The single-cell eQTLGen consortium
- University of Groningen, University Medical Center Groningen, Netherlands
- Wellcome Sanger Institute, United Kingdom
- RIKEN Center for Integrative Medical Sciences, Japan
- European Molecular Biology Laboratory, European Bioinformatics Institute, United Kingdom
- DKFZ, Germany
- New York University Abu Dhabi, United Arab Emirates
- University of California, San Francisco, United States
- Garvan Institute, Australia
- Helmholtz Zentrum München, Germany
- Leiden University Medical Center, Netherlands
- Institute of Computational Biology, Helmholtz Zentrum München, Technical University of Munich, Germany
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.
Data availability
Not applicable
Article and author information
Author details
Monique GP van der Wijst
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.
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.
Metrics
-
- 11,061
- views
-
- 1,265
- downloads
-
- 173
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Download links
A two-part list of links to download the article, or parts of the article, in various formats.
Downloads (link to download the article as PDF)
Open citations (links to open the citations from this article in various online reference manager services)
Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)
The single-cell eQTLGen consortium
eLife 9:e52155.
https://doi.org/10.7554/eLife.52155
Further reading
-
- Genetics and Genomics
- Neuroscience
The central complex (CX) plays a key role in many higher-order functions of the insect brain including navigation and activity regulation. Genetic tools for manipulating individual cell types, and knowledge of what neurotransmitters and neuromodulators they express, will be required to gain mechanistic understanding of how these functions are implemented. We generated and characterized split-GAL4 driver lines that express in individual or small subsets of about half of CX cell types. We surveyed neuropeptide and neuropeptide receptor expression in the central brain using fluorescent in situ hybridization. About half of the neuropeptides we examined were expressed in only a few cells, while the rest were expressed in dozens to hundreds of cells. Neuropeptide receptors were expressed more broadly and at lower levels. Using our GAL4 drivers to mark individual cell types, we found that 51 of the 85 CX cell types we examined expressed at least one neuropeptide and 21 expressed multiple neuropeptides. Surprisingly, all co-expressed a small molecule neurotransmitter. Finally, we used our driver lines to identify CX cell types whose activation affects sleep, and identified other central brain cell types that link the circadian clock to the CX. The well-characterized genetic tools and information on neuropeptide and neurotransmitter expression we provide should enhance studies of the CX.
-
- Cancer Biology
- Genetics and Genomics
Tyrosine kinases play a crucial role in cell proliferation and survival and are extensively investigated as targets for cancer treatment. However, the efficacy of most tyrosine kinase inhibitors (TKIs) in cancer therapy is limited due to resistance. In this study, we identify a synergistic combination therapy involving TKIs for the treatment of triple negative breast cancer. By employing pairwise tyrosine kinase knockout CRISPR screens, we identify FYN and KDM4 as critical targets whose inhibition enhances the effectiveness of TKIs, such as NVP-ADW742 (IGF-1R inhibitor), gefitinib (EGFR inhibitor), and imatinib (ABL inhibitor) both in vitro and in vivo. Mechanistically, treatment with TKIs upregulates the transcription of KDM4, which in turn demethylates H3K9me3 at FYN enhancer for FYN transcription. This compensatory activation of FYN and KDM4 contributes to the resistance against TKIs. FYN expression is associated with therapy resistance and persistence by demonstrating its upregulation in various experimental models of drug-tolerant persisters and residual disease following targeted therapy, chemotherapy, and radiotherapy. Collectively, our study provides novel targets and mechanistic insights that can guide the development of effective combinatorial targeted therapies, thus maximizing the therapeutic benefits of TKIs.
