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.

Differential expression analysis of scRNA-seq data is central for characterizing how experimental factors affect the distribution of gene expression. However, it remains challenging to distinguish biological and technical sources of cell-cell variability and to assess the statistical significance of quantitative comparisons between groups of cells. We introduce memento to address these limitations and enable accurate and efficient differential expression analysis of the mean, variability, and gene correlation from scRNA-seq. We used memento to analyze 70,000 tracheal epithelial cells to identify interferon response genes with distinct variability and correlation patterns, 160,000 T cells perturbed with CRISPR-Cas9 to reconstruct gene-regulatory networks that control T cell activation, and 1.2 million PMBCs to map cell-type-specific cis expression quantitative trait loci (eQTLs). In all cases, memento identified more significant and reproducible differences in mean expression but also identified differences in variability and gene correlation that suggest distinct modes of transcriptional regulation imparted by cytokines, genetic perturbations, and natural genetic variation. These results demonstrate memento as a first-in-class method for the quantitative comparisons of scRNA-seq data scalable to millions of cells and thousands of samples.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Human regulatory T (T-reg) cells are essential for immune homeostasis. The transcription factor FOXP3 maintains T-reg cell identity, yet the complete set of key transcription factors that control T-reg cell gene expression remains unknown. Here, we used pooled and arrayed Cas9 ribonucleoprotein screens to identify transcription factors that regulate critical proteins in primary human T-reg cells under basal and proinflammatory conditions. We then generated 54,424 single-cell transcriptomes from T-reg cells subjected to genetic perturbations and cytokine stimulation, which revealed distinct gene networks individually regulated by FOXP3 and PRDM1, in addition to a network coregulated by FOXO1 and IRF4. We also discovered that HIVEP2, to our knowledge not previously implicated in T(reg)cell function, coregulates another gene network with SATB1 and is important for T-reg cell-mediated immunosuppression. By integrating CRISPR screens and single-cell RNA-sequencing profiling, we have uncovered transcriptional regulators and downstream gene networks in human T-reg cells that could be targeted for immunotherapies.

Genetic multiplexing of barcoded single cell RNA-seq Introduction demuxlet is a software tool to deconvolute sample identity and identify multiplets when multiple samples are pooled by barcoded single cell sequencing.demuxlet takes (1) a SAM/BAM/CRAM file produced by the standard 10x sequencing platform, or any other barcoded single cell RNA-seq (with proper --tag-UMI and --tag-group) options (2) a VCF/BCF file containing the genotype (GT), posterior probability (GP), or genotype likelihood (GL) to assign each barcode to a specific sample (or a pair of samples) in the VCF file. Tutorial for demuxlet This tutorial provides streamlined instructions for using the tool demuxlet. For a more detailed description of all of the options available to use with demuxlet, please refer to the README (attached in .zip file). demuxlet has several dependencies and this tutorial provides steps to use a docker instance to minimize compatibility issues and an alternative of installing demuxlet from source. demuxlet is a software tool to deconvolute sample identity and identify multiplets when multiple samples are pooled by barcoded single cell sequencing. demuxlet requires the following input files: a SAM/BAM/CRAM file produced by the standard 10x sequencing platform, or any other barcoded single cell RNA-seq (with proper --tag-UMI and --tag-group) options. a VCF/BCF file containing the genotype (GT), posterior probability (GP), or genotype likelihood (GL) to assign each barcode to a specific sample (or a pair of samples) in the VCF file.

Gene regulatory programs controlling the activation and polarization of CD4 + T cells are incompletely mapped and the interindividual variability in these programs remain unknown. We sequenced the transcriptomes of ~160k CD4 + T cells from 9 donors following pooled CRISPR perturbation targeting 140 regulators. We identified 134 regulators that affect T cell functionalization, including IRF2 as a positive regulator of Th 2 polarization. Leveraging correlation patterns between cells, we mapped 194 pairs of interacting regulators, including known (e.g. BATF and JUN ) and novel interactions (e.g. ETS1 and STAT6 ). Finally, we identified 80 natural genetic variants with effects on gene expression, 48 of which are modified by a perturbation. In CD4 + T cells, CRISPR perturbations can influence in vitro polarization and modify the effects of trans and cis regulatory elements on gene expression.

Kv7 (KCNQ) voltage-gated potassium channels control excitability in the brain, heart, and ear. Calmodulin (CaM) is crucial for Kv7 function, but how this calcium sensor affects activity has remained unclear. Here, we present X-ray crystallographic analysis of CaM: Kv7.4 and CaM: Kv7.5 AB domain complexes that reveal an Apo/CaM clamp conformation and calcium binding preferences. These structures, combined with small-angle X-ray scattering, biochemical, and functional studies, establish a regulatory mechanism for Kv7 CaM modulation based on a common architecture in which a CaM C-lobe calcium-dependent switch releases a shared Apo/CaM clamp conformation. This C-lobe switch inhibits voltage dependent activation of Kv7.4 and Kv7.5 but facilitates Kv7.1, demonstrating that mechanism is shared by Kv7 isoforms despite the different directions of CaM modulation. Our findings provide a unified framework for understanding how CaM controls different Kv7 isoforms and highlight the role of membrane proximal domains for controlling voltage-gated channel function.

In this Letter, analysis of steady-state regulatory T (Treg) cell percentages from Il2ra enhancer deletion (EDEL) and wild-type (WT) mice revealed no differences between them (Extended Data Fig. 9d). This analysis included two mice whose genotypes were incorrectly assigned. Even after correction of the genotypes, no significant differences in Treg cell percentages were seen when data across experimental cohorts were averaged (as was done in Extended Data Fig. 9d). However, if we normalize the corrected data to account for variation among experimental cohorts, a subtle decrease in EDEL Treg cell percentages is revealed and, using the corrected and normalized data, we have redrawn Extended Data Fig. 9d in Supplementary Fig. 1. The Supplementary Information to this Amendment contains the corrected and reanalysed Extended Data Fig. 9d. The sentence "This enhancer deletion (EDEL) strain also had no obvious T cell phenotypes at steady state (Extended Data Fig. 9)." should read: "This enhancer deletion (EDEL) strain had a small decrease in the percentage of Treg cells (Extended Data Fig. 9).". This error does not affect any of the main figures in the Letter or the data from mice with the human autoimmune-associated single nucleotide polymorphism (SNP) knocked in or with a 12-base-pair deletion at the site (12DEL). In addition, we stated in the Methods that we observed consistent immunophenotypes of EDEL mice across three founders, but in fact, we observed consistent phenotypes in mice from two founders. This does not change any of our conclusions and the original Letter has not been corrected.

While genetic variants are known to be associated with overall gene abundance in stimulated immune cells, less is known about their effects on alternative isoform usage. By analyzing RNA-seq profiles of monocyte-derived dendritic cells from 243 individuals, we uncovered thousands of unannotated isoforms synthesized in response to influenza infection and type 1 interferon stimulation. We identified more than a thousand quantitative trait loci (QTLs) associated with alternate isoform usage (isoQTLs), many of which are independent of expression QTLs (eQTLs) for the same gene. Compared with eQTLs, isoQTLs are enriched for splice sites and untranslated regions, but depleted of sequences upstream of annotated transcription start sites. Both eQTLs and isoQTLs explain a significant proportion of the disease heritability attributed to common genetic variants. At the ERAP2 locus, we shed light on the function of the gene and how two frequent, highly differentiated haplotypes with intermediate frequencies could be maintained by balancing selection. At baseline and following type 1 interferon stimulation, the major haplotype is associated with low ERAP2 expression caused by nonsense-mediated decay, while the minor haplotype, known to increase Crohn's disease risk, is associated with high ERAP2 expression. In response to influenza infection, we found two uncharacterized isoforms expressed from the major haplotype, likely the result of multiple perfectly linked variants affecting the transcription and splicing at the locus. Thus, genetic variants at a single locus could modulate independent gene regulatory processes in innate immune responses and, in the case of ERAP2, may confer a historical fitness advantage in response to virus.

Over 90% of genetic variants associated with complex human traits map to non-coding regions, but little is understood about how they modulate gene regulation in health and disease. One possible mechanism is that genetic variants affect the activity of one or more cis-regulatory elements leading to gene expression variation in specific cell types. To identify such cases, we analyzed ATAC-seq and RNA-seq profiles from stimulated primary CD4+ T cells in up to 105 healthy donors. We found that regions of accessible chromatin (ATAC-peaks) are co-accessible at kilobase and megabase resolution, consistent with the three-dimensional chromatin organization measured by in situ Hi-C in T cells. Fifteen percent of genetic variants located within ATAC-peaks affected the accessibility of the corresponding peak (local-ATAC-QTLs). Local-ATAC-QTLs have the largest effects on co-accessible peaks, are associated with gene expression and are enriched for autoimmune disease variants. Our results provide insights into how natural genetic variants modulate cis-regulatory elements, in isolation or in concert, to influence gene expression.

Immunotherapies with chimeric antigen receptor (CAR) T cells and checkpoint inhibitors (including antibodies that antagonize programmed cell death protein 1 [PD-1]) have both opened new avenues for cancer treatment, but the clinical potential of combined disruption of inhibitory checkpoints and CAR T cell therapy remains incompletely explored. Here we show that programmed death ligand 1 (PD-L1) expression on tumor cells can render human CAR T cells (anti-CD19 4-1BBζ) hypo-functional, resulting in impaired tumor clearance in a sub-cutaneous xenograft model. To overcome this suppressed anti-tumor response, we developed a protocol for combined Cas9 ribonucleoprotein (Cas9 RNP)-mediated gene editing and lentiviral transduction to generate PD-1 deficient anti-CD19 CAR T cells. Pdcd1 (PD-1) disruption augmented CAR T cell mediated killing of tumor cells in vitro and enhanced clearance of PD-L1+ tumor xenografts in vivo. This study demonstrates improved therapeutic efficacy of Cas9-edited CAR T cells and highlights the potential of precision genome engineering to enhance next-generation cell therapies.

Droplet-based single-cell RNA-sequencing (dscRNA-seq) has enabled rapid, massively parallel profiling of transcriptomes from tens of thousands of cells. Multiplexing samples for single cell capture and library preparation in dscRNA-seq would enable cost-effective designs of differential expression and genetic studies while avoiding technical batch effects, but its implementation remains challenging. Here, we introduce an in-silico algorithm demuxlet that harnesses natural genetic variation to discover the sample identity of each cell and identify droplets containing two cells. These capabilities enable multiplexed dscRNA-seq experiments where cells from unrelated individuals are pooled and captured at higher throughput than standard workflows. To demonstrate the performance of demuxlet, we sequenced 3 pools of peripheral blood mononuclear cells (PBMCs) from 8 lupus patients. Given genotyping data for each individual, demuxlet correctly recovered the sample identity of > 99% of singlets, and identified doublets at rates consistent with previous estimates. In PBMCs, we demonstrate the utility of multiplexed dscRNA-seq in two applications: characterizing cell type specificity and inter-individual variability of cytokine response from 8 lupus patients and mapping genetic variants associated with cell type specific gene expression from 23 donors. Demuxlet is fast, accurate, scalable and could be extended to other single cell datasets that incorporate natural or synthetic DNA barcodes.

Group 2 innate lymphoid cells (ILC2s) and CD4+ type 2 helper T cells (TH2 cells) are defined by their similar effector cytokines, which together mediate the features of allergic immunity. We found that tissue ILC2s and TH2 cells differentiated independently but shared overlapping effector function programs that were mediated by exposure to the tissue-derived cytokines interleukin 25 (IL-25), IL-33 and thymic stromal lymphopoietin (TSLP). Loss of these three tissue signals did not affect lymph node priming, but abrogated the terminal differentiation of effector TH2 cells and adaptive lung inflammation in a T cell-intrinsic manner. Our findings suggest a mechanism by which diverse perturbations can activate type 2 immunity and reveal a shared local-tissue-elicited checkpoint that can be exploited to control both innate and adaptive allergic inflammation.

Ubiquitin is essential for eukaryotic life and varies in only 3 amino acid positions between yeast and humans. However, recent deep sequencing studies indicate that ubiquitin is highly tolerant to single mutations. We hypothesized that this tolerance would be reduced by chemically induced physiologic perturbations. To test this hypothesis, a class of first year UCSF graduate students employed deep mutational scanning to determine the fitness landscape of all possible single residue mutations in the presence of five different small molecule perturbations. These perturbations uncover 'shared sensitized positions' localized to areas around the hydrophobic patch and the C-terminus. In addition, we identified perturbation specific effects such as a sensitization of His68 in HU and a tolerance to mutation at Lys63 in DTT. Our data show how chemical stresses can reduce buffering effects in the ubiquitin proteasome system. Finally, this study demonstrates the potential of lab-based interdisciplinary graduate curriculum.

The majority of genetic variants associated with common human diseases map to enhancers, non-coding elements that shape cell type-specific transcriptional programs and responses to specific extracellular cues1-3. In order to understand the mechanisms by which non-coding genetic variation contributes to disease, systematic mapping of functional enhancers and their biological contexts is required. Here, we develop an unbiased discovery platform that can identify enhancers for a target gene without prior knowledge of their native functional context. We used tiled CRISPR activation (CRISPRa) to synthetically recruit transcription factors to sites across large genomic regions (u003e100 kilobases) surrounding two key autoimmunity risk loci, CD69 and IL2RA (interleukin-2 receptor alpha; CD25). We identified several CRISPRa responsive elements (CaREs) with stimulation-dependent enhancer activity, including an IL2RA enhancer that harbors an autoimmunity risk variant. Using engineered mouse models and genome editing of human primary T cells, we found that sequence perturbation of the disease-associated IL2RA enhancer does not block IL2RA expression, but rather delays the timing of gene activation in response to specific extracellular signals. This work develops an approach to rapidly identify functional enhancers within non-coding regions, decodes a key human autoimmunity association, and suggests a general mechanism by which genetic variation can cause immune dysfunction.

Significance T-cell genome engineering holds great promise for cancer immunotherapies and cell-based therapies for HIV, primary immune deficiencies, and autoimmune diseases, but genetic manipulation of human T cells has been inefficient. We achieved efficient genome editing by delivering Cas9 protein pre-assembled with guide RNAs. These active Cas9 ribonucleoproteins (RNPs) enabled successful Cas9-mediated homology-directed repair in primary human T cells. Cas9 RNPs provide a programmable tool to replace specific nucleotide sequences in the genome of mature immune cells—a longstanding goal in the field. These studies establish Cas9 RNP technology for diverse experimental and therapeutic genome engineering applications in primary human T cells.