Rahel Liesch: Statistical Genetics for the Budset in Norway Spruce

Adviser: Peter Bühlmann

March 2005

Abstract
Genetic variations is needed for plants to respond and adapt to environmental challenges. Understanding the genetic variation of adaptive traits and the forces that shaped it is one of the main goals of evolutionary biology. This is a difficult task, as most adaptive traits are quantitative traits, i.e. traits that are controlled by many loci intercting with the environment. The aim of this thesis was (i) to analyze the genetic variation of the timing of budset of Norway spruce (Picea abies L) within and among 15 populations covering the natural range of the species and (ii) to relate the variation among population for timing of budset with the variation observed at both neutral and candidate genes. The former was done through a classical ANOVA after choosing the adequate model. The latter was achieved by estimating and calculating confidence intervals for Wright's fixation indices (a measure of among-population differentiation) for budset, on the one hand, and neutral or candidate genes, on the other hand. Estimating confidence intervals for Wright's fixation index for quantitative trait, such as timing of busdet, has been and can be done in many different ways. In some studies the delta method has been used whereas in others nonparametric bootstrapping was favored. In almost all studies, the choice of a certain method was not justified or discussed, nor, when bootstrap was retained, was the choice of a particular bootstrap strategy of type warranted. We therefore simulated several datasets and applied miscellaneous methods to find the most appropriate method. We concluded that either a semiparametric of a parametric bootstrap gave the best results in the case of the spruce dataset. Using a nonparametric bootstrap, sampling over populations and families would definitely be the most adequate way of obtaining a confidence interval. Finally, Wright's fixation index for budset was significatly larger than differentiation at both candidate and neutral loci suggesting strong local adaptation.

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