Multiplexed Single-Nucleus RNA Sequencing Using Lipid-Oligo Barcodes.

Area of Science:

• Molecular Biology
• Genomics
• Bioinformatics

Background:

• Single-nucleus RNA sequencing (snRNA-seq) is a powerful technique for analyzing gene expression at the cellular level.
• Existing protocols often require fresh cells and can be limited in multiplexing capabilities.
• Analyzing multiple samples simultaneously can reduce experimental costs and batch effects.

Purpose of the Study:

• To develop a robust protocol for simultaneous snRNA-seq analysis of multiple, including frozen, cell samples.
• To optimize nuclei recovery and minimize artifacts during sample processing.
• To provide a computational pipeline for data deconvolution and quality control.

Main Methods:

• Lipid-coupled oligonucleotide barcoding of cDNA from individual samples.
• Pooling of nuclei from up to 12 samples for simultaneous library construction and sequencing.
• Incorporation of high sucrose buffered solutions and trypan blue for efficient nuclei recovery.
• Removal of cell debris to reduce artifacts prior to single nuclear fractionation.
• Bioinformatic analysis for filtering poorly labeled nuclei and assigning sample identity using unique molecular identifier (UMI) read counts.

Main Results:

• A protocol optimized for quick-frozen cell samples, enabling efficient nuclei recovery.
• Successful simultaneous processing and sequencing of multiplexed snRNA-seq libraries.
• A computational pipeline capable of deconvoluting multiplexed data from various cell types and conditions.
• Demonstrated reduction in batch effects and experimental costs.

Conclusions:

• The developed protocol enables cost-effective, high-throughput snRNA-seq analysis of multiple samples, including frozen tissues.
• This method enhances the comparability of samples and reduces experimental variability.
• The integrated bioinformatic pipeline ensures accurate data processing and sample identification.