Research Groups > Genes and Metabolism Integrative Genomics and Medicine
Our research focuses on the integration of genomic, phenotypic and genetic resources to identify risk factors and molecular networks for complex traits and disease.
Understanding how complex disease systems operate requires the integration of multiple layers of biological information from DNA to phenotype. In our group, we integrate informatics and multi-dimensional modelling of genomic data to elucidate the regulatory processes underlying complex traits, including metabolic, cardiovascular, inflammatory, neurological and behavioral phenotypes. In particular, rather than focusing on single disease susceptibility genes, we explore pathways and networks to better predict the consequences of genetic and epigenetic variations on complex disease. We employ systems-genetics approaches, from model organisms to humans, to provide functional annotation of genes in biological processes and reveal the signal of common genetic variation of small effect that is not captured by typical genome wide association studies.
Figure 1. Systems-level approaches for identifying genetic regulators of gene expression. Schematic view of multiple tissues modeling of gene expression profiles using multivariate Bayesian approaches (Petretto*, Bottolo* et al. PLoS Computational Biology 2010)
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In our group, we are bringing forward an highly multidisciplinary and ambitious research programme by combining computational approaches for statistical genetics/bioinformatics (collaboration with Prof. Sylvia Richardson and the Biostatistics Group at Imperial College) with functional genomics approaches (Dr. Stuart Cook, Prof. Tim Aitman)and human genetics (collaboration with Dr. Michael Johnson) using high-throughput genomic data and next generation sequencing (for instance RNA-seq and ChIP-seq). We are also leading a research program in collaboration with Prof. Norbert Hübner (Max Delbruck Centre, Berlin) for building gene regulatory networks that underlie metabolic and cardiovascular diseases, and integrate multi-modality data (genomic, epigenetic, transcriptomic, proteomic, metabonomic and phenotypic) in the rat model system to inform and complement human genetics studies.
Figure 2. System-genetics to dissect disease mechanisms. Complex gene network driven by the Irf7 transcription factor, which was identified in multiple rat tissues. Nodes represent individual genes: the node representing Irf7 is coloured red and its predicted targets are coloured blue. Edges connect genes that are either predicted Irf7-targets (black) or show significant correlation of expression levels to one of the predicted targets (grey). The network is highly enriched for immune response genes and has been named “Irf7-driven inflammatory gene network” or iDIN. iDIN genes contribute to Type 1 Diabetes (T1D) risk in humans and Ebi2 (or Gpr183), which controls Irf7 in macrophages, represents a candidate for trans-regulation of the human iDIN and for T1D risk (Heinig*, Petretto* et al. Nature 2010).
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Group head
Enrico Petretto (Dr)
Telephone 31468
Email
Group members
Seham Awadh Alshehri
Sarah Langley (Ms)
Thomas Oates (Dr)
Silvia Pitzoi (Dr)
Visiting worker
Gianfilippo Coppola (Dr)
Admin contact
Sabika Ali (Mrs)
Telephone 38288
Contact details
Selected publications
Heinig, M.*, Petretto, E.*, Wallace, C., Bottolo, L., Rotival, M., Lu, H., Li, Y., Sarwar, R., Langley, S. R., Bauerfeind, A., Hummel, O., Lee, Y.-A. A., Paskas, S., Rintisch, C., Saar, K., Cooper, J., Buchan, R., Gray, E. E., Cyster, J. G., Cardiogenics Consortium, Erdmann, J., Hengstenberg, C., Maouche, S., Ouwehand, W. H., Rice, C. M., Samani, N. J., Schunkert, H., Goodall, A. H., Schulz, H., Roider, H. G., Vingron, M., Blankenberg, S., Münzel, T., Zeller, T., Szymczak, S., Ziegler, A., Tiret, L., Smyth, D. J., Pravenec, M., Aitman, T. J., Cambien, F., Clayton, D., Todd, J. A., Hubner, N., Cook, S. A. (2010). A trans-acting locus regulates an anti-viral expression network and type 1 diabetes risk. Nature 467, 460–464. Abstract
Petretto, E.*, Bottolo, L.*, Langley, S. R., Heinig, M., McDermott-Roe, C., Sarwar, R., Pravenec, M., Hübner, N., Aitman, T. J., Cook, S. A., Richardson, S. (2010). New insights into the genetic control of gene expression using a Bayesian multi-tissue approach. PLoS Computational Biology 6 (4), e1000737. (*joint first authors) Abstract
Ioannidis, J. P. A., Allison, D. B., Ball, C. A., Coulibaly, I., Cu, X., Culhane, A. C., Falchi, M., Furlanello, C., Game, L., Jurman, G., Mehta, T., Mangion, J., Nitzberg, M., Page, G. P., Petretto, E., van Noort, V. (2009). Replication of analysis of published microarray gene expression analyses. Nature Genetics 41, 149–155. Abstract
Petretto, E.*, Sarwar, R.*, Grieve, I., Lu, H., Kumaran, M. K., Muckett, P. J., Mangion, J., Schroen, B., Benson, M., Punjabi, P. P., Prasad, S. K., Pennell, D. J., Kiesewetter, C., Tasheva, E. S., Corpuz, L. M., Webb, M. D., Conrad, G. W., Kurtz, T. W., Kren, V., Fischer, J., Hubner, N., Pinto, Y. M., Pravenec, M., Aitman, T. J., Cook, S. A. (2008). Integrated genomic approaches implicate osteoglycin (Ogn) in the regulation of left ventricular mass. Nature Genetics 40, 546–552. Abstract
Petretto, E., Mangion, J., Dickens, N. J., Cook, S. A., Kumaran, M. K., Lu, H., Fischer, J., Maatz, H., Kren, V., Pravenec, M., Hubner, N., Aitman, T. J. (2006). Heritability and Tissue Specificity of Expression Quantitative Trait Loci. PLoS Genetics 2, e172. Abstract
Hubner, N., Wallace, C. A., Zimdahl, H., Petretto, E., Schulz, H., Maciver, F., Mueller, M., Hummel, O., Monti, J., Zidek, V., Musilova, A., Kren, V., Causton, H., Game, L., Born, G., Schmidt, S., Müller, A., Cook, S. A., Kurtz, T. W., Whittaker, J., Pravenec, M., Aitman, T. J., (2005). Integrated transcriptional profiling and linkage analysis for identification of genes underlying disease. Nature Genetics 37, 243–253. Abstract
Petretto, E.*, Bottolo, L.*, Langley, S. R., Heinig, M., McDermott-Roe, C., Sarwar, R., Pravenec, M., Hübner, N., Aitman, T. J., Cook, S. A., Richardson, S. (2010). New insights into the genetic control of gene expression using a Bayesian multi-tissue approach. PLoS Computational Biology 6 (4), e1000737. (*joint first authors) Abstract
Ioannidis, J. P. A., Allison, D. B., Ball, C. A., Coulibaly, I., Cu, X., Culhane, A. C., Falchi, M., Furlanello, C., Game, L., Jurman, G., Mehta, T., Mangion, J., Nitzberg, M., Page, G. P., Petretto, E., van Noort, V. (2009). Replication of analysis of published microarray gene expression analyses. Nature Genetics 41, 149–155. Abstract
Petretto, E.*, Sarwar, R.*, Grieve, I., Lu, H., Kumaran, M. K., Muckett, P. J., Mangion, J., Schroen, B., Benson, M., Punjabi, P. P., Prasad, S. K., Pennell, D. J., Kiesewetter, C., Tasheva, E. S., Corpuz, L. M., Webb, M. D., Conrad, G. W., Kurtz, T. W., Kren, V., Fischer, J., Hubner, N., Pinto, Y. M., Pravenec, M., Aitman, T. J., Cook, S. A. (2008). Integrated genomic approaches implicate osteoglycin (Ogn) in the regulation of left ventricular mass. Nature Genetics 40, 546–552. Abstract
Petretto, E., Mangion, J., Dickens, N. J., Cook, S. A., Kumaran, M. K., Lu, H., Fischer, J., Maatz, H., Kren, V., Pravenec, M., Hubner, N., Aitman, T. J. (2006). Heritability and Tissue Specificity of Expression Quantitative Trait Loci. PLoS Genetics 2, e172. Abstract
Hubner, N., Wallace, C. A., Zimdahl, H., Petretto, E., Schulz, H., Maciver, F., Mueller, M., Hummel, O., Monti, J., Zidek, V., Musilova, A., Kren, V., Causton, H., Game, L., Born, G., Schmidt, S., Müller, A., Cook, S. A., Kurtz, T. W., Whittaker, J., Pravenec, M., Aitman, T. J., (2005). Integrated transcriptional profiling and linkage analysis for identification of genes underlying disease. Nature Genetics 37, 243–253. Abstract
