Inferring fitness effects from time-resolved sequence data with a delay-deterministic model

Nené, N. R., Dunham, A. S. and Illingworth, C. J. R. (2018) Inferring fitness effects from time-resolved sequence data with a delay-deterministic model. Genetics, 209(1), pp. 255-264. (doi: 10.1534/genetics.118.300790) (PMID:29500183) (PMCID:PMC5937181)

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Abstract

A common challenge arising from the observation of an evolutionary system over time is to infer the magnitude of selection acting upon a specific genetic variant, or variants, within the population. The inference of selection may be confounded by the effects of genetic drift in a system, leading to the development of inference procedures to account for these effects. However, recent work has suggested that deterministic models of evolution may be effective in capturing the effects of selection even under complex models of demography, suggesting the more general application of deterministic approaches to inference. Responding to this literature, we here note a case in which a deterministic model of evolution may give highly misleading inferences, resulting from the nondeterministic properties of mutation in a finite population. We propose an alternative approach that acts to correct for this error, and which we denote the delay-deterministic model. Applying our model to a simple evolutionary system, we demonstrate its performance in quantifying the extent of selection acting within that system. We further consider the application of our model to sequence data from an evolutionary experiment. We outline scenarios in which our model may produce improved results for the inference of selection, noting that such situations can be easily identified via the use of a regular deterministic model.

Item Type:Articles
Additional Information:This work was supported by a Sir Henry Dale Fellowship, jointly funded by the Wellcome Trust and the Royal Society (grant number 101239/Z/13/Z).
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Illingworth, Dr Chris
Authors: Nené, N. R., Dunham, A. S., and Illingworth, C. J. R.
College/School:College of Medical Veterinary and Life Sciences > School of Infection & Immunity
College of Medical Veterinary and Life Sciences > School of Infection & Immunity > Centre for Virus Research
Journal Name:Genetics
Publisher:Genetics Society of America
ISSN:0016-6731
ISSN (Online):1943-2631
Published Online:02 March 2018

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