Mots-Clés
single-cell
multiomics
neuroblastoma
Hi-C
conformation
Description
Neuroblastoma, an embryonal tumor accounting for 15% of cancer-related death in children, is a devastating disease, which arises during the development of the sympathetic lineage involving neural crest cells. The vast clinical diversity corresponds to a molecular heterogeneity, which is partly shaped by the chromatin conformation and the epigenetic landscape. In prior work, the Health Data Science Unit (www.hdsu.org ) in collaboration with our partners at the German Cancer Research Center (DKFZ) has contributed to the description of this diversity at bulk and single-cell level, highlighted the role of super-enhancers, and connected the oncogenic process in different subtypes to distinct phases and lineages in normal embryonal development (adrenal medulla) (Gartlgruber et al., 2021; Jansky et al., 2021).
Within the DFG special priority program (SPP) “3D Genome Architecture in Disease and Development”, our 3-year funded project “Modeling embryonal neuroblastoma tumorigenesis by activation of chromosomal 3D super-enhancer interactions and genomic instability” aims at going further in the understanding of the role of 3D genome architecture in driving the malignant transformation during neuroblastoma. We want to test the hypothesis that certain timepoints during normal embryonal development show higher susceptibility to oncogenic transformation and that these are defined by certain conformational and chromatin properties. In collaboration with the group of Frank Westermann, DKFZ, we are thus planning to:
- Complement our high-resolution scRNA-seq atlas of neuroblastoma tumors and normal adrenal glands with scATAC-seq and use this multiome data to reconstruct single-cell gene regulatory networks.
- Perform scHi-C on normal adrenal medulla and establish a temporal map of chromatin conformation changes along normal developmental trajectory
- Identify perturbations in the regulatory networks driven by conformation changes through integration of the different data modalities.
The computational predictions will be validated by functional assays based on hiPSC using CRISPR-induced looping and enhancer surgery in the group of Frank Westermann.
For the computational part of this project, we are looking for a highly motivated postdoctoral researcher in computational genomics.
What we expect:
- Prior experience and expertise in computational single-cell analysis.
- Expertise in cancer (epi)genomics.
- High interest in a collaborative project involving computational and experimental groups.
We are offering:
- A 3-year funded postdoc position according to the german salary scale TV-L E13
- An excellent scientific environment in the middle of the Heidelberg Campus, with many opportunities for exchanging with groups involved in single-cell analysis within the Heidelberg-Mannheim Alliance
- Being involved in a network of many research projects within the special priority program with many opportunities for scientific exchange and scientific meetings with groups involved in this SPP