Performance evaluation of Arabidopsis scRNA-seq sample processing strategies

Optimizing methodologies for cell enrichment and single-cell transcriptomics is therefore critical for accurately capturing cellular diversity. Here, we systematically compared protoplast enrichment technologies (including conventional and image-based flow cytometry, as well as magnetic cell sorting) and single-cell RNA sequencing (scRNA-seq) platforms (10X Genomics Chromium, BD Rhapsody) using Arabidopsis roots.

Image-based flow cytometry offered greater precision due to customizable gating strategies, while magnetic sorting provided faster processing and better representation of cell size heterogeneity. Both scRNA-seq platforms captured root cell heterogeneity and yielded reproducible gene expression profiles, but we observed platform-specific biases in cell type composition. Notably, single nucleotide polymorphism analysis of a mixed ecotype sample revealed that computational doublet detection algorithms misclassified two-thirds of the cells as doublets.