| Literature DB >> 25446528 |
Thomas Ha1, Douglas Swanson1, Matt Larouche1, Randy Glenn1, Dave Weeden1, Peter Zhang1, Kristin Hamre2, Michael Langston3, Charles Phillips3, Mingzhou Song4, Zhengyu Ouyang4, Elissa Chesler5, Suman Duvvurru5, Roumyana Yordanova5, Yan Cui6, Kate Campbell1, Greg Ricker7, Carey Phillips7, Ramin Homayouni8, Dan Goldowitz9.
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. CrownEntities:
Keywords: Cerebellum; Development; Granule cell; Mouse; Transcriptome
Mesh:
Year: 2014 PMID: 25446528 DOI: 10.1016/j.ydbio.2014.09.032
Source DB: PubMed Journal: Dev Biol ISSN: 0012-1606 Impact factor: 3.582