生物谷报道：要将由基因组测序工作所产生的大量信息变成关于基因的生物功能的知识，需要进行本期Nature上所报道的对线虫（Caenorhabditis elegans）所做的那种规模的筛选研究。该项目识别细胞分裂所需的基因，采用基因组范围内的RNA干涉来阻断基因组中98%的基因的表达，然后通过“差异干涉对比显微方法”拍摄4000幅以上影像，并对其进行观察，搞清哪些基因图像影响了受精后前两轮的细胞“有丝分裂”。这些早期阶段的胚胎生成需要650个以上基因。
该文发表在： Full-genome RNAi profiling of early embryogenesis in Caenorhabditis elegans
B. SÖNNICHSEN1, L. B. KOSKI1,6, A. WALSH1, P. MARSCHALL1,6, B. NEUMANN1,6, M. BREHM1, A.-M. ALLEAUME1,6, J. ARTELT1,6, P. BETTENCOURT1,6, E. CASSIN2,6, M. HEWITSON1, C. HOLZ1, M. KHAN1, S. LAZIK1, C. MARTIN1, B. NITZSCHE1,6, M. RUER2, J. STAMFORD2, M. WINZI1, R. HEINKEL1,6, M. RÖDER1,6, J. FINELL1,6, H. HÄNTSCH1, S. J. M. JONES3, M. JONES4,6, F. PIANO5, K. C. GUNSALUS5, K. OEGEMA2,6, P. GÖNCZY2,6, A. COULSON4,6, A. A. HYMAN2 & C. J. ECHEVERRI1
1 Cenix BioScience GmbH, Tatzberg 47-51, D-01307 Dresden, Germany
2 Max-Planck-Institute for Cell Biology and Genetics (MPI-CBG), Pfotenhauerstrasse 108, D-01307 Dresden, Germany
3 Genome Sciences Centre, British Columbia Cancer Research Centre, 570 West 7th Avenue, Vancouver, British Columbia V5Z 4E6, Canada
4 The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK
5 Department of Biology, Centre for Comparative Functional Genomics, New York University, 1009 Silver Centre, 100 Washington Square East, New York, New York 10003, USA
* Present addresses: Centre Robert Cedergren, Centre de Recherche en Bioinformatique et en Sciences Génomiques de l'Université de Montréal, 2900 Edouard-Montpetit, Montreal, Quebec H3T 1J4, Canada (L.B.K.); Max Planck Institute of Infection Biology, Schumannstrasse 21/22, 10117 Berlin, Germany (P.M.); European Molecular Biology Laboratory (EMBL), Meyerhofstrasse 1, D-69117 Heidelberg; Germany (B. Neumann); Institut Cochin, Département de Biologie Cellulaire, 22 rue Méchain, 75014 Paris, France (A.-M.A.); Institut für Klinische Genetik, Medizinische Fakultät Carl Gustav Carus, TU Dresden, Fetscherstrasse 74, 01307 Dresden, Germany (J.A.); Instituto Gulbenkian de Ciência, Rua da Quinta Grande n 6, 2780-901 Oeiras, Portugal (P.B.); Cavaleri Ottolenghi Scientific Institut (COSI) of Neurobiology, Azienda Ospedale San Luigi Gonzaga, Regione Gonzole 10-1004 Orbassano, Italy (E.C.); Mühlstrasse 36, 04317 Leipzig, Germany (B. Nitzche); Brombeerweg 2, 76275 Ettlingen, Germany (R.H.); Ingeniweb, 2 cours du 14 Juillet, 78300 Poissy, France (M.R.); Rätiälänkatu 20 A 11, 20810 Turku, Finland (J.F.); Institute of Molecular Biology and Biochemistry, Department of Biological Sciences, Simon Fraser University, Burnaby, British Columbia V5A 1S6, Canada (M.J.); University of California, San Diego, CMM-East 3080, 9500 Gilman Drive, La Jolla, California 92093, USA (K.O.); Swiss Institute for Experimental Cancer Research (ISREC), CH-1066 Lausanne, Switzerland (P.G.); MRC Laboratory of Molecular Biology, Hills Road, Cambridge CB2 2QH, UK (A.C.)
Correspondence and requests for materials should be addressed to B.S. (soennichsen@cenix-bioscience.com).
A 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.
