Project description:Single-cell mRNA sequencing (scRNA-seq) technologies are reshaping current cell-type classification system. In previous studies, we constructed the Mouse Cell Atlas (MCA) and Human Cell Landscape (HCL) to catalog all cell types by collecting scRNA-seq data. Howerver, the systematic study for organism-level dynamic changes of cellular states across zebrafish life span are still lacking. Here, we constructed the zebrafish cell Landscape covering different development periods using Microwell-seq protocol. The zebrafish cell landscape provides a valuable resource for studying cross-sepciess development, maturation and aging.
Project description:Single-cell mRNA sequencing (mRNA-seq) technologies are reshaping the current cell-type classification system. In previous studies, we built a comprehensive mouse cell atlas to catalog all cell types by collecting scRNA-seq data in the fetal and adult stages. Howerver, systematically study for organism-level dynamic changes of cellular states across mouse life span are still lacking. Here, We made an updated version of mouse cell atlas (MCA) by adding scRNA-seq data covering 14 major mouse organs during different mouse development period. We revealed aging related regulatory networks and pathways that have not been well characterized previously. We found that the expressions of immune-related genes, such as antigen-presenting genes and immunoglobulin genes, appeared in non-immune cell types in aging process. We also focused on the expression of lung epithelial immunoglobulin genes and revealed their related transcriptional regulation mechanisms. The updated MCA resource provides a valuable resource for studying mammalian development, maturation and aging.
Project description:Single-cell mRNA sequencing (scRNA-seq) technologies are reshaping current cell-type classification system. In previous studies, we constructed the Mouse Cell Atlas (MCA) and Human Cell Landscape (HCL) to catalog all cell types by collecting scRNA-seq data. Howerver, the systematic study for organism-level dynamic changes of cellular states across fruit fly (Drosophila melanogaster) life span are still lacking. Here, we constructed the Drosophila cell Landscape covering different development periods using Microwell-seq protocol. The Drosophila cell landscape provides a valuable resource for studying cross-sepciess development, maturation and aging.
Project description:Aging is accompanied by the functional decline of all tissues, but it is still largely unknown how aging impacts different tissues in a cell type-specific manner. Here, we present the Aging Fly Cell Atlas (AFCA) that includes single-nucleus transcriptomes of the entire Drosophila head and body from both males and females at four different ages. We characterize 162 distinct cell types and present an in-depth analysis of cell type-specific aging features, including changes of cell composition, gene expression, number of expressed genes, transcriptome noise, and cell identity. By combining all aging features, including aging clock models predicting a cell’s age, we find cell-type specific aging patterns. Adipose tissues showed the highest aging score, followed by two cell types from the reproductive system. This transcriptomic atlas provides a valuable resource for the community to study fundamental principles of aging in complex organisms.