Subfunctionalized expression drives evolutionary retention of ribosomal protein paralogs Rps27 and Rps27l in vertebrates

  1. Adele Francis Xu
  2. Rut Molinuevo
  3. Elisa Fazzari
  4. Harrison Tom
  5. Zijian Zhang
  6. Julien Menendez
  7. Kerriann M Casey
  8. Davide Ruggero
  9. Lindsay Hinck
  10. Jonathan K Pritchard
  11. Maria Barna  Is a corresponding author
  1. Stanford University, United States
  2. University of California, Santa Cruz, United States
  3. University of California, Los Angeles, United States
  4. University of California, San Francisco, United States

Abstract

The formation of paralogs through gene duplication is a core evolutionary process. For paralogs that encode components of protein complexes such as the ribosome, a central question is whether they encode functionally distinct proteins, or whether they exist to maintain appropriate total expression of equivalent proteins. Here, we systematically tested evolutionary models of paralog function using the ribosomal protein paralogs Rps27 (eS27) and Rps27l (eS27L) as a case study. Evolutionary analysis suggests that Rps27 and Rps27l likely arose during whole-genome duplication(s) in a common vertebrate ancestor. We show that Rps27 and Rps27l have inversely correlated mRNA abundance across mouse cell types, with the highest Rps27 in lymphocytes and the highest Rps27l in mammary alveolar cells and hepatocytes. By endogenously tagging the Rps27 and Rps27l proteins, we demonstrate that Rps27- and Rps27l-ribosomes associate preferentially with different transcripts. Furthermore, murine Rps27 and Rps27l loss-of-function alleles are homozygous lethal at different developmental stages. However, strikingly, expressing Rps27 protein from the endogenous Rps27l locus or vice versa completely rescues loss-of-function lethality and yields mice with no detectable deficits. Together, these findings suggest that Rps27 and Rps27l are evolutionarily retained because their subfunctionalized expression patterns render both genes necessary to achieve the requisite total expression of two equivalent proteins across cell types. Our work represents the most in-depth characterization of a mammalian ribosomal protein paralog to date and highlights the importance of considering both protein function and expression when investigating paralogs.

Data availability

Ribosome profiling sequencing data have been deposited in GEO under accession code GSE201845. Other data generated in this study are provided in the supplementary materials and Source Data files. Code used for data analysis is available at https://gitfront.io/r/adelefxu/f94QE89EJwyp/eS27-paralogs/.

The following data sets were generated
The following previously published data sets were used
    1. Han X
    2. Guo G
    3. et al
    (2018) MCA DGE Data
    Figshare, doi:10.6084/m9.figshare.5435866.v8.

Article and author information

Author details

  1. Adele Francis Xu

    Department of Genetics, Stanford University, Stanford, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-3332-5285
  2. Rut Molinuevo

    Department of Molecular, Cell, and Developmental Biology, University of California, Santa Cruz, Santa Cruz, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Elisa Fazzari

    Helen Diller Family Comprehensive Cancer Center, University of California, Los Angeles, Los Angeles, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Harrison Tom

    Helen Diller Family Comprehensive Cancer Center, University of California, Los Angeles, Los Angeles, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. Zijian Zhang

    Department of Chemical and Systems Biology, Stanford University, Stanford, United States
    Competing interests
    The authors declare that no competing interests exist.
  6. Julien Menendez

    Department of Molecular, Cell, and Developmental Biology, University of California, Santa Cruz, Santa Cruz, United States
    Competing interests
    The authors declare that no competing interests exist.
  7. Kerriann M Casey

    Department of Biology, Stanford University, Stanford, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4228-928X
  8. Davide Ruggero

    Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-9444-5865
  9. Lindsay Hinck

    Department of Molecular, Cell, and Developmental Biology, University of California, Santa Cruz, Santa Cruz, United States
    Competing interests
    The authors declare that no competing interests exist.
  10. Jonathan K Pritchard

    Department of Genetics, Stanford University, Stanford, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-8828-5236
  11. Maria Barna

    Department of Genetics, Stanford University, Stanford, United States
    For correspondence
    mbarna@stanford.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-6843-4396

Funding

National Institutes of Health (F30HD100123)

  • Adele Francis Xu

Stanford Bio-X

  • Adele Francis Xu

National Institutes of Health (5R01HG008140)

  • Jonathan K Pritchard

New York Stem Cell Foundation (NYSCF-R-I36)

  • Maria Barna

National Institutes of Health (R01HD086634)

  • Maria Barna

Alfred P. Sloan Foundation

  • Maria Barna

Pew Charitable Trusts

  • Maria Barna

National Institutes of Health (R01HD098722)

  • Lindsay Hinck

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

Reviewing Editor

  1. Shigehiro Kuraku, National Institute of Genetics, Japan

Ethics

Animal experimentation: All animal work was reviewed and approved by the Stanford Administrative Panel on Laboratory Animal Care (APLAC, protocol #27463). The Stanford APLAC is accredited by the American Association for the Accreditation of Laboratory Animal Care. All mice used in the study were housed at Stanford University except where otherwise noted. CRISPR-edited mouse lines were generated at the Gladstone Institute Transgenic Gene Targeting Core (San Francisco, CA). All animal procedures were approved by the Institutional Animal Care and Use Committee at the University of California, San Francisco (protocol #AN180952-01B).

Version history

  1. Received: March 16, 2022
  2. Preprint posted: May 4, 2022 (view preprint)
  3. Accepted: June 9, 2023
  4. Accepted Manuscript published: June 12, 2023 (version 1)
  5. Version of Record published: June 30, 2023 (version 2)

Copyright

© 2023, Xu 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. Adele Francis Xu
  2. Rut Molinuevo
  3. Elisa Fazzari
  4. Harrison Tom
  5. Zijian Zhang
  6. Julien Menendez
  7. Kerriann M Casey
  8. Davide Ruggero
  9. Lindsay Hinck
  10. Jonathan K Pritchard
  11. Maria Barna
(2023)
Subfunctionalized expression drives evolutionary retention of ribosomal protein paralogs Rps27 and Rps27l in vertebrates
eLife 12:e78695.
https://doi.org/10.7554/eLife.78695

Share this article

https://doi.org/10.7554/eLife.78695

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