Comparative genomics is of crucial importance to unravel gene function and regulation. We are using domestic animals and other model organisms (Schizosaccharamyces pombe and mouse) to study genotype-phenotype relationships, gene regulation, chromatin organization and epigenetics.
Functional genomics in domestic animals. Domestic animals constitute a unique resource of genetic diversity due to their long history of selective breeding. We use a variety of domestic animals, including chicken, dogs, horse, pig, and honeybee, for in-depth studies of genes underlying both monogenic and multifactorial traits, as well as diseases of human relevance. We use both pedigree-based analysis and genome-wide association studies combined with high-throughput genomics and functional studies to achieve these goals.
Genome evolution. We use comparative analysis to identify functional elements in the human genome and those of model organisms to study the evolution of these elements and other genomic sequences. For example, comparison across 29 mammals identifies 3.6 million elements of which we can suggest a function for ~60%. Evolutionary analysis also identifies lineage-specific selection and innovation of both protein coding and regulatory elements. Furthermore, analysis of genetic variation within species enables us to identify regions targeted by selection, and to understand the mechanisms and evolution of recombination.
Chromatin organization and epigenetics. We investigate how transcription factors and silencer proteins influence the epigenome, both by changes in chromatin modifications and organisation of the chromatin within the cell nucleus. For example, we are investigating the newly identified human transcription factor ZBED6, its mechanism of action and its possible role in human diseases. In addition, we are using the S. pombe model system to get a deeper understanding of the molecular mechanism behind chromatin dynamics.
Retrovirus-host evolution. Retroviruses have colonized vertebrate hosts for millions of years, leaving traces in their genetic makeup as endogenous retroviruses (ERVs). This genomic ERV record provides a unique perspective on the long-term coevolution of retroviruses and their hosts. We use mainly bioinformatics to identify ERVs in genomic sequences of domestic animals and other vertebrate hosts to better understand retrovirus evolution and the effects of ERVs on host genome function and evolution.
Computational biology. Computational biology plays a key role for all of the above research areas. To support novel research questions and new data types we develop new algorithms and analysis methodologies, and we make the software publicly available for researchers around the world. These include tools to align entire genomes to each other to determine their relationships on a highly localized level, to de-novo assemble transcripts from RNA-Seq data, and to identify signals of selection within populations on a genome-wide scale.