Location: Children's Nutrition Research CenterTitle: In "silico" QTL mapping of maternal nurturing ability using the mouse divesity panel Author
Submitted to: Physiological Genomics
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 6/28/2012
Publication Date: 6/28/2012
Citation: Hadsell, D.L., Wei, J., Olea, W., Hadsell, L.A., Renwick, A., Thomson, P.C., Shariflou, M. 2012. In "silico" QTL mapping of maternal nurturing ability using the mouse divesity panel. Physiological Genomics. 44(16):787-798. Interpretive Summary: Lactation is the most energetically demanding stage of a female's lifetime. The identification of genes that are responsible for lactation capacity is needed. The goal of this study was to identify regions in the mouse genome that are associated with variation in milk production. We were able to use an existing dataset in conjunction with mouse mapping to identify regions in the mouse genome that contains genes that may be targets of novel approaches to enhancing lactation. These findings could have importance in furthering our understanding of mammary gland biology.
Technical Abstract: Significant variation exists for maternal nurturing ability in inbred mice. Although classical mapping approaches have identified quantitative trait loci (QTL) that may account for this variation, the underlying genes are unknown. In this study, lactation performance data among the mouse diversity panel was used to map genomic regions associated with this variation. Females from each of 32 inbred strains (N=8 - 19 dams/strain) were studied during the first 8 days of lactation by allowing them to raise weight- and size-normalized cross-foster litters (10 pups/litter). Average daily weight gain (ADG) of litters served as the primary indicator of milk production. The number of pups successfully reared to 8 days (PNUM8) also served as a related indicator of maternal performance. Initial haplotype association analysis using a Bonferroni-corrected, genome-wide threshold revealed 10 and 15 associations encompassing 11 and 13 genes for ADG, and PNUM8, respectively. The most significant of these associated haplotype blocks were found on MMU 8, 11, and 19 and contained the genes Nr3c2, Egfr, Sec61g, and Gnaq. Lastly, two haplotype blocks on MMU9 were detected in association with PNUM8. These overlapped with the previously described maternal performance QTL, Neogq1. These results suggest that the application of in silico QTL mapping is a useful tool in discovering the presence of novel candidate genes involved in determining lactation capacity in mice.