Research Report 2010 - MDC

Pinar Oenal*Marlon StoeckiusNadine ThierfelderTechnical AssistantsSalah Ayoub*Signe Knespel (Lab Manager)Tatjana Luganskaja*SecretariatAlex Tschernycheff*part of the period reportedFigure 1. C. elegansIt is clear that a better understanding of gene regulationand in particular of the just emerging universe ofnon-coding RNAs can only come by integrating variousdata sources (comparative sequence analysis, mRNAexpression data, protein-protein interactions, mutantphenotypes from RNAi screens, polymorphism data,experimentally defined gene regulatory networks,ChIP-chip data, etc) since each data source alone is onlya partial description of how cells function. For example,to understand microRNA function, we not only need toidentify their targets but also to decode howmicroRNAs are transcriptionally regulated. A majorfocus of the lab is therefore in developing methods thatintegrate different data sources and methods to produceglobal and yet specific predictions about how,when, and where gene are regulated. This will ultimatelylead to the identification and functional descriptionof gene regulatory networks. We will continue to test,develop and “translate” these methods and their predictionsusing specific biological systems, such asmetabolism in mammals, regeneration in planarians,early embryogenesis in C. elegans, and within collaborationswith other experimental groups.Function of microRNAs(Azra Krek, Marc Friedlaender, Minnie Fang, MarlonStoeckius, Jonas Maaskola, Nadine Thierfelder,Svetlana Lebedeva, Sebastian Mackowiak, MarvinJens).We have developed one of the first microRNA targetfinding algorithms and could later on show thatmicroRNAs very likely regulate thousands of geneswithin vertebrates, flies, and nematodes. We have furtherhelped to elucidate the function of microRNAs inpancreatic beta cells (insulin secretion), in liver (cholesterollevel), and other systems. More recently, we haveshown that microRNAs can leave cell type specificmRNA expression signatures on hundreds of genes,and that human genotyped SNP data can be used toexplicitly demonstrate and quantify the contribution ofmicroRNA targets to human fitness. All microRNA targetpredictions of our algorithm PicTar can be accessedat our searchable PicTar website. We have further developedcomputational methods to predict miRNAs fromhigh throughput sequencing data (see miRDeep webpage).We have also pioneered approaches that allowedCardiovascular and Metabolic Disease Research 27