Benchmarking metabolic RNA labeling techniques for high-throughput single-cell RNA sequencing.

Area of Science:

• Molecular Biology
• Genomics
• Cell Biology

Background:

• Metabolic RNA labeling coupled with single-cell RNA sequencing (scRNA-seq) is crucial for studying gene expression dynamics.
• Key factors for success include conversion efficiency, RNA integrity, and transcript recovery, influenced by chemical methods and platform choice.
• A lack of comprehensive comparisons has hindered optimal method selection.

Purpose of the Study:

• To benchmark ten chemical conversion methods for metabolic RNA labeling using the Drop-seq platform.
• To evaluate the performance of these methods on commercial scRNA-seq platforms.
• To provide guidance on selecting optimal chemical methods and platforms for scRNA-seq applications.

Main Methods:

• Benchmarking ten chemical conversion methods on the Drop-seq platform with 52,529 cells.
• Applying optimized methods to 9883 zebrafish embryonic cells during maternal-to-zygotic transition.
• Evaluating two commercial scRNA-seq platforms with high capture efficiency.

Main Results:

• On-beads methods, particularly meta-chloroperoxy-benzoic acid/2,2,2-trifluoroethylamine, showed superior performance over in-situ methods.
• Optimized methods successfully identified and validated zygotically activated transcripts during zebrafish embryogenesis.
• On-beads iodoacetamide chemistry proved most effective on commercial platforms.

Conclusions:

• On-beads chemical conversion methods offer enhanced efficiency for metabolic RNA labeling in scRNA-seq.
• The study provides critical guidance for researchers to select optimal chemical methods and platforms.
• This work advances the study of RNA dynamics in complex biological systems, including early development.