ingle-cell sequencing data of the optic nerve in adult zebrafish two weeks post-injury

Adult zebrafish possess a strong regenerative capacity. Focusing on the heterogeneity of zebrafish optic nerve regeneration, single-cell sequencing analysis of the optic nerve of adult zebrafish two weeks after injury identified five major cell types: fibroblasts, vascular wall cells, immune cells, mature oligodendrocytes, and oligodendrocytes in the process of myelination.Experimental ProcedureDissociation of optic nerve to a single-cell suspensionOptic nerve samples from n=18 zebrafish (half of male and female) at 2 wpi were pooled to create a single-cell suspension, ensuring sufficient cell capture while minimizing inter-individual variability. Therefore, there are no biological replicates due to small tissue size of the optic nerve in zebrafish and low expression of mRNA in the optic nerve (Yu et al., 2024). Dissection of the optic nerve and then were minced with a sterile scalpel into 1 mm fragments, suspended in 5ml of digestion buffer consisting of 2 mg/mL Collagenase type II and 200U/ml DNase I in RPMI medium, and incubated in 37℃ water bath with shaking for 30 min. The suspension was passed through a 100 μm filter and centrifugated (400g, 10 min, 4℃). Pelleted cells were resuspended in red blood cell lysis buffer, incubated for 2 min, passed through a 40 μm filter, collected by centrifugation (400g, 10 min, 4℃) and resuspended in PBS containing 0.04% BSA. Cells were manually counted by Trypan blue and AO-PI (LUNA, D23001) after each centrifugation (400g, 10 min, 4℃) and resuspended. Single cells were processed using Chromium Controller (10X Genomics) according to the manufacturer’s protocol.Single-cell RNA sequencingBy using Chromium Next GEM Single Cell 3ʹ Kit v3.1and Chromium Next GEM Chip G Single Cell Kit, we performed single cell 3’gene expression profiling. The cell suspension was loaded onto the Chromium single cell controller (10x Genomics) to generate single-cell gel beads in the emulsion according to the manufacturer’s protocol. Captured cells were lysed and the released RNA were barcoded through reverse transcription in individual GEMs. Cell-barcoded 3’gene expression libraries were sequenced on an Illumina NovaSeq6000 system (Illumina, USA) by Shanghai Biochip Co., Ltd.,China.Single-cell RNA sequencing and data analysisThe raw single-cell RNA sequencing (scRNA-Seq) data were processed as described in previous paper ((Yu et al., 2024)). Low-quality cells were excluded based on the retaining criteria as RNA feature count between 300 and 5000, RNA count between 500-8000, a mitochondrial gene percentage below 20%, hemoglobin- and red blood cell–related gene percentages below 10%, and total RNA counts not exceeding the 95th percentile. A total of 3,359 cells were sequenced, and 1,341 cells were retrieved after sequencing and quality control. Clusters that did not belong to optic nerve tissue were excluded from further analysis. The detailed quality control workflow is present in Supplementary file1. Optic nerve samples were integrated using Seurat v5.1, followed by data normalizing, scaling, dimensional reduction, and clustering. Visualization was performed with t-SNE using the first 30 principal components. Cell types were annotated based on canonical marker genes, including mature oligodendrocyte (tspan2a, mag, mbpa), myelin forming oligodendrocyte (egr2b, gldn, mbpb, s100b, si:ch211-234p6.5, ndrg1a), fibroblast (col1a1a, col1a1b, dcn), immune cell (nr4a1, srgn) and mural cell (rgs5a, rbpms2a, myh11a). We note that this immune cell cluster does not express any microglial or macrophage markers but instead shows high expression of more generalized immune function–related genes. Consequently, we can only designate it as an “immune cell” cluster and cannot further subdivide it. Gene Ontology (GO) enrichment analysis was conducted to identify functional pathways and biological processes associated with each group. Proliferation scores were computed based on curated gene sets representing proliferation-related pathways