INFERRING THE DEMOGRAPHIC HISTORY AND JOINT DISTRIBUTION OF FITNESS EFFECTS IN THE WILD HOUSE MOUSE, MUS MUSCULUS DOMESTICUS
Publisher
The University of Arizona.Rights
Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.Abstract
Much can be learned about a species' recent evolutionary past by fitting models to contemporary patterns of genetic variation. We aim to infer the distribution of mutation fitness effects (DFE) among multiple populations of wild house mice, so that the extensive knowledge of mouse molecular biology can be leveraged to understand the biological basis of the DFE. To infer the DFE, we first use synonymous mutations to infer a model of demographic history. Inferring a demographic history can be done for a single population or for two populations and helps us learn about population size(s), divergence time(s), migration rate(s), and level(s) of inbreeding. We then use the demographic model describing two populations to create a set of frequency spectra for nonsynonymous sites under a range of strengths of selection (selection coefficients), which allows us to infer the DFE. A distribution of fitness effects provides information about what proportions of mutations in nonsynonymous sites are deleterious, neutral, and advantageous, which can provide key input into the evolutionary process. We inferred demographic histories and DFEs for pairs of populations of Mus musculus domesticus from Iran and France, France and Germany, and Germany and Heligoland and found that in all population pairs, the best demographic models are those that include migration between populations following a distinct split into two populations and that account for potential inbreeding with populations. We also found that distributions of fitness effects had very high to perfect correlations for each population pair.Type
Electronic Thesistext
Degree Name
B.S.Degree Level
bachelorsDegree Program
Molecular and Cellular BiologyHonors College