Highly sensitive and scalable time-resolved RNA sequencing in single cells with scNT-seq2

Area of Science:

• Molecular Biology
• Genomics
• Cell Biology

Background:

• Understanding gene expression dynamics necessitates distinguishing newly synthesized RNA from existing RNA at the single-cell level.
• Existing methods face challenges in sensitivity and accuracy for time-resolved analyses.

Purpose of the Study:

• To introduce scNT-seq2, an optimized and scalable method for time-resolved single-cell RNA sequencing.
• To enhance the detection and quantification of newly synthesized transcripts in individual cells.

Main Methods:

• Systematic optimization of the second-strand cDNA synthesis (2nd SS) step.
• Application of scNT-seq2 to 4sU-labeled K562 cells for benchmarking.
• Evaluation of read alignment rates, background mutations, and library complexity.

Main Results:

• scNT-seq2 demonstrated improved read alignment, reduced background mutations, and increased library complexity compared to previous methods.
• The method accurately quantifies newly synthesized transcripts and RNA turnover at the gene level.
• Enhanced sensitivity allowed for robust detection of dynamic, cell-cycle-specific genes.

Conclusions:

• scNT-seq2 is a highly sensitive and scalable tool for time-resolved single-cell RNA sequencing.
• The optimized method provides a versatile approach for dissecting transcriptional dynamics in various biological systems.
• scNT-seq2 enables precise analysis of gene expression changes at single-cell resolution.