What we do

We develop and apply new genomics technologies to study the architecture and functions of chromosomes and chromatin. We use both Drosophila and mammalian cell lines as model systems.

Chromatin Systems Biology


We aim to elucidate how hundreds of chromatin proteins work together to package the genome and regulate gene expression. We study the domain organization of chromatin along the genome, and we investigate the protein interaction networks that underlie the principal chromatin types. Among others, we have identified five principal chromatin types in Drosophila, and we have constructed a network model of the interactions among >100 chromatin proteins, including dozens of proteins not previously known to be part of chromatin.

Genome – Nuclear Lamina interactions

Lamin DamID

We investigate the role of the nuclear lamina in the spatial organization of chromosomes, and how this contributes to gene regulation and other nuclear functions. We discovered LADs, which are large chromosomal domains that associate with the lamina. Most genes in LADs are transcriptionally inactive, suggesting a repressive role for LADs. We now investigate how LADs are formed, and how they contribute to chromosome architecture and function.

New technologies for chromatin genomics


We have developed DamID, an efficient approach for large-scale mapping of in vivo protein-genome interactions. Related to this is our m6A-tracer technology, which can track DNA in live cells after it has been in contact with a specific protein such as lamin. TRIP is a method to measure the impact of chromatin on gene function at thousands of genomic locations in parallel. TIDE is a simple, cheap and quantitiative method to measure the efficiency of genome editing tools such as CRISPR/Cas9. We are also developing methods for single-cell epigenomics and high-throughput mapping of regulatory elements.


PCA animation

Whole-genome datasets cannot be interpreted without the help of bioinformatics. We develop analytical tools to extract relevant biological information from our large datasets. All students and postdocs in the lab are familiar with R programming.