A method for automated detection of gene expression required for the establishment of a digital transcriptome-wide gene expression atlas

Authors

  • J. P. CARSON,

    Corresponding author
    1. National Center for Macromolecular Imaging, Verna and Marrs McLean Department of Biochemistry and Molecular Biology, Baylor College of Medicine, Houston, TX 77030, U.S.A.
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  • G. EICHELE,

    1. Max Planck Institute of Experimental Endocrinology, Hannover, Germany
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  • W. CHIU

    1. National Center for Macromolecular Imaging, Verna and Marrs McLean Department of Biochemistry and Molecular Biology, Baylor College of Medicine, Houston, TX 77030, U.S.A.
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Dr James P. Carson. Tel.: +1 713 7986989; e-mail: james.carson@bcm.tmc.edu

Summary

Acquiring information about the expression of a gene in different cell populations and tissues can provide key insight into the function of the gene. A high-throughput in situ hybridization (ISH) method was recently developed for rapid and reproducible acquisition of gene expression patterns in serial tissue sections at cellular resolution. Characterizing and analysing expression patterns on thousands of sections requires efficient methods for locating cells and estimating the level of expression in each cell. Such cellular quantification is an essential step in both annotating and quantitatively comparing high-throughput ISH results. Here we describe a novel automated and efficient methodology for performing this quantification on postnatal mouse brain.

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