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A Large-Scale, Gene-Driven Mutagenesis Approach for the Functional Analysis of the Mouse Genome
A major challenge of the postgenomic era is the functional characterization of every single gene within the mammalian genome. In an effort to address this challenge, we assembled a collection of mutations in mouse embryonic stem (ES) cells, which is the largest publicly accessible collection of such...
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Published in: | Proceedings of the National Academy of Sciences - PNAS 2003-08, Vol.100 (17), p.9918-9922 |
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Main Authors: | , , , , , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | A major challenge of the postgenomic era is the functional characterization of every single gene within the mammalian genome. In an effort to address this challenge, we assembled a collection of mutations in mouse embryonic stem (ES) cells, which is the largest publicly accessible collection of such mutations to date. Using four different gene-trap vectors, we generated 5,142 sequences adjacent to the gene-trap integration sites (gene-trap sequence tags; http://genetrap.de) from >11,000 ES cell clones. Although most of the gene-trap vector insertions occurred randomly throughout the genome, we found both vector-independent and vector-specific integration "hot spots." Because >50% of the hot spots were vector-specific, we conclude that the most effective way to saturate the mouse genome with gene-trap insertions is by using a combination of gene-trap vectors. When a random sample of gene-trap integrations was passaged to the germ line, 59% (17 of 29) produced an observable phenotype in transgenic mice, a frequency similar to that achieved by conventional gene targeting. Thus, gene trapping allows a large-scale and cost-effective production of ES cell clones with mutations distributed throughout the genome, a resource likely to accelerate genome annotation and the in vivo modeling of human disease. |
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ISSN: | 0027-8424 1091-6490 |
DOI: | 10.1073/pnas.1633296100 |