Benchmarking Metabolic RNA Labeling Techniques for High-Throughput Single-Cell RNA Sequencing (PRJCA037071)

Metabolic RNA labeling with high-throughput single-cell RNA sequencing (scRNA-seq) enables precise measurement of gene expression dynamics in complex biological processes, such as cell state transitions and embryogenesis. This technique, which tags newly synthesized RNA for detection through induced base conversions, relies on conversion efficiency, RNA integrity, and transcript recovery. These factors are influenced by the chosen chemical conversion method and platform compatibility. Despite its potential, a comprehensive comparison of chemical methods and platform compatibility has been lacking. Here, we benchmarked ten chemical conversion methods using the Drop-seq platform, analyzing xxx cells. We found that on-beads methods, particularly the meta-chloroperoxy-benzoic acid/2,2,2-trifluoroethylamine combination, outperformed in-situ approaches. To assess in vivo applications, we applied these optimized methods to 9,883 zebrafish embryonic cells during the maternal-to-zygotic transition, identifying and experimentally validating novel zygotically activated transcripts, which enhanced zygotic gene detection capabilities. Additionally, we evaluated a commercial platform with higher capture efficiency and found that on-beads iodoacetamide chemistry was the most effective. Our results provide critical guidance for selecting optimal chemical methods and scRNA-seq platforms, advancing the study of RNA dynamics in complex biological systems.