Demuxafy: improvement in droplet assignment by integrating multiple single-cell demultiplexing and doublet detection methods.

Recent innovations in single-cell RNA-sequencing (scRNA-seq) provide the technology to investigate biological questions at cellular resolution. Pooling cells from multiple individuals has become a common strategy, and droplets can subsequently be assigned to a specific individual by leveraging their inherent genetic differences. An implicit challenge with scRNA-seq is the occurrence of doublets-droplets containing two or more cells. We develop Demuxafy, a framework to enhance donor assignment and doublet removal through the consensus intersection of multiple demultiplexing and doublet detecting methods. Demuxafy significantly improves droplet assignment by separating singlets from doublets and classifying the correct individual.

CD4+ CAR-T cell exhaustion associated with early relapse of multiple myeloma after BCMA CAR-T cell therapy.

Multiple myeloma is characterized by frequent clinical relapses following conventional therapy. Recently, chimeric antigen receptor T (CAR-T) cells targeting B-cell maturation antigen (BCMA) has been established as a treatment option for patients with relapsed or refractory disease. However, while >70% of patients initially respond to this treatment, clinical relapse and disease progression occur in most cases. Recent studies showed persistent expression of BCMA at the time of relapse, indicating that immune intrinsic mechanisms may contribute to this resistance. While there were no pre-existing T cell features associated with clinical outcomes, we found that patients with a durable response to CAR-T cell treatment had greater persistence of their CAR-T cells compared to patients with transient clinical responses. They also possessed a significantly higher proportion of CD8+ T effector memory cells. In contrast, patients with short-lived responses to treatment have increased frequencies of cytotoxic CD4+ CAR-T cells. These cells expand in vivo early after infusion but express exhaustion markers (HAVCR2 and TIGIT) and remain polyclonal. Finally, we demonstrate that non-classical monocytes are enriched in the myeloma niche and may induce CAR-T cell dysfunction through mechanisms that include TGFß. These findings shed new light on the role of cytotoxic CD4+ T cells in disease progression after CAR-T cell therapy.

Cell subtype-specific effects of genetic variation in the Alzheimer's disease brain.

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.

SingleQ: a comprehensive database of single-cell expression quantitative trait loci (sc-eQTLs) cross human tissues.

Mapping of expression quantitative trait loci (eQTLs) and other molecular QTLs can help characterize the modes of action of disease-associated genetic variants. However, current eQTL databases present data from bulk RNA-seq approaches, which cannot shed light on the cell type- and environment-specific regulation of disease-associated genetic variants. Here, we introduce our Single-cell eQTL Interactive Database which collects single-cell eQTL (sc-eQTL) datasets and provides online visualization of sc-eQTLs across different cell types in a user-friendly manner. Although sc-eQTL mapping is still in its early stage, our database curates the most comprehensive summary statistics of sc-eQTLs published to date. sc-eQTL studies have revolutionized our understanding of gene regulation in specific cellular contexts, and we anticipate that our database will further accelerate the research of functional genomics. Database URL: http://www.sqraolab.com/scqtl.

Functional genomics in inborn errors of immunity.

Inborn errors of immunity (IEI) comprise a diverse spectrum of 485 disorders as recognized by the International Union of Immunological Societies Committee on Inborn Error of Immunity in 2022. While IEI are monogenic by definition, they illuminate various pathways involved in the pathogenesis of polygenic immune dysregulation as in autoimmune or autoinflammatory syndromes, or in more common infectious diseases that may not have a significant genetic basis. Rapid improvement in genomic technologies has been the main driver of the accelerated rate of discovery of IEI and has led to the development of innovative treatment strategies. In this review, we will explore various facets of IEI, delving into the distinctions between PIDD and PIRD. We will examine how Mendelian inheritance patterns contribute to these disorders and discuss advancements in functional genomics that aid in characterizing new IEI. Additionally, we will explore how emerging genomic tools help to characterize new IEI as well as how they are paving the way for innovative treatment approaches for managing and potentially curing these complex immune conditions.

Population Diversity at the Single-Cell Level.

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.

SURGE: uncovering context-specific genetic-regulation of gene expression from single-cell RNA sequencing using latent-factor models.

Genetic regulation of gene expression is a complex process, with genetic effects known to vary across cellular contexts such as cell types and environmental conditions. We developed SURGE, a method for unsupervised discovery of context-specific expression quantitative trait loci (eQTLs) from single-cell transcriptomic data. This allows discovery of the contexts or cell types modulating genetic regulation without prior knowledge. Applied to peripheral blood single-cell eQTL data, SURGE contexts capture continuous representations of distinct cell types and groupings of biologically related cell types. We demonstrate the disease-relevance of SURGE context-specific eQTLs using colocalization analysis and stratified LD-score regression.

Base-editing mutagenesis maps alleles to tune human T cell functions.

CRISPR-enabled screening is a powerful tool for the discovery of genes that control T cell function and has nominated candidate targets for immunotherapies1-6. However, new approaches are required to probe specific nucleotide sequences within key genes. Systematic mutagenesis in primary human T cells could reveal alleles that tune specific phenotypes. DNA base editors are powerful tools for introducing targeted mutations with high efficiency7,8. Here we develop a large-scale base-editing mutagenesis platform with the goal of pinpointing nucleotides that encode amino acid residues that tune primary human T cell activation responses. We generated a library of around 117,000 single guide RNA molecules targeting base editors to protein-coding sites across 385 genes implicated in T cell function and systematically identified protein domains and specific amino acid residues that regulate T cell activation and cytokine production. We found a broad spectrum of alleles with variants encoding critical residues in proteins including PIK3CD, VAV1, LCP2, PLCG1 and DGKZ, including both gain-of-function and loss-of-function mutations. We validated the functional effects of many alleles and further demonstrated that base-editing hits could positively and negatively tune T cell cytotoxic function. Finally, higher-resolution screening using a base editor with relaxed protospacer-adjacent motif requirements9 (NG versus NGG) revealed specific structural domains and protein-protein interaction sites that can be targeted to tune T cell functions. Base-editing screens in primary immune cells thus provide biochemical insights with the potential to accelerate immunotherapy design.

ADPKD-Causing Missense Variants in Polycystin-1 Disrupt Cell Surface Localization or Polycystin Channel Function.

Autosomal dominant polycystic kidney disease (ADPKD) is the leading monogenic cause of kidney failure and affects millions of people worldwide. Despite the prevalence of this monogenic disorder, our limited mechanistic understanding of ADPKD has hindered therapeutic development. Here, we successfully developed bioassays that functionally classify missense variants in polycystin-1 (PC1). Strikingly, ADPKD pathogenic missense variants cluster into two major categories: 1) those that disrupt polycystin cell surface localization or 2) those that attenuate polycystin ion channel activity. We found that polycystin channels with defective surface localization could be rescued with a small molecule. We propose that small-molecule-based strategies to improve polycystin cell surface localization and channel function will be effective therapies for ADPKD patients.

Coordinated immune dysregulation in Juvenile Dermatomyositis revealed by single-cell genomics.

Juvenile Dermatomyositis (JDM) is one of several childhood-onset autoimmune disorders characterized by a type I interferon response and autoantibodies. Treatment options are limited due to incomplete understanding of how the disease emerges from dysregulated cell states across the immune system. We therefore investigated the blood of JDM patients 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 towards an immature naive state as a hallmark of JDM. Furthermore, we find that these changes in B cells are paralleled by signatures of Th2-mediated inflammation. Additionally, our work identified SIGLEC-1 expression in monocytes as a composite measure of heterogeneous type I interferon activity in disease. We applied network analysis to reveal that hyperactivation of the type I interferon response in all immune populations is coordinated with dysfunctional protein processing and regulation of cell death programming. This analysis separated the ubiquitously expressed type I interferon response into a central hub and revealed previously masked cell states. Together, these findings reveal the coordinated immune dysregulation underpinning JDM and provide novel insight into strategies for restoring balance in immune function.

Systematic functional interrogation of SARS-CoV-2 host factors using Perturb-seq.

Genomic and proteomic screens have identified numerous host factors of SARS-CoV-2, but efficient delineation of their molecular roles during infection remains a challenge. Here we use Perturb-seq, combining genetic perturbations with a single-cell readout, to investigate how inactivation of host factors changes the course of SARS-CoV-2 infection and the host response in human lung epithelial cells. Our high-dimensional data resolve complex phenotypes such as shifts in the stages of infection and modulations of the interferon response. However, only a small percentage of host factors showed such phenotypes upon perturbation. We further identified the NF-κB inhibitor IκBα (NFKBIA), as well as the translation factors EIF4E2 and EIF4H as strong host dependency factors acting early in infection. Overall, our study provides massively parallel functional characterization of host factors of SARS-CoV-2 and quantitatively defines their roles both in virus-infected and bystander cells.

Mitigation of chromosome loss in clinical CRISPR-Cas9-engineered T cells.

CRISPR-Cas9 genome editing has enabled advanced T cell therapies, but occasional loss of the targeted chromosome remains a safety concern. To investigate whether Cas9-induced chromosome loss is a universal phenomenon and evaluate its clinical significance, we conducted a systematic analysis in primary human T cells. Arrayed and pooled CRISPR screens revealed that chromosome loss was generalizable across the genome and resulted in partial and entire loss of the targeted chromosome, including in preclinical chimeric antigen receptor T cells. T cells with chromosome loss persisted for weeks in culture, implying the potential to interfere with clinical use. A modified cell manufacturing process, employed in our first-in-human clinical trial of Cas9-engineered T cells (NCT03399448), reduced chromosome loss while largely preserving genome editing efficacy. Expression of p53 correlated with protection from chromosome loss observed in this protocol, suggesting both a mechanism and strategy for T cell engineering that mitigates this genotoxicity in the clinic.

A myeloid program associated with COVID-19 severity is decreased by therapeutic blockade of IL-6 signaling.

Altered myeloid inflammation and lymphopenia are hallmarks of severe infections. We identified the upregulated EN-RAGE gene program in airway and blood myeloid cells from patients with acute lung injury from SARS-CoV-2 or other causes across 7 cohorts. This program was associated with greater clinical severity and predicted future mechanical ventilation and death. EN-RAGEhi myeloid cells express features consistent with suppressor cell functionality, including low HLA-DR and high PD-L1. Sustained EN-RAGE program expression in airway and blood myeloid cells correlated with clinical severity and increasing expression of T cell dysfunction markers. IL-6 upregulated many EN-RAGE program genes in monocytes in vitro. IL-6 signaling blockade by tocilizumab in a placebo-controlled clinical trial led to rapid normalization of EN-RAGE and T cell gene expression. This identifies IL-6 as a key driver of myeloid dysregulation associated with worse clinical outcomes in COVID-19 patients and provides insights into shared pathophysiological mechanisms in non-COVID-19 ARDS.

Functional characterization of Alzheimer's disease genetic variants in microglia.

Candidate cis-regulatory elements (cCREs) in microglia demonstrate the most substantial enrichment for Alzheimer's disease (AD) heritability compared to other brain cell types. However, whether and how these genome-wide association studies (GWAS) variants contribute to AD remain elusive. Here we prioritize 308 previously unreported AD risk variants at 181 cCREs by integrating genetic information with microglia-specific 3D epigenome annotation. We further establish the link between functional variants and target genes by single-cell CRISPRi screening in microglia. In addition, we show that AD variants exhibit allelic imbalance on target gene expression. In particular, rs7922621 is the effective variant in controlling TSPAN14 expression among other nominated variants in the same cCRE and exerts multiple physiological effects including reduced cell surface ADAM10 and altered soluble TREM2 (sTREM2) shedding. Our work represents a systematic approach to prioritize and characterize AD-associated variants and provides a roadmap for advancing genetic association to experimentally validated cell-type-specific phenotypes and mechanisms.

Genome-wide prediction of disease variant effects with a deep protein language model.

Predicting the effects of coding variants is a major challenge. While recent deep-learning models have improved variant effect prediction accuracy, they cannot analyze all coding variants due to dependency on close homologs or software limitations. Here we developed a workflow using ESM1b, a 650-million-parameter protein language model, to predict all ~450 million possible missense variant effects in the human genome, and made all predictions available on a web portal. ESM1b outperformed existing methods in classifying ~150,000 ClinVar/HGMD missense variants as pathogenic or benign and predicting measurements across 28 deep mutational scan datasets. We further annotated ~2 million variants as damaging only in specific protein isoforms, demonstrating the importance of considering all isoforms when predicting variant effects. Our approach also generalizes to more complex coding variants such as in-frame indels and stop-gains. Together, these results establish protein language models as an effective, accurate and general approach to predicting variant effects.

Reply to Barton et al: signatures of natural selection during the Black Death.

Barton et al.1 raise several statistical concerns regarding our original analyses2 that highlight the challenge of inferring natural selection using ancient genomic data. We show here that these concerns have limited impact on our original conclusions. Specifically, we recover the same signature of enrichment for high FST values at the immune loci relative to putatively neutral sites after switching the allele frequency estimation method to a maximum likelihood approach, filtering to only consider known human variants, and down-sampling our data to the same mean coverage across sites. Furthermore, using permutations, we show that the rs2549794 variant near ERAP2 continues to emerge as the strongest candidate for selection (p = 1.2×10-5), falling below the Bonferroni-corrected significance threshold recommended by Barton et al. Importantly, the evidence for selection on ERAP2 is further supported by functional data demonstrating the impact of the ERAP2 genotype on the immune response to Y. pestis and by epidemiological data from an independent group showing that the putatively selected allele during the Black Death protects against severe respiratory infection in contemporary populations.

Mitigation of chromosome loss in clinical CRISPR-Cas9-engineered T cells.

CRISPR-Cas9 genome editing has enabled advanced T cell therapies, but occasional loss of the targeted chromosome remains a safety concern. To investigate whether Cas9-induced chromosome loss is a universal phenomenon and evaluate its clinical significance, we conducted a systematic analysis in primary human T cells. Arrayed and pooled CRISPR screens revealed that chromosome loss was generalizable across the genome and resulted in partial and entire loss of the chromosome, including in pre-clinical chimeric antigen receptor T cells. T cells with chromosome loss persisted for weeks in culture, implying the potential to interfere with clinical use. A modified cell manufacturing process, employed in our first-in-human clinical trial of Cas9-engineered T cells, 1 dramatically reduced chromosome loss while largely preserving genome editing efficacy. Expression of p53 correlated with protection from chromosome loss observed in this protocol, suggesting both a mechanism and strategy for T cell engineering that mitigates this genotoxicity in the clinic.

Pooled screening of CAR T cells identifies diverse immune signaling domains for next-generation immunotherapies.

Chimeric antigen receptors (CARs) repurpose natural signaling components to retarget T cells to refractory cancers but have shown limited efficacy in persistent, recurrent malignancies. Here, we introduce "CAR Pooling," a multiplexed approach to rapidly identify CAR designs with clinical potential. Forty CARs with signaling domains derived from a range of immune cell lineages were evaluated in pooled assays for their ability to stimulate critical T cell effector functions during repetitive stimulation that mimics long-term tumor antigen exposure. Several domains were identified from the tumor necrosis factor (TNF) receptor family that have been primarily associated with B cells. CD40 enhanced proliferation, whereas B cell-activating factor receptor (BAFF-R) and transmembrane activator and CAML interactor (TACI) promoted cytotoxicity. These functions were enhanced relative to clinical benchmarks after prolonged antigen stimulation, and CAR T cell signaling through these domains fell into distinct states of memory, cytotoxicity, and metabolism. BAFF-R CAR T cells were enriched for a highly cytotoxic transcriptional signature previously associated with positive clinical outcomes. We also observed that replacing the 4-1BB intracellular signaling domain with the BAFF-R signaling domain in a clinically validated B cell maturation antigen (BCMA)-specific CAR resulted in enhanced activity in a xenotransplant model of multiple myeloma. Together, these results show that CAR Pooling is a general approach for rapid exploration of CAR architecture and activity to improve the efficacy of CAR T cell therapies.

Evolution of immune genes is associated with the Black Death.

Infectious diseases are among the strongest selective pressures driving human evolution1,2. This includes the single greatest mortality event in recorded history, the first outbreak of the second pandemic of plague, commonly called the Black Death, which was caused by the bacterium Yersinia pestis3. This pandemic devastated Afro-Eurasia, killing up to 30-50% of the population4. To identify loci that may have been under selection during the Black Death, we characterized genetic variation around immune-related genes from 206 ancient DNA extracts, stemming from two different European populations before, during and after the Black Death. Immune loci are strongly enriched for highly differentiated sites relative to a set of non-immune loci, suggesting positive selection. We identify 245 variants that are highly differentiated within the London dataset, four of which were replicated in an independent cohort from Denmark, and represent the strongest candidates for positive selection. The selected allele for one of these variants, rs2549794, is associated with the production of a full-length (versus truncated) ERAP2 transcript, variation in cytokine response to Y. pestis and increased ability to control intracellular Y. pestis in macrophages. Finally, we show that protective variants overlap with alleles that are today associated with increased susceptibility to autoimmune diseases, providing empirical evidence for the role played by past pandemics in shaping present-day susceptibility to disease.