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Combining Lipophilic dye, in situ Hybridization, Immunohistochemistry, and Histology
Journal article   Open access   Peer reviewed

Combining Lipophilic dye, in situ Hybridization, Immunohistochemistry, and Histology

Jeremy Duncan, Jennifer Kersigo, Brian Gray and Bernd Fritzsch
Journal of Visualized Experiments, Vol.49, e2451
2011
DOI: 10.3791/2451
PMCID: PMC3197290
PMID: 21445047
url
https://doi.org/10.3791/2451View
Published (Version of record) Open Access

Abstract

Going beyond single gene function to cut deeper into gene regulatory networks requires multiple mutations combined in a single animal. Such analysis of two or more genes needs to be complemented with in situ hybridization of other genes, or immunohistochemistry of their proteins, both in whole mounted developing organs or sections for detailed resolution of the cellular and tissue expression alterations. Combining multiple gene alterations requires the use of cre or flipase to conditionally delete genes and avoid embryonic lethality. Required breeding schemes dramatically enhance effort and cost proportional to the number of genes mutated, with an outcome of very few animals with the full repertoire of genetic modifications desired. Amortizing the vast amount of effort and time to obtain these few precious specimens that are carrying multiple mutations necessitates tissue optimization. Moreover, investigating a single animal with multiple techniques makes it easier to correlate gene deletion defects with expression profiles. We have developed a technique to obtain a more thorough analysis of a given animal; with the ability to analyze several different histologically recognizable structures as well as gene and protein expression all from the same specimen in both whole mounted organs and sections. Although mice have been utilized to demonstrate the effectiveness of this technique it can be applied to a wide array of animals. To do this we combine lipophilic dye tracing, whole mount in situ hybridization, immunohistochemistry, and histology to extract the maximal possible amount of data.
Neuroscience

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