The Cerebellar Gene Database: a Collective Database of Genes Critical for Cerebellar Development.

This report presents the first comprehensive database that specifically compiles genes critical for cerebellar development and function. The Cerebellar Gene Database details genes that, when perturbed in mouse models, result in a cerebellar phenotype according to available data from both Mouse Genome Informatics and PubMed, as well as references to the corresponding studies for further examination. This database also offers a compilation of human genetic disorders with a cerebellar phenotype and their associated gene information from the Online Mendelian Inheritance in Man (OMIM) database. By comparing and contrasting the mouse and human datasets, we observe that only a small proportion of human mutant genes with a cerebellar phenotype have been studied in mouse knockout models. Given the highly conserved nature between mouse and human genomes, this surprising finding highlights how mouse genetic models can be more frequently employed to elucidate human disease etiology. On the other hand, many mouse genes identified in the present study that are known to lead to a cerebellar phenotype when perturbed have not yet been found to be pathogenic in the cerebellum of humans. This database furthers our understanding of human cerebellar disorders with yet-to-be-identified genetic causes. It is our hope that this gene database will serve as an invaluable tool for gathering background information, generating hypotheses, and facilitating translational research endeavors. Moreover, we encourage continual inputs from the research community in making this compilation a living database, one that remains up-to-date with the advances in cerebellar research.

CbGRiTS: cerebellar gene regulation in time and space.

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.