Background Elucidation of immune populations with single-cell RNA-seq has greatly benefited the field of immunology by deepening the characterization of immune heterogeneity and leading to the discovery of new subtypes. However, single-cell methods inherently suffer from limitations in the recovery of complete transcriptomes due to the prevalence of cellular and transcriptional dropout events. This issue is often compounded by limited sample availability and limited prior knowledge of heterogeneity, which can confound data interpretation. Results Here, we systematically benchmarked seven high-throughput single-cell RNA-seq methods. We prepared 21 libraries under identical conditions of a defined mixture of two human and two murine lymphocyte cell lines, simulating heterogeneity across immune-cell types and cell sizes. We evaluated methods by their cell recovery rate, library efficiency, sensitivity, and ability to recover expression signatures for each cell type. We observed higher mRNA detection sensitivity with the 10x Genomics 5′ v1 and 3′ v3 methods. We demonstrate that these methods have fewer dropout events, which facilitates the identification of differentially-expressed genes and improves the concordance of single-cell profiles to immune bulk RNA-seq signatures. Conclusion Overall, our characterization of immune cell mixtures provides useful metrics, which can guide selection of a high-throughput single-cell RNA-seq method for profiling more complex immune-cell heterogeneity usually found in vivo.

In the present study, we characterize a polymorphism in the CD93 molecule, originally identified as the receptor for the C1q complement component (i.e., C1qRp, or AA4.1) in non-obese diabetic (NOD) mice. This allele carries a coding polymorphism in the first epidermal growth factor-like domain of CD93, which results in an amino acid substitution from Asn→His at position 264. This polymorphism does not appear to influence protein translation or ecto-domain cleavage, as CD93 is detectable in bone-marrow-derived macrophage and B-cell precursor lysates and in soluble form in the serum. The NOD CD93 isoform causes a phenotypic aberrancy in the early B-cell developmental stages (i.e., pro-, pre-, immature, and transitional), likely related to a conformational variation. Interestingly, the NZB/W F1 strain, which serves as a murine model of Lupus, also expresses an identical CD93 sequence polymorphism. Cd93 is located within the NOD Idd13 locus and is also tightly linked to the NZB/W F1 Wbw1 and Nkt2 disease susceptibility loci, which are thought to regulate natural killer T (NKT) cell homeostasis. Consistent with this genetic linkage, we found B6 CD93−/− and B6.NODIdd13 mice to be susceptible to a profound CD4+ NKT cell deficient state. These data suggest that Cd93 may be an autoimmune susceptibility gene residing within the Idd13 locus, which plays a role in regulating absolute numbers of CD4+ NKT cells.

Background: Elucidation of immune populations with single-cell RNA-seq has greatly benefited the field of immunology by deepening the characterization of immune heterogeneity and leading to the discovery of new subtypes. However, single-cell methods inherently suffer from limitations in the recovery of complete transcriptomes due to the prevalence of cellular and transcriptional dropout events. This issue is often compounded by limited sample availability and limited prior knowledge of heterogeneity, which can confound data interpretation. Results: Here, we systematically benchmarked seven high-throughput single-cell RNA-seq methods. We prepared 21 libraries under identical conditions of a defined mixture of two human and two murine lymphocyte cell lines, simulating heterogeneity across immune-cell types and cell sizes. We evaluate methods by their cell recovery rate, library efficiency, sensitivity, and ability to recover expression signatures for each cell type. We observed higher mRNA detection sensitivity with the 10x Genomics 5’ v1 and 3’ v3 methods. We demonstrate that these methods have fewer drop-out events which facilitates the identification of differentially-expressed genes and improves the concordance of single-cell profiles to immune bulk RNA-seq signatures.Conclusion: Overall, our characterization of immune cell mixtures provides useful metrics, which can guide selection of a high-throughput single-cell RNA-seq method for profiling more complex immune-cell heterogeneity usually found in vivo.

Phagocytosis is a key macrophage function, but how phagocytosis shapes tumor-associated macrophage (TAM) phenotypes and heterogeneity in solid tumors remains unclear. Here, we utilized both syngeneic and novel autochthonous lung tumor models in which neoplastic cells express the fluorophore tdTomato (tdTom) to identify TAMs that have phagocytosed neoplastic cells in vivo. Phagocytic tdTompos TAMs upregulated antigen presentation and anti-inflammatory proteins, but downregulated classic proinflammatory effectors compared to tdTomneg TAMs. Single-cell transcriptomic profiling identified TAM subset-specific and common gene expression changes associated with phagocytosis. We uncover a phagocytic signature that is predominated by oxidative phosphorylation (OXPHOS), ribosomal, and metabolic genes, and this signature correlates with worse clinical outcome in human lung cancer. Expression of OXPHOS proteins, mitochondrial content, and functional utilization of OXPHOS were increased in tdTompos TAMs. tdTompos tumor dendritic cells also display similar metabolic changes. Our identification of phagocytic TAMs as a distinct myeloid cell state links phagocytosis of neoplastic cells in vivo with OXPHOS and tumor-promoting phenotypes.

Defining the molecular and genetic basis for heart rate regulation and for susceptibility to atrial arrhythmias has been challenging due to the complexity of the human sinoatrial node (SAN), a tiny structure with limiting numbers of several distinct pacemaker cardiomyocyte (PC) subtypes in a spatially patterned array. Here we describe a novel method to derive large numbers of human PCs from human induced pluripotent stem cells (hiPSCs) that recapitulates key features of SAN development including differentiation into anatomically and functionally distinct PC subtypes of the SAN. Single cell (sc) RNA-sequencing, sc-ATAC-sequencing, and time course analyses of cellular differentiation were used to define epigenetic and transcriptomic signatures of cellular specialization within the SAN, and to identify transcriptional pathways important for PC differentiation. Intersection of our multi-omics datasets with existing human genome wide association studies uncovered regulatory elements with differential accessibility in different PC subtypes that harbored SNPs that associated with human heart rate regulation and susceptibility to atrial fibrillation, enabling disease gene discovery and prioritization.