Automated deep-phenotyping of the vertebrate brain

Author:

Allalou Amin12ORCID,Wu Yuelong1ORCID,Ghannad-Rezaie Mostafa13,Eimon Peter M1ORCID,Yanik Mehmet Fatih13ORCID

Affiliation:

1. Massachusetts Institute of Technology, Cambridge, United States

2. Uppsala University, Uppsala, Sweden

3. ETH Zürich, Zürich, Switzerland

Abstract

Here, we describe an automated platform suitable for large-scale deep-phenotyping of zebrafish mutant lines, which uses optical projection tomography to rapidly image brain-specific gene expression patterns in 3D at cellular resolution. Registration algorithms and correlation analysis are then used to compare 3D expression patterns, to automatically detect all statistically significant alterations in mutants, and to map them onto a brain atlas. Automated deep-phenotyping of a mutation in the master transcriptional regulator fezf2 not only detects all known phenotypes but also uncovers important novel neural deficits that were overlooked in previous studies. In the telencephalon, we show for the first time that fezf2 mutant zebrafish have significant patterning deficits, particularly in glutamatergic populations. Our findings reveal unexpected parallels between fezf2 function in zebrafish and mice, where mutations cause deficits in glutamatergic neurons of the telencephalon-derived neocortex.

Funder

National Institutes of Health

David and Lucile Packard Foundation

The Eli and Edythe L. Broad Institute of MIT and Harvard

Epilepsy Foundation

Publisher

eLife Sciences Publications, Ltd

Subject

General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,General Medicine,General Neuroscience

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