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Whole-organism eQTL mapping at cellular resolution with single-cell sequencing

View ORCID ProfileEyal Ben-David, James Boocock, View ORCID ProfileLonghua Guo, View ORCID ProfileStefan Zdraljevic, View ORCID ProfileJoshua S. Bloom, Leonid Kruglyak
doi: https://doi.org/10.1101/2020.08.23.263798
Eyal Ben-David
1Department of Human Genetics, Department of Biological Chemistry, and Howard Hughes Medical Institute, University of California, Los Angeles, CA 90095, USA
2Department of Biochemistry and Molecular Biology, Institute for Medical Research Israel-Canada, The Hebrew University School of Medicine, Jerusalem, Israel
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  • ORCID record for Eyal Ben-David
  • For correspondence: eyal.bendavid@mail.huji.ac.il jbloom@mednet.ucla.edu lkruglyak@mednet.ucla.edu
James Boocock
1Department of Human Genetics, Department of Biological Chemistry, and Howard Hughes Medical Institute, University of California, Los Angeles, CA 90095, USA
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Longhua Guo
1Department of Human Genetics, Department of Biological Chemistry, and Howard Hughes Medical Institute, University of California, Los Angeles, CA 90095, USA
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Stefan Zdraljevic
1Department of Human Genetics, Department of Biological Chemistry, and Howard Hughes Medical Institute, University of California, Los Angeles, CA 90095, USA
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Joshua S. Bloom
1Department of Human Genetics, Department of Biological Chemistry, and Howard Hughes Medical Institute, University of California, Los Angeles, CA 90095, USA
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  • For correspondence: eyal.bendavid@mail.huji.ac.il jbloom@mednet.ucla.edu lkruglyak@mednet.ucla.edu
Leonid Kruglyak
1Department of Human Genetics, Department of Biological Chemistry, and Howard Hughes Medical Institute, University of California, Los Angeles, CA 90095, USA
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  • For correspondence: eyal.bendavid@mail.huji.ac.il jbloom@mednet.ucla.edu lkruglyak@mednet.ucla.edu
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Abstract

Genetic regulation of gene expression underlies variation in disease risk and other complex traits. The effect of expression quantitative trait loci (eQTLs) varies across cell types; however, the complexity of mammalian tissues makes studying cell-type eQTLs highly challenging. We developed a novel approach in the model nematode Caenorhabditis elegans that uses single cell RNA sequencing to map eQTLs at cellular resolution in a single one-pot experiment. We mapped eQTLs across cell types in an extremely large population of genetically distinct C. elegnas individuals. We found cell-type-specific trans-eQTL hotspots that affect the expression of core pathways in the relevant cell types. Finally, we found single-cell-specific eQTL effects in the nervous system, including an eQTL with opposite effects in two individual neurons. Our results show that eQTL effects can be specific down to the level of single cells.

Competing Interest Statement

The authors have declared no competing interest.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted December 15, 2020.
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Whole-organism eQTL mapping at cellular resolution with single-cell sequencing
Eyal Ben-David, James Boocock, Longhua Guo, Stefan Zdraljevic, Joshua S. Bloom, Leonid Kruglyak
bioRxiv 2020.08.23.263798; doi: https://doi.org/10.1101/2020.08.23.263798
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Whole-organism eQTL mapping at cellular resolution with single-cell sequencing
Eyal Ben-David, James Boocock, Longhua Guo, Stefan Zdraljevic, Joshua S. Bloom, Leonid Kruglyak
bioRxiv 2020.08.23.263798; doi: https://doi.org/10.1101/2020.08.23.263798

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