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. Mehr anzeigen
Persistenter Link
https://doi.org/10.3929/ethz-b-000130432Publikationsstatus
publishedExterne Links
Zeitschrift / Serie
eLifeBand
Seiten / Artikelnummer
Verlag
eLife Sciences PublicationsOrganisationseinheit
09474 - Yanik, Mehmet Fatih / Yanik, Mehmet Fatih
09474 - Yanik, Mehmet Fatih / Yanik, Mehmet Fatih