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Evaluating genetic drift in time-series evolutionary analysis.

ABSTRACT: The Wright-Fisher model is the most popular population model for describing the behaviour of evolutionary systems with a finite population size. Approximations have commonly been used but the model itself has rarely been tested against time-resolved genomic data. Here, we evaluate the extent to which it can be inferred as the correct model under a likelihood framework. Given genome-wide data from an evolutionary experiment, we validate the Wright-Fisher drift model as the better option for describing evolutionary trajectories in a finite population. This was found by evaluating its performance against a Gaussian model of allele frequency propagation. However, we note a range of circumstances under which standard Wright-Fisher drift cannot be correctly identified.

SUBMITTER: R Nene N

PROVIDER: S-EPMC5703635 | biostudies-literature | 2018 Jan

REPOSITORIES: biostudies-literature

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Evaluating genetic drift in time-series evolutionary analysis.

R Nené Nuno N Mustonen Ville V J R Illingworth Christopher C

Journal of theoretical biology 20170925

The Wright-Fisher model is the most popular population model for describing the behaviour of evolutionary systems with a finite population size. Approximations have commonly been used but the model itself has rarely been tested against time-resolved genomic data. Here, we evaluate the extent to which it can be inferred as the correct model under a likelihood framework. Given genome-wide data from an evolutionary experiment, we validate the Wright-Fisher drift model as the better option for descr ...[more]

PMID: 28958783

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Project description:BACKGROUND:Red Queen dynamics are defined as long term co-evolutionary dynamics, often with oscillations of genotype abundances driven by fluctuating selection in host-parasite systems. Much of our current understanding of these dynamics is based on theoretical concepts explored in mathematical models that are mostly (i) deterministic, inferring an infinite population size and (ii) evolutionary, thus ecological interactions that change population sizes are excluded. Here, we recall the different mathematical approaches used in the current literature on Red Queen dynamics. We then compare models from game theory (evo) and classical theoretical ecology models (eco-evo), that are all derived from individual interactions and are thus intrinsically stochastic. We assess the influence of this stochasticity through the time to the first loss of a genotype within a host or parasite population. RESULTS:The time until the first genotype is lost ("extinction time"), is shorter when ecological dynamics, in the form of a changing population size, is considered. Furthermore, when individuals compete only locally with other individuals extinction is even faster. On the other hand, evolutionary models with a fixed population size and competition on the scale of the whole population prolong extinction and therefore stabilise the oscillations. The stabilising properties of intra-specific competitions become stronger when population size is increased and the deterministic part of the dynamics gain influence. In general, the loss of genotype diversity can be counteracted with mutations (or recombination), which then allow the populations to recurrently undergo negative frequency-dependent selection dynamics and selective sweeps. CONCLUSION:Although the models we investigated are equal in their biological motivation and interpretation, they have diverging mathematical properties both in the derived deterministic dynamics and the derived stochastic dynamics. We find that models that do not consider intraspecific competition and that include ecological dynamics by letting the population size vary, lose genotypes - and thus Red Queen oscillations - faster than models with competition and a fixed population size.

Project description:BackgroundPublicly-funded drug plans often use prior authorization policies to limit drug prescribing. To guide physician prescribing of a class of antibiotics with broad antimicrobial activity (quinolone antibiotics) in accordance with new prescribing guidelines, Alberta's provincial health ministry implemented a new mechanism for formulary restriction entitled the optional special authorization (OSA) program. We conducted an observational study to determine the impact of this new formulary restriction policy on antimicrobial prescription rates as well as any clinical consequences.MethodsQuinolone antibiotic use, and adherence with quinolone prescribing guidelines, was assessed before and after implementation of the OSA program in patients with common outpatient infections using an administrative data cohort and a chart review cohort, respectively. At the same time this policy was implemented to limit quinolone prescribing, two new quinolone antibiotics were added to the formulary. Using administrative data, we analysed a total of 397,534 unique index visits with regard to overall antibiotic utilization, and through chart review, we analysed 1681 charts of patients with infections of interest to determine the indications for quinolone usage.ResultsUsing segmented regression models adjusting for age, sex and physician enrollment in the OSA program, there was no statistically significant change in the monthly rate of all quinolone use (-3.5 (95% CI -5.5, 1.4) prescriptions per 1000 index visits) following implementation of the OSA program (p = 0.74). There was a significant level change in the rate of quinolone antibiotic use for urinary tract infection (-33.6 (95% CI: -23.8, -43.4) prescriptions and upper respiratory tract infection (-16.1 (95%CI: -11.6, -20.6) prescriptions per 1000 index visits. Among quinolone prescriptions identified on chart review, 42.5% and 58.5% were consistent with formulary guidelines before and after the implementation of the OSA program, respectively (p = 0.002). There was no change in hospitalization, mortality or use of physician services after implementation of the OSA program.ConclusionsDespite the addition of two new quinolone antibiotics to the formulary, we found that there was no change in the use of quinolones after implementation of a new formulary restriction policy for outpatients with common outpatient infections.

Dataset Information

Evaluating genetic drift in time-series evolutionary analysis.

Publications

Evaluating genetic drift in time-series evolutionary analysis.

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