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Title: The estimation of recombination rates from population genetic data
Author: Auton, Adam
ISNI:       0000 0004 2743 6103
Awarding Body: University of Oxford
Current Institution: University of Oxford
Date of Award: 2007
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Genetic recombination is an important process that generates new combinations of genes on which natural selection can operate. As such, an understanding of recombination in the human genome will provide insight into the evolutionary processes that have shaped our genetic history. The aim of this thesis is to use samples of population genetic data to explore the patterns of variation in the rate of recombination in the human genome. To do this I introduce a novel means of estimating recombination rates from population genetic data. The new, computationally efficient method incorporates a model of recombination hotspots that was absent in existing methods. I use samples from the International HapMap Project to obtain recombination rate estimates for the autosomal portion of the genome. Using these estimates, I demonstrate that recombination has a number of interesting relationships with other genome features such as genes, DNA repeats, and sequence motifs. Furthermore, I show that genes of differing function have significantly different rates of recombination. I explore the relationship between recombination and specific sequence motifs and argue that while sequence motifs are an important factor in determining the location of recombination hotspots, the factor that controls motif activity is unknown. The observation of many relationships between recombination and other genome features motivates an attempt to quantify the contributions to the recombination rate from specific features. I employ a wavelet analysis to investigate scale-specific patterns of recombination. In doing so, I reveal a number of highly significant correlations between recombination and other features of the genome at both the fine and broad scales, but find that relatively little of the variation in recombination rates can be explained. I conclude with a discussion of the results contained in the body of the thesis, and suggest a number of areas for future research.
Supervisor: McVean, Gilean Sponsor: Engineering and Physical Sciences Research Council
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Bioinformatics (life sciences) ; Genetics (life sciences) ; Mathematical genetics and bioinformatics (statistics) ; genetic recombination