Project description:Rett syndrome is an X-linked neurodevelopmental disorder caused by mutation in the methyl-CpG-binding protein 2 gene in the majority of cases. We describe an RNA sequencing dataset of postmortem brain tissue samples from four females clinically diagnosed with Rett syndrome and four age-matched female donors. The dataset contains transcriptomes from two brain regions, temporal and cingulate cortex, for each individual, providing a valuable resource to explore the biology of the human brain in Rett syndrome.
Project description:The receptors engaged during phagocytic particle uptake determine the signaling events that occur during phagosome formation and maturation. However, pathogens generally have multiple ligands, making it difficult to dissect the roles of individual receptors in these processes. Here, we used latex beads coupled to single ligands, focusing on IgG, mannan, LPS and avidin, and monitored phagocytic uptake rates, phago-lysosomal fusion events, macrophage gene expression and the proteomic composition of isolated phagosomes. The pattern of gene expression and the protein composition of isolated phagosomes showed that each bead ligand altered a distinct pattern of genes and led to a different composition of phagosomes. These data argue that activation of each receptor initiates a specific signature of signaling events that last many hours and influences several phagocytosis functions.
Project description:This dataset contains single-cell RNA sequencing data from lung tissues of Trav4 gene-edited mice . The samples were collected for the investigation of molecular changes induced by Trav4 gene mutations, specifically focusing on lung injury. The dataset includes gene expression profiles of individual cells and enables the study of cell-type-specific responses, immune cell changes, and alterations in key cellular pathways. This dataset is useful for further understanding the pathophysiology of lung injury associated with Trav4 gene mutations.
Project description:This dataset contains bulk RNA sequencing data from primary tumor biopsy samples of patients with prostate adenocarcinoma. TPM-normalized expression values are provided along with sample metadata. The data were generated to support transcriptomic profiling of human prostate tumors and are related to a companion single-cell RNA-seq dataset from the same cohort.
Project description:Cell-cell fusion is a tightly controlled process in the human body known to be involved in fertilization, placental development, muscle growth, bone remodeling, and viral response. Fusion between cancer cells results first in a whole-genome doubled state, which may be followed by the generation of aneuploidies; these genomic alterations are known drivers of tumor evolution. The role of cell-cell fusion in cancer progression and treatment response has been understudied due to limited experimental systems for tracking and analyzing individual fusion events. To meet this need, we developed a molecular toolkit to map the origins and outcomes of individual cell fusion events within a tumor cell population. This platform, ClonMapper Duo (‘CMDuo’), identifies cells that have undergone cell-cell fusion through a combination of reporter expression and engineered fluorescence-associated index sequences paired to random barcode sets. scRNA-seq of the indexed barcodes enables the mapping of each set of parental cells and fusion progeny throughout the cell population. In triple negative breast cancer cells CMDuo uncovered subclonal transcriptomic hybridization and unveiled distinct cell-states which arise in direct consequence of homotypic cell-cell fusion. CMDuo is a platform that enables mapping of cell-cell fusion events in high-throughput single cell data and enables the study of cell fusion in disease progression and therapeutic response.
Project description:Cell-cell fusion is a tightly controlled process in the human body known to be involved in fertilization, placental development, muscle growth, bone remodeling, and viral response. Fusion between cancer cells results first in a whole-genome doubled state, which may be followed by the generation of aneuploidies; these genomic alterations are known drivers of tumor evolution. The role of cell-cell fusion in cancer progression and treatment response has been understudied due to limited experimental systems for tracking and analyzing individual fusion events. To meet this need, we developed a molecular toolkit to map the origins and outcomes of individual cell fusion events within a tumor cell population. This platform, ClonMapper Duo (‘CMDuo’), identifies cells that have undergone cell-cell fusion through a combination of reporter expression and engineered fluorescence-associated index sequences paired to random barcode sets. scRNA-seq of the indexed barcodes enables the mapping of each set of parental cells and fusion progeny throughout the cell population. In triple negative breast cancer cells CMDuo uncovered subclonal transcriptomic hybridization and unveiled distinct cell-states which arise in direct consequence of homotypic cell-cell fusion. CMDuo is a platform that enables mapping of cell-cell fusion events in high-throughput single cell data and enables the study of cell fusion in disease progression and therapeutic response.
Project description:This dataset contains RNA-seq results from rat embryonic striatal neuronal cultures treated with CRISPRi machinery (dCas9-KRAB-MeCP2 fusion) with a CRISPR sgRNA targeting lacZ (a bacterial gene not found in the mammalian genome; used as a non-targeting control) or Reln.
Project description:This dataset contains single-cell RNA sequencing data from lung tissues of Galt gene-edited (GAL) mice and wild-type (WT) mice. The samples were collected for the investigation of molecular changes induced by Galt gene mutations, specifically focusing on lung injury. The dataset includes gene expression profiles of individual cells and enables the study of cell-type-specific responses, immune cell changes, and alterations in key cellular pathways. This dataset is useful for further understanding the pathophysiology of lung injury associated with Galt gene mutations and provides a resource for research into the molecular mechanisms of galactosemia.
Project description:Rhodopsin P23H mutation is the most comment mutation causing autosomal dominant retinitis pigmentosa in the USA. The goal of this project is to compare the transcriptome changes of the Rhodopsin P23H knock-in mouse model of adRP to the wildtype control at different ages. The transcriptomic profile will help us understand the molecular events along the pathophysiology of reititis pigmentosa in this mouse model. We include the RNA seq data of Rhodopsin P23H heterozygous mouse retinas at 1, 3 and 6 months of age to compare with age-matched wildtype mouse retinas. N=3 and each sample is from an individual animal.
Project description:This dataset contains kinobeads selectivity profile data for Kinase inhibitors and Kinase inhibitor based PROTACs along with data for the cellular perturbation of those molecules.