The human genome is full of genetic variation, such as single nucleotide changes. Particularly structural genomic variations cover a large part of the human genome. Structural variations are characterized by a difference in the copy number, orientation, or location of relatively large genomic segments (typically > 1 kb), such as deletions, duplications, insertions, inversions and translocations. When structural variations occur de novo from one generation to the other, this may lead to congenital disease, for example mental retardation or developmental delay. Likewise, in somatic cells structural variations contribute to cancer development.
Our research group studies the origin of structural variations underlying congenital disease and cancer. We are particularly focused on complex chromosome rearrangements caused by chromothripsis, a phenomenon which involves massive chromosome shattering and repair. By sequencing complex chromosomal rearrangements in patients with congenital malformations, we were the first to show that chromothripsis can also explain complex genomic rearrangements underlying developmental abnormalities. In fact, many apparently simple genomic rearrangements – when detected by karyotyping or other low-resolution techniques – appear much more complex when analysed by whole genome sequencing. We have shown that chromothripsis rearrangements preferentially occur on paternal chromosomes, suggesting an origin in the male germline.
Currently, we are actively dissecting the molecular trigger of chromothripsis and the pathogenic effects in order to understand the causes of congenital disease and cancer. This is achieved by combining a large array of genomic technologies (RNA-seq, ChIP-seq, genome seq) with functional testing in cell systems and model organisms.
Our group is also actively participating in the Genome of the Netherlands (GoNL) project (http://www.nlgenome.nl/) – a large consortium that aims at characterizing genetic variation within the Dutch population. The structural variation subgroup of the GoNL project focuses on exploring structural variation in GoNL dataset, including detection of de novo changes. A primary aim of these efforts is also to gain experience with analysis of population-scale sequencing datasets, including development of novel bioinformatics tools and establishment of a collaborative network of genomic researches.