A spatial and temporal map of C. elegans gene expression
- W. Clay Spencer1,7,
- Georg Zeller2,3,7,8,
- Joseph D. Watson1,9,
- Stefan R. Henz3,
- Kathie L. Watkins1,
- Rebecca D. McWhirter1,
- Sarah Petersen1,
- Vipin T. Sreedharan2,
- Christian Widmer2,
- Jeanyoung Jo4,
- Valerie Reinke4,
- Lisa Petrella5,
- Susan Strome5,
- Stephen E. Von Stetina1,10,
- Menachem Katz6,
- Shai Shaham6,
- Gunnar Rätsch2 and
- David M. Miller III1,11
- 1 Department of Cell and Developmental Biology, Vanderbilt University, Nashville, Tennessee 37232, USA;
- 2 Friedrich Miescher Laboratory of the Max Planck Society, 72076 Tübingen, Germany;
- 3 Department of Molecular Biology, Max Planck Institute for Developmental Biology, 72076 Tübingen, Germany;
- 4 Department of Genetics, Yale University School of Medicine, New Haven, Connecticut 06520, USA;
- 5 Department of MCD Biology, University of California Santa Cruz, Santa Cruz, California 95064, USA;
- 6 Laboratory of Developmental Genetics, The Rockefeller University, New York, New York 10065, USA
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↵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
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↵11 Corresponding author.
E-mail david.miller{at}vanderbilt.edu.
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[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.]
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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.
- Copyright © 2011 by Cold Spring Harbor Laboratory Press
Freely available online through the Genome Research Open Access option.
