Yang Luning, Tao Yiwen, Pan Qi, Cai Tengda, Ye Yunyan, Liu Jianhui, Zhou Yang, Shao Yongqing, Yi Quanyong, Lu Zen Huat, Chen Lie, McKay Gareth, Rankin Richard, Meng Weihua
Nottingham Ningbo China Beacons of Excellence Research and Innovation Institute, University of Nottingham Ningbo China, Ningbo, 315100, China.
Department of Ophthalmology, Lihuili Hospital affiliated with Ningbo University, Ningbo, 315040, China.
Hum Genomics. 2025 Jul 14;19(1):81. doi: 10.1186/s40246-025-00796-9.
Current human retina studies predominantly utilize post-mortem tissue, and the sample accessibility constraints make the characterization of the living human retina at single-cell resolution a challenge. Although single-nucleus RNA-seq expands the utility of frozen samples, it provides a nuclear-centric view, potentially missing key cytoplasmic information and transient biological processes. Thus, it is important to generate resources directly from living human retinal tissue to complement existing datasets.
We profiled 106,829 single cells from nine unfrozen human retina samples. Living samples were collected within 10 min of therapeutic enucleation and four postmortem samples were collected within 6 h. After standardized dissociation, single-cell transcriptomes were generated using 10x Genomics 3' RNA-seq and applied scVI to generate batch-corrected integrated atlas. Major cell types and subtypes were annotated through iterative Leiden clustering, canonical markers. Subsequent analyses included differential expression comparisons between cell states and regulon activity profiling to further characterize cellular identities and regulatory networks. Transcriptional dynamics were assessed using RNA velocity, and cell-cell signaling pathways were inferred with CellChat. Key findings were validated in independent samples from two additional donors (four samples) using the identical workflow.
We contribute to establishing a reference for retinal cell type proportions and cellular states. Our analysis revealed ELF1-mlCone, a distinct cluster of mlCone photoreceptors identified by distinct transcriptional features. The presence and transcriptional features of this cluster were validated in independent samples. Additionally, by comparing living and post-mortem samples, our study highlights differences in transcriptional dynamics: living tissue preserved coherent RNA velocity streams, enabling clear dynamic state transitions, while post-mortem tissue exhibited disorganized patterns. These findings suggest that using living tissue can improve the capture of active cellular states and transitions.
Our atlas provides a single-cell reference contrasting living versus early postmortem human retina, integrating cell type composition, transcriptional diversity, and functional insights. It may serve as a useful resource for retinal research and for understanding aspects of human retinal biology, particularly given its inclusion of living tissue and diverse pathological states.
目前人类视网膜研究主要利用死后组织，样本获取的限制使得以单细胞分辨率对活体人类视网膜进行表征成为一项挑战。尽管单核RNA测序扩展了冷冻样本的实用性，但它提供的是以细胞核为中心的视角，可能会遗漏关键的细胞质信息和瞬时生物学过程。因此，直接从活体人类视网膜组织生成资源以补充现有数据集非常重要。
我们对来自9个未冷冻的人类视网膜样本的106,829个单细胞进行了分析。活体样本在治疗性眼球摘除后10分钟内采集，4个死后样本在6小时内采集。经过标准化解离后，使用10x Genomics 3' RNA测序生成单细胞转录组，并应用scVI生成批次校正的整合图谱。通过迭代莱顿聚类、典型标记对主要细胞类型和亚型进行注释。后续分析包括细胞状态之间的差异表达比较和调控子活性分析，以进一步表征细胞身份和调控网络。使用RNA速度评估转录动力学，并通过CellChat推断细胞间信号通路。使用相同的工作流程在另外两名捐赠者的独立样本（4个样本）中验证了关键发现。
我们为视网膜细胞类型比例和细胞状态建立了参考。我们分析发现了ELF1-mlCone，这是一类通过独特转录特征鉴定的mlCone光感受器的独特簇。该簇的存在和转录特征在独立样本中得到了验证。此外，通过比较活体和死后样本，我们的研究突出了转录动力学的差异：活体组织保留了连贯的RNA速度流，能够实现清晰的动态状态转变，而死后组织则呈现出无序模式。这些发现表明，使用活体组织可以改善对活跃细胞状态和转变的捕获。
我们的图谱提供了一个单细胞参考，对比了活体与早期死后人类视网膜，整合了细胞类型组成、转录多样性和功能见解。它可能是视网膜研究以及理解人类视网膜生物学方面的有用资源，特别是考虑到它包含了活体组织和多种病理状态。
