Evolutionary Genetics of Plants and Microorganisms

1. Molecular evolution: neutral and nearly neutral theory of evolution, mutation-drift equilibrium, natural selection, molecular clock, sexual/asexual reproduction and recombination, inbreeding, Hardy-Weinberg equilibrium.
2. Population genetics and their application in the genome analysis of plants and microorganisms: coalescence models, application of the coalescent in genome analysis for detection of selection, analysis of population structure, inference of past demographic history.
3. Population genetics and applications: genomics of crop domestication and plant breeding, genomics of human evolution and medicine, evolution of pathogens (bacteria, viruses, fungi), evolution of bacteria populations in laboratory experiments.

At the end of the module the students can 1) apply general methods for acquiring published data from internet databases. They 2) can independently analyze DNA sequences with the software DnaSP or PopGenom (in R). 3) The students understand the principles of evolutionary genetics and population genetics, for example the effects and change in frequencies of mutations in populations, the role of natural selection and link to phenotyping, and the role and importance of stochastic processes in evolution. They can analyze the effects of these mechanisms in genetic data, and independently apply such analyses on full genomes. 4) The students can apply, evaluate and critically discuss the basics of population genetics theory, especially for its application to plant breeding, animal breeding, human genetics (medicine) and changes in micro-organisms populations (bacteria, fungi). They are able to critically analyze published results in these areas, possibly further develop novel data analyses using full genomes and apply the concepts and techniques to any species.

The examination consists of a written exam (60 min). The students are given a set of statistics from published datasets or figures from publications. The aim is to demonstrate that the students can analyze and interpret genetic diversity data obtained as sequence of few genes or full genomes using all concepts from the course. The exam questions cover in particular the interpretation of the computed statistics. This includes, for example, understanding how statistics are computed, explaining the underlying principles of evolutionary genetics and population genetics, as well as evaluating and interpretating the results. The students should for example, explain how the various evolutionary forces influence sequence data polymorphism, and how the mathematical models presented in the course predict these outcomes.

Basic knowledge in genetics and statistics.

• Hartl and Clark, Principles of Population Genetics 4th Edition (2007); Hedrick, Genetics Of Populations 4th Edition (2009); Wakeley, Coalescent Theory: An Introduction (2008)

Teaching method: The course includes 2 SWS lectures and 2 SWS exercises. The lectures provide the theoretical and mathematical background to the theory of evolution. During exercises, the software DnaSP and PopGenome (in R) are used for sequence data analysis. In the exercises, the students apply the classical statistics computed from population polymorphism and also discuss their interpretation in connection to the theory. The paper presentation part of the course allows to exemplify the application of evolutionary theory to full genome data. Learning Activity: Study of scientific articles on evolution of pathogens, plant breeding, human evolution and laboratory evolution experiments and critical analysis of the published results. The exercises develop the process of problem solving and finding interpretation of the data.