A dataset examining technical factors on fixed white blood cell single-cell RNA-seq.

Area of Science:

• Immunology
• Genomics
• Cell Biology

Background:

• Single-cell RNA sequencing (scRNA-seq) reveals cellular heterogeneity but struggles with fragile cells like neutrophils due to ex vivo loss.
• High RNase content and cryopreservation issues further complicate neutrophil analysis using traditional scRNA-seq.

Purpose of the Study:

• To evaluate the performance of two commercial fixed scRNA-seq platforms (10x Genomics Flex v1 and Honeycomb HIVE v1) for analyzing neutrophils.
• To assess the impact of fixation, storage time, and cell numbers on neutrophil transcriptome data.
• To determine how well fixed neutrophil transcriptomes reflect their native state.

Main Methods:

• Comparison of 10x Genomics Flex v1 and Honeycomb HIVE v1 platforms using red blood cell-depleted whole blood.
• Application of fixed scRNA-seq methodology to preserve fragile neutrophil integrity.
• Analysis of publicly available data (GEO accession: GSE266615) including batch effect correction for storage time and cell numbers.

Main Results:

• Fixed scRNA-seq methodology presents a viable solution for analyzing fragile neutrophils.
• Performance evaluation of two distinct commercial platforms provides comparative data for researchers.
• Identification of potential batch and technical effects related to fixation and storage time.

Conclusions:

• Fixed scRNA-seq effectively addresses the challenges associated with analyzing neutrophils.
• The study provides valuable data for optimizing scRNA-seq protocols for sensitive cell types.
• Further analysis can elucidate the fidelity of fixed neutrophil transcriptomes to native cellular environments.