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BMC Mol Biol. 2010 Sep 15;11:70. doi: 10.1186/1471-2199-11-70.

High-resolution melting curve analysis for rapid detection of mutations in a Medaka TILLING library.

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Department of Radiation Biology and Medical Genetics, Graduate School of Medicine, Osaka University, B4, 2-2 Yamadaoka, Suita, Osaka 565-0871, Japan.



During the last two decades, DNA sequencing has led to the identification of numerous genes in key species; however, in most cases, their functions are still unknown. In this situation, reverse genetics is the most suitable method to assign function to a gene. TILLING (Targeting Induced Local Lesions IN Genomes) is a reverse-genetic strategy that combines random chemical mutagenesis with high-throughput discovery of the induced mutations in target genes. The method has been applied to a variety of plant and animal species. Screening of the induced mutations is the most important step in TILLING. Currently, direct sequencing or nuclease-mediated screening of heteroduplexes is widely used for detection of mutations in TILLING. Both methods are useful, but the costs are substantial and turnaround times are relatively long. Thus, there is a need for an alternative method that is of higher throughput and more cost effective.


In this study, we developed a high resolution melting (HRM) assay and evaluated its effectiveness for screening ENU-induced mutations in a medaka TILLING library. We had previously screened mutations in the p53 gene by direct sequencing. Therefore, we first tested the efficiency of the HRM assay by screening mutations in p53, which indicated that the HRM assay is as useful as direct sequencing. Next, we screened mutations in the atr and atm genes with the HRM assay. Nonsense mutations were identified in each gene, and the phenotypes of these nonsense mutants confirmed their loss-of-function nature.


These results demonstrate that the HRM assay is useful for screening mutations in TILLING. Furthermore, the phenotype of the obtained mutants indicates that medaka is an excellent animal model for investigating genome stability and gene function, especially when combined with TILLING.

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