In silico mapping of quantitative trait loci (QTL) regulating the milk ionome in mice identifies a milk iron locus on chromosome 1.

The breast-feeding neonate depends on mother's milk for both macronutrients and micronutrients including minerals. The goals of the present study were to document the effects of genetic background in mice on milk concentrations of select minerals and to use genome-wide association study (GWAS) to identify quantitative trait loci (QTL) regulating milk mineral concentrations. Milk samples from lactating mice in each of 31 different inbred strains of the mouse diversity panel (MDP) were analyzed by inductively coupled plasma-optical emission spectroscopy to determine the concentrations of calcium (Ca), copper (Cu), iron (Fe), potassium (K), magnesium (Mg), sodium (Na), phosphorus (P), sulfur (S), and zinc (Zn). GWAS identified a single pleiotropic milk mineral concentration QTL (Mmcq) on chromosome 3 for Ca, Mg, and P. For the remaining minerals, six QTL were detected for Fe, four for K, three for Zn, and one for S. Intersecting the Mmcq with published chromatin immunoprecipitation sequence data identified 15 out of 4633 high-linkage disequilibrium single-nucleotide polymorphisms that resided in signal transducer and activation of transcription 5 (STAT5) binding regions. A milk Fe-associated locus (Mmcq9) on chromosome 1 contained an SNP that localized to a STAT5 binding region and intersected with a HOMER motif predicted to bind the transcriptional regulator E74-Like ETS transcription factor 5. This locus also contained the genes for solute carrier family (Slc) members Slc9a2, Slc9a4, Slc39a10, and Slc40a1. Expression analysis of these transporters supports the conclusion that Slc9a2 and Slc40a1 within the mammary gland could mediate the effect of Mmcq9 on milk Fe concentration.

In-silico QTL mapping of postpubertal mammary ductal development in the mouse uncovers potential human breast cancer risk loci.

Genetic background plays a dominant role in mammary gland development and breast cancer (BrCa). Despite this, the role of genetics is only partially understood. This study used strain-dependent variation in an inbred mouse mapping panel, to identify quantitative trait loci (QTL) underlying structural variation in mammary ductal development, and determined if these QTL correlated with genomic intervals conferring BrCa susceptibility in humans. For about half of the traits, developmental variation among the complete set of strains in this study was greater (P < 0.05) than that of previously studied strains, or strains in current common use for mammary gland biology. Correlations were also detected with previously reported variation in mammary tumor latency and metastasis. In-silico genome-wide association identified 20 mammary development QTL (Mdq). Of these, five were syntenic with previously reported human BrCa loci. The most significant (P = 1 × 10(-11)) association of the study was on MMU6 and contained the genes Plxna4, Plxna4os1, and Chchd3. On MMU5, a QTL was detected (P = 8 × 10(-7)) that was syntenic to a human BrCa locus on h12q24.5 containing the genes Tbx3 and Tbx5. Intersection of linked SNP (r(2) > 0.8) with genomic and epigenomic features, and intersection of candidate genes with gene expression and survival data from human BrCa highlighted several for further study. These results support the conclusion that mammary tumorigenesis and normal ductal development are influenced by common genetic factors and that further studies of genetically diverse mice can improve our understanding of BrCa in humans.