Spatial gene expression analysis of neuroanatomical differences in mouse models

Darren J. Fernandes, Jacob Ellegood, Rand Askalan, Randy D. Blakely, Emanuel Dicicco-Bloom, Sean E. Egan, Lucy R. Osborne, Craig M. Powell, Armin Raznahan, Diane M. Robins, Michael W. Salter, Ameet S. Sengar, Jeremy Veenstra-VanderWeele, Jason P. Lerch

Research output: Contribution to journalArticlepeer-review

10 Scopus citations


MRI is a powerful modality to detect neuroanatomical differences that result from mutations and treatments. Knowing which genes drive these differences is important in understanding etiology, but candidate genes are often difficult to identify. We tested whether spatial gene expression data from the Allen Brain Institute can be used to inform us about genes that cause neuroanatomical differences. For many single-gene-mutation mouse models, we found that affected neuroanatomy was not strongly associated with the spatial expression of the altered gene and there are specific caveats for each model. However, among models with significant neuroanatomical differences from their wildtype controls, the mutated genes had preferential spatial expression in affected neuroanatomy. In mice exposed to environmental enrichment, candidate genes could be identified by a genome-wide search for genes with preferential spatial expression in the altered neuroanatomical regions. These candidates have functions related to learning and plasticity. We demonstrate that spatial gene expression of single-genes is a poor predictor of altered neuroanatomy, but altered neuroanatomy can identify candidate genes responsible for neuroanatomical phenotypes.

Original languageEnglish (US)
Pages (from-to)220-230
Number of pages11
StatePublished - Dec 2017

ASJC Scopus subject areas

  • Neurology
  • Cognitive Neuroscience


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