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Authors :
Richard Weiszmann
Amy Beaton
Pavel Tomancak
ShengQiang Shu
Stephen Richards
Michael Ashburner
Elaine Kwan
Gerald M. Rubin
Volker Hartenstein
Suzanna E. Lewis
Susan E. Celniker
Source :
Genome Biology. 3:research0088.1
Publication Year :
2002
Publisher :
Springer Science and Business Media LLC, 2002.

Abstract

Background: Cell-fate specification and tissue differentiation during development are largely achieved by the regulation of gene transcription. Results: As a first step to creating a comprehensive atlas of gene-expression patterns during Drosophila embryogenesis, we examined 2,179 genes by in situ hybridization to fixed Drosophila embryos. Of the genes assayed, 63.7% displayed dynamic expression patterns that were documented with 25,690 digital photomicrographs of individual embryos. The photomicrographs were annotated using controlled vocabularies for anatomical structures that are organized into a developmental hierarchy. We also generated a detailed time course of gene expression during embryogenesis using microarrays to provide an independent corroboration of the in situ hybridization results. All image, annotation and microarray data are stored in publicly available database. We found that the RNA transcripts of about 1% of genes show clear subcellular localization. Nearly all the annotated expression patterns are distinct. We present an approach for organizing the data by hierarchical clustering of annotation terms that allows us to group tissues that express similar sets of genes as well as genes displaying similar expression patterns. Conclusions: Analyzing gene-expression patterns by in situ hybridization to whole-mount embryos provides an extremely rich dataset that can be used to identify genes involved in developmental processes that have been missed by traditional genetic analysis. Systematic analysis of rigorously annotated patterns of gene expression will complement and extend the types of analyses carried out using expression microarrays.

Details

ISSN :
14656906
Volume :
3
Database :
OpenAIRE
Journal :
Genome Biology
Accession number :
edsair.doi...........650fc80b9d320c0936cb40cb7c7f60f8
Full Text :
https://doi.org/10.1186/gb-2002-3-12-research0088