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An integrated pipeline to count individual transcripts with single-cell resolution

Sheardown, E.; Yan To Ling, J.; van der Burght, S. N.; Vaikkinen, H.; Gowing, B.; Ahringer, J.; Hamid, F.; Ch'ng, Q.

2026-04-17 molecular biology
10.64898/2026.04.15.718387 bioRxiv
Show abstract

Quantifying transcript abundance at single-cell resolution is important for understanding gene regulation in intact multicellular organisms. In Caenorhabditis elegans, RNA fluorescence in situ hybridization has been widely used to visualize transcripts, but conventional smFISH approaches can be limited by low signal-to-noise, poor performance with short transcripts, and workflows that do not readily support absolute transcript counting in identified cells. Here, we present an integrated experimental and computational pipeline for quantitative transcript analysis in whole-mount C. elegans embryos, larvae, and adults. The pipeline combines Hybridization Chain Reaction (HCR), confocal microscopy, RS-FISH spot detection, manual cell annotation in FIJI, and custom MATLAB-based spot assignment to quantify individual transcripts within defined cells. We show that this approach enables sensitive, specific, and multiplexed detection of transcripts, including short insulin-like peptide mRNAs, with single-cell resolution. Known spatial expression patterns were resolved in embryos, larvae, and adults, and probe specificity was validated. Applying this pipeline to ins-6 in ASI and ASJ sensory neurons revealed cell-specific regulatory relationships across multiple mutant backgrounds. This workflow provides an accessible method for absolute transcript counting in anatomically intact C. elegans and should support mechanistic studies of gene regulation, cellular heterogeneity, and transcriptional network function.

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