Real-time Targeted Enrichment in Single-cell Long-read Sequencing.

Area of Science:

• Genomics
• Molecular Biology
• Neuroscience

Background:

• Alternative splicing generates diverse, cell-type-specific gene isoforms with distinct functions.
• Single-cell long-read sequencing captures transcriptomic heterogeneity but requires efficient enrichment.
• Previous exome-probe enrichment is effective but costly and time-consuming.

Purpose of the Study:

• To develop and evaluate a real-time targeting method for cost-efficient enrichment of single-cell long reads.
• To enhance the detection of alternatively spliced transcripts, particularly for brain-related genes.
• To improve the resolution of differential isoform usage analysis across cell types.

Main Methods:

• Implemented real-time enrichment targeting spliced transcripts from 3377 brain-related genes.
• Applied the method to single-cell long-read sequencing data.
• Compared enrichment efficiency and downstream analysis power against control (naïve sequencing).

Main Results:

• Real-time targeting increased spliced on-target reads by up to 1.82 times compared to controls.
• Targeting lowly expressed genes yielded 1.39 to 1.89 times more spliced on-target reads.
• The method identified 2.42 times more genes with significant cell-type-specific isoform usage differences (neurons vs. glia).

Conclusions:

• Real-time targeting is a versatile and cost-efficient strategy for enhancing single-cell long-read sequencing.
• It significantly improves the ability to detect differential isoform usage across cell types.
• This approach offers a more comprehensive view of cellular isoform diversity and splicing events.