Tek hücreli RNA sıralama Fluorescently etiketli fare nöronların el ile sıralama ve çift Vitro transkripsiyon mutlak sayar (DIVA-Seq) sıralama kullanarak

Overview

This protocol details a manual sorting method for isolating single fluorescently labeled neurons, followed by in vitro transcription-based mRNA amplification to facilitate high-depth single-cell RNA sequencing. The aim is to overcome challenges in single-neuron isolation and sequencing by collecting specific neuronal populations from defined brain areas.

Key Study Components

Area of Science

• Neuroscience
• Cell biology
• Genomics

Background

• The method addresses challenges in isolating and sequencing single neurons.
• It focuses on collecting targeted neuronal populations without contamination.
• The approach is gentle and suitable for fragile neuron types.
• Single-cell RNA sequencing is gaining importance for understanding neuron function.

Purpose of Study

• To develop a method for reliable isolation of fluorescently labeled neurons.
• To enable high-depth RNA sequencing of individual neurons.
• To assess the genomic diversity and functionality of neuronal subpopulations.

Methods Used

• This protocol employs a manual sorting approach for neuron isolation from mouse brain slices.
• Fluorescently labeled GABAergic neurons from the cingulate cortex were specifically targeted.
• No multiomics workflow is used; the focus is on single-cell RNA sequencing.
• Key steps include preparing microcapillaries, dissecting the brain, and micro-dissecting sections.
• Single neurons were collected using capillary action and processed for RNA amplification.

Main Results

• Successfully isolated up to 150 neurons with minimized contamination.
• RNA from sorted neurons showed a peak distribution just above 500 base pairs, with sequencing yielding a high number of mapped reads.
• Demonstrated linearity in RNA input versus output, allowing for quantification of gene expression.
• Detected an average of 10,000 genes per neuron, with >95% of cells detecting >6,000 genes.

Conclusions

• This study enables precise isolation of specific neuronal subpopulations for RNA analysis.
• The findings can enhance our understanding of neuronal gene expression patterns.
• Implications include potential applications in neurobiology and disease models.

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