Mouse Genomics Resource Laboratory (MGRL) • Koide Group

Genetic mapping using congenic strains is one of the most powerful methods available to show the existence of QTLs in the genomic regions substituted into recipient strains. In this case, genetic mapping can be conducted by making a series of congenic strains that cover genomic regions that partially overlap with the adjacent congenic strains. In the analysis of the phenotype using a series of congenic strains, however, the phenotype shows a variety of levels, which indicates the existence of multiple QTLs in the mapped chromosomal regions. These results show that the precise genetic mapping of fine QTLs is extremely difficult using current methods.

Dr. Tsuyoshi Koide’s group collaborated with Drs. Shogo Kato and Satoshi Kuriki in the Institute of Statistical Mathematics and established a new method for mapping multiple QTLs using data from a series of congenic strains by applying a regression model for the analysis of total home-cage activity in mice. The results of the analysis identified four significant QTLs in a 14.5 Mb genomic region. Among these, three have negative effects but one has a positive effect on total home-cage activity. In further analysis of recombinants obtained from the congenic strains, we confirmed the existence of the QTL that has a positive effect on the activity as well as another QTL that suppresses the effect of this positive QTL. These results clarify for the first time the association of a complex genetic mechanism in the QTL cluster on chromosome 6 with the regulation of home-cage activity.

This work was supported by the Research Organization of Information and Systems, Transdisciplinary Research Integration Center, JSPS KAKENHI (Grant Numbers 23650243 and 25116527), and Yamada Science Foundation.

A cluster of four QTLs for behavior segregated by new method using a statistical regression model. The data of genomic regions carried in the congenic strains as well as the data of home-cage activity exhibited by congenic strains are analyzed with regression model. The study revealed four QTLs which are clustered in a small genomic region.