Meena Subramaniam

Generation of knock-in primary human T cells using Cas9 ribonucleoproteins

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. T-cell genome engineering holds great promise for cell-based therapies for cancer, HIV, primary immune deficiencies, and autoimmune diseases, but genetic manipulation of human T cells has been challenging. Improved tools are needed to efficiently “knock out” genes and “knock in” targeted genome modifications to modulate T-cell function and correct disease-associated mutations. CRISPR/Cas9 technology is facilitating genome engineering in many cell types, but in human T cells its efficiency has been limited and it has not yet proven useful for targeted nucleotide replacements. Here we report efficient genome engineering in human CD4+ T cells using Cas9:single-guide RNA ribonucleoproteins (Cas9 RNPs). Cas9 RNPs allowed ablation of CXCR4, a coreceptor for HIV entry. Cas9 RNP electroporation caused up to ∼40% of cells to lose high-level cell-surface expression of CXCR4, and edited cells could be enriched by sorting based on low CXCR4 expression. Importantly, Cas9 RNPs paired with homology-directed repair template oligonucleotides generated a high frequency of targeted genome modifications in primary T cells. Targeted nucleotide replacement was achieved in CXCR4 and PD-1 (PDCD1), a regulator of T-cell exhaustion that is a validated target for tumor immunotherapy. Deep sequencing of a target site confirmed that Cas9 RNPs generated knock-in genome modifications with up to ∼20% efficiency, which accounted for up to approximately one-third of total editing events. These results establish Cas9 RNP technology for diverse experimental and therapeutic genome engineering applications in primary human T cells.

The landscape of genomic imprinting across diverse adult human tissues

Genomic imprinting is an important regulatory mechanism that silences one of the parental copies of a gene. To systematically characterize this phenomenon, we analyze tissue specificity of imprinting from allelic expression data in 1582 primary tissue samples from 178 individuals from the Genotype-Tissue Expression (GTEx) project. We characterize imprinting in 42 genes, including both novel and previously identified genes. Tissue specificity of imprinting is widespread, and gender-specific effects are revealed in a small number of genes in muscle with stronger imprinting in males. IGF2 shows maternal expression in the brain instead of the canonical paternal expression elsewhere. Imprinting appears to have only a subtle impact on tissue-specific expression levels, with genes lacking a systematic expression difference between tissues with imprinted and biallelic expression. In summary, our systematic characterization of imprinting in adult tissues highlights variation in imprinting between genes, individuals, and tissues.

Discovery of stimulation-responsive immune enhancers with CRISPR activation

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 extracellular cues. Systematic mapping of functional enhancers and their biological contexts is required to understand the mechanisms by which variation in non-coding genetic sequences contributes to disease. Functional enhancers can be mapped by genomic sequence disruption, but this approach is limited to the subset of enhancers that are necessary in the particular cellular context being studied. We hypothesized that recruitment of a strong transcriptional activator to an enhancer would be sufficient to drive target gene expression, even if that enhancer was not currently active in the assayed cells. Here we describe a discovery platform that can identify stimulus-responsive enhancers for a target gene independent of stimulus exposure. We used tiled CRISPR activation (CRISPRa) to synthetically recruit a transcriptional activator to sites across large genomic regions (more than 100 kilobases) surrounding two key autoimmunity risk loci, CD69 and IL2RA. We identified several CRISPRa-responsive elements with chromatin features of stimulus-responsive enhancers, including an IL2RA enhancer that harbours an autoimmunity risk variant. Using engineered mouse models, we found that sequence perturbation of the disease-associated Il2ra enhancer did not entirely block Il2ra expression, but rather delayed the timing of gene activation in response to specific extracellular signals. Enhancer deletion skewed polarization of naive T cells towards a pro-inflammatory T helper (TH17) cell state and away from a regulatory T cell state. This integrated approach identifies functional enhancers and reveals how non-coding variation associated with human immune dysfunction alters context-specific gene programs.

Multiplexed droplet single-cell RNA-sequencing using natural genetic variation

Droplet single-cell RNA-sequencing (dscRNA-seq) has enabled rapid, massively parallel profiling of transcriptomes. However, assessing differential expression across multiple individuals has been hampered by inefficient sample processing and technical batch effects. Here we describe a computational tool, demuxlet, that harnesses natural genetic variation to determine the sample identity of each droplet containing a single cell (singlet) and detect droplets containing two cells (doublets). These capabilities enable multiplexed dscRNA-seq experiments in which cells from unrelated individuals are pooled and captured at higher throughput than in standard workflows. Using simulated data, we show that 50 single-nucleotide polymorphisms (SNPs) per cell are sufficient to assign 97% of singlets and identify 92% of doublets in pools of up to 64 individuals. Given genotyping data for each of eight pooled samples, demuxlet correctly recovers the sample identity of >99% of singlets and identifies doublets at rates consistent with previous estimates. We apply demuxlet to assess cell-type-specific changes in gene expression in 8 pooled lupus patient samples treated with interferon (IFN)-β and perform eQTL analysis on 23 pooled samples.

Genetic determinants of chromatin accessibility and gene regulation in T cell activation across human individuals

The vast majority 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. Here, we analyzed Assay for Transposase-Accessible Chromatin (ATAC-seq) profiles from activated primary CD4+ T cells of 105 healthy donors to identify ATAC-QTLs: genetic variants that affect chromatin accessibility. We found that ATAC-QTLs are widespread, disrupt binding sites for transcription factors known to be important for CD4+ T cell differentiation and activation, overlap and mediate expression QTLs from the same cells and are enriched for SNPs associated with autoimmune diseases. We also identified numerous pairs of ATAC-peaks with highly correlated chromatin accessibility. When we characterize 3D chromosome organization in primary CD4+ T cells by in situ-Hi-C, we found that correlated peaks tend to reside in the same chromatin contact domains, span super-enhancers, and are more impacted by ATAC-QTLs than single peaks. Thus, variability in chromatin accessibility in primary CD4+ T cells is heritable, is determined by genetic variation in a manner affected by the 3D organization of the genome, and mediates genetic effects on gene expression. Our results provide insights into how genetic variants modulate chromatin state and gene expression in primary immune cells that play a key role in many human diseases.

Multiplexing droplet-based single cell RNA-sequencing using natural genetic barcodes

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 experimentally challenging. Here, we introduce an in-silico algorithm demuxlet that harnesses natural genetic variation in a pool of cells from unrelated individuals to discover the sample identity of each cell and identify droplets containing cells from two different individuals (doublets). These capabilities enable simple experimental designs where cells from genetically diverse samples are multiplexed and captured at higher throughput than standard workflows. To demonstrate the performance of our method, we sequenced 3 multiplexed 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 enriched for multiple cell types and at rates consistent with previous estimates. We further demonstrate the utility of sample multiplexing by characterizing cell type-specific responses and interindividual variability in 2 pools of PBMCs from 8 additional lupus patients before and after cytokine stimulation. Demuxlet enables droplet-based single cell RNA-seq for large-scale studies of population variation and could be extended to other single cell datasets that incorporate natural or synthetic DNA barcodes.

Discovery of an autoimmunity-associated IL2RA enhancer by unbiased targeting of transcriptional activation

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 cues 1-3. 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 (>100 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.

Genetic analysis of isoform usage in the human anti-viral response reveals influenza-specific regulation of ERAP2 transcripts under balancing selection

While the impact of common genetic variants on transcript abundance in response to cellular stimuli has been analyzed in depth, less is known about how stimulation modulates the genetic control of isoform usage. Using RNA-seq profiles of monocyte-derived dendritic cells from 243 individuals, we uncovered thousands of unannotated isoforms synthesized in response to viral infection or stimulation with Type 1 interferon. We identified more than a thousand single nucleotide polymorphisms associated with isoform usage (isoQTLs), many of which are independent of expression QTLs for the same gene. Compared to eQTLs, isoQTLs are enriched for splice sites and untranslated regions, and depleted of upstream sequences. In five loci, they provide a possible mechanism of action underlying DNA variants associated with immune-related disorders. Among these five is the ERAP2 locus, where the major haplotype is under balancing selection and associated with Crohn’s disease risk. At baseline and following Type 1 interferon stimulation, the major haplotype is associated with absence of ERAP2 expression; but in response to influenza infection, the major haplotype results in the expression of two previously uncharacterized, alternatively transcribed, spliced and translated short isoforms. Thus, genetic variants at a single locus could modulate independent gene regulatory processes in the innate immune response, and in the case of ERAP2, may confer a historical fitness advantage in response to virus, but increase risk for autoimmunity in the modern environment.

Functional Interpretation of Single-Cell Similarity Maps

We present VISION, a tool for annotating the sources of variation in single cell RNA-seq data in an automated, unbiased and scalable manner. VISION operates directly on the manifold of cell-cell similarity and employs a flexible annotation approach that can operate either with or without preconceived stratification of the cells into groups or along a continuum. We demonstrate the utility of VISION using a relatively homogeneous set of B cells from a cohort of lupus patients and healthy controls and show that it can derive important sources of cellular variation and link them to clinical phenotypes in a stratification free manner. VISION produces an interactive, low latency and feature rich web-based report that can be easily shared amongst researchers.

GBAT: a gene-based association method for robust trans-gene regulation detection

Identification of trans-eQTLs has been limited by a heavy multiple testing burden, read-mapping biases, and hidden confounders. To address these issues, we developed GBAT, a powerful gene-based method that allows robust detection of trans gene regulation. Using simulated and real data, we show that GBAT drastically increases detection of trans-gene regulation over standard trans-eQTL analyses.