Genetic effects on gene expression are often cell type-specific and obscured in bulk analyses. To resolve this context-dependent regulation, we performed a federated cis-eQTL meta-analysis across 12 PBMC datasets (2,032 individuals, 2.5 million cells). Across six immune cell types, we identified cis-eQTLs for 6,592 genes and fine-mapped 14,985 independent loci. Notably, the 42% of eQTLs that were undetected in a bulk eQTL study on 43,301 whole blood samples also showed stronger enrichment for disease GWAS loci. We further identified three genome-wide significant and 65 suggestive loci affecting the abundance of (rare) immune cell types and validated these using previously reported hematological GWAS and bulk-derived trans-eQTLs. Integrating single-cell cis-eQTLs with bulk trans-eQTLs enabled us to anchor 6,382 trans-eGenes (37.2% novel) to upstream regulators and reconstruct directed gene regulatory relationships. For example, a hemorrhoidal disease-associated variant showed a CD4+ T cell-specific cis-eQTL on BACH1 that colocalized with 45 immune and metabolic trans-eGenes. These results demonstrate the power of single-cell QTL meta-analysis in interpreting complex trait genetics.

Abstract Surface proteins define T cell identity and function, but the abundance of each protein is not determined by transcription alone. Existing genome-wide CRISPR screens in primary human T cells either profile the transcriptome or isolate cells based on a single functional or protein phenotype. Here we present SCITO-Perturb-seq, a novel platform that couples combinatorial-indexed single-cell cytometry sequencing with pooled CRISPR activation (CRISPRa) to map the causal regulation of 201 surface proteins across 3.6 million human CD4 T cells. We find that 16% of activated genes significantly alter the expression of at least one surface protein. By applying semi-nonnegative matrix factorization to the perturbation effect matrix, we identified five modules corresponding to known CD4 T cell states. Notably, these modules group surface proteins by their shared response to perturbation, revealing coordinated regulation of proteins that are not co-expressed in unperturbed cells. SCITO-Perturb-seq represents the first genome-wide CRISPRa screen paired with direct, high-dimensional surface protein profiling, providing a comprehensive regulatory map of the CD4 T cell surface proteome.

Missense variants can have pleiotropic effects on protein function and predicting these effects can be difficult. We performed near-saturation deep mutational scanning of P2RY8, a G-protein-coupled receptor that promotes germinal center B cell confinement. We assayed the effect of each variant on surface expression, migration, and proliferation. We delineated variants that affected both expression and function, affected function independently of expression, and discrepantly affected migration and proliferation. We also used cryo-electron microscopy to determine the structure of activated, ligand-bound P2RY8, providing structural insights into the effects of variants on ligand binding and signal transmission. We applied the deep mutational scanning results to both improve computational variant effect predictions and to characterize the phenotype of germline variants and lymphoma-associated variants. Together, our results demonstrate the power of integrating deep mutational scanning, structure determination, and in silico prediction to advance the understanding of a receptor important in human health.

Engineering T cell specificity and function at multiple loci can generate more effective cellular therapies, but current manufacturing methods produce heterogenous mixtures of partially engineered cells. Here we develop a one-step process to enrich unlabeled cells containing knock-ins at multiple target loci using a family of repair templates named synthetic exon expression disruptors (SEEDs). SEEDs associate transgene integration with the disruption of a paired target endogenous surface protein while preserving target expression in nonmodified and partially edited cells to enable their removal (SEED-Selection). We design SEEDs to modify three critical loci encoding T cell specificity, coreceptor expression and major histocompatibility complex expression. The results demonstrate up to 98% purity after selection for individual modifications and up to 90% purity for six simultaneous edits (three knock-ins and three knockouts). This method is compatible with existing clinical manufacturing workflows and can be readily adapted to other loci to facilitate production of complex gene-edited cell therapies.

Systemic lupus erythematosus (SLE) presents with diverse and heterogenous cutaneous manifestations. However, the molecular and immunologic pathways driving specific cutaneous manifestations of SLE are poorly understood. Here, we leverage transcriptomics from a large well-phenotyped longitudinal cohort of SLE patients to map molecular pathways linked to ten distinct SLE-related rashes. Through whole blood and immune cell-sorted bulk RNA sequencing, we identified immune signatures specific to cutaneous subtypes of SLE. Subacute cutaneous lupus (SCLE) exhibited broad upregulation of type I interferon, TNF-α, and IL6-JAK-STAT3, pathways suggesting potential unique therapeutic responses to JAK and type I interferon inhibition. While interferon signaling is prominent in SCLE, discoid lupus, and acute lupus, it is unexpectedly absent in patients with skin and mucosal ulcers. Pathway and cell-type enrichment analysis revealed unexpected roles for CD14+ monocytes in photosensitivity of SLE and NK cells in alopecia, mucosal ulceration, and livedo reticularis. These findings illuminate the immune heterogeneity of rashes in SLE, highlighting subtype-specific mechanistic targets, and presenting opportunities to identify precision therapies for SLE-associated skin phenotypes.

Respiratory syncytial virus (RSV) is a globally prevalent pathogen, causes severe disease in older adults, and is the leading cause of bronchiolitis and pneumonia in the United States for children during their first year of life [1]. Despite its prevalence worldwide, RSV-specific treatments remain unavailable for most infected patients. Here, we leveraged a combination of genome-wide CRISPR knockout screening and single-cell RNA sequencing to improve our understanding of the host determinants of RSV infection and the host response in both infected cells, and uninfected bystanders. These data reveal temporal transcriptional patterns that are markedly different between RSV infected and bystander activated cells. Our data show that expression of interferon-stimulated genes is primarily observed in bystander activated cells, while genes implicated in the unfolded protein response and cellular stress are upregulated specifically in RSV infected cells. Furthermore, genome-wide CRISPR screens identified multiple host factors important for viral infection, findings which we contextualize relative to 29 previously published screens across 17 additional viruses. These unique data complement and extend prior studies that investigate the proinflammatory response to RSV infection, and juxtaposed to other viral infections, provide a rich resource for further hypothesis testing.

Respiratory syncytial virus (RSV) is a globally prevalent pathogen, causes severe disease in older adults, and is the leading cause of bronchiolitis and pneumonia in the United States for children during their first year of life. Despite its prevalence worldwide, RSV-specific treatments remain unavailable for most infected patients. Here, we leveraged a combination of genome-wide CRISPR knockout screening and single-cell RNA sequencing to improve our understanding of the host determinants of RSV infection and the host response in both infected cells and uninfected bystanders. These data reveal temporal transcriptional patterns that are markedly different between RSV-infected and bystander-activated cells. Our data show that expression of interferon-stimulated genes is primarily observed in bystander activated cells, while genes implicated in the unfolded protein response and cellular stress are upregulated specifically in RSV-infected cells. Furthermore, genome-wide CRISPR screens identified multiple host factors important for viral infection, findings which we contextualize relative to 29 previously published screens across 17 additional viruses. These unique data complement and extend prior studies that investigate the proinflammatory response to RSV infection, and juxtaposed to other viral infections, provide a rich resource for further hypothesis testing.IMPORTANCERespiratory syncytial virus (RSV) is a leading cause of lower respiratory tract infection in infants and the elderly. Despite its substantial global health burden, RSV-targeted treatments remain unavailable for the majority of individuals. While vaccine development is underway, a detailed understanding of the host response to RSV infection and identification of required human host factors for RSV may provide insight into combatting this pathogen. Here, we utilized single-cell RNA sequencing and functional genomics to understand the host response in both RSV-infected and bystander cells, identify what host factors mediate infection, and contextualize these findings relative to dozens of previously reported screens across 17 additional viruses.

While cytotoxic CD4+ tumor-infiltrating lymphocytes have anticancer activity in patients, whether these can be noninvasively monitored and how these are regulated remains obscure. By matching single cells with T cell receptors (TCRs) in tumor and blood of patients with bladder cancer, we identified distinct pools of tumor-matching cytotoxic CD4+ T cells in the periphery directly reflecting the predominant antigenic specificities of intratumoral CD4+ tumor-infiltrating lymphocytes. On one hand, the granzyme B-expressing (GZMB-expressing) cytotoxic CD4+ subset proliferated in blood in response to PD-1 blockade but was separately regulated by the killer cell lectin-like receptor G1 (KLRG1), which inhibited their killing by interacting with E-cadherin. Conversely, a clonally related, GZMK-expressing circulating CD4+ population demonstrated basal proliferation and a memory phenotype that may result from activation of GZMB+ cells, but was not directly mobilized by PD-1 blockade. As KLRG1 marked the majority of circulating tumor-TCR-matched cytotoxic CD4+ T cells, this work nominates KLRG1 as a means to isolate them from blood and provide a window into intratumoral CD4+ recognition, as well as a putative regulatory receptor to mobilize the cytolytic GZMB+ subset for therapeutic benefit. Our findings also underscore ontogenic relationships of GZMB- and GZMK-expressing populations and the distinct cues that regulate their activity.

Although antibody sequences are highly diverse, they are constrained by requirements for expression and limited off-target reactivity. Describing which sequences violate such constraints has proven to be difficult. Here, we introduce a machine-learning framework to leverage a previously underutilized source of data for this problem. We use human single-cell sequencing data to find instances of allelic inclusion, a rare event where B cells express two different antibody light chains as mRNA. Previous studies suggest that one of these chains is either autoreactive or non-expressing as protein. We train machine-learning models to identify abnormal sequences associated with allelic inclusion. The resulting models generalize to predict antibody properties including polyreactivity, surface expression, and mutation usage, outperforming methods that do not use allelic inclusion data. We also investigate similar selection forces on the heavy chain in mice and observe that surrogate light-chain pairing has a large impact on heavy-chain diversity.

Sjögren's disease (SjD) is a heterogeneous autoimmune disorder with significant clinical and molecular diversity. While anti-SSA antibodies serve as a hallmark serological biomarker, nearly half of patients lack them, raising fundamental questions about distinct pathogenic mechanisms. To address this, we performed single-cell RNA sequencing with surface protein profiling on 1.5 million PBMCs from 333 participants in the Sjögren's International Collaborative Clinical Alliance cohort, comparing those with and without SjD and stratifying them by anti-SSA status. Our analysis identified two immunologically distinct subtypes of SjD, with SSA-positive patients exhibiting a dominant and persistent IFN-I signature, profoundly impacting immune cell maturation. Notably, transitional B cells were disproportionately affected, displaying signs of premature maturation, reduced BCR diversity, and shorter CDR3 regions, reinforced interactions with proinflammatory cells, thereby fostering an environment conducive to autoreactivity. By contrast, SSA-negative SjD participants lacked an upregulated IFN-I signature, challenging prevailing pathogenic models and suggesting alternative immune dysregulation pathways. These findings support a two-disease model of SjD and highlight transitional B cells as both a key biomarker and a potential therapeutic target. Targeting IFN-I signaling and transitional B cell maturation may represent a novel therapeutic avenue to modulate immune dysregulation and prevent autoreactivity in SjD. ### Competing Interest Statement C.J.Y. is founder for and holds equity in DropPrint Genomics (now ImmunAI) and Survey Genomics; a Scientific Advisory Board member for and holds equity in Related Sciences and ImmunAI; and a consultant for and holds equity in Maze Therapeutics. C.J.Y. has received research support from the Chan Zuckerberg Initiative, Chan Zuckerberg Biohub, Arc Institute, Parker Institute for Cancer Immunotherapy, Genentech, BioLegend, ScaleBio, and Illumina.

In the general population, aging is associated with an increase in systemic inflammation and chronic disease burden. However, in systemic lupus erythematosus (SLE), older age is uniquely associated with a decrease in disease activity, suggesting a distinct relationship between aging and inflammation. Using a multiomic approach, we compared aging-related changes in the peripheral blood immune profiles of 287 patients with SLE and 928 healthy controls. In patients with SLE, aging correlated with lower expression of interferon (IFN)–stimulated genes (ISGs) across multiple cell types, decreased plasma IFN-α2, and differential genome methylation. Both patients with SLE and controls demonstrated age-related declines in naïve T cells, but only patients with SLE exhibited increases in CD56 dim natural killer cells with older age. Of the genes both down-regulated and hypermethylated with older age, ISGs were disproportionately represented, suggesting a role for epigenetic silencing. Altogether, we found that patients with SLE exhibit unique aging-related decreases in IFN signaling that correlate with improved disease activity.

In the general human population, aging is associated with a rise in systemic inflammation, primarily involving innate immune pathways related to interferon (IFN), toll-like receptor, and cytokine signaling. In systemic lupus erythematosus (SLE), a prototypical systemic autoimmune disease, aging is distinctly associated with improvements in disease activity, suggesting a unique relationship between aging and inflammation in this disease. Using a multi-omic approach incorporating transcriptional profiling, single cell RNA sequencing, proteomics and methylation analysis, we studied age-related changes in the immune profiles of 287 SLE patients between 20 and 83 years old, and compared the results against 928 healthy controls aged between 21 and 89 years old. In contrast to the increase in inflammatory gene expression that occurs with aging in most healthy adults, SLE patients exhibited the opposite. Most notable was a decrease in type I IFN signaling that was evident across multiple cell types, with CD56-dim natural killer (NK) cells, CD4 + effector memory T cells, and naïve B cells exhibiting the most significant differences. We found that aging in SLE patients was also associated with decreased IFN-α2 and IFN-λ1 levels, and differential methylation of the genome. Notably, of the genes both downregulated and hypermethylated with older age, IFN-related genes were disproportionately represented, suggesting that age-related decreases in IFN signaling were driven in part by epigenetic silencing. Both SLE patients and healthy controls demonstrated age-related declines in naïve T cells and lymphoid progenitor cells, but only SLE patients demonstrated age-related increases in CD56-dim NK cells. Taken together, our work provides new insight into the phenomenon of inflammaging and the unique clinical improvement in disease activity that occurs in SLE patients as they age.

A20, encoded by the TNFAIP3 gene, is a protein linked to Crohn's disease and celiac disease in humans. We now find that mice expressing point mutations in A20's M1 ubiquitin binding motif (ZF7) spontaneously develop proximate enteritis that requires both luminal microbes and T cells. Cellular and transcriptomic profiling reveal expansion of TH17/22 cells and aberrant expression of IL-17A and IL-22 in intestinal lamina propria of A20ZF7 mice. While deletion of IL-17A from A20ZF7/ZF7 mice exacerbates enteritis, deletion of IL-22 abrogates intestinal epithelial cell hyperproliferation, barrier dysfunction, and alarmin expression. A20ZF7/ZF7 TH17/22 cells autonomously express more RORγt and IL-22 after differentiation in vitro. ATAC sequencing identified an enhancer region upstream of the Il22 gene in A20ZF7/ZF7 T cells, and this enhancer demonstrated increased activating histone acetylation coupled with exaggerated Il22 transcription. Finally, CRISPR/Cas9-mediated ablation of A20ZF7 in human T cells increases RORγt expression and IL22 transcription. These studies link A20's M1 ubiquitin binding function with RORγt expression, epigenetic activation of TH17/22 cells, and IL-22 driven enteritis. ### Competing Interest Statement The authors have declared no competing interest.

A20, encoded by the TNFAIP3 gene, is a protein linked to Crohn's disease and celiac disease in humans. We now find that mice expressing point mutations in A20's M1-ubiquitin-binding zinc finger 7 (ZF7) motif spontaneously develop proximal enteritis that requires both luminal microbes and T cells. Cellular and transcriptomic profiling reveals expansion of Th17 cells and exuberant expression of IL-17A and IL-22 in intestinal lamina propria of A20ZF7 mice. While deletion of IL-17A from A20ZF7/ZF7 mice exacerbates enteritis, deletion of IL-22 abrogates intestinal epithelial cell hyperproliferation, barrier dysfunction, and alarmin expression. Colonization of adult germ-free mice with microbiota from adult WT specific pathogen-free mice drives duodenal IL-22 expression and duodenitis. A20ZF7/ZF7 Th17 cells autonomously express more RORγt and IL-22 after differentiation in vitro. ATAC sequencing identified an enhancer region upstream of the Il22 gene, and this enhancer demonstrated increased activating histone acetylation coupled with exaggerated Il22 transcription in A20ZF7/ZF7 T cells. Acute inhibition of RORγt normalized histone acetylation at this enhancer. Finally, CRISPR/Cas9-mediated ablation of A20ZF7 in human T cells increases RORγt expression and IL22 transcription. These studies link A20's M1-ubiquitin binding function with RORγt expression, expansion of Th17 cells, and epigenetic activation of IL-22-driven enteritis.

Cis-regulatory elements (CREs) interact with trans regulators to orchestrate gene expression, but how transcriptional regulation is coordinated in multi-gene loci has not been experimentally defined. We sought to characterize the CREs controlling dynamic expression of the adjacent costimulatory genes CD28, CTLA4 and ICOS, encoding regulators of T cell-mediated immunity. Tiling CRISPR interference (CRISPRi) screens in primary human T cells, both conventional and regulatory subsets, uncovered gene-, cell subset- and stimulation-specific CREs. Integration with CRISPR knockout screens and assay for transposase-accessible chromatin with sequencing (ATAC-seq) profiling identified trans regulators influencing chromatin states at specific CRISPRi-responsive elements to control costimulatory gene expression. We then discovered a critical CCCTC-binding factor (CTCF) boundary that reinforces CRE interaction with CTLA4 while also preventing promiscuous activation of CD28. By systematically mapping CREs and associated trans regulators directly in primary human T cell subsets, this work overcomes longstanding experimental limitations to decode context-dependent gene regulatory programs in a complex, multi-gene locus critical to immune homeostasis.

Rheumatoid arthritis (RA) management leans toward achieving remission or low disease activity. In this study, we conducted single-cell RNA sequencing (scRNA-Seq) of peripheral blood mononuclear cells (PBMCs) from 36 individuals (18 patients with RA and 18 matched controls, accounting for age, sex, race, and ethnicity), to identify disease-relevant cell subsets and cell type-specific signatures associated with disease activity. Our analysis revealed 18 distinct PBMC subsets, including an IFN-induced transmembrane 3-overexpressing (IFITM3-overexpressing) IFN-activated monocyte subset. We observed an increase in CD4+ T effector memory cells in patients with moderate-high disease activity (DAS28-CRP ≥ 3.2) and a decrease in nonclassical monocytes in patients with low disease activity or remission (DAS28-CRP < 3.2). Pseudobulk analysis by cell type identified 168 differentially expressed genes between RA and matched controls, with a downregulation of proinflammatory genes in the γδ T cell subset, alteration of genes associated with RA predisposition in the IFN-activated subset, and nonclassical monocytes. Additionally, we identified a gene signature associated with moderate-high disease activity, characterized by upregulation of proinflammatory genes such as TNF, JUN, EGR1, IFIT2, MAFB, and G0S2 and downregulation of genes including HLA-DQB1, HLA-DRB5, and TNFSF13B. Notably, cell-cell communication analysis revealed an upregulation of signaling pathways, including VISTA, in both moderate-high and remission-low disease activity contexts. Our findings provide valuable insights into the systemic cellular and molecular mechanisms underlying RA disease activity.

The relationship between genetic variation and gene expression in brain cell types and subtypes remains understudied. Here, we generated single-nucleus RNA sequencing data from the neocortex of 424 individuals of advanced age; we assessed the effect of genetic variants on RNA expression in cis ( cis -expression quantitative trait loci) for seven cell types and 64 cell subtypes using 1.5 million transcriptomes. This effort identified 10,004 eGenes at the cell type level and 8,099 eGenes at the cell subtype level. Many eGenes are only detected within cell subtypes. A new variant influences APOE expression only in microglia and is associated with greater cerebral amyloid angiopathy but not Alzheimer’s disease pathology, after adjusting for APOEε4 , providing mechanistic insights into both pathologies. Furthermore, only a TMEM106B variant affects the proportion of cell subtypes. Integration of these results with genome-wide association studies highlighted the targeted cell type and probable causal gene within Alzheimer’s disease, schizophrenia, educational attainment and Parkinson’s disease loci.

Differential expression analysis of single-cell RNA sequencing (scRNA-seq) data is central for characterizing how experimental factors affect the distribution of gene expression. However, distinguishing between biological and technical sources of cell-cell variability and assessing the statistical significance of quantitative comparisons between cell groups remain challenging. We introduce Memento, a tool for robust and efficient differential analysis of mean expression, variability, and gene correlation from scRNA-seq data, scalable to millions of cells and thousands of samples. We applied Memento to 70,000 tracheal epithelial cells to identify interferon-responsive genes, 160,000 CRISPR-Cas9 perturbed T cells to reconstruct gene-regulatory networks, 1.2 million peripheral blood mononuclear cells (PBMCs) to map cell-type-specific quantitative trait loci (QTLs), and the 50-million-cell CELLxGENE Discover corpus to compare arbitrary cell groups. In all cases, Memento identified more significant and reproducible differences in mean expression compared with existing methods. It also identified differences in variability and gene correlation that suggest distinct transcriptional regulation mechanisms imparted by perturbations.

Population-scale single-cell genomics is a transformative approach for unraveling the intricate links between genetic and cellular variation. This approach is facilitated by cutting-edge experimental methodologies, including the development of high-throughput single-cell multiomics and advances in multiplexed environmental and genetic perturbations. Examining the effects of natural or synthetic genetic variants across cellular contexts provides insights into the mutual influence of genetics and the environment in shaping cellular heterogeneity. The development of computational methodologies further enables detailed quantitative analysis of molecular variation, offering an opportunity to examine the respective roles of stochastic, intercellular, and interindividual variation. Future opportunities lie in leveraging long-read sequencing, refining disease-relevant cellular models, and embracing predictive and generative machine learning models. These advancements hold the potential for a deeper understanding of the genetic architecture of human molecular traits, which in turn has important implications for understanding the genetic causes of human disease. Expected final online publication date for the Annual Review of Genomics and Human Genetics, Volume 25 is August 2024. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.