Explorations in studying natural selection

The three main chapters of my thesis are three projects I did during my Ph.D. The exact topics are rather disparate. The coherent framework piecing them together is natural selection, one of the central topics in population genetics.;The first chapter stands as a short introduction to the three main chapters.;In the second chapter, I studied patterns of adaptive evolution of influenza H3N2 virus. One of the major motivations for studying influenza viral evolution is that patterns of molecular evolution might give instructive hints about forecasting which viral strains might be the major cause for the upcoming epidemic season. Especially, there is this notion that future epidemics are more likely to arise from the strains in which positive selection on the so-called "trunk lineages" of the evolutionary tree is most pervasive. This is especially important for vaccine design and general public health. In our study, we used a maximum-likelihood based method to study the distributions of mutations on the phylogeny. We find no differences in the strength of selection along the trunk lineages versus other evolutionary lineages in terms of dn/ds ratios. Our results suggest that it may be more difficult to use inferences regarding the strength of selection on mutations to make predictions regarding viral epidemics than previously thought.;In the third chapter, we investigate the statistical power of several tests of selective neutrality based on patterns of genetic diversity within and between species. The goal is to compare tests based solely on population genetic data with tests using comparative data or a combination of comparative and population genetic data. We show that in the presence of repeated selective sweeps on relatively neutral background, tests based on the dn/ds ratios in comparative data almost always have more power to detect selection than tests based on population genetic data, even if the overall level of divergence is low. Tests based solely on the distribution of allele frequencies or the site frequency spectrum, such as the Ewens-Watterson test or Tajima's D, have less power in detecting both positive and negative selection because of the transient nature of positive selection and the weak signal left by negative selection. The Hudson-Kreitman Aguadé (HKA) test is the most powerful test for detecting positive selection among the population genetic tests investigated, while MacDonald-Kreitman (MK) test typically has more power to detect negative selection. We discuss our findings in the light of the discordant results obtained in several recently published genomic scans.;In the fourth chapter, I explore the classical example of balancing selected system-the human major histocompatibility complex. There are two major goals we are trying to address in this chapter. First of all, what are the forces generating the observed genetic diversity within population and divergence between species. Secondly, we are trying to develop a method in the framework of strong selection weak mutation (SSWM) to model the changes in allele frequency across different populations under a branching population history. Patterns of diversity between and within species give supports for a larger effective population size in the human ancestral population than current estimates. We develop a simple model for capturing differences in allele frequencies among populations and we discuss major limitations and hurdles in our current method.