A research team led by researchers at University of California San Francisco has developed a new technique called HybriSeq for studying RNA inside individual cells. Unlike traditional methods that rely heavily on physical devices to capture and sequence RNA, HybriSeq uses a clever combination of probes and barcoding to track specific transcripts.

The process begins with in situ hybridization, where multiple probes attach directly to target RNAs inside cells. These probes are then assigned unique barcodes using a split-pool method, making it possible to identify which transcript came from which cell once sequencing is performed.

Schematic and validation of HybriSeq

a Multiple split probes are designed per transcript of interest. b Hybridization and ligation of split probes. c Labeling probes with unique cell barcodes via the split-and-pool method. Rounds 1 and 2 barcodes are ligated, and round 3 barcodes are added via PCR. d Sequencing results of 1:1 mixed HEK293 cells and Do-11-10 cells. 1.8% of barcodes contain probes targeting human and mouse transcripts. 98.2% of barcodes contain probes targeting only human or only mouse transcripts. e Scatter plot of average HybriSeq UMIs per cell in two independent biological replicates. Each dot represents a single probe. Pearson Correlation Coefficient (r = 0.992, p < 0.0001). f Scatter plot of gene-level average HybriSeq UMIs per cell and expression of the same gene obtained via bulk RNA-Seq. Each dot represents a gene-level measurement. Pearson Correlation Coefficient (r = 0.90, p < 0.0001).

One of the biggest advantages of HybriSeq is its high sensitivity. By using multiple probes for each transcript, the method reduces the chance of missing RNA molecules and can capture full-length transcripts without the end bias that often affects other RNA sequencing techniques.

The team demonstrated the power of HybriSeq by analyzing 196 genes in human peripheral blood mononuclear cells. They were able to uncover differences between cells that would have been difficult to detect otherwise, as well as find transcripts that had been overlooked in previous annotations.

This approach offers researchers a powerful new way to profile RNA at the single-cell level, making it easier to explore how cells vary within complex tissues and how these differences contribute to health and disease.