Parent-of-origin effects propagate through networks to shape metabolic traits

  1. Juan F Macias-Velasco
  2. Celine L St. Pierre
  3. Jessica P Wayhart
  4. Li Yin
  5. Larry Spears
  6. Mario A Miranda
  7. Caryn Carson
  8. Katsuhiko Funai
  9. James Cheverud
  10. Clay F Semenkovich
  11. Heather A Lawson  Is a corresponding author
  1. Washington University in Saint Louis, United States
  2. University of Utah, United States
  3. Loyola University Chicago, United States

Abstract

Parent-of-origin effects are unexpectedly common in complex traits, including metabolic and neurological traits. Parent-of-origin effects can be modified by the environment, but the architecture of these gene-by-environmental effects on phenotypes remains to be unraveled. Previously, quantitative trait loci (QTL) showing context-specific parent-of-origin effects on metabolic traits were mapped in the F16 generation of an advanced intercross between LG/J and SM/J inbred mice. However, these QTL were not enriched for known imprinted genes, suggesting another mechanism is needed to explain these parent-of-origin effects phenomena. We propose that non-imprinted genes can generate complex parent-of-origin effects on metabolic traits through interactions with imprinted genes. Here, we employ data from mouse populations at different levels of intercrossing (F0, F1, F2, F16) of the LG/J and SM/J inbred mouse lines to test this hypothesis. Using multiple populations and incorporating genetic, genomic, and physiological data, we leverage orthogonal evidence to identify networks of genes through which parent-of-origin effects propagate. We identify a network comprised of 3 imprinted and 6 non-imprinted genes that show parent-of-origin effects. This epistatic network forms a nutritional responsive pathway and the genes comprising it jointly serve cellular functions associated with growth. We focus on 2 genes, Nnat and F2r, whose interaction associates with serum glucose levels across generations in high fat-fed females. Single-cell RNAseq reveals that Nnat expression increases and F2r expression decreases in pre-adipocytes along an adipogenic trajectory, a result that is consistent with our observations in bulk white adipose tissue.

Data availability

Sequencing data are available through the NCBI-SRA under accession code PRJNA753198

The following data sets were generated
The following previously published data sets were used

Article and author information

Author details

  1. Juan F Macias-Velasco

    Department of Genetics, Washington University in Saint Louis, Saint Louis, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-2827-4647
  2. Celine L St. Pierre

    Department of Genetics, Washington University in Saint Louis, Saint Louis, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5465-6601
  3. Jessica P Wayhart

    Department of Genetics, Washington University in Saint Louis, Saint Louis, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Li Yin

    Department of Medicine, Washington University in Saint Louis, Saint Louis, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. Larry Spears

    Department of Medicine, Washington University in Saint Louis, Saint Louis, United States
    Competing interests
    The authors declare that no competing interests exist.
  6. Mario A Miranda

    Department of Genetics, Washington University in Saint Louis, Saint Louis, United States
    Competing interests
    The authors declare that no competing interests exist.
  7. Caryn Carson

    Department of Genetics, Washington University in Saint Louis, Saint Louis, United States
    Competing interests
    The authors declare that no competing interests exist.
  8. Katsuhiko Funai

    Diabetes and Metabolism Research Center, University of Utah, Salt Lake City, United States
    Competing interests
    The authors declare that no competing interests exist.
  9. James Cheverud

    Department of Biology, Loyola University Chicago, Chicago, United States
    Competing interests
    The authors declare that no competing interests exist.
  10. Clay F Semenkovich

    Department of Medicine, Washington University in Saint Louis, Saint Louis, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1163-1871
  11. Heather A Lawson

    Department of Genetics, Washington University in Saint Louis, Saint Louis, United States
    For correspondence
    lawson@wustl.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-3550-5485

Funding

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Ethics

Animal experimentation: Mouse colony was maintained at the Washington University School of Medicine and all experiments were approved by the Institutional Animal Care and Use Committee in accordance with the National Institutes of Health guidelines for the care and use of laboratory animals. Protocol #20-0384

Copyright

© 2022, Macias-Velasco et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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  1. Juan F Macias-Velasco
  2. Celine L St. Pierre
  3. Jessica P Wayhart
  4. Li Yin
  5. Larry Spears
  6. Mario A Miranda
  7. Caryn Carson
  8. Katsuhiko Funai
  9. James Cheverud
  10. Clay F Semenkovich
  11. Heather A Lawson
(2022)
Parent-of-origin effects propagate through networks to shape metabolic traits
eLife 11:e72989.
https://doi.org/10.7554/eLife.72989

Share this article

https://doi.org/10.7554/eLife.72989

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