1. Genetics and Genomics
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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
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Cite this article as: eLife 2020;9:e52155 doi: 10.7554/eLife.52155

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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Further reading

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    Gabriel A Guerrero et al.
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    Longevity is often associated with stress resistance, but whether they are causally linked is incompletely understood. Here we investigate chemosensory-defective Caenorhabditis elegans mutants that are long-lived and stress resistant. We find that mutants in the intraflagellar transport protein gene osm-3 were significantly protected from tunicamycin-induced ER stress. While osm-3 lifespan extension is dependent on the key longevity factor DAF-16/FOXO, tunicamycin resistance was not. osm-3 mutants are protected from bacterial pathogens, which is pmk-1 p38 MAP kinase dependent, while TM resistance was pmk-1 independent. Expression of P-glycoprotein (PGP) xenobiotic detoxification genes was elevated in osm-3 mutants and their knockdown or inhibition with verapamil suppressed tunicamycin resistance. The nuclear hormone receptor nhr-8 was necessary to regulate a subset of PGPs. We thus identify a cell-nonautonomous regulation of xenobiotic detoxification and show that separate pathways are engaged to mediate longevity, pathogen resistance, and xenobiotic detoxification in osm-3 mutants.

    1. Epidemiology and Global Health
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    Mohd Anisul et al.
    Research Article Updated

    Background:

    The virus SARS-CoV-2 can exploit biological vulnerabilities (e.g. host proteins) in susceptible hosts that predispose to the development of severe COVID-19.

    Methods:

    To identify host proteins that may contribute to the risk of severe COVID-19, we undertook proteome-wide genetic colocalisation tests, and polygenic (pan) and cis-Mendelian randomisation analyses leveraging publicly available protein and COVID-19 datasets.

    Results:

    Our analytic approach identified several known targets (e.g. ABO, OAS1), but also nominated new proteins such as soluble Fas (colocalisation probability >0.9, p=1 × 10-4), implicating Fas-mediated apoptosis as a potential target for COVID-19 risk. The polygenic (pan) and cis-Mendelian randomisation analyses showed consistent associations of genetically predicted ABO protein with several COVID-19 phenotypes. The ABO signal is highly pleiotropic, and a look-up of proteins associated with the ABO signal revealed that the strongest association was with soluble CD209. We demonstrated experimentally that CD209 directly interacts with the spike protein of SARS-CoV-2, suggesting a mechanism that could explain the ABO association with COVID-19.

    Conclusions:

    Our work provides a prioritised list of host targets potentially exploited by SARS-CoV-2 and is a precursor for further research on CD209 and FAS as therapeutically tractable targets for COVID-19.

    Funding:

    MAK, JSc, JH, AB, DO, MC, EMM, MG, ID were funded by Open Targets. J.Z. and T.R.G were funded by the UK Medical Research Council Integrative Epidemiology Unit (MC_UU_00011/4). JSh and GJW were funded by the Wellcome Trust Grant 206194. This research was funded in part by the Wellcome Trust [Grant 206194]. For the purpose of open access, the author has applied a CC BY public copyright licence to any Author Accepted Manuscript version arising from this submission.