Optimizing the hybridization chain reaction-fluorescence in situ hybridization (HCR-FISH) protocol for Pleurodeles waltl
Advances in transcriptomic technologies have transformed the study of complex biological processes, including tissue regeneration, by enabling high-resolution characterization of gene expression programs. In regenerative vertebrate models such as the Iberian ribbed newt (Pleurodeles waltl), these approaches can provide critical insight into the molecular mechanisms underlying retina and lens regeneration. However, single-cell and single-nucleus RNA sequencing studies lack spatial resolution, therefore the ability to validate gene expression patterns within ocular tissues is essential and requires optimization. In this study, we optimized hybridization chain reaction fluorescent in situ hybridization (HCR-FISH) for use in P. waltl eyes. HCR-FISH enables sensitive and specific detection of mRNA transcripts through split-initiator probes and hairpin-based signal amplification with automatic background suppression. In addition, because incomplete genome annotation in emerging model organisms complicates transcript selection and probe design, we optimized an optional in silico workflow to support transcript screening, orthology confirmation, and split-initiator probe generation. We systematically optimized fixation duration, proteinase K concentration, and tissue processing parameters to preserve tissue integrity while enhancing signal quality. To overcome imaging constraints imposed by highly pigmented ocular tissues, we implemented a whole-mount protocol with optional bleaching followed by cryosectioning, enabling improved visualization without compromising spatial localization. Using this workflow, we successfully detected key retinal markers including SLC1A3 (Muller glia cells) and RPE65 (retinal pigment epithelium) within the newt eye. Notably, the RPE65 probe was designed in house and showed comparable detection to a standard Molecular Instruments probe across two sample-preparation protocols. This study presents a reproducible framework for spatial transcript detection in an emerging eye regenerative model and facilitates integration of transcriptomic and anatomical data. Together, the integrated design-to-detection pipeline will strengthen spatial validation of RNA sequencing profiles in P. waltl.