Figure 1: Extensive variation in transcript start and end sites revealed by TIF-Seq, a novel technique for transcript isoform profiling (Pelechano et al., 2013)
Figure 2: Gene-environment interactions reveal causal pathways (A-B) that mediate genetic effects on phenotype (Gagneur et al., 2013)
The Steinmetz group bridges diverse domains of genome science, from deciphering the structure and function of genomes to the application of these insights in understanding diseases.
Previous and current research
One of the most daunting challenges in medicine is the complex nature of most common diseases (including cancer, diabetes, and heart disease) due to interactions between multiple genetic variants and environmental influences. Our research is directed at understanding such complex traits; to do so, we develop novel genomic approaches to investigate the molecular processes that link genotype to phenotype, identify the underlying factors, and quantify their contributions. We investigate 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:
Function and mechanisms of transcription: We have developed several technologies to characterise pervasive transcription at the genome-wide level as well as its functional impact. We are interested in the function and regulation of non-coding RNAs, antisense transcription, and the molecular phenotypes that arise from transcriptome complexity. Recently, we discovered extensive variation in the start and end sites of transcript molecules produced by each gene by developing a novel technique to map full-length transcript isoforms genome-wide (figure 1).
Systems genetics: We have worked extensively on dissecting the genetic basis of complex phenotypes. We are interested in studying the network-level consequences of genetic variation and learning to predict phenotype from genotype. Recently, by studying genetic interactions with the environment, we have defined new experimental and statistical techniques that facilitate the distinction of genes that play a causal role in mediating genetic effects on phenotype (figure 2).
Mitochondria: Using an array of systematic and biochemical approaches, we investigate the effects of genetically perturbing mitochondrial function and strategies to rescue these perturbations. We also study mitochondrial genetics, including recombination of mitochondrial DNA in yeast and the relocation of mitochondrial genes to the nucleus.
Future projects and goals
We are integrating multiple layers of molecular data in order to understand how the genome is read for function. Using novel algorithms, intervention points can be identified from such data that can be targeted to modulate phenotypes of interest. We are also following up on our studies of transcriptional regulation through targeted investigations of the interplay between epigenetics and transcription, the functional consequences of complex transcriptome architecture, and its contribution to single-cell heterogeneity. Ultimately, by integrating genetics, genomics, systems biology, and computational modelling, we aim to develop approaches that unravel disease mechanisms and predict effective therapeutics, enabling personalised and preventive medicine.
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