Programme in Cardiovascular and Metabolic Disorders and Centre for Computational Biology, Duke-NUS Medical School, 8 College Road, Singapore 169857, Singapore.
Translational Immunology Institute, SingHealth/Duke-NUS Academic Medical Centre, Academia, Singapore 169856, Singapore.
Int J Mol Sci. 2024 Mar 29;25(7):3828. doi: 10.3390/ijms25073828.
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.
单细胞 RNA 测序 (scRNA-seq) 已成为一种强大的技术，可以在人类系统和模式生物中研究单细胞水平的生物学异质性。scRNA-seq 的最新进展使得可以将来自多个样本的细胞汇集到单个文库中，从而提高了样本通量，同时减少了技术批次效应、文库制备时间和总体成本。然而，缺乏对具有和不具有样本多路复用的 scRNA-seq 方法的比较分析。在这项研究中，我们对来自两个代表性平台的方法进行了基准测试：Parse Biosciences (Parse；具有样本多路复用) 和 10x Genomics (10x；没有样本多路复用)。我们使用来自两个健康个体的外周血单核细胞 (PBMC) 证明，与未进行样本多路复用的 10x 数据相比，从 Parse 获得的去复用 scRNA-seq 数据显示出相似的细胞类型频率。尽管相对较低的细胞捕获影响了文库制备，但 Parse 可以检测到稀有细胞类型（例如浆母细胞和树突状细胞），这可能是由于其在基因检测方面相对较高的灵敏度。此外，对两个平台之间的转录本定量进行比较分析揭示了基因长度和 GC 含量的平台特异性分布。这些结果为研究人员设计高通量 scRNA-seq 研究提供了指导。
