A spatial and temporal map of C. elegans gene expression

  1. David M. Miller III1,11
  1. 1 Department of Cell and Developmental Biology, Vanderbilt University, Nashville, Tennessee 37232, USA;
  2. 2 Friedrich Miescher Laboratory of the Max Planck Society, 72076 Tübingen, Germany;
  3. 3 Department of Molecular Biology, Max Planck Institute for Developmental Biology, 72076 Tübingen, Germany;
  4. 4 Department of Genetics, Yale University School of Medicine, New Haven, Connecticut 06520, USA;
  5. 5 Department of MCD Biology, University of California Santa Cruz, Santa Cruz, California 95064, USA;
  6. 6 Laboratory of Developmental Genetics, The Rockefeller University, New York, New York 10065, USA
    • 8 Present addresses: European Molecular Biology Laboratory, 69117 Heidelberg, Germany;

    • 9 Department of Biochemistry & Biophysics, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, 27599, USA;

    • 10 Department of Molecular and Cellular Biology, Harvard University, Cambridge, Massachusetts 02138, USA.

    1. 7 These authors contributed equally to this work.

    Abstract

    The C. elegans genome has been completely sequenced, and the developmental anatomy of this model organism is described at single-cell resolution. Here we utilize strategies that exploit this precisely defined architecture to link gene expression to cell type. We obtained RNAs from specific cells and from each developmental stage using tissue-specific promoters to mark cells for isolation by FACS or for mRNA extraction by the mRNA-tagging method. We then generated gene expression profiles of more than 30 different cells and developmental stages using tiling arrays. Machine-learning–based analysis detected transcripts corresponding to established gene models and revealed novel transcriptionally active regions (TARs) in noncoding domains that comprise at least 10% of the total C. elegans genome. Our results show that about 75% of transcripts with detectable expression are differentially expressed among developmental stages and across cell types. Examination of known tissue- and cell-specific transcripts validates these data sets and suggests that newly identified TARs may exercise cell-specific functions. Additionally, we used self-organizing maps to define groups of coregulated transcripts and applied regulatory element analysis to identify known transcription factor– and miRNA-binding sites, as well as novel motifs that likely function to control subsets of these genes. By using cell-specific, whole-genome profiling strategies, we have detected a large number of novel transcripts and produced high-resolution gene expression maps that provide a basis for establishing the roles of individual genes in cellular differentiation.

    Footnotes

    • 11 Corresponding author.

      E-mail david.miller{at}vanderbilt.edu.

    • [Supplemental material is available for this article. The microarray data from this study have been submitted to the Gene Expression Omnibus (GEO) (http://www.ncbi.nlm.nih.gov/geo) under accession nos. GSE23245–GSE23271, GSE23278–GSE23287, GSE23769–GSE23770, and GSE25350–GSE25351.]

    • Article published online before print. Article, supplemental material, and publication date are at http://www.genome.org/cgi/doi/10.1101/gr.114595.110.

    • Received September 3, 2010.
    • Accepted December 8, 2010.

    Freely available online through the Genome Research Open Access option.

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