stationary distribution for genome size non-trivially depends on the rates and mean sizes of the different mutation types. We also give upper bounds for the median and other quantiles of the genome size distribution, and argue that these bounds cannot be overcome by selection. Taken together, our results show that the spontaneous dynamics of genome size naturally prevents it from growing infinitely, even in cases where intuition would suggest an infinite growth. Using quantitative numerical examples, we show that, in practice, a shrinkage bias appears very quickly in genomes undergoing mutation accumulation, even though DNA gains and losses appear to be perfectly symmetrical at first sight. We discuss this spontaneous dynamics in the light of the other evolutionary forces proposed in the literature and argue that it provides them a stability-related size limit below which they can act.
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We present a model for genome size evolution that takes into account both local mutations such as small insertions and small deletions, and large chromosomal rearrangements such as duplications and large deletions. We introduce the possibility of undergoing several mutations within one generation. The model, albeit minimalist, reveals a non-trivial spontaneous dynamics of genome size: in the absence of selection, an arbitrary large part of genomes remains beneath a finite size, even for a duplication rate 2.6-fold higher than the rate of large deletions, and even if there is also a systematic bias toward small insertions compared to small deletions. Specifically, we show that the condition of existence of an asymptotic stationary distribution for genome size non-trivially depends on the rates and mean sizes of the different mutation types. We also give upper bounds for the median and other quantiles of the genome size distribution, and argue that these bounds cannot be overcome by selection. Taken together, our results show that the spontaneous dynamics of genome size naturally prevents it from growing infinitely, even in cases where intuition would suggest an infinite growth. Using quantitative numerical examples, we show that, in practice, a shrinkage bias appears very quickly in genomes undergoing mutation accumulation, even though DNA gains and losses appear to be perfectly symmetrical at first sight. We discuss this spontaneous dynamics in the light of the other evolutionary forces proposed in the literature and argue that it provides them a stability-related size limit below which they can act.
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