Systemic lupus erythematosus (SLE) is a heterogeneous autoimmune disease. Knowledge of circulating immune cell types and states associated with SLE remains incomplete. We profiled more than 1.2 million peripheral blood mononuclear cells (162 cases, 99 controls) with multiplexed single-cell RNA sequencing (mux-seq). Cases exhibited elevated expression of type 1 interferon–stimulated genes (ISGs) in monocytes, reduction of naïve CD4 ⁺ T cells that correlated with monocyte ISG expression, and expansion of repertoire-restricted cytotoxic GZMH ⁺ CD8 ⁺ T cells. Cell type–specific expression features predicted case-control status and stratified patients into two molecular subtypes. We integrated dense genotyping data to map cell type–specific cis–expression quantitative trait loci and to link SLE-associated variants to cell type–specific expression. These results demonstrate mux-seq as a systematic approach to characterize cellular composition, identify transcriptional signatures, and annotate genetic variants associated with SLE.

Type I interferon autoantibodies in patients with COVID-19 are associated with poor interferon responses and increased LAIR1 abundance in leukocytes.

XYZeq is a novel scalable platform that directly encodes spatial location from tissue into single-cell RNA sequencing libraries.

Juvenile dermatomyositis (JDM) is one of several childhood-onset autoimmune disorders characterized by a type I IFN response and autoantibodies. Treatment options are limited due to an incomplete understanding of how the disease emerges from dysregulated cell states across the immune system. We therefore investigated the blood of patients with JDM at different stages of disease activity using single-cell transcriptomics paired with surface protein expression. By immunophenotyping peripheral blood mononuclear cells, we observed skewing of the B cell compartment toward an immature naive state as a hallmark of JDM at diagnosis. Furthermore, we find that these changes in B cells are paralleled by T cell signatures suggestive of Th2-mediated inflammation that persist despite disease quiescence. We applied network analysis to reveal that hyperactivation of the type I IFN response in all immune populations is coordinated with previously masked cell states including dysfunctional protein processing in CD4 ⁺ T cells and regulation of cell death programming in NK cells, CD8 ⁺ T cells, and γδ T cells. Together, these findings unveil the coordinated immune dysregulation underpinning JDM and provide insight into strategies for restoring balance in immune function.

Multiplexed single-cell sequencing (mux-seq) using single-nucleotide polymorphisms (SNPs) has emerged as an efficient approach to perform expression quantitative trait loci (eQTL) studies that map interactions between genetic variants and cell types, cell states, or experimental perturbations. Here we introduce the clue framework, a novel approach to encode mux-seq experiments that eliminates the need for reference genotypes and experimental barcoding. The clue framework is made possible by the development of freemuxlet , an algorithm that clusters cells based on SNPs called from single-cell RNA-seq or ATAC-seq data. To demonstrate the feasibility of clue , we profiled the surface protein and RNA abundances of peripheral blood mononuclear cells from 64 individuals, stimulated with 5 distinct extracellular stimuli — all within a single day. Our analysis of the demultiplexed data identified rare immune cell types and cell type-specific responses to interferon and toll-like receptor stimulation. Furthermore, by integrating genotyping data, we mapped response eQTLs specific to certain cell types. These findings showcase the potential and scalability of the clue framework for reference-free multiplexed single-cell sequencing studies.

The development of DNA-barcoded antibodies to tag cell-surface molecules has enabled the use of droplet-based single cell sequencing (dsc-seq) to profile the surface proteomes of cells. Compared to flow and mass cytometry, the major limitation of current dsc-seq-based workflows is the high cost associated with profiling each cell, thus precluding its use in applications where millions of cells are required. Here, we introduce SCITO-seq, a new workflow that combines combinatorial indexing and commercially available dsc-seq to enable cost-effective cell surface proteomic sequencing of greater than 10 ⁵ cells per microfluidic reaction. We demonstrate SCITO-seq’s feasibility and scalability by profiling mixed species cell lines and mixed human T and B lymphocytes. To further demonstrate its applicability, we show comparable cellular composition estimates in peripheral blood mononuclear cells obtained with SCITO-seq and mass cytometry. SCITO-seq can be extended to include simultaneous profiling of additional modalities such as transcripts and accessible chromatin or tracking of experimental perturbations such as genome edits or extracellular stimuli.