Integrative Genomics. Our lab develops approaches to comprehensively chart genomic and epigenetic variation using sequencing data and elucidates their contributions to somatic evolution, tumour heterogeneity, and treatment resistance.
Our lab explores the vast amounts of (epi)genetic variation generated during this process of somatic evolution. We strive to reconstruct when this variation arose, how it influences different ‘omics layers, and affects cell phenotypes such as genome instability and transcriptional plasticity.
Merits of the lab:
Our lab is embedded in the university hospital Gasthuisberg, KULeuven and the Department of Oncology Leuven. Several research projects running in my lab are linked with Francis Crick Institute and UCL hospital, London, UK and MD Anderson Cancer Center, Houston Texas. We collaborate in major international cancer consortia s.a. PCAWG, TRACERx.
Why do we want medical doctors?
We are a junior research group with high diversity in backgrounds (biomedical, bioengineering, computational) and nationalities. The team is currently hosting a good balance of female and male researchers.
Next-generation sequencing has revolutionised medical genetics, but limitations remain. Third-generation long reads improve de novo assembly, mapping, phasing, and identification of structural variants and transcript isoforms. Moreover, direct sequencing eliminates amplification bias while allowing detection of base modifications and inference of molecular function (e.g. promoter methylation).
Capitalising on these advances and addressing a key need for innovative computational method development in the area, our lab aims to leverage long-read and single-cell multi-omics to level up our understanding of the impact of variation on human genome function. In a leap towards truly personalised genomic medicine, we will advance both germline genetics and yield insights into tumour heterogeneity and evolution.
How we will do it?
In particular, we develop computational approaches and collaborate on new experimental methods leveraging single-molecule multi-omics sequencing. By improving de novo assembly and mapping, long reads enable unbiased detection of variation while yielding valuable context information through phasing and isoform information. Moreover, direct sequencing allows the detection of base modifications, linking genotypes, isoforms and molecular phenotypes at the single-molecule level.
Why is this important?
Capitalising on these advances, as well as those in single-cell and spatial techniques, we are developing the tools to comprehensively chart the variation in ‘omics layers and their interplay underpinning somatic evolution, tumour heterogeneity, and treatment resistance.
Who is a good fit for the project?
Experience in clinical (pathology) or translational research in the oncology field. Experience or keen interest in technologies and computational biology.
Medical background or training in the field of oncology and/or pathology will accelerate the integration of the MD in the project.
IDIBAPS#1 – Developing and investigating computing, machine learning and physiological modelling for understanding each individual heart towards personalised medicineDavid Brena2022-05-17T10:37:53+00:00