Mapping Mouse Cell Atlas by Microwell-seq
Ontology highlight
ABSTRACT:
OTHER RELATED OMICS DATASETS IN: GSE108097
PROVIDER: PRJNA422441 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:We developed Microwell-seq, a high-throughput and low-cost scRNA-seq platform using simple, inexpensive devices. Using Microwell-seq, we constructed a basic scheme for the Mouse Cell Atlas. We reveal single cell hierarchy for many tissues that have not been well previously characterized. Our study demonstrates the wide applicability of the Microwell-seq technology and the Mouse Cell Atlas resource.
2018-02-14 | GSE108097 | GEO
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.
2022-07-23 | GSE198831 | GEO
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.
2022-07-23 | GSE198571 | GEO
Project description:Combining in-cell RT and Microwell-seq 1.0, we established Microwell-seq 2.0 for cost-effective HTS with scRNA-seq-based phenotyping. To assess the fidelity of the Microwell-seq 2.0, we performed a species-mixing experiment with cultured human (293T) and mouse (3T3) cells. Moreover, we assessed the platform on tissue cells with more heterogeneous cell types. By harnessing the power of Microwell-seq 2.0, we analyzed massively multiplexed chemical perturbation of human embryonic stem cells (hESCs) at the single-cell resolution.
2021-11-09 | GSE175413 | GEO
Project description:Single-cell mRNA sequencing (mRNA-seq) technologies are reshaping the current cell-type classification system. In previous studies, we built the mouse cell atlas (MCA) and human cell landscape (HCL) to catalog all cell types by collecting scRNA-seq data. However, systematically study for zebrafish (Danio rerio) and fruit fly (Drosophila melanogaster) are still lacking. Here, we construct the zebrafish and Drosophila cell atlas with Microwell-seq protocols, which provides valuable resources for characterization of diverse cell populations of zebrafish and Drosophila, and studying difference between vertebrates and Invertebrates at single cell level.
2022-07-08 | GSE178149 | GEO
Project description:Single-cell mRNA sequencing (scRNA-seq) technologies are reshaping the current cell-type classification system. In previous studies, we built the mouse cell atlas (MCA) and human cell landscape (HCL) to catalog all cell types by collecting scRNA-seq data. However, systematically study for zebrafish (Danio rerio), fruit fly (Drosophila melanogaster) and earthworm (Eisenia andrei) are still lacking. Here, we construct the zebrafish, Drosophila and earthworm cell atlas with Microwell-seq protocols, which provides valuable resources for characterization of diverse cell populations of zebrafish, Drosophila and earthworm, and studying difference between vertebrates and Invertebrates at single cell level.
2022-07-08 | GSE181511 | GEO
Project description:Single-cell mRNA sequencing (scRNA-seq) technologies are reshaping the current cell-type classification system. In previous studies, we built the mouse cell atlas (MCA) and human cell landscape (HCL) to catalog all cell types by collecting scRNA-seq data. However, systematically study for zebrafish (Danio rerio) and fruit fly (Drosophila melanogaster) are still lacking. Here, we construct the zebrafish and Drosophila cell atlas with Microwell-seq protocols, which provides valuable resources for characterization of diverse cell populations of zebrafish and Drosophila, and studying difference between vertebrates and Invertebrates at single cell level.
2022-07-08 | GSE178150 | GEO
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.
2022-07-23 | GSE153562 | GEO
Project description:We report an automated microwell array platform for single cell RNA-seq with significantly improved performance over previous implementations. We demonstrate cell capture efficiencies of >50%, compatibility with commercially available barcoded mRNA capture beads, and parallel expression profiling from thousands of individual cells. We apply our system to comprehensively assess heterogeneity in gene expression of patient-derived glioma neurospheres and uncover subpopulations similar to those observed in human glioma tissue.
2016-08-13 | GSE85575 | GEO