ayout 1 - EMBL Grenoble

Gene Expression UnitFunctional genomics of complex traitsPrevious and current researchIndividuals differ at thousands of DNA sequence positions. These differences interact with eachother and with the environment in complex ways to give rise to heritable phenotypic variation. Thisis the basis of quantitative phenotypes such as body height, cancer, diabetes, crop yield and fungalvirulence. Naturally occurring genetic variants also influence the onset and intensity of diseases,as well as their treatment susceptibility, thus providing an incentive for personalised medicine.The overall aim of our research is to elucidate how genetic variation conditions complex phenotypes.To this end, we integrate experimental and computational biology approaches at multiplelayers along the molecular processes linking genotype to phenotype. In particular we investigatethe level of the genome, transcriptome and proteome.Some selected projects include genotyping single-nucleotide polymorphisms across entire yeastgenomes to infer meiotic recombination-activity distributions that define trait inheritance; studyingthe function of pervasive transcription of non-coding RNAs and the mechanisms of how theyare generated; and analysing protein-interaction networks to enable the prediction of candidate diseasegenes for mitochondrial disorders.Future projects and goalsWe are developing new technologies to determine the phenotypic contribution for all sequencevariants between two genomes in a single step. In addition, we are dissecting the genetic basis of sensitivity and resistance to malaria parasitesin the mosquito, Anopheles gambiae. Ultimately, by integrating genetics, genomics, systems biology and computational modelling withhigh-throughput sequencing and microarrays, we aim to develop approaches that will enable personalised and preventative medicine acrossthe world.The group is associated with the Stanford Genome Technology Center at Stanford University.Lars SteinmetzPhD 2001, StanfordUniversity.Postdoctoral research at theStanford GenomeTechnology Center.Group leader at EMBL since2003. Academic Mentor,predoctoral training since2008.Joint Unit Coordinator since2009.Figure 1: High-resolutionmap of meioticrecombination inferred fromgenotype calls for all fourspores of a single meiosis(Mancera et al., Nature,2008)Figure 3 (right):From yeast proteininteractiondatasetsto the identificationof candidate genesfor human diseases(Perocchi et al.,Mol. Biosyst., 2008)Figure 2:Bidirectionalpromotersgeneratepervasivetranscription ofnon-coding RNAs(Xu et al., Nature2009)Selected referencesNeil, H., Malabat, C., d’Aubenton-Carafa, Y., Xu, Z., Steinmetz, L.M.& Jacquier, A. (2009). Widespread bidirectional promoters are themajor source of cryptic transcripts in yeast. Nature, 57, 1038-2Xu, Z., Wei, W., Gagneur, J., Perocchi, F., Clauder-Munster, S.,Camblong, J., Guffanti, E., Stutz, F., Huber, W. & Steinmetz, L.M.(2009). Bidirectional promoters generate pervasive transcription inyeast. Nature, 57, 1033-7Mancera, E., Bourgon, R., Brozzi, A., Huber, W. & Steinmetz, L.M.(2008). High-resolution mapping of meiotic crossovers and noncrossoversin yeast. Nature, 5, 79-85Sinha, H., David, L., Pascon, R.C., Clauder-Munster, S.,Krishnakumar, S., Nguyen, M. et al. (2008). Sequential elimination ofmajor-effect contributors identifies additional quantitative trait lociconditioning high-temperature growth in yeast. Genetics, 180, 1661-167033