Human Eye Cell Atlas

CELLxGENE provides data collection for the Human Retina Cell Atlas (HRCA) with six datasets. It is suitable for exploring gene expression for either a single gene or a set of genes, as well as for analyzing the differential gene expression between cell clusters for various retinal cell types.

UCSC Cell Browser provides specialized interfaces to explore multi-omic data of the Human Retina Cell Atlas (HRCA).

To provide a comprehensive view of the human fetal retina at the molecular level and investigate transcriptional regulatory mechanisms controlling the differentiation process, we profiled more than 300,000 single nuclei of the human fetal retina from 12 donors spanning post conception week 10 and 23 with Multiome RNA-seq and ATAC-seq. To check ATAC-seq data, click peak track Hub and processed union peak. Please cite our article.

Two parallel references were derived from single cell and single nuclei RNA-seq, respectively. Over 110 cell types in the human retina are identified, nearly doubling the number reported in previous studies. Integrative atlas with RNA and ATAC-seq, generating comprehensive gene regulatory landscape at single-cell resolution for the human retina.

By integrating newly generated and previously published datasets, we developed version 1 of the human RPE and choroid cell atlas. This atlas includes scRNA-seq data from 205,925 cells from 67 donors and snRNA-seq data from 742,625 nuclei from 54 donors. Additionally, we incorporated snRNA-seq data from 136,555 nuclei from developmental RPE/choroid tissues spanning post-conception weeks (PCW) 10-23.

In total, the atlas includes over 1 million cells and nuclei from 102 donors. We identified 10 major cell classes and 31 types in the atlas, including rare populations such as limbal progenitor cells, Schlemn’s canel endothelium, and specific immune subtypes.

All data were uniformly preprocessed and combined, resulting in a comprehensive TM and CB atlas that includes transcriptomic profiles of over 1 million cells from 70 donors. We identified 19 distinct cell types, including rare populations such as immune cells, with the least abundant types representing as little as 0.08% of the total cell population.

By integrating newly generated and previously published snRNA-seq datasets, we constructed a comprehensive ONH and ON cell atlas encompassing transcriptomic profiles of 959,629 nuclei. Our analysis identified 25 distinct cell classes and 86 cell types/states, including diverse populations of astrocytes, oligodendrocytes, oligodendrocyte precursor cells, microglia, and macrophages.