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Large scale ENU screens in the mouse: genetics meets genomics.

作者信息

Hrabé de Angelis M, Balling R

机构信息

Institute of Mammalian Genetics, GSF Research Center for Environment and Health, 85764 Neuherberg, Germany.

出版信息

Mutat Res. 1998 May 25;400(1-2):25-32. doi: 10.1016/s0027-5107(98)00061-x.

Abstract

The worldwide effort to completely sequence the human and mouse genome will be accomplished within the next years. The focus of current activities within the framework of human genome research is mainly on the assembly of high resolution genetic and physical maps and genomic sequencing. Cloning of new genes is getting more easy using those maps. Nevertheless, it is necessary to work on a systematic analysis of gene function. Results obtained from these efforts will be of enormous value for future biological and biomedical research. However, even the complete sequence will not in all cases reveal the molecular and cellular role of the different genes. Therefore, the next phase of the Human Genome Project will have at its core the functional analysis of genes. Those genes relevant for the diagnosis, prevention and therapy of human diseases are of particular interest. Looking at the history of life sciences, mutants have been the most important tool to obtain insight into the biological function of genes. The mouse is the model of choice for the study of inherited diseases in man. In order to meet the requirements for functional human genome analysis, we need a large number of mouse mutants similar to the collection of mutants available for other model organisms such as flys and worms. To fully apply the power of genetics, multiple alleles of the same gene such as hypomorphs or hypermorphs are required. Efficient production of mouse mutants showing specific phenotypes can be achieved by the use of ethylnitrosourea (ENU). ENU is the most powerful mutagen known and we currently see a renaissance of ENU mutagenesis. The application of ENU mutagenesis is reviewed and discussed in the context of a new era of functional genomics.

摘要

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