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Proceedings of the National Academy of Sciences
Article . 2003 . Peer-reviewed
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A large-scale, gene-driven mutagenesis approach for the functional analysis of the mouse genome

Authors: Hansen, J.; Floss, T.; van Sloun, P.; Füchtbauer, Ernst-Martin; Vauti, F.; Arnold, H.; Schnütgen, F.; +3 Authors

A large-scale, gene-driven mutagenesis approach for the functional analysis of the mouse genome

Abstract

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.

Keywords

Base Sequence, Stem Cells, Genetic Vectors, Mice, Transgenic, DNA, Genomics, Cell Line, Mice, Inbred C57BL, Mice, Mutagenesis, Insertional, Phenotype, Animals, Humans, Sequence Tagged Sites

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
135
Top 10%
Top 1%
Top 1%
bronze