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Related Experiment Video

Updated: Nov 15, 2025

Single-cell RNA Sequencing of Fluorescently Labeled Mouse Neurons Using Manual Sorting and Double In Vitro Transcription with Absolute Counts Sequencing DIVA-Seq

Single-cell RNA Sequencing of Fluorescently Labeled Mouse Neurons Using Manual Sorting and Double In Vitro Transcription with Absolute Counts Sequencing DIVA-Seq

Published on: October 26, 2018

Population-scale single-cell RNA-seq profiling across dopaminergic neuron differentiation.

Julie Jerber^1,2, Daniel D Seaton³, Anna S E Cuomo³

¹Open Targets, Wellcome Genome Campus, Hinxton, Cambridge, UK.

Nature Genetics

|March 5, 2021

Summary

This summary is machine-generated.

This study differentiates human stem cells into neurons to analyze genetic variants. Researchers identified thousands of expression quantitative trait loci (eQTLs), advancing the study of neurological disease genetics.

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Last Updated: Nov 15, 2025

Single-cell RNA Sequencing of Fluorescently Labeled Mouse Neurons Using Manual Sorting and Double In Vitro Transcription with Absolute Counts Sequencing DIVA-Seq

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Published on: October 26, 2018

Single-cell Profiling of Developing and Mature Retinal Neurons

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Reliable Identification of Living Dopaminergic Neurons in Midbrain Cultures Using RNA Sequencing and TH-promoter-driven eGFP Expression

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Published on: February 10, 2017

Area of Science:

Neuroscience
Genetics
Stem Cell Biology

Background:

Studying common genetic variants in human development and tissues is difficult.
Induced pluripotent stem cells (iPSCs) offer a model system for developmental studies.
Single-cell RNA sequencing (scRNA-seq) enables high-resolution profiling of cellular populations.

Purpose of the Study:

To develop a scalable method for studying genetic variant function during human neurodevelopment.
To characterize expression quantitative trait loci (eQTLs) in developing neurons.
To identify novel genetic associations with neurological traits.

Main Methods:

Differentiated 215 human iPSC lines towards a midbrain neural fate, including dopaminergic neurons.
Utilized scRNA-seq to profile over 1 million cells across three differentiation time points.
Analyzed eQTLs in developing neurons and under oxidative stress conditions.

Main Results:

Achieved reproducible neuronal differentiation across iPSC lines, predictable by pluripotent cell markers.
Identified 1,284 eQTLs that colocalize with known neurological trait risk loci.
Discovered that 46% of identified eQTLs are not present in the Genotype-Tissue Expression (GTEx) catalog.

Conclusions:

Coupling iPSC differentiation with scRNA-seq provides a powerful platform for studying genetic variant function in human neurodevelopment.
This approach enables mechanistic insights into genetic variants associated with neurological traits, including those not previously characterized.
The study highlights the utility of iPSC models for uncovering the functional consequences of genetic variation in human disease.