Research abstract

Article abstract


Nature Biotechnology 25, 663 - 668 (2007)
Published online: 7 May 2007 | doi:10.1038/nbt1305

Genome-scale analysis of in vivo spatiotemporal promoter activity in Caenorhabditis elegans

Denis Dupuy1,10, Nicolas Bertin1,2,10, César A Hidalgo1,3,10, Kavitha Venkatesan1, Domena Tu4, David Lee4, Jennifer Rosenberg1, Nenad Svrzikapa1, Aurélie Blanc1, Alain Carnec1, Anne-Ruxandra Carvunis1, Rock Pulak5, Jane Shingles6, John Reece-Hoyes6, Rebecca Hunt-Newbury7, Ryan Viveiros7, William A Mohler8, Murat Tasan9, Frederick P Roth9, Christian Le Peuch2, Ian A Hope6, Robert Johnsen4, Donald G Moerman7, Albert-László Barabási1,3, David Baillie4 & Marc Vidal1


Differential regulation of gene expression is essential for cell fate specification in metazoans. Characterizing the transcriptional activity of gene promoters, in time and in space, is therefore a critical step toward understanding complex biological systems. Here we present an in vivo spatiotemporal analysis for ~900 predicted C. elegans promoters (~5% of the predicted protein-coding genes), each driving the expression of green fluorescent protein (GFP). Using a flow-cytometer adapted for nematode profiling, we generated 'chronograms', two-dimensional representations of fluorescence intensity along the body axis and throughout development from early larvae to adults. Automated comparison and clustering of the obtained in vivo expression patterns show that genes coexpressed in space and time tend to belong to common functional categories. Moreover, integration of this data set with C. elegans protein-protein interactome data sets enables prediction of anatomical and temporal interaction territories between protein partners.

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  1. Center for Cancer Systems Biology (CCSB), and Department of Cancer Biology, Dana-Farber Cancer Institute and Department of Genetics, Harvard Medical School, 44 Binney Street, Boston, Massachusetts 02115, USA.
  2. Centre de Recherche en Biochimie Macromoléculaire, Centre National de la Recherche Scientifique FRE 2593, 1919 Route de Mende, 34293 Montpellier Cedex 5, France.
  3. Center for Complex Network Research, Department of Physics, University of Notre Dame, 225 Nieuwland Science Hall, Notre Dame, Indiana 46556, USA.
  4. Department of Molecular Biology and Biochemistry, Simon Fraser University, 8888 University Drive, Burnaby, British Columbia V5A 1S6, Canada.
  5. Union Biometrica, 84 October Hill Road, Holliston, Massachusetts 01746, USA.
  6. Institute of Integrative and Comparative Biology, University of Leeds, Clarendon Way, Leeds LS2 9JT, West Yorkshire, UK.
  7. Department of Zoology, The University of British Columbia, 6270 University Boulevard, Vancouver, British Columbia V6T 1Z4, Canada.
  8. Department of Genetics and Developmental Biology and Center for Cell Analysis and Modeling, University of Connecticut Health Center, 263 Farmington Avenue, Farmington, Connecticut 06030, USA.
  9. Center for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, and Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, Massachusetts 02115, USA.
  10. These authors contributed equally to this work.

Correspondence to: Marc Vidal1 e-mail: marc_vidal@dfci.harvard.edu

Correspondence to: David Baillie4 e-mail: baillie@sfu.ca

Correspondence to: Albert-László Barabási1,3 e-mail: alb@nd.edu



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