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Dev Biol. 2015 Jan 1;397(1):18-30. doi: 10.1016/j.ydbio.2014.09.032. Epub 2014 Oct 23.

CbGRiTS: cerebellar gene regulation in time and space.

Author information

1
Centre for Molecular Medicine and Therapeutics, Child and Family Research Institute, Department of Medical Genetics, University of British Columbia, 950 West 28th Avenue, Vancouver, BC, Canada V5Z 4H4.
2
Department of Anatomy and Neurobiology, University of Tennessee Health Science Center, Memphis, TN, USA.
3
Department of Electrical Engineering and Computer Science, University of Tennessee, Knoxville, TN, USA.
4
Department of Computer Science, New Mexico State University, Las Cruces, NM, USA.
5
The Jackson Laboratory, Bar Harbor, ME, USA.
6
Department of Molecular Science, University of Tennessee Health Science Center, Memphis, TN, USA.
7
Department of Biology, Bowdoin College, Brunswick, ME, USA.
8
Bioinformatics Program, Department of Biology, University of Memphis, Memphis, TN, USA.
9
Centre for Molecular Medicine and Therapeutics, Child and Family Research Institute, Department of Medical Genetics, University of British Columbia, 950 West 28th Avenue, Vancouver, BC, Canada V5Z 4H4. Electronic address: dang@cmmt.ubc.ca.

Abstract

The mammalian CNS is one of the most complex biological systems to understand at the molecular level. The temporal information from time series transcriptome analysis can serve as a potent source of associative information between developmental processes and regulatory genes. Here, we introduce a new transcriptome database called, Cerebellar Gene Regulation in Time and Space (CbGRiTS). This dataset is populated with transcriptome data across embryonic and postnatal development from two standard mouse strains, C57BL/6J and DBA/2J, several recombinant inbred lines and cerebellar mutant strains. Users can evaluate expression profiles across cerebellar development in a deep time series with graphical interfaces for data exploration and link-out to anatomical expression databases. We present three analytical approaches that take advantage of specific aspects of the time series for transcriptome analysis. We demonstrate the use of CbGRiTS dataset as a community resource to explore patterns of gene expression and develop hypotheses concerning gene regulatory networks in brain development.

KEYWORDS:

Cerebellum; Development; Granule cell; Mouse; Transcriptome

PMID:
25446528
DOI:
10.1016/j.ydbio.2014.09.032
[Indexed for MEDLINE]
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