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

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Abstract

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.

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Acknowledgements

The authors thank Walter Olea for technical assistance. Thanks also to Mr. David Dworak for his assistance in the mineral analysis, Ms. Clarissa Aguilar for help with immunohistochemistry, Ms. Jessica Elswood for help with the EMSA, and Dr. Karen Triff for assistance with SNP and genomic feature analysis. This project was funded by USDA/ARS cooperative agreement # 250-51000-052. The contents of this publication do not necessarily reflect the views or policies of the U.S. Department of Agriculture, nor does mention of trade names, commercial products, or organizations imply endorsement by the U.S. Government.

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Authors and Affiliations

  1. Department of Pediatrics, USDA/ARS Children’s Nutrition Research Center, Baylor College of Medicine, Houston, TX, 77030, USA

    Darryl L. Hadsell, Louise A. Hadsell & Yareli Carcamo-Bahena

  2. Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX, 77030, USA

    Darryl L. Hadsell

  3. Department of Veterinary Integrative Biosciences, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX, USA

    Monique Rijnkels

  4. Department of Medical Genomics, Royal Prince Alfred Hospital, Sydney, NSW, Australia

    Jerry Wei

  5. School of Veterinary Science, University of Sydney, Sydney, NSW, Australia

    Peter Williamson

  6. School of life and Environmental Sciences, University of Sydney, Sydney, NSW, Australia

    Peter Williamson

  7. USDA/ARS Red River Valley Agricultural Research Center, Fargo, ND, USA

    Michael A. Grusak

  8. Department of Pediatrics, USDA/ARS Children’s Nutrition Research Center, 1100 Bates St. Suite 10072, Mail Stop: BCM-320, Houston, TX, 77030-2600, USA

    Darryl L. Hadsell

Authors
  1. Darryl L. Hadsell
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  2. Louise A. Hadsell
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  3. Monique Rijnkels
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Correspondence to Darryl L. Hadsell.

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Accession IDs

The experimental organism described in this paper in the mouse has accession ID 10090. The MGI accession numbers for all of the genes mentioned in this paper can be found in Online Resource 5.

Electronic supplementary material

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Supplementary material 1 (PDF 39 KB)

Supplementary material 2 (PDF 43 KB)

Supplementary material 3 (PDF 58 KB)

Supplementary material 4 (PDF 63 KB)

335_2018_9762_MOESM5_ESM.xlsx

Online Resource 5. Mammary Expression of Genes underlying milk mineral QTL detected in the mouse diversity panel. (XLSX 212 KB)

335_2018_9762_MOESM6_ESM.tif

Online Resource 6. The figure shows an ideogram of the 19 autosomes along with X and Y chromosomes for the mouse. Colored symbols and bars on each chromosome show the location of each of the 15 murine Mmcq along with the locations of milk mineral QTL that were identified in dairy cows. To map cattle milk mineral QTL (MM-QTL) to the mouse genome, bovine coordinates were obtained from the Animal QTL db (https://www.animal genome.org/cgi-bin/QTLdb/BT/index). These intervals were extended 10 kb on each side and resulting overlapping MM-QTL regions were merged for each mineral. The resulting bovine genome (Btau6) intervals were then lifted over to mm10 to be visualized alongside the mouse Mmcq loci using Liftover tool on the UCSC Genome Browser (http://genome-test.cse.ucsc.edu/). The ideogram was constructed using Ideographica (http://rtools.cbrc.jp/idiographica/). (TIF 543 KB)

Supplementary material 7 (PDF 12 KB)

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Hadsell, D.L., Hadsell, L.A., Rijnkels, M. et al. In silico mapping of quantitative trait loci (QTL) regulating the milk ionome in mice identifies a milk iron locus on chromosome 1. Mamm Genome 29, 632–655 (2018). https://doi.org/10.1007/s00335-018-9762-7

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