Second-generation high-throughput forward genetic screen in mice to isolate subtle behavioral mutants.

利用第二代高通量正向遗传筛选技术在小鼠中分离出细微的行为突变体

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作者:Kumar Vivek, Kim Kyungin, Joseph Chryshanthi, Thomas Lisa C, Hong Heekyung, Takahashi Joseph S
Forward genetic screens have been highly successful in revealing roles of genes and pathways in complex biological events. Traditionally these screens have focused on isolating mutants with the greatest phenotypic deviance, with the hopes of discovering genes that are central to the biological event being investigated. Behavioral screens in mice typically use simple activity-based assays as endophenotypes for more complex emotional states of the animal. They generally set the selection threshold for a putative mutant at 3 SDs (z score of 3) from the average behavior of normal animals to minimize false-positive results. Behavioral screens using a high threshold for detection have generally had limited success, with high false-positive rates and subtle phenotypic differences that have made mapping and cloning difficult. In addition, targeted reverse genetic approaches have shown that when genes central to behaviors such as open field behavior, psychostimulant response, and learning and memory tasks are mutated, they produce subtle phenotypes that differ from wild-type animals by 1 to 2 SDs (z scores of 1 to 2). We have conducted a second-generation (G2) dominant N-ethyl-N-nitrosourea (ENU) screen especially designed to detect subtle behavioral mutants for open field activity and psychostimulant response behaviors. We successfully detect mutant lines with only 1 to 2 SD shifts in mean response compared with wild-type control animals and present a robust statistical and methodological framework for conducting such forward genetic screens. Using this methodology we have screened 229 ENU mutant lines and have identified 15 heritable mutant lines. We conclude that for screens in mice that use activity-based endophenotypic measurements for complex behavioral states, this G2 screening approach yields better results.

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