Generation of knockout alleles by RFLP based BAC targeting of polymorphic embryonic stem cells

Tahsin Stefan Barakat*, Joost Gribnau

*Corresponding author for this work

Research output: Chapter/Conference proceedingChapterAcademic

1 Citation (Scopus)

Abstract

The isolation of germ line competent mouse Embryonic Stem (ES) cells and the ability to modify the genome by homologous recombination has revolutionized life science research. Since its initial discovery, several approaches have been introduced to increase the efficiency of homologous recombination, including the use of isogenic DNA for the generation of targeting constructs, and the use of Bacterial Artificial Chromosomes (BACs). BACs have the advantage of combining long stretches of homologous DNA, thereby increasing targeting efficiencies, with the possibilities delivered by BAC recombineering approaches, which provide the researcher with almost unlimited possibilities to efficiently edit the genome in a controlled fashion. Despite these advantages of BAC targeting approaches, a widespread use has been hampered, mainly because of the difficulties in identifying BAC-targeted knockout alleles by conventional methods like Southern Blotting. Recently, we introduced a novel BAC targeting strategy, in which Restriction Fragment Length Polymorphisms (RFLPs) are targeted in polymorphic mouse ES cells, enabling an efficient and easy PCR-based readout to identify properly targeted alleles. Here we provide a detailed protocol for the generation of targeting constructs, targeting of ES cells, and convenient PCRbased analysis of targeted clones, which enable the user to generate knockout ES cells of almost every gene in the mouse genome within a 2-month period.

Original languageEnglish
Title of host publicationBacterial Artificial Chromosomes
Subtitle of host publicationSecond Edition
EditorsKumaran Narayanan
Chapter7
Pages143-180
Number of pages38
ISBN (Electronic)9781493916528
DOIs
Publication statusPublished - 19 Sept 2014

Bibliographical note

Publisher Copyright: © Springer Science+Business Media New York 2015. All rights are reserved.

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