Comparison of melanoblast expression patterns identifies distinct classes of genes
Article first published online: 26 MAY 2009
DOI: 10.1111/j.1755-148X.2009.00584.x
© 2009 John Wiley & Sons A/S. This article is a US Government work and is in the public domain in the USA
Additional Information
How to Cite
Loftus, S. K., Baxter, L. L., Buac, K., Watkins-Chow, D. E., Larson, D. M. and Pavan, W. J. (2009), Comparison of melanoblast expression patterns identifies distinct classes of genes. Pigment Cell & Melanoma Research, 22: 611–622. doi: 10.1111/j.1755-148X.2009.00584.x
Publication History
- Issue published online: 26 AUG 2009
- Article first published online: 26 MAY 2009
- PUBLICATION DATA Received 24 March 2009, revised and accepted for publication 19 May 2009
Keywords:
- melanoblast;
- retinal pigmented epithelium;
- in situ hybridization;
- MITF;
- SOX10
Summary
A full understanding of transcriptional regulation requires integration of information obtained from multiple experimental datasets. These include datasets annotating gene expression within the context of an entire organism under normal and genetically perturbed conditions. Here we describe an expression dataset annotating pigment cell-expressed genes of the developing melanocyte and retinal pigmented epithelium lineages. Expression images are annotated and available at http://research.nhgri.nih.gov/manuscripts/Loftus/March2009/. Data are also summarized in a standardized manner using a universal melanoblast scoring scale that accounts for the embryonic location of cells and regional cell density. This approach allowed us to classify 14 pigment genes into four groupings classified by cell lineage expression, temporal-spatial context, and differential alteration in response to altered MITF and SOX10 status. Significant differences in regional populations were also observed across inbred strain backgrounds, highlighting the value of this approach to identify modifier allele influences on melanoblast number and distributions. This analysis revealed novel features of in vivo expression patterns that are not measurable by in vitro-based assays, providing data that in combination with genomic analyses will allow modeling of pigment cell gene expression in development and disease.

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