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Comparative Analysis of Single-Cell RNA Sequencing Methods with and without Sample Multiplexing

Authors :
Yi Xie
Huimei Chen
Vasuki Ranjani Chellamuthu
Ahmad bin Mohamed Lajam
Salvatore Albani
Andrea Hsiu Ling Low
Enrico Petretto
Jacques Behmoaras
Source :
International Journal of Molecular Sciences, Vol 25, Iss 7, p 3828 (2024)
Publication Year :
2024
Publisher :
MDPI AG, 2024.

Abstract

Single-cell RNA sequencing (scRNA-seq) has emerged as a powerful technique for investigating biological heterogeneity at the single-cell level in human systems and model organisms. Recent advances in scRNA-seq have enabled the pooling of cells from multiple samples into single libraries, thereby increasing sample throughput while reducing technical batch effects, library preparation time, and the overall cost. However, a comparative analysis of scRNA-seq methods with and without sample multiplexing is lacking. In this study, we benchmarked methods from two representative platforms: Parse Biosciences (Parse; with sample multiplexing) and 10x Genomics (10x; without sample multiplexing). By using peripheral blood mononuclear cells (PBMCs) obtained from two healthy individuals, we demonstrate that demultiplexed scRNA-seq data obtained from Parse showed similar cell type frequencies compared to 10x data where samples were not multiplexed. Despite relatively lower cell capture affecting library preparation, Parse can detect rare cell types (e.g., plasmablasts and dendritic cells) which is likely due to its relatively higher sensitivity in gene detection. Moreover, a comparative analysis of transcript quantification between the two platforms revealed platform-specific distributions of gene length and GC content. These results offer guidance for researchers in designing high-throughput scRNA-seq studies.

Details

Language :
English
ISSN :
14220067 and 16616596
Volume :
25
Issue :
7
Database :
Directory of Open Access Journals
Journal :
International Journal of Molecular Sciences
Publication Type :
Academic Journal
Accession number :
edsdoj.bec439f169424ea680043f137d3c61d2
Document Type :
article
Full Text :
https://doi.org/10.3390/ijms25073828