Sonnichsen, B.Koski, L. B.Walsh, A.Marschall, P.Neumann, B.Brehm, M.Alleaume, A. M.Artelt, J.Bettencourt, P.Cassin, E.Hewitson, M.Holz, C.Khan, M.Lazik, S.Martin, C.Nitzsche, B.Ruer, M.Stamford, J.Winzi, M.Heinkel, R.Roder, M.Finell, J.Hantsch, H.Jones, S. J.Jones, M.Piano, F.Gunsalus, K. C.Oegema, K.Gönczy, P.Coulson, A.Hyman, A. A.Echeverri, C. J.2006-08-242006-08-242006-08-24200510.1038/nature03353https://infoscience.epfl.ch/handle/20.500.14299/23379515791247A key challenge of functional genomics today is to generate well-annotated data sets that can be interpreted across different platforms and technologies. Large-scale functional genomics data often fail to connect to standard experimental approaches of gene characterization in individual laboratories. Furthermore, a lack of universal annotation standards for phenotypic data sets makes it difficult to compare different screening approaches. Here we address this problem in a screen designed to identify all genes required for the first two rounds of cell division in the Caenorhabditis elegans embryo. We used RNA-mediated interference to target 98% of all genes predicted in the C. elegans genome in combination with differential interference contrast time-lapse microscopy. Through systematic annotation of the resulting movies, we developed a phenotypic profiling system, which shows high correlation with cellular processes and biochemical pathways, thus enabling us to predict new functions for previously uncharacterized genes.AnimalsCaenorhabditis elegans/*embryology/*genetics/physiologyCaenorhabditis elegans Proteins/*genetics/*metabolismComputational BiologyEmbryonic Development/*geneticsGenesHelminth/genetics*GenomeGenomicsPhenotype*RNA InterferenceRNAHelminth/genetics/metabolismRNAMessenger/genetics/metabolismResearch SupportNon-U.S. Gov'ttext::journal::journal article::research article