1. Genetics and Genomics

The single-cell eQTLGen consortium

  1. Monique GP van der Wijst  Is a corresponding author
  2. Dylan H de Vries
  3. Hilde E Groot
  4. Gosia Trynka
  5. Chung-Chau Hon
  6. Marc-Jan Bonder
  7. Oliver Stegle
  8. Martijn Nawijn
  9. Youssef Idaghdour
  10. Pim van der Harst
  11. Chun J Ye
  12. Joseph Powell
  13. Fabian J Theis
  14. Ahmed Mahfouz
  15. Matthias Heinig
  16. Lude Franke
  1. University of Groningen, University Medical Center Groningen, Netherlands
  2. Wellcome Sanger Institute, United Kingdom
  3. RIKEN Center for Integrative Medical Sciences, Japan
  4. European Molecular Biology Laboratory, European Bioinformatics Institute, United Kingdom
  5. DKFZ, Germany
  6. New York University Abu Dhabi, United Arab Emirates
  7. University of California, San Francisco, United States
  8. Garvan Institute, Australia
  9. Helmholtz Zentrum München, Germany
  10. Leiden University Medical Center, Netherlands
  11. Institute of Computational Biology, Helmholtz Zentrum München, Technical University of Munich, Germany
https://doi.org/10.7554/eLife.52155
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Cite this article
  1. Monique GP van der Wijst
  2. Dylan H de Vries
  3. Hilde E Groot
  4. Gosia Trynka
  5. Chung-Chau Hon
  6. Marc-Jan Bonder
  7. Oliver Stegle
  8. Martijn Nawijn
  9. Youssef Idaghdour
  10. Pim van der Harst
  11. Chun J Ye
  12. Joseph Powell
  13. Fabian J Theis
  14. Ahmed Mahfouz
  15. Matthias Heinig
  16. Lude Franke
(2020)
The single-cell eQTLGen consortium
eLife 9:e52155.
https://doi.org/10.7554/eLife.52155
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Abstract

In recent years, functional genomics approaches combining genetic information with bulk RNA-sequencing data have identified the downstream expression effects of disease-associated genetic risk factors through so-called expression quantitative trait locus (eQTL) analysis. Single-cell RNA-sequencing creates enormous opportunities for mapping eQTLs across different cell types and in dynamic processes, many of which are obscured when using bulk methods. Rapid increase in throughput and reduction in cost per cell now allow this technology to be applied to large-scale population genetics studies. To fully leverage these emerging data resources, we have founded the single-cell eQTLGen consortium (sc-eQTLGen), aimed at pinpointing the cellular contexts in which disease-causing genetic variants affect gene expression. Here, we outline the goals, approach and potential utility of the sc-eQTLGen consortium. We also provide a set of study design considerations for future single-cell eQTL studies.

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Article and author information

Author details

  1. Monique GP van der Wijst

    Genetics, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
    For correspondence
    m.g.p.van.der.wijst@umcg.nl
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1520-3970

  2. Dylan H de Vries

    Genetics, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
    Competing interests
    The authors declare that no competing interests exist.

  3. Hilde E Groot

    Cardiology, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-8265-3085

  4. Gosia Trynka

    Cellular Genetics, Wellcome Sanger Institute, Hinxton, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-6955-9529

  5. Chung-Chau Hon

    Genome Information Analysis, RIKEN Center for Integrative Medical Sciences, Yokahama, Japan
    Competing interests
    The authors declare that no competing interests exist.

  6. Marc-Jan Bonder

    Wellcome Trust Genome Campus, European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-8431-3180

  7. Oliver Stegle

    DKFZ, Heidelberg, Germany
    Competing interests
    The authors declare that no competing interests exist.

  8. Martijn Nawijn

    Department of Pathology and Medical Biology, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-3372-6521

  9. Youssef Idaghdour

    Program in Biology, Public Health Research Center, New York University Abu Dhabi, Abu Dhabi, United Arab Emirates
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-2768-9376

  10. Pim van der Harst

    Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-2713-686X

  11. Chun J Ye

    Division of Rheumatology, Department of Medicine, Department of Bioengineering and Therapeutic Sciences, Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.

  12. Joseph Powell

    Garvan Institute, Sydney, Australia
    Competing interests
    The authors declare that no competing interests exist.

  13. Fabian J Theis

    Institute of Computational Biology, German Research Center for Environmental Health, Helmholtz Zentrum München, Neuherberg, Germany
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-2419-1943

  14. Ahmed Mahfouz

    Single cell analysis, Leiden University Medical Center, Leiden, Netherlands
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-8601-2149

  15. Matthias Heinig

    Germany Department of Informatics, Institute of Computational Biology, Helmholtz Zentrum München, Technical University of Munich, Neuherberg, München, Germany
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5612-1720

  16. Lude Franke

    Genetics, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
    Competing interests
    The authors declare that no competing interests exist.

Funding

Dutch Research Council (NWO-Veni 192.029)

  • Monique GP van der Wijst

Dutch Research Council (ZonMW-VIDI 917.14.374)

  • Lude Franke

European Research Council (ERC Starting grant Immrisk 637640)

  • Lude Franke

Oncode Institute

  • Lude Franke

National Health and Medical Research Council (Investigator grant 1175781)

  • Joseph Powell

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

Reviewing Editor

  1. Helena Pérez Valle, eLife, United Kingdom

Publication history

  1. Received: September 24, 2019
  2. Accepted: March 3, 2020
  3. Accepted Manuscript published: March 9, 2020 (version 1)
  4. Version of Record published: March 17, 2020 (version 2)

Copyright

© 2020, van der Wijst 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. Monique GP van der Wijst
  2. Dylan H de Vries
  3. Hilde E Groot
  4. Gosia Trynka
  5. Chung-Chau Hon
  6. Marc-Jan Bonder
  7. Oliver Stegle
  8. Martijn Nawijn
  9. Youssef Idaghdour
  10. Pim van der Harst
  11. Chun J Ye
  12. Joseph Powell
  13. Fabian J Theis
  14. Ahmed Mahfouz
  15. Matthias Heinig
  16. Lude Franke
(2020)
The single-cell eQTLGen consortium
eLife 9:e52155.
https://doi.org/10.7554/eLife.52155

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