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Editorial |

Coexpression Networks Predict Ataxia Genes

Stefan M. Pulst, MD1; Lance T. Pflieger, BS2
[+] Author Affiliations
1Department of Neurology, University of Utah, Salt Lake City
2Department of Biomedical Informatics, University of Utah, Salt Lake City
JAMA Neurol. 2014;71(7):825-828. doi:10.1001/jamaneurol.2014.757.
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The genomics revolution has introduced novel platforms and bioinformatics approaches to the study of human diseases and model organisms. In this issue of JAMA Neurology, Bettencourt et al1 apply advanced bioinformatics techniques to elucidate the molecular functions and mechanisms of cerebellar gene expression networks using samples from a human brain bank. Their results have the potential to inform our understanding of degenerative diseases of the cerebellum and of shared pathways and discovery of novel disease genes.

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ataxia ; genes

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Figure 1.
GPR63 Expression

Midsagittal section of a mouse brain hybridized with a probe complementary to Gpr63. A, Nissl staining (original magnification ×10). B, In situ hybridization with expression masking (original magnification ×10). Strong expression in Purkinje cells is seen with virtually absent signal in other neuronal groups. Image is from the Allen Mouse Brain Atlas (http://mouse.brain-map.org; Accessed April 4, 2014).

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Figure 2.
Visualization of Calcium Module

Spider plot, created with Cytoscape (the Cytoscape Consortium), of the black module derived by weighted gene coexpression network analysis of cerebellar RNAs from wild-type and transgenic mice at 3 time points (postnatal day 1, 3 weeks, and 6 weeks). Overrepresentation analysis of Gene Ontology terms indicates enrichment of genes (yellow) associated with calcium ion binding (P < .01). The gene Grm1 (red), encoding the metabotropic glutamate receptor type 1, is a highly interconnected hub gene for this module.

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