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Neuroimage. 2017 Dec;163:220-230. doi: 10.1016/j.neuroimage.2017.08.065. Epub 2017 Sep 4.

Spatial gene expression analysis of neuroanatomical differences in mouse models.

Author information

1
Mouse Imaging Centre, Hospital for Sick Children, Toronto, ON, Canada; Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada. Electronic address: darren.fernandes@sickkids.ca.
2
Mouse Imaging Centre, Hospital for Sick Children, Toronto, ON, Canada.
3
Department of Paediatrics, University of Toronto, Toronto, ON, Canada.
4
Charles E. Schmidt College of Medicine, Florida Atlantic University, Boca Raton, FL, USA.
5
Department of Neuroscience and Cell Biology, Rutgers Robert Wood Johnson Medical School, Piscataway, NJ, USA.
6
Developmental and Stem Cell Biology, Hospital for Sick Children, Toronto, ON, Canada; Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada.
7
Departments of Medicine and Molecular Genetics, University of Toronto, Toronto, ON, Canada.
8
Departments of Neurology and Neurotherapeutics, Psychiatry, Neuroscience Graduate Program, University of Texas Southwestern Medical Center, Dallas, TX, USA.
9
Child Psychiatry Branch, National Institutes of Mental Health, Bethesda, MD, USA.
10
Department of Human Genetics, University of Michigan Medical School, Ann Arbor, MI, USA.
11
Neurosciences and Mental Health Program, Hospital for Sick Children, Toronto, ON, Canada; Department of Physiology, University of Toronto, Toronto, ON, Canada.
12
Neurosciences and Mental Health Program, Hospital for Sick Children, Toronto, ON, Canada.
13
Department of Pharmacology, Vanderbilt Kennedy Center, Vanderbilt Brain Institute, Nashville, TN, USA.
14
Mouse Imaging Centre, Hospital for Sick Children, Toronto, ON, Canada; Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada.

Abstract

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.

[Indexed for MEDLINE]

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