The group of Diethard Tautz is interested in the identification and characterization of genes involved in adaptation processes using the house mouse (Mus musculus) as a model system. It applies a broad range of genomic techniques, but also behavioral, morphological and mapping approaches. The characterization of the identified genes includes experiments in semi-natural environments.
Current research of the department is organized in many major projects, which investigate amongst others selective sweep analysis, copy-number evolution, morphology and genes, parallel selection mapping, mating and utrasound communication and de-novo evolution of genes. [more]
Research in the fledgling bioinformatics group is focused on two topics: computational genomics and speciation. In computational genomics we use modern string algorithms based on suffix trees to compare closely related genomes. [more]
The group's aim is to understand how complex molecular systems evolve. Our research is therefore at the interface of molecular evolution and systems biology. Complex systems are characterized by distinct levels of organization, comprising various systems in interaction. As a given system's properties result from the interactions of its constitutive subsystems, it is fundamental to characterize these interactions to understand evolution at both levels. In order to achieve this goal, we are using evolutionary comparative analysis of sequences, modeling of sequence evolution and molecular dynamics, but also bioinformatic and statistical analysis.
Our current projects include (i) the impact of biomolecules (RNA and proteins) structures on sequence (co)evolution and (ii) the effect of stochasticity in gene regulation.
Research interests of the Research Group Meiotic Recombination and Genome Instability revolve around meiotic recombination, the regulation of accurate recombination placement and its impact on genome dynamics. We use single-molecule and small-pool allele-specific PCR approaches to study de-novo recombination in germ cells. We then apply this knowledge to computational approaches to understand how meiotic recombination shapes the genome.