Single-cell profiling of the developing mouse brain and spinal cord with split-pool barcoding

Area of Science:

• Molecular Biology
• Genomics
• Neuroscience

Background:

• Single-cell RNA sequencing (scRNA-seq) is crucial for understanding complex biological systems.
• Existing scRNA-seq methods face challenges in scalability and compatibility with fixed samples.

Purpose of the Study:

• To develop a scalable and versatile scRNA-seq method for comprehensive cellular profiling.
• To analyze the transcriptomes of developing mouse central nervous system at single-cell resolution.

Main Methods:

• Developed split-pool ligation-based transcriptome sequencing (SPLiT-seq) utilizing combinatorial barcoding.
• Applied SPLiT-seq to analyze 156,049 single-nucleus transcriptomes from postnatal mouse brains and spinal cords.
• Utilized pseudotime analysis to investigate developmental trajectories.

Main Results:

• Identified over 100 distinct cell types based on gene expression patterns.
• Characterized cell types by function, regional specificity, and differentiation stage.
• Revealed transcriptional programs driving four major developmental lineages in the early postnatal murine CNS.

Conclusions:

• SPLiT-seq enables scalable and efficient single-cell transcriptomic profiling.
• Provides a detailed snapshot of early postnatal central nervous system development.
• Offers a method for comprehensive analysis of other complex multicellular systems.