Project description:Purpose: To compare the transcriptomes of activated CD4 T effector cell populations in the presence and absence of STAT3 at 8 days post-infection using high-throughput RNA sequencing analysis. Methods: Cell sorting of the populations was done using the markers Ly6c and PSGL-1 CD4 T cell Ly6c and PSGL-1 population mRNA profiles 8 days post-LCMV infection of wild type (WT) and STAT3fl/fl Cd4cre mice were generated by mRNA sequencing using Illumina HiSeq 2000.
Project description:<p>We use next generation sequencing to investigate the different transcriptomes of closely related CD4+ T-cells from healthy human donors to elucidate the genetic programs that underlie their specialized immune functions. Six cell types were included: Regulatory T-cells (CD25hiCD127low/neg with >95% FOXP3+ purity), regulatory T-cells activated using PMA/ionomycin, CD25-CD45RA+ ('naive' helper T-cells), CD25-CD45RO+ ('memory' helper T-cells), activated Th17 cells (>98% IL17A+ purity) and activated IL17-CD4+ T-cells (called 'ThPI'). Poly-T capture beads were used to isolate mRNA from total RNA, and fragment sizes of ~200 were sequenced from both ends on Illumina's genome analyzer. We confirm many of the canonical signature genes of T-cell populations, but also discover new genes whose expression is limited to specific CD4 T-cell lineages, including long non-coding RNAs. Additionally, we find that genes encoded at loci linked to multiple human autoimmune diseases are enriched for preferential expression upon T-cell activation, suggesting that an aberrant response to T-cell activation is fundamental to pathogenesis.</p>
Project description:With improved whole-cell isolation protocols, we performed single-cell RNA sequencing (scRNA-seq) and profiled the transcriptomes from adult non-human primate brain. We identified discriminative cell populations with canonical and novel markers. Cross-species projection demonstrated the evolutionary conservation among mouse, monkey, and human. This dataset serves as a detailed transcriptomic atlas for understanding the adult primate central nervous system.
Project description:Naive CD4+ T cells are the common precursors of multiple effector and memory T cell subsets and possess a high plasticity in terms of differentiation potential. This stem-cell like character is important for cell therapies aiming at regeneration of specific immunity. Cell surface proteins are crucial for recognition and response to signals mediated by other cells or environmental changes. Knowledge of cell surface proteins of human naive CD4+ T cells and their changes during the early phase of T cell activation is urgently needed for a guided differentiation of naive T cells and may support the selection of pluripotent cells for cell therapy.<br>Periodate oxidation and aniline-catalyzed oxime ligation (PAL) technology was applied with subsequent quantitative LC-MS/MS (PAL-qLC-MS/MS) to generate a dataset describing the surface proteome of human naive CD4+ T cells and to monitor dynamic changes during the early phase of activation. This led to the identification of 173 N-glycosylated surface proteins, of which 24 were previously not known to be expressed on human naive CD4+ T cells or have no defined role within T cell activation. To independently confirm the proteomic dataset and to analyse the cell surface by an alternative technique a systematic phenotypic expression analysis of surface antigens via flow cytometry was performed. This screening expanded the previous dataset, resulting in 229 surface proteins which are expressed on naive unstimulated and activated CD4+ T cells. Furthermore, we generated a surface expression atlas based on transcriptome data, experimental annotation and predicted subcellular localization, and correlated the proteomics result with this transcriptional dataset.<br>This extensive surface atlas provides an overall naive CD4+ T cell surface resource and will enable future studies aiming at a deeper understanding of mechanisms of T cell biology allowing the identification of novel immune targets usable for the development of therapeutic treatments.
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.
Project description:<p>RNA sequencing was performed on human DRGs and relative gene abundances were calculated.</p> <p>Various analyses were performed:</p> <p> <ol> <li>Human DRG gene expression profiles were contrasted with a panel of gene expression profiles of relevant tissues in human and mouse ( integrating, among other sources, datasets from ENCODE and GTex ) in order to identify.</li> <ol type="a"> <li>DRG-enriched gene expression, co-expression modules of DRG-expressed genes, and key transcriptional regulators in humans.</li> <li>Contrasting the human and mouse DRG transcriptomes to identify DRG-enriched gene expression patterns that were conserved between human and mouse, identifying putative cell types of expression of these genes, and potential known drugs that might target the corresponding gene products.</li> <li>Characterization of non-coding RNA profile of human and mouse DRGs.</li> <li>Characterization of DRG-enriched alternative splicing and alternative transcription start site usage based transcript variants in humans and mouse, and the overlap between these two species.</li> <li>Contrasting of human DRG and GTex human tibial nerve samples to identify putative axonally transported mRNAs in sensory neurons.</li> </ol> <li>Human DRG transcriptomes from donors suffering from neuropathic and/or chronic pain were contrasted with controls to identify.</li> <ol type="a"> <li>Differentially expressed genes, pathways and regulators path play a potential role in neuronal plasticity, electrophysiological activity, immune signaling and response.</li> <li>Predictive models (Random Forests) were built to jointly predict the sex and pain state of samples based on information contained solely in autosomal gene expression profile.</li> <li>Gene co-expression modules were identified and gene set enrichment analysis performed.to identify sample - pathway associations, and to broadly characterize plasticity in human DRG cell types.</li> </ol> </ol> </p>