Applications / Open positions

Using deep learning to decode transcriptional specification of cell types
Research area : Computational biology
Leading PI: Prof. Dr. Uwe Ohler

Collaborating with the lab of Philip Benfey at Duke, we aim to build deep neural networks to learn sequence codes that define gene expression across all distinct cell types of the Arabidopsis root. In this context, we want to investigate how to make use of information on natural sequence variation, and how to interpret the networks to identify cooperative sequence codes and use them for designing new regulatory regions with specific expression patterns.

Transcription factor binding site make-up, composition, and synergy in active enhancers
Research area : Computational biology
Leading PI: Prof. Dr. Martin Vingron

What determines whether a binding site for a transcription factor (TF) will actually be functional? The current assumption is that genomic targeting by TFs is controlled mainly through accessibility of promoters and enhancers for TF-binding, and cofactors that interact with TFs and modulate their DNA binding activity. We want to study individual bindings sites and the binding site composition in regulatory regions.

Modelling regulatory sequences and tissue-specificity using functional read-outs
Research area : Computational biology
Leading PI: Dr. Martin Kircher

The Kircher lab devises computational approaches to identify functionally relevant genetic changes in studies of human disease and adaptation. In collaboration with Tim E Reddy (Biostatistics & Bioinformatics) and Charles A Gersbach (Biomedical Engineering) at Duke, we use data sets from high-throughput reporter assays and CRISPR/Cas9 screens in combination with other functional read outs to study the effects of regulatory sequences. We will develop comprehensive and generalizable models of regulatory sequences, which can then be integrated into predictors of variant effects across the human genome.

Regulatory Diversity within Neurons
Research area : Developmental systems biology
Leading PI: Dr. Robert Zinzen

Collaborating with the lab of Debbie Silver at Duke, we aim to unravel regulatory networks driving neurogenesis in embryonic development. Using extensive datasets in the fruitfly as a guide, candidate regulatory hubs will be chosen and tested, both in the fly embryo and the mouse neural tube. The goal is a mechanistic understanding of how neurogenesis proceeds by subdividing a primordium, specifying territories and allowing individual cell types to emerge.

Characterising GRN evolution via single-cell sequencing
Research area : Developmental systems biology
Leading PI: Dr. David Garfield

Our lab works at the intersection of evolution and development to understand how regulatory interactions in development can shape, and are shaped by, evolutionary processes. Our primary model system for this work is the sea urchin embryo, and we will be working with Sayan Mukherjee (statistics) and Greg Wray (developmental biology/evolution) to understand, using single-cell ATAC-Seq and RNA-Seq, how sequence differences between species influence the function of the well-characterized developmental program underlying the specification and growth of the larval skeleton.

Chromatin architecture in disease associated mutations
Research area : Developmental systems biology
Leading PI: Prof. Dr. Stefan Mundlos

New technologies are now available to identify pathogenic changes such as structural variations (SVs) in the genome, but their interpretation remains a challenge. In this project we plan to dissect a developmentallty important locus (Sox9) to try to understand how complex expression patterns during develoment are achieved and how mutations (in particular SVs) can inter with this process. We wil use CRSPR-based genome editing technologies to identify all regulatory and structurally important elements within the locus and manipulate them in oder to define their effect on gene regulation. This will be done in vitro (stem cells - neural progenitors) as well as in vivo (mouse limb buds). We will use CRISPR-based approaches that enable the delivery of epigenome-modifying proteins directly to the site of interest to CTCF sites that are important for TAD formation at the locus with the aim of blocking CTCF binding sites through the creation of blocks of repressive chromatin modifcations. With these studies we aim at understanding what keeps a locus in its 3D folding regime and how alterations of structure as well as chromatin characteristics can interfer with its proper function.

Context specificity of transcription factors in plant development
Research area : Developmental systems biology
Leading PI: Prof. Dr. Kerstin Kaufmann

Multicellular development is controlled by transcription factors (TFs) that act together to determine organ and cell type identities. The functions of master TFs change depending on developmental stage, tissue context, and/or the presence of interacting proteins. However, the molecular mechanisms underlying context-specificity of these TFs are still poorly understood. In collaboration with the Gordan lab at Duke University, we will study the regulatory code of plant developmental master TF functions.

Unravelling the regulatory links between nascent transcription & chromatin structure
Research area : High-throughput genomics
Leading PI: Dr. Andreas Mayer

In collaboration with the group of Alexander Hartemink at Duke, we will employ high-resolution genome-wide approaches, induced target protein degradation and integrative computational analysis tools to uncover the regulatory links between nascent RNA polymerase II transcription and the chromatin structure that underlie gene expression in human cells. Hence, this project has the potential to reveal novel principles that drive gene transcription in a native chromatin context and will expose causal links between transcription and chromatin organization.

Dissecting the cis- and trans-regulatory logic at the Xist locus with CRISPR-screens
Research area : High-throughput genomics
Leading PI: Dr. Edda Schulz

Together with the lab of Charles Gersbach at Duke, this project will use a combination of different pooled CRISPR-screening approaches to identify and characterize enhancers that control Xist, the master regulator of X-inactivation. First, transcription factors and enhancers that regulate Xist will be identified and then combinatorial screens to link transcription factors to the enhancers they regulate will be performed.

Single-cell approaches to identify chromatin architecture
Research area : High-throughput genomics
Leading PI: Prof. Ana Pombo

following soon

Statistical approaches for sparse single-cell data in developmental systems
Research area : High-throughput genomics
Leading PI: Prof. Dr. Nikolaus Rajewsky

following soon

HU Berlin

Humboldt-Universität zu Berlin
Unter den Linden 6
10099 Berlin
Germany

Duke University

Durham, 27708
North Carolina
USA