Scalable single-cell total RNA sequencing unifies coding and noncoding transcriptomics

Area of Science:

• Genomics
• Molecular Biology
• Neuroscience

Background:

• Current single-cell RNA sequencing (scRNA-seq) primarily analyzes polyadenylated transcripts.
• This misses crucial regulatory information encoded in noncoding RNAs.
• A comprehensive understanding of cellular identity and regulation requires broader RNA profiling.

Purpose of the Study:

• To develop a generalizable framework for total RNA profiling in standard droplet-based single-cell platforms.
• To capture a wide range of coding and noncoding RNAs within a unified pipeline.
• To enable a deeper understanding of cellular identity and gene regulation at the atlas scale.

Main Methods:

• Adaptation of total RNA profiling for droplet-based single-cell platforms.
• Development of a unified pipeline for capturing diverse RNA biotypes.
• Application to developing human brain, peripheral blood mononuclear cells, and dengue-infected hepatocytes.

Main Results:

• Generated a comprehensive RNA atlas of the developing human brain, detailing cell-type and temporally specific expression programs across diverse RNA biotypes.
• Identified microRNA (MIR137) dynamics in specific neuronal populations, linking its enrichment and target anticorrelation to neurodevelopmental disorders.
• Characterized transcriptional modules combining coding and noncoding RNAs in human peripheral blood mononuclear cells.
• Captured non-adenylated viral transcripts in infected hepatocytes, distinguishing infection states.

Conclusions:

• The developed framework significantly expands the scope of single-cell RNA profiling to include noncoding RNAs.
• This comprehensive approach provides novel insights into cell-type-specific gene regulation and cellular identity.
• The findings have implications for understanding neurodevelopment, immune responses, and infectious diseases.