Project description:Microfluidic deterministic barcoding of mRNAs and proteins in tissue slides followed by high throughput sequencing enables the construction of high-spatial-resolution multi-omics atlas at the genome scale. Applying it to mouse embryo tissues revealed major tissue (sub)types in early-stage organogenesis, brain micro-vasculatures, and the fine structure of an optical vesicle at the single-cell-layer resolution.
Project description:We conducted a multi-omics analysis including single-cell RNA transcriptome, single-cell T cell receptor (scTCR), whole exome sequencing and multiplex immunohistochemistry (mIHC) to decipher single cell atlas of precursor lung adenocarcinoma and mechanisms of diverse immune cells during precursor lesions development in hopes of digging out potential therapeutic targets.
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:Multiple distinct cell types of the human lung and airways have been defined by single cell RNA sequencing (scRNAseq). Here we present a multi-omics spatial lung atlas to define novel cell types which we map back into the macro- and micro-anatomical tissue context to define functional tissue microenvironments. Firstly, we have generated single cell and nuclei RNA sequencing, VDJ-sequencing and Visium Spatial Transcriptomics data sets from 5 different locations of the human lung and airways. Secondly, we define additional cell types/states, as well as spatially map novel and known human airway cell types, such as adult lung chondrocytes, submucosal gland (SMG) duct cells, distinct pericyte and smooth muscle subtypes, immune-recruiting fibroblasts, peribronchial and perichondrial fibroblasts, peripheral nerve associated fibroblasts and Schwann cells. Finally, we define a survival niche for IgA-secreting plasma cells at the SMG, comprising the newly defined epithelial SMG-Duct cells, and B and T lineage immune cells. Using our transcriptomic data for cell-cell interaction analysis, we propose a signalling circuit that establishes and supports this niche. Overall, we provide a transcriptional and spatial lung atlas with multiple novel cell types that allows for the study of specific tissue microenvironments such as the newly defined gland-associated lymphoid niche (GALN).
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.
Project description:Integrated single-cell transcriptome and DNA methylome profiling has provided insight into the complex regulatory networks of cells. Existing methods are based on picking a single-cell and performing library construction in a tube, which is costly and cumbersome. Here, we propose DIRECT, a digital microfluidics-based method for simultaneous analysis of the methylome and transcriptome in a single library construction. The accuracy of DIRECT is demonstrated in comparison with bulk and single-omics data, and the high CpG site coverage of DIRECT allows for precise analysis of copy number variation information, enabling expansion of single cell analysis from two- to three-omics. By applying DIRECT to monitor the dynamics of mouse embryonic stem cell differentiation, the relationship between DNA methylation and changes in gene expression during differentiation was revealed. DIRECT enables accurate, robust, and reproducible single-cell DNA methylation and gene expression co-analysis at a lower cost and with greater efficiency, broadening the application scenarios of single-cell multi-omics analysis and revealing a more comprehensive and fine-grained map of cellular regulatory landscapes.
Project description:To illuminate the evolutionary trajectory of LUAD from AIS to IAC, high-throughput scRNA-seq and ST data were generated and integrated to create a large-scale, single-cell spatiotemporal atlas of LUAD. We compiled a multi-omics atlas of the early-stage LUAD invasion process that reflects the heterogeneity of cancer cells, the competitive polyclonal origin of LUAD, signalling interactions between cancer cells and the TME, and the pseudo-chronological nature of LUAD invasion. The spatial distribution characteristics of LUAD cells revealed the spatial heterogeneity of LUAD and the mechanism of spatial immune escape in LUAD, which provides strong evidence supporting clinical diagnosis and surgical intervention at the single-cell level.