A digital atlas to characterize the mouse brain transcriptome.
Massive amounts of data are being generated in an effort to represent for the brain the expression of all genes at cellular resolution. Critical to exploiting this effort is the ability to place these data into a common frame of reference. Here we have developed a computational method for annotating gene expression patterns in the context of a digital atlas to facilitate custom user queries and comparisons of this type of data. This procedure has been applied to 200 genes in the postnatal mouse brain. As an illustration of utility, we identify candidate genes that may be related to Parkinson disease by using the expression of a dopamine transporter in the substantia nigra as a search query pattern. In addition, we discover that transcription factor Rorb is down-regulated in the barrelless mutant relative to control mice by quantitative comparison of expression patterns in layer IV somatosensory cortex. The semi-automated annotation method developed here is applicable to a broad spectrum of complex tissues and data modalities.
Carson
James P
JP
Program in Structural and Computational Biology and Molecular Biophysics, National Center for Macromolecular Imaging, Baylor College of Medicine, Houston, Texas, United States of America. james.carson@bcm.edu
Ju
Tao
T
Lu
Hui-Chen
HC
Thaller
Christina
C
Xu
Mei
M
Pallas
Sarah L
SL
Crair
Michael C
MC
Warren
Joe
J
Chiu
Wah
W
Eichele
Gregor
G
D000716:Anatomy, Artistic; D000818:Animals; D001921:Brain / Q000378:metabolism*; D019295:Computational Biology; D003198:Computer Simulation; D016208:Databases, Factual; D020869:Gene Expression Profiling; D017403:In Situ Hybridization; D008488:Medical Illustration; D051379:Mice; D014158:Transcription, Genetic / Q000235:genetics*