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Published on: July 28, 2023
A reliable strategy for single-cell RNA sequencing analysis using cryoconserved primary cortical cells.
Lucia Verrillo1, Eleonora Mangano2, Denise Drongitis3
1Institute of Genetics and Biophysics "Adriano Buzzati-Traverso", National Research Council, Naples, Italy; University of Campania "Luigi Vanvitelli", Caserta, Italy.
This study introduces a novel method using Neurostore medium for cryopreserving mouse embryonic cortical cells for single-cell RNA sequencing (scRNASeq). This approach ensures high cell viability and data integrity, enabling flexible experimental designs in neuroscience research.
Area of Science:
- Neuroscience
- Genomics
- Cell Biology
Background:
- Single-cell RNA sequencing (scRNASeq) is crucial for studying mammalian cortical development.
- Traditional scRNASeq methods require fresh tissue, limiting experimental flexibility.
- Cryopreservation of primary cortical cells for scRNASeq has been challenging due to viability issues.
Purpose of the Study:
- To develop and validate a method for cryopreserving primary cortical cells for scRNASeq.
- To assess the viability and cellular integrity of cryopreserved cells.
- To demonstrate the feasibility of performing scRNASeq on cryopreserved embryonic mouse cortex.
Main Methods:
- Primary cortical cells from E15.5 mouse embryos were cryopreserved using a novel medium, Neurostore.
- Cell viability was assessed using trypan blue assay and flow cytometry.
- scRNASeq was performed on 35,763 cryopreserved single cells, followed by data analysis and marker gene validation.
Main Results:
- Neurostore-cryopreserved cortical cells exhibited approximately 95% viability.
- High-quality RNA recovery and cDNA library preparation were achieved.
- scRNASeq analysis identified 25 distinct cell clusters, confirming cellular integrity and diversity post-thawing.
Conclusions:
- Cryopreserved primary cortical cells are suitable for scRNASeq experiments.
- This method offers significant flexibility in experimental planning and execution.
- The approach allows for off-line sample preparation and processing in distributed locations.

