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.
Project description:Cognitive decline is a common occurrence of the natural aging process in animals, and studying age-related changes in gene expression in the brain might shed light on disrupted molecular pathways that play a role in this decline. The fruit fly is a useful neurobiological model for studying aging due to its short generational time and relatively small brain size. We investigated age-dependent changes in the Drosophila melanogaster whole-brain transcriptome by comparing 5-, 20-, 30- and 40-day-old flies of both sexes. We used RNA-Sequencing of dissected brain samples followed by differential expression, temporal clustering, co-expression network and gene ontology enrichment analyses. Our study provides the first transcriptome profile of aging brains from fruit flies of both sexes, and it will serve as an important resource for those who study aging and cognitive decline in this model.
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 a multifactorial process with significant functional alterations of the human body including endocrinal systems which control the whole-body physiology and metabolism. In this vein, aging-induced decline of endocrine function are associated with multiple physiological and metabolic diseases. However, aging-associated molecular shifts in the pituitary gland, the central organ of the endocrine system, have not been dissected systemically. In this study, we conducted single-cell transcriptomic analysis of the anterior pituitary gland by comparing old and young male mice. Single-cell transcriptomics not only increased the resolution for clustering of various cell types in the pituitary gland, but also enabled detailed analysis of differential expression and intercellular communication caused by aging. In summary, our study constructed the first single-cell transcriptomic atlas of pituitary aging and identified associated features of in a single-cell level, providing resources to develop novel potential therapeutic targets for aging-associated endocrine dysfunction.
Project description:Single-cell technologies have ushered in a new era for Drosophila research, allowing researchers to obtain transcriptomes for all stable cell types and dynamic cell states. Here we present the first release of the adult Fly Cell Atlas (FCA), which includes 580k cells from 15 individually dissected sexed tissues, as well as from the entire head and body. We annotated more than 250 distinct cell types across all tissues. Few cell types were uniquely detected in the entire head and body samples, suggesting high cell-type saturation. We provide an in-depth analysis of gene signatures and transcription factor combinations, as well as sexual dimorphism, across the whole animal. Finally, we studied cell type lineages that are shared between tissues, such as blood cells and muscle cells, allowing the retrieval of rare cell types and tissue- specific subtypes. This atlas provides a valuable resource for the entire Drosophila community as a reference to study genetic perturbations and disease models at single-cell resolution.