The single-cell eQTLGen consortium.

IF: 8.713

Cited by: 122

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.

Keywords

seqFISH+

Gene Expression

Omics

Slide-seq

Spatial Transcriptomics

MERFISH

PBMC

eQTL

gene regulatory network

genetics

genomics

human

science forum

single-cell

MeSH terms

Gene Expression

Gene Regulatory Networks

Genetic Predisposition to Disease

Genetics, Population

Genotype

Humans

Polymorphism, Single Nucleotide

Quantitative Trait Loci

RNA-Seq

Sequence Analysis, RNA

Single-Cell Analysis

Authors

van der Wijst, Mgp

de Vries, D H

Groot, H E

Trynka, G

Hon, C C

Bonder, M J

Stegle, O

Nawijn, M C

Idaghdour, Y

van der Harst, P

Ye, C J

Powell, J

Theis, F J

Mahfouz, A

Heinig, M

Franke, L

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