DISCO: a database of Deeply Integrated human Single-Cell Omics data.

The ability to study cellular heterogeneity at single cell resolution is making single-cell sequencing increasingly popular. However, there is no publicly available resource that offers an integrated cell atlas with harmonized metadata that users can integrate new data with. Here, we present DISCO (https://www.immunesinglecell.org/), a database of Deeply Integrated Single-Cell Omics data. The current release of DISCO integrates more than 18 million cells from 4593 samples, covering 107 tissues/cell lines/organoids, 158 diseases, and 20 platforms. We standardized the associated metadata with a controlled vocabulary and ontology system. To allow large scale integration of single-cell data, we developed FastIntegration, a fast and high-capacity version of Seurat Integration. We also developed CELLiD, an atlas guided automatic cell type identification tool. Employing these two tools on the assembled data, we constructed one global atlas and 27 sub-atlases for different tissues, diseases, and cell types. DISCO provides three online tools, namely Online FastIntegration, Online CELLiD, and CellMapper, for users to integrate, annotate, and project uploaded single-cell RNA-seq data onto a selected atlas. Collectively, DISCO is a versatile platform for users to explore published single-cell data and efficiently perform integrated analysis with their own data.

Iqgap3-Ras axis drives stem cell proliferation in the stomach corpus during homoeostasis and repair.

OBJECTIVE: Tissue stem cells are central regulators of organ homoeostasis. We looked for a protein that is exclusively expressed and functionally involved in stem cell activity in rapidly proliferating isthmus stem cells in the stomach corpus. DESIGN: We uncovered the specific expression of Iqgap3 in proliferating isthmus stem cells through immunofluorescence and in situ hybridisation. We performed lineage tracing and transcriptomic analysis of Iqgap3 +isthmus stem cells with the Iqgap3-2A-tdTomato mouse model. Depletion of Iqgap3 revealed its functional importance in maintenance and proliferation of stem cells. We further studied Iqgap3 expression and the associated gene expression changes during tissue repair after tamoxifen-induced damage. Immunohistochemistry revealed elevated expression of Iqgap3 in proliferating regions of gastric tumours from patient samples. RESULTS: Iqgap3 is a highly specific marker of proliferating isthmus stem cells during homoeostasis. Iqgap3+isthmus stem cells give rise to major cell types of the corpus unit. Iqgap3 expression is essential for the maintenance of stem potential. The Ras pathway is a critical partner of Iqgap3 in promoting strong proliferation in isthmus stem cells. The robust induction of Iqgap3 expression following tissue damage indicates an active role for Iqgap3 in tissue regeneration. CONCLUSION: IQGAP3 is a major regulator of stomach epithelial tissue homoeostasis and repair. The upregulation of IQGAP3 in gastric cancer suggests that IQGAP3 plays an important role in cancer cell proliferation.

Establishing a human bone marrow single cell reference atlas to study ageing and diseases.

Introduction: Ageing in the human bone marrow is associated with immune function decline that results in the elderly being vulnerable to illnesses. A comprehensive healthy bone marrow consensus atlas can serve as a reference to study the immunological changes associated with ageing, and to identify and study abnormal cell states. Methods: We collected publicly available single cell transcriptomic data of 145 healthy samples encompassing a wide spectrum of ages ranging from 2 to 84 years old to construct our human bone marrow atlas. The final atlas has 673,750 cells and 54 annotated cell types. Results: We first characterised the changes in cell population sizes with respect to age and the corresponding changes in gene expression and pathways. Overall, we found significant age-associated changes in the lymphoid lineage cells. The naïve CD8+ T cell population showed significant shrinkage with ageing while the effector/memory CD4+ T cells increased in proportion. We also found an age-correlated decline in the common lymphoid progenitor population, in line with the commonly observed myeloid skew in haematopoiesis among the elderly. We then employed our cell type-specific ageing gene signatures to develop a machine learning model that predicts the biological age of bone marrow samples, which we then applied to healthy individuals and those with blood diseases. Finally, we demonstrated how to identify abnormal cell states by mapping disease samples onto the atlas. We accurately identified abnormal plasma cells and erythroblasts in multiple myeloma samples, and abnormal cells in acute myeloid leukaemia samples. Discussion: The bone marrow is the site of haematopoiesis, a highly important bodily process. We believe that our healthy bone marrow atlas is a valuable reference for studying bone marrow processes and bone marrow-related diseases. It can be mined for novel discoveries, as well as serve as a reference scaffold for mapping samples to identify and investigate abnormal cells.

Notch-dependent cooperativity between myeloid lineages promotes Langerhans cell histiocytosis pathology.

Langerhans cell histiocytosis (LCH) is a potentially fatal neoplasm characterized by the aberrant differentiation of mononuclear phagocytes, driven by mitogen-activated protein kinase (MAPK) pathway activation. LCH cells may trigger destructive pathology yet remain in a precarious state finely balanced between apoptosis and survival, supported by a unique inflammatory milieu. The interactions that maintain this state are not well known and may offer targets for intervention. Here, we used single-cell RNA-seq and protein analysis to dissect LCH lesions, assessing LCH cell heterogeneity and comparing LCH cells with normal mononuclear phagocytes within lesions. We found LCH discriminatory signatures pointing to senescence and escape from tumor immune surveillance. We also uncovered two major lineages of LCH with DC2- and DC3/monocyte-like phenotypes and validated them in multiple pathological tissue sites by high-content imaging. Receptor-ligand analyses and lineage tracing in vitro revealed Notch-dependent cooperativity between DC2 and DC3/monocyte lineages during expression of the pathognomonic LCH program. Our results present a convergent dual origin model of LCH with MAPK pathway activation occurring before fate commitment to DC2 and DC3/monocyte lineages and Notch-dependent cooperativity between lineages driving the development of LCH cells.

A benchmark of batch-effect correction methods for single-cell RNA sequencing data.

BACKGROUND: Large-scale single-cell transcriptomic datasets generated using different technologies contain batch-specific systematic variations that present a challenge to batch-effect removal and data integration. With continued growth expected in scRNA-seq data, achieving effective batch integration with available computational resources is crucial. Here, we perform an in-depth benchmark study on available batch correction methods to determine the most suitable method for batch-effect removal. RESULTS: We compare 14 methods in terms of computational runtime, the ability to handle large datasets, and batch-effect correction efficacy while preserving cell type purity. Five scenarios are designed for the study: identical cell types with different technologies, non-identical cell types, multiple batches, big data, and simulated data. Performance is evaluated using four benchmarking metrics including kBET, LISI, ASW, and ARI. We also investigate the use of batch-corrected data to study differential gene expression. CONCLUSION: Based on our results, Harmony, LIGER, and Seurat 3 are the recommended methods for batch integration. Due to its significantly shorter runtime, Harmony is recommended as the first method to try, with the other methods as viable alternatives.