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A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
Published on: December 9, 2015
A structured coalescent process for seasonally fluctuating populations
Max Shpak1, John Wakeley, Daniel Garrigan
1Department of Biological Sciences, University of Texas at El Paso, El Paso, Texas 79968, USA. mshpak@utep.edu
Abstract:
Many short-lived organisms pass through several generations during favorable growing seasons, separated by inhospitable periods during which only small hibernating or estivating refugia remain. This induces pronounced seasonal fluctuations in population size and metapopulation structure. The first generations in the growing season will be characterized by small, relatively isolated demes whereas the later generations will experience larger deme sizes with more extensive gene flow. Fluctuations of this sort can induce changes in the amount of genetic variation in early season samples compared to late season samples, a classical example being the observations of seasonal variation in allelism in New England Drosophila populations by P.T. Ives. In this article, we study the properties of a structured coalescent process under seasonal fluctuations using numerical analysis of exact state equations, analytical approximations that rely on a separation of timescales between intrademic versus interdemic processes, and individual-based simulations. We show that although an increase in genetic variation during each favorable growing season is observed, it is not as pronounced as in the empirical observations. This suggests that some of the temporal patterns of variation seen by Ives may be due to selection against deleterious lethals rather than neutral processes.
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