Single-Cell Characterization of the Frizzled 5 (Fz5) Mutant Mouse and Human Persistent Fetal Vasculature (PFV)

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. 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.在胚胎发育早期，玻璃体透明血管（hyaloid vessels, HV）这一暂时性胎儿脉管系统会为发育中的晶状体和视网膜提供临时营养支持。当视网膜内脉管系统发育成熟以接替其功能时，HV会自然退化。若HV退化失败，则会引发持续性胎儿脉管综合征（persistent fetal vasculature, PFV）——该病理状况在美国占儿童失明病例的4.8%。迄今为止，HV的形成与退化过程以及相关PFV的发病机制仍尚未完全阐明。 本研究针对正常小鼠及Fzd5突变小鼠的玻璃体细胞，于产后第3天（postnatal day 3, P3）和产后第6天（postnatal day 6, P6）两个时间点开展单细胞RNA测序（single-cell RNA sequencing, scRNA-seq）。我们共鉴定出10种主要细胞类型，这些细胞类型在野生型（wild type）和突变型发育中的玻璃体中均有存在，但P3突变体样本中的内皮细胞、巨噬细胞、类红细胞、周细胞、平滑肌细胞、成纤维细胞及黑素细胞数量显著更高。至P6时，突变型与野生型的细胞类型丰度均降至相近水平，但亚簇（sub clusters）组成存在差异。 我们进一步比对了P6时残留主要亚簇的基因表达谱（gene expression profiles），发现突变细胞的代谢活动发生了改变。此外，有两类巨噬细胞亚簇表达透明细胞（hyalocytes）的标志物，这支持了此类细胞起源于巨噬细胞的观点。黑素细胞主要存在于Fzd5突变体中，其表达包括Pax3和Sox10在内的神经嵴标志物（neural crest markers），这与脉络膜色素细胞（choroidal pigment cells）的特征相似。 综上，本研究揭示了正常与病理性透明脉管组织的细胞特征，此前尚无相关报道。Illumina BCL文件通过10X Genomics Cell Ranger流程的mkfastq功能转换为fastq文件（详见https://support.10xgenomics.com/）。随后，使用cellranger count功能从fastq文件生成基因-条形码矩阵（Gene-Barcode matrices），该流程借助STAR算法（STAR algorithm）将高质量测序reads比对至小鼠参考基因组（mm10），随后进行UMI计数（UMI counting）。人类scRNA-seq数据分析由NovelBio Co.,Ltd.依托NovelBrain云分析平台（NovelBrain Cloud Analysis Platform）完成。我们使用默认参数的fastp工具过滤接头序列（adaptor sequence）并去除低质量测序reads，以获得清洁数据（clean data）。通过UMI-tools进行单细胞转录组分析（Single Cell Transcriptome Analysis），以鉴定细胞条形码白名单（cell barcode whitelist）。基于UMI的清洁数据通过UMI-tools标准流程的自定义STAR比对参数，比对至人类基因组（Ensemble版本100），以获取每个样本的UMI计数。满足"表达基因数超过200且线粒体UMI占比低于40%"的细胞通过了细胞质量过滤（cell quality filtering），且表达矩阵中已剔除线粒体基因（mitochondria genes）。鉴于患者隐私问题，人类样本的原始数据将通过GSA（受控访问）开放获取。