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Generation and characterization of a novel transgenic mouse harboring conditional nuclear factor-kappa B/RelA knockout alleles

Overview of attention for article published in BMC Developmental Biology, September 2016
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Title
Generation and characterization of a novel transgenic mouse harboring conditional nuclear factor-kappa B/RelA knockout alleles
Published in
BMC Developmental Biology, September 2016
DOI 10.1186/s12861-016-0135-8
Pubmed ID
Authors

Talha Ijaz, Maki Wakamiya, Hong Sun, Adrian Recinos, Ronald G. Tilton, Allan R. Brasier

Abstract

Nuclear Factor-Kappa B (NF-kB) is a family of transcription factors that are important in embryonic development, inflammation, epithelial-to-mesenchymal transition and cancer. The 65 kDa RelA subunit is the major transcriptional activator of the NF-kB pathways. Whole-body deficiency of RelA leads to massive apoptosis of liver hepatocytes and death in utero. To study the role of RelA in physiology and in disease states in a manner that circumvents this embryonic lethal phenotype, we have generated a mouse with RelA conditional knockout (CKO) alleles containing loxP sites that are deleted by activated Cre recombinase. We demonstrate that RelA(CKO/CKO) mice are fertile, do not display any developmental defects and can be crossed with Cre-expressing mice to delete RelA in a temporal, tissue-specific manner. Our mating of RelA(CKO/CKO) mice with Zp3-Cre transgenic led to embryonic lethality of RelA-deficient embryos. In contrast, mating of RelA(CKO/CKO) mice with Col1α2-CreER mice allowed for the generation of double transgenics which could be stimulated with tamoxifen to induce fibroblast-specific RelA deletion in adulthood. Based on our collective data, we conclude that this novel RelA(CKO/CKO) mouse allows for efficient deletion of RelA in a tissue-specific manner. This RelA(CKO/CKO) mouse will be an invaluable tool for deciphering the mechanistic roles of RelA in various cells and tissues during development and in disease.

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The data shown below were compiled from readership statistics for 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 22 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 32%
Other 2 9%
Student > Master 2 9%
Student > Bachelor 1 5%
Researcher 1 5%
Other 1 5%
Unknown 8 36%
Readers by discipline Count As %
Agricultural and Biological Sciences 4 18%
Biochemistry, Genetics and Molecular Biology 3 14%
Neuroscience 3 14%
Medicine and Dentistry 2 9%
Immunology and Microbiology 1 5%
Other 0 0%
Unknown 9 41%