Location: Location not imported yet.Title: In-silico mapping of quantitative trait loci for lactation-associated traits in inbred mice) Author
Submitted to: Meeting Abstract
Publication Type: Abstract only
Publication Acceptance Date: 10/20/2011
Publication Date: 11/15/2011
Citation: Hadsell, D.L., Wei, J., Olea, W., Shariflou, M., Thomson, P.C., Renwick, A., Williamson, P. 2011. In-silico mapping of quantitative trait loci for lactation-associated traits in inbred mice [abstract]. Proceedings of the 8th International Symposium on Milk Genomics and Human Health, November 15-17, 2011, Melbourne, Australia. Interpretive Summary:
Technical Abstract: Significant variation exists for fecundity and maternal nurturing ability in inbred mice. Classical gene mapping approaches in mice have identified several quantitative trait loci (QTL) that account for some this variation. Current studies in our laboratory are aimed at identifying QTL genes that underlie variation in lactation-associated traits in the inbred mouse. The recent generation of high-density SNP databases is facilitating this work. Quantitative data for a panel of lactation-associated traits were collected from females representing each of 32 inbred strains (N=8 - 19 dams/strain) during the first 10 days of their second lactation. Average daily weight gain of crossfoster litters served as the primary indicator of milk production and was analyzed both for the limited subset of dams that successfully reared 10 pups/litter (ADG10) and for all dams regardless of pup-rearing ability (ADG_ALL). The number of pups successfully reared to 8 days (PNUM8) also served as a related indicator of maternal ability and/or milk production. Additional lactation-related traits studied included pups born, maternal body mass, maternal food intake, and milk composition, as well as two traits related to mitochondrial biogenesis and function, and three traits related to maternal behavior. All three of the milk production traits were significantly affected by strain (P<0.0001). The range of strain means was -0.71+/-0.63 to 4.59+/-0.24 g/day and 1.48+/-0.29 to 4.75+/-0.20 g/day for ADG_ALL and ADG10, respectively. For PNUM8, the range of strain means was 6.4+/-1.1 to 10.0+/-0.0. Both ADG10 and PNUM8 were highly correlated with ADG_ALL (r>0.90, P<0.0001). Several of the related maternal traits listed above were also significantly correlated with ADG_ALL. Haplotype association using a false discovery rate of 5% detected haplotype blocks containing 70, 3513, and 387 genes for ADG10, ADG_ALL, and PNUM8, respectively. Comparison of gene enrichment among the three traits revealed only 7 common genes between ADG10 and PNUM8, while there were 40 genes in common between ADG10 and ADG_ALL, and 225 in common between PNUM8 and ADG_ALL. Ontology analysis of the 225 genes in common between ADG_ALL and PNUM8 using IPA produced networks linked to cell signaling, carbohydrate metabolism, small molecule biochemistry, cell morphology, cellular movement, and cellular assembly and organization. The most highly enriched cannonical pathway for this gene set was Erk5 signaling (P=10-5). With a more conservative genome-wide threshold of (10-5), haplotype associations to ADG10 were detected on 9 chromosomes, with two strong associations on MMU13. The strongest (P=10-8) was with a block of 94 kbp that contained the gene, namely Emb. For ADG_ALL, there were also associations on 9 chromosomes. All but two of these were unique in comparison to ADG10. The strongest associations were detected using PNUM8. For this trait, associations were detected on 11 chromosomes. The strongest of these were found on MMU11, which contained a total of 11 associated (P=10-6 to 10-10) blocks. Genes within these blocks included Sec61g, Egfr, Krt17, and Krt42. A previously identified fecundity QTL (Pregq2) was also present. A block on MMU8 (P=10-9) contained the gene Nr3c2, which encodes for the mineralocorticoid receptor. A cluster of blocks on MMU9 overlapped with the previously described litter gain QTL, Neogq1, and contained 3 genes. Lastly, a block (P=10-7) on mMU19 contained the gene Gnaq, which encodes a quanine nucleotide binding protein that interacts with the Erk5 signaling pathway. These results suggest that in-silico haplotype association mapping is a useful tool for identifying the genes and possibly even pathways that contribute to natural variations in milk production and other lactation-related traits.