Research

The main focus of our lab is to understand how different mechanisms contribute to gene regulation. We are focusing or transcription factors and their binding to DNA, 3D genome organisation and DNA methylation.

3D genome organisation

Our lab is interested in understanding the mechanism of of how the genome folds in 3D within the nucleus and what is the functional role of this 3D organisation. We are using Drosophila melanogaster to understand this process and combine both experimental  methods (including Hi-C, RNA-seq and ChIP-seq) and computational ones (both using published tools and custom scripts, but also developing new tools). We are able to generate contact maps at subkilobase resolution (approximately 500 bp), which allows us to address questions about the mechanism and functional role of the 3D genome organisation.

tads_track_keerthi_bg3_only_150bp_2l_2845000_2985000

Hi-C map of Drosophila neuronal cell line (data generated in our lab). Triangle view of the normalised contact map at the 2L:2,845,000-2,985,000 locus. Darker colours indicate higher number of contacts, while lighter colours lower number of contacts. TADs are marked by the black line triangles.

Transcription factors

Transcription factors (TFs) are proteins that bind to the DNA to regulate gene expression. Our lab is looking at the steady state behaviour of TF binding. In particular, we proposed a mathematical framework based on statistical thermodynamics, which is able to recapitulate binding profiles of TFs in eukaryotic systems (see paper).

OccupancyProfileAteveBoundMolecules10000CADAccessibilityRegionsPWMThreshold070lambda125

Estimating the binding profiles using statistical thermodynamics. The grey shade represents the ChIP-seq profile, the red line represents our predictions, the yellow regions represent nucleosome dense regions and vertical blue bars the binding sites.

In addition, we are also interested to determine the contribution of the TFs binding mechanisms to the DNA. TFs use a mechanism called facilitated diffusion when binding to their targets sites and this mechanisms assumes that the molecules perform both three-dimensional diffusion and one-dimensional random walk on the DNA.

graphical_abstract

 

DNA methylation

Finally, we are also interested in understanding the mechanisms behind transgenerational inheritance of DNA methylation in plants and mammals. For this, we developed an R/Bioconductor package DMRcaller that can detect differentially methylated regions between two samples from bisulfite converted libraries. The tool implements several methods for the detection of DMRs (binning the data, using a noise filter kernel, calling differentially methylated cytosines or filtering predefined regions). This is a highly versatile tool that can compute differential methylation in a context dependent manner on the entire human genome in few hours.

DMRcaller_example