During early development, a transitory fetal vasculature of the vitreous hyaloid vessels (HV) provides temporary nutrients for the developing lens and retina. HV regresses when the intraretinal vasculature develops to replace its function. Failure in regression of the HV leads to persistent fetal vasculature (PFV), a pathological condition accounting for 4.8% children blindness in the USA. To date, the HV formation and regression as well as the related PFV pathogenesis are largely unknown. In this study, by single-cell RNA sequencing (scRNA-seq) the vitreous cells derived from normal and the Fzd5 mutant mice at two time points, postnatal day 3 (P3) and P6, we collectively defined 10 major cell types, present in both wild type and mutant developing vitreous but with much higher numbers of endothelial cells, macrophages, erythroid-like cells, pericytes, smooth muscle cells, fibroblasts and melanocytes in the P3 mutants. Both mutant and wild type cell types declined to similar sizes at P6 with varied compositions of sub clusters. We further compared gene expression profiles of residual major sub clusters at P6, and showed altered metabolic activities of the mutant cells. Additionally, two macrophage clusters expressed markers for hyalocytes supporting the notion that these cells are of macrophage origin. The melanocytes predominantly existed in the Fzd5 mutants expressing neural crest markers including Pax3 and Sox10, similar to that of choroidal pigment cells. Taken together, these data revealed cell features of normal and pathological hyaloid tissues, which has not been known precedentially.
Overall design: Illumina BCL files were converted to fastq files by using 10X Genomics Cell Ranger pipeline mkfastq function (https://support.10xgenomics.com/). Next, cellranger count function was used to generate Gene-Barcode matrices from the fastq files, which uses the STAR algorithm to map high-quality reads to the mouse reference genome (mm10), followed by UMI counting.
Human scRNA-seq data analysis was performed by NovelBio Co.,Ltd. with NovelBrain Cloud Analysis Platform. We applied fastp with default parameter filtering the adaptor sequence and removed the low quality reads to achieve the clean data. UMI-tools was applied for Single Cell Transcriptome Analysis to identify the cell barcode whitelist. The UMI-based clean data was mapped to human genome (Ensemble version 100) utilizing STAR mapping with customized parameter from UMI-tools standard pipeline to obtain the UMIs counts of each sample. Cells contained over 200 expressed genes and mitochondria UMI rate below 40% passed the cell quality filtering and mitochondria genes were removed in the expression table.
Raw data (for human sample) will be available through GSA (controlled access) due to patient privacy concerns.
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