Project description:Joint profiling of chromatin accessibility and gene expression from the same single cell provides critical information about cell types in a tissue and cell states during a dynamic process. These emerging multi-omics techniques help the investigation of cell-type resolved gene regulatory mechanisms. Here, we developed in situ SHERRY after ATAC-seq (ISSAAC-seq), a highly sensitive and flexible single cell multi-omics method to interrogate chromatin accessibility and gene expression from the same single cell. We demonstrated that ISSAAC-seq is sensitive and provides high quality data with orders of magnitude more features than existing methods. Using the joint profiles from thousands of nuclei from the mouse cerebral cortex, we uncovered major and rare cell types together with their cell-type specific regulatory elements and expression profiles. Finally, we revealed distinct dynamics and relationships of transcription and chromatin accessibility during an oligodendrocyte maturation trajectory.
Project description:Multi-omics single-cell profiling of surface proteins, gene expression and lymphocyte immune receptors from hospitalised COVID-19 patient peripheral blood immune cells and healthy controls donors. Identification of the coordinated immune cell compositional and state changes in response to SARS-CoV-2 infection or LPS challenge, compared to healthy control immune cells.
Project description:Multi-omics profiling of H3-K27M DMGs across different age groups and locations, using fresh single whole cell RNA-seq, scATACseq, spatial in situ sequencing, and WES/targeted exome sequencing.
Project description:Although genomic instability, epigenetic abnormality, and gene expression dysregulation are hallmarks of colorectal cancer, these features have not been simultaneously analyzed at single-cell resolution. Using optimized single-cell multi-omics sequencing together with multi-regional sampling of the primary tumor, lymphatic and distant metastases, we provide insights beyond intratumoral heterogeneity. Genome-wide DNA methylation levels were relatively consistent within a single genetic sub-lineage. The genome-wide DNA demethylation patterns of cancer cells were consistent in all 10 sequenced patients. Our work demonstrates the feasibility of reconstructing genetic lineages, and tracing their epigenomic and transcriptomic dynamics with single-cell multi-omics sequencing.
Project description:Developing female human germ cells undergo genome-wide epigenetic reprogramming, but de novo DNA methylation dynamics and their interplay with chromatin states and transcriptional activation in developing oocytes is poorly understood. Here, we developed a single-cell multi-omics sequencing method, scChaRM-seq, that enables simultaneous profiling of the DNA methylome, transcriptome, and chromatin accessibility in single human oocytes and ovarian somatic cells. We observed a global increase in DNA methylation during human oocyte growth that correlates with chromatin accessibility, whereas increases of DNA methylation at specific features were associated with active transcription. Integrated analyses of multi-omics data from humans and mice revealed species-specific gene expression, and promoter accessi- bility contributes to gene body methylation programs. Alu elements retained low DNA methylation levels and high accessibility in early growing oocytes and were located near developmental genes in humans and mice. Together, these findings show how scChaRM-seq can provide insight into DNA methylation pattern estab- lishment.
Project description:Despite early clinical success, the mechanisms of action of low-dose interleukin-2 (LD-IL-2) immunotherapy remain only partly understood. This dataset was generated using samples from the DILfrequency clinical trail, to examine the effects of interval administration of low-dose recombinant IL-2 (iLD-IL-2) using high-resolution, single-cell multi-omics.
Project description:Cell types in the human retina are highly heterogeneous with their abundance varies by several orders of magnitude. To decipher the complexity of gene expression and regulation of the human retinal cell types, we generated a multi-omics single-cell atlas of the adult human retina, including over 250K nuclei for single-nuclei RNA-seq and 150K nuclei for single-nuclei ATAC-seq. Over 60 cell subtypes have been identified based on their transcriptomic profiles, reaching a sensitivity of 0.01%. Integrative analysis of this single-cell multi-omics dataset identified gene regulatory elements across the genome for each cell subtype. In addition, when combined with other data modalities, such as eQTL, potential causal variants can be identified through fine mapping. Taken together, this new dataset represents the most comprehensive single-cell multi-omics profiling for the human retina that enables in-depth molecular characterization of most cell subtypes.