Figure 1: Gene-environment interactions reveal causal pathways (A-B) that mediate genetic effects on phenotype (Gagneur et al., PLOS Genetics 2013)
Figure 2: Dying mRNA tells a story of its life: Co-translational degradation revealed by 5P-Seq, a novel method that profiles ribosome dynamics (Pelechano et al., Cell 2015)
The Steinmetz group develops and applies interdisciplinary, genome-wide technologies to study genome regulation, the genetic basis of complex phenotypes and the genetic and molecular systems underpinning disease.
Previous and current research
One of the most daunting obstacles in biomedicine is the complex nature of most phenotypes (including cancer, diabetes, heart disease and some rare diseases) due to interactions between multiple genetic variants and environmental influences. A central challenge is to understand how genetic and environmental perturbations affect health, wellness and disease. Our research is directed at understanding such complex traits. To do so, we develop novel genomic approaches to study the molecular processes that link genotype to phenotype, identify the causal underlying factors, and quantify their contributions. We investigate inter-individual variation at the level of the genome, transcriptome, and proteome, which we integrate with higher-level phenotypes. Our projects are mainly in the following areas:
Quantitative genetics: We have piloted new technologies to dissect the genetic and environmental interactions that underlie complex, multifactorial phenotypes. We are interested in studying the consequences of genetic variation, learning to predict phenotype from genotype, and integrating multiple layers of molecular data to define intervention points that can be targeted to modulate phenotypes of interest (figure 1).
Functions and mechanisms of gene regulation: We have developed several technologies to characterise and quantify transcriptome architecture as well as its functional impact. In particular, we are interested in the function and regulation of non-coding RNAs, antisense transcription, transcriptional heterogeneity, and the molecular phenotypes that arise from pervasive transcription. Recently, we discovered that translation and degradation occur in parallel on the same mRNA allowing ribosome movement to be captured (figure 2).
Disease models: Using multiple model systems, primarily yeast and human cells, we have characterised the genetic and cellular processes affected in certain diseases and assessed potential therapeutic strategies. We apply personalised functional genomics to study diseases in patient-derived cells using systematic and targeted approaches to unravel mechanisms and discover novel treatments (see video). We also develop point-of-care biosensors that monitor an individual’s health and facilitate early disease diagnosis and intervention, even before symptoms set in.
Recent scientific presentations:
2016 International Symposium on Emerging Technologies, Institute for Systems Biology, Seattle: "Biosensors for personal molecular monitoring of health and disease"
Future projects and goals
Using novel algorithms, we aim to identify causal intervention points from multi-omic datasets to modulate phenotypes of interest, including those associated with diseases. We are expanding our studies of transcriptional regulation through targeted investigations of the functional consequences of complex transcriptome architecture and its contributions to single-cell heterogeneity. Ultimately, by integrating genome technologies, biomedical engineering and computational modelling, we aim to uncover the molecular features of health and enable personalised and preventative medicine.
Our lab operates in an integrated manner across sites in Heidelberg, Germany, and at Stanford University in the US.
Stanford l EMBL Personalized Health Conference
November 1-4 2017
Frances C. Arrillaga Alumni Center, Stanford University
Yeast Genetics Meeting
August 22-26 2018
|ERC ADVANCED INVESTIGATOR|