Mapping information-rich genotype-phenotype landscapes with genome-scale Perturb-seq.

A central goal of genetics is to define the relationships between genotypes and phenotypes. High-content phenotypic screens such as Perturb-seq (CRISPR-based screens with single-cell RNA-sequencing readouts) enable massively parallel functional genomic mapping but, to date, have been used at limited scales. Here, we perform genome-scale Perturb-seq targeting all expressed genes with CRISPR interference (CRISPRi) across >2.5 million human cells. We use transcriptional phenotypes to predict the function of poorly characterized genes, uncovering new regulators of ribosome biogenesis (including CCDC86, ZNF236, and SPATA5L1), transcription (C7orf26), and mitochondrial respiration (TMEM242). In addition to assigning gene function, single-cell transcriptional phenotypes allow for in-depth dissection of complex cellular phenomena-from RNA processing to differentiation. We leverage this ability to systematically identify genetic drivers and consequences of aneuploidy and to discover an unanticipated layer of stress-specific regulation of the mitochondrial genome. Our information-rich genotype-phenotype map reveals a multidimensional portrait of gene and cellular function.

Lineage tracing reveals the phylodynamics, plasticity, and paths of tumor evolution.

Tumor evolution is driven by the progressive acquisition of genetic and epigenetic alterations that enable uncontrolled growth and expansion to neighboring and distal tissues. The study of phylogenetic relationships between cancer cells provides key insights into these processes. Here, we introduced an evolving lineage-tracing system with a single-cell RNA-seq readout into a mouse model of Kras;Trp53(KP)-driven lung adenocarcinoma and tracked tumor evolution from single-transformed cells to metastatic tumors at unprecedented resolution. We found that the loss of the initial, stable alveolar-type2-like state was accompanied by a transient increase in plasticity. This was followed by the adoption of distinct transcriptional programs that enable rapid expansion and, ultimately, clonal sweep of stable subclones capable of metastasizing. Finally, tumors develop through stereotypical evolutionary trajectories, and perturbing additional tumor suppressors accelerates progression by creating novel trajectories. Our study elucidates the hierarchical nature of tumor evolution and, more broadly, enables in-depth studies of tumor progression.

Mapping transcriptomic vector fields of single cells.

Single-cell (sc)RNA-seq, together with RNA velocity and metabolic labeling, reveals cellular states and transitions at unprecedented resolution. Fully exploiting these data, however, requires kinetic models capable of unveiling governing regulatory functions. Here, we introduce an analytical framework dynamo (https://github.com/aristoteleo/dynamo-release), which infers absolute RNA velocity, reconstructs continuous vector fields that predict cell fates, employs differential geometry to extract underlying regulations, and ultimately predicts optimal reprogramming paths and perturbation outcomes. We highlight dynamo's power to overcome fundamental limitations of conventional splicing-based RNA velocity analyses to enable accurate velocity estimations on a metabolically labeled human hematopoiesis scRNA-seq dataset. Furthermore, differential geometry analyses reveal mechanisms driving early megakaryocyte appearance and elucidate asymmetrical regulation within the PU.1-GATA1 circuit. Leveraging the least-action-path method, dynamo accurately predicts drivers of numerous hematopoietic transitions. Finally, in silico perturbations predict cell-fate diversions induced by gene perturbations. Dynamo, thus, represents an important step in advancing quantitative and predictive theories of cell-state transitions.

Genome-wide programmable transcriptional memory by CRISPR-based epigenome editing.

A general approach for heritably altering gene expression has the potential to enable many discovery and therapeutic efforts. Here, we present CRISPRoff-a programmable epigenetic memory writer consisting of a single dead Cas9 fusion protein that establishes DNA methylation and repressive histone modifications. Transient CRISPRoff expression initiates highly specific DNA methylation and gene repression that is maintained through cell division and differentiation of stem cells to neurons. Pairing CRISPRoff with genome-wide screens and analysis of chromatin marks establishes rules for heritable gene silencing. We identify single guide RNAs (sgRNAs) capable of silencing the large majority of genes including those lacking canonical CpG islands (CGIs) and reveal a wide targeting window extending beyond annotated CGIs. The broad ability of CRISPRoff to initiate heritable gene silencing even outside of CGIs expands the canonical model of methylation-based silencing and enables diverse applications including genome-wide screens, multiplexed cell engineering, enhancer silencing, and mechanistic exploration of epigenetic inheritance.

GIGYF2 and 4EHP Inhibit Translation Initiation of Defective Messenger RNAs to Assist Ribosome-Associated Quality Control.

Ribosome-associated quality control (RQC) pathways protect cells from toxicity caused by incomplete protein products resulting from translation of damaged or problematic mRNAs. Extensive work in yeast has identified highly conserved mechanisms that lead to degradation of faulty mRNA and partially synthesized polypeptides. Here we used CRISPR-Cas9-based screening to search for additional RQC strategies in mammals. We found that failed translation leads to specific inhibition of translation initiation on that message. This negative feedback loop is mediated by two translation inhibitors, GIGYF2 and 4EHP. Model substrates and growth-based assays established that inhibition of additional rounds of translation acts in concert with known RQC pathways to prevent buildup of toxic proteins. Inability to block translation of faulty mRNAs and subsequent accumulation of partially synthesized polypeptides could explain the neurodevelopmental and neuropsychiatric disorders observed in mice and humans with compromised GIGYF2 function.

A dual sgRNA library design to probe genetic modifiers using genome-wide CRISPRi screens.

Mapping genetic interactions is essential for determining gene function and defining novel biological pathways. We report a simple to use CRISPR interference (CRISPRi) based platform, compatible with Fluorescence Activated Cell Sorting (FACS)-based reporter screens, to query epistatic relationships at scale. This is enabled by a flexible dual-sgRNA library design that allows for the simultaneous delivery and selection of a fixed sgRNA and a second randomized guide, comprised of a genome-wide library, with a single transduction. We use this approach to identify epistatic relationships for a defined biological pathway, showing both increased sensitivity and specificity than traditional growth screening approaches.

Rheumatoid arthritis-associated RBPJ polymorphism alters memory CD4+ T cells.

Notch signaling has recently emerged as an important regulator of immune responses in autoimmune diseases. The recombination signal-binding protein for immunoglobulin kappa J region (RBPJ) is a transcriptional repressor, but converts into a transcriptional activator upon activation of the canonical Notch pathway. Genome-wide association studies of rheumatoid arthritis (RA) identified a susceptibility locus, rs874040(CC), which implicated the RBPJ gene. Here, chromatin state mapping generated using the chromHMM algorithm reveals strong enhancer regions containing DNase I hypersensitive sites overlapping the rs874040 linkage disequilibrium block in human memory, but not in naïve CD4(+) T cells. The rs874040 overlapping this chromatin state was associated with increased RBPJ expression in stimulated memory CD4(+) T cells from healthy subjects homozygous for the risk allele (CC) compared with memory CD4(+) T cells bearing the protective allele (GG). Transcriptomic analysis of rs874040(CC) memory T cells showed a repression of canonical Notch target genes IL (interleukin)-9, IL-17 and interferon (IFN)γ in the basal state. Interestingly, activation of the Notch pathway using soluble Notch ligand, Jagged2-Fc, induced IL-9 and IL-17A while delta-like 4Fc, another Notch ligand, induced higher IFNγ expression in the rs874040(CC) memory CD4(+) T cells compared with their rs874040(GG) counterparts. In RA, RBPJ expression is elevated in memory T cells from RA patients compared with control subjects, and this was associated with induced inflammatory cytokines IL-9, IL-17A and IFNγ in response to Notch ligation in vitro. These findings demonstrate that the rs874040(CC) allele skews memory T cells toward a pro-inflammatory phenotype involving Notch signaling, thus increasing the susceptibility to develop RA.

Interindividual variation in human T regulatory cells.

FOXP3(+) regulatory T (Treg) cells enforce immune self-tolerance and homeostasis, and variation in some aspects of Treg function may contribute to human autoimmune diseases. Here, we analyzed population-level Treg variability by performing genome-wide expression profiling of CD4(+) Treg and conventional CD4(+) T (Tconv) cells from 168 donors, healthy or with established type-1 diabetes (T1D) or type-2 diabetes (T2D), in relation to genetic and immunologic screening. There was a range of variability in Treg signature transcripts, some almost invariant, others more variable, with more extensive variability for genes that control effector function (ENTPD1, FCRL1) than for lineage-specification factors like FOXP3 or IKZF2. Network analysis of Treg signature genes identified coregulated clusters that respond similarly to genetic and environmental variation in Treg and Tconv cells, denoting qualitative differences in otherwise shared regulatory circuits whereas other clusters are coregulated in Treg, but not Tconv, cells, suggesting Treg-specific regulation of genes like CTLA4 or DUSP4. Dense genotyping identified 110 local genetic variants (cis-expression quantitative trait loci), some of which are specifically active in Treg, but not Tconv, cells. The Treg signature became sharper with age and with increasing body-mass index, suggesting a tuning of Treg function with repertoire selection and/or chronic inflammation. Some Treg signature transcripts correlated with FOXP3 mRNA and/or protein, suggesting transcriptional or posttranslational regulatory relationships. Although no single transcript showed significant association to diabetes, overall expression of the Treg signature was subtly perturbed in T1D, but not T2D, patients.

CD33: increased inclusion of exon 2 implicates the Ig V-set domain in Alzheimer's disease susceptibility.

We previously demonstrated that the Alzheimer's disease (AD) associated risk allele, rs3865444(C), results in a higher surface density of CD33 on monocytes. Here, we find alternative splicing of exon 2 to be the primary mechanism of the genetically driven differential expression of CD33 protein. We report that the risk allele, rs3865444(C), is associated with greater cell surface expression of CD33 in both subjects of European and African-American ancestry and that there is a single haplotype influencing CD33 surface expression. A meta-analysis of the two populations narrowed the number of significant SNPs in high linkage disequilibrium (LD) (r(2) > 0.8) with rs3865444 to just five putative causal variants associated with increased protein expression. Using gene expression data from flow-sorted CD14(+)CD16(-) monocytes from 398 healthy subjects of three populations, we show that the rs3865444(C) risk allele is strongly associated with greater expression of CD33 exon 2 (pMETA = 2.36 × 10(-60)). Western blotting confirms increased protein expression of the full-length CD33 isoform containing exon 2 relative to the rs3865444(C) allele (P < 0.0001). Of the variants in strong LD with rs3865444, rs12459419, which is located in a putative SRSF2 splice site of exon 2, is the most likely candidate to mediate the altered alternative splicing of CD33's Immunoglobulin V-set domain 2 and ultimately influence AD susceptibility.

Common risk alleles for inflammatory diseases are targets of recent positive selection.

Genome-wide association studies (GWASs) have identified hundreds of loci harboring genetic variation influencing inflammatory-disease susceptibility in humans. It has been hypothesized that present day inflammatory diseases may have arisen, in part, due to pleiotropic effects of host resistance to pathogens over the course of human history, with significant selective pressures acting to increase host resistance to pathogens. The extent to which genetic factors underlying inflammatory-disease susceptibility has been influenced by selective processes can now be quantified more comprehensively than previously possible. To understand the evolutionary forces that have shaped inflammatory-disease susceptibility and to elucidate functional pathways affected by selection, we performed a systems-based analysis to integrate (1) published GWASs for inflammatory diseases, (2) a genome-wide scan for signatures of positive selection in a population of European ancestry, (3) functional genomics data comprised of protein-protein interaction networks, and (4) a genome-wide expression quantitative trait locus (eQTL) mapping study in peripheral blood mononuclear cells (PBMCs). We demonstrate that loci for inflammatory-disease susceptibility are enriched for genomic signatures of recent positive natural selection, with selected loci forming a highly interconnected protein-protein interaction network. Further, we identify 21 loci for inflammatory-disease susceptibility that display signatures of recent positive selection, of which 13 also show evidence of cis-regulatory effects on genes within the associated locus. Thus, our integrated analyses highlight a set of susceptibility loci that might subserve a shared molecular function and has experienced selective pressure over the course of human history; today, these loci play a key role in influencing susceptibility to multiple different inflammatory diseases, in part through alterations of gene expression in immune cells.

A TREM1 variant alters the accumulation of Alzheimer-related amyloid pathology.

OBJECTIVE: Genome-wide association studies have linked variants in TREM2 (triggering receptor expressed on myeloid cells 2) and TREML2 with Alzheimer disease (AD) and AD endophenotypes. Here, we pursue a targeted analysis of the TREM locus in relation to cognitive decline and pathological features of AD. METHODS: Clinical, cognitive, and neuropathological phenotypes were collected in 3 prospective cohorts on aging (n = 3,421 subjects). Our primary analysis was an association with neuritic plaque pathology. To functionally characterize the associated variants, we used flow cytometry to measure TREM1 expression on monocytes. RESULTS: We provide evidence that an intronic variant, rs6910730(G) , in TREM1, is associated with an increased burden of neuritic plaques (p = 3.7 × 10(-4) ), diffuse plaques (p = 4.1 × 10(-3) ), and Aß density (p = 2.6 × 10(-3) ) as well as an increased rate of cognitive decline (p = 5.3 × 10(-3) ). A variant upstream of TREM2, rs7759295(C) , is independently associated with an increased tau tangle density (p = 4.9 × 10(-4) ), an increased burden of neurofibrillary tangles (p = 9.1 × 10(-3) ), and an increased rate of cognitive decline (p = 2.3 × 10(-3) ). Finally, a cytometric analysis shows that the TREM1 rs6910730(G) allele is associated with decreased TREM1 expression on the surface of myeloid cells (p = 1.7 × 10(-3) ). INTERPRETATION: We provide evidence that 2 common variants within the TREM locus are associated with pathological features of AD and aging-related cognitive decline. Our evidence suggests that these variants are likely to be independent of known AD variants and that they may work through an alteration of myeloid cell function.

A pharmacogenetic study implicates SLC9a9 in multiple sclerosis disease activity.

OBJECTIVE: A proportion of multiple sclerosis (MS) patients experience disease activity despite treatment. The early identification of the most effective drug is critical to impact long-term outcome and to move toward a personalized approach. The aim of the present study is to identify biomarkers for further clinical development and to yield insights into the pathophysiology of disease activity. METHODS: We performed a genome-wide association study in interferon-ß (IFNß)-treated MS patients followed by validation in 3 independent cohorts. The role of the validated variant was examined in several RNA data sets, and the function of the presumed target gene was explored using an RNA interference approach in primary T cells in vitro. RESULTS: We found an association between rs9828519(G) and nonresponse to IFNß (pdiscovery = 4.43 × 10(-8)) and confirmed it in a meta-analysis across 3 replication data sets (preplication = 7.78 × 10(-4)). Only 1 gene is found in the linkage disequilibrium block containing rs9828519: SLC9A9. Exploring the function of this gene, we see that SLC9A9 mRNA expression is diminished in MS subjects who are more likely to have relapses. Moreover, SLC9A9 knockdown in T cells in vitro leads an increase in expression of IFNγ, which is a proinflammatory molecule. INTERPRETATION: This study identifies and validates the role of rs9828519, an intronic variant in SLC9A9, in IFNß-treated subjects, demonstrating a successful pharmacogenetic screen in MS. Functional characterization suggests that SLC9A9, an Na(+) -H(+) exchanger found in endosomes, appears to influence the differentiation of T cells to a proinflammatory fate and may have a broader role in MS disease activity, outside of IFNß treatment.

Transcriptome-wide characterization of genetic perturbations.

Single cell CRISPR screens such as Perturb-seq enable transcriptomic profiling of genetic perturbations at scale. However, the data produced by these screens are often noisy due to cost and technical constraints, limiting power to detect true effects with conventional differential expression analyses. Here, we introduce TRanscriptome-wide Analysis of Differential Expression (TRADE), a statistical framework which estimates the transcriptome-wide distribution of true differential expression effects from noisy gene-level measurements. Within TRADE, we derive multiple novel, interpretable statistical metrics, including the "transcriptome-wide impact", an estimator of the overall transcriptional effect of a perturbation which is stable across sampling depths. We analyze new and published large-scale Perturb-seq datasets to show that many true transcriptional effects are not statistically significant, but detectable in aggregate with TRADE. In a genome-scale Perturb-seq screen, we find that a typical gene perturbation affects an estimated 45 genes, whereas a typical essential gene perturbation affects over 500 genes. An advantage of our approach is its ability to compare the transcriptomic effects of genetic perturbations across contexts and dosages despite differences in power. We use this ability to identify perturbations with cell-type dependent effects and to find examples of perturbations where transcriptional responses are not only larger in magnitude, but also qualitatively different, as a function of dosage. Lastly, we expand our analysis to case/control comparison of gene expression for neuropsychiatric conditions, finding that transcriptomic effect correlations are greater than genetic correlations for these diagnoses. TRADE lays an analytic foundation for the systematic comparison of genetic perturbation atlases, as well as differential expression experiments more broadly.

Nucleotide depletion promotes cell fate transitions by inducing DNA replication stress.

Control of cellular identity requires coordination of developmental programs with environmental factors such as nutrient availability, suggesting that perturbing metabolism can alter cell state. Here, we find that nucleotide depletion and DNA replication stress drive differentiation in human and murine normal and transformed hematopoietic systems, including patient-derived acute myeloid leukemia (AML) xenografts. These cell state transitions begin during S phase and are independent of ATR/ATM checkpoint signaling, double-stranded DNA break formation, and changes in cell cycle length. In systems where differentiation is blocked by oncogenic transcription factor expression, replication stress activates primed regulatory loci and induces lineage-appropriate maturation genes despite the persistence of progenitor programs. Altering the baseline cell state by manipulating transcription factor expression causes replication stress to induce genes specific for alternative lineages. The ability of replication stress to selectively activate primed maturation programs across different contexts suggests a general mechanism by which changes in metabolism can promote lineage-appropriate cell state transitions.

A dual sgRNA library design to probe genetic modifiers using genome-wide CRISPRi screens.

Mapping genetic interactions is essential for determining gene function and defining novel biological pathways. We report a simple to use CRISPR interference (CRISPRi) based platform, compatible with Fluorescence Activated Cell Sorting (FACS)-based reporter screens, to query epistatic relationships at scale. This is enabled by a flexible dual-sgRNA library design that allows for the simultaneous delivery and selection of a fixed sgRNA and a second randomized guide, comprised of a genome-wide library, with a single transduction. We use this approach to identify epistatic relationships for a defined biological pathway, showing both increased sensitivity and specificity than traditional growth screening approaches.

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.

Microfluidics-free single-cell genomics with templated emulsification.

Current single-cell RNA-sequencing approaches have limitations that stem from the microfluidic devices or fluid handling steps required for sample processing. We develop a method that does not require specialized microfluidic devices, expertise or hardware. Our approach is based on particle-templated emulsification, which allows single-cell encapsulation and barcoding of cDNA in uniform droplet emulsions with only a vortexer. Particle-templated instant partition sequencing (PIP-seq) accommodates a wide range of emulsification formats, including microwell plates and large-volume conical tubes, enabling thousands of samples or millions of cells to be processed in minutes. We demonstrate that PIP-seq produces high-purity transcriptomes in mouse-human mixing studies, is compatible with multiomics measurements and can accurately characterize cell types in human breast tissue compared to a commercial microfluidic platform. Single-cell transcriptional profiling of mixed phenotype acute leukemia using PIP-seq reveals the emergence of heterogeneity within chemotherapy-resistant cell subsets that were hidden by standard immunophenotyping. PIP-seq is a simple, flexible and scalable next-generation workflow that extends single-cell sequencing to new applications.

MTCH2 is a mitochondrial outer membrane protein insertase.

In the mitochondrial outer membrane, α-helical transmembrane proteins play critical roles in cytoplasmic-mitochondrial communication. Using genome-wide CRISPR screens, we identified mitochondrial carrier homolog 2 (MTCH2), and its paralog MTCH1, and showed that it is required for insertion of biophysically diverse tail-anchored (TA), signal-anchored, and multipass proteins, but not outer membrane ß-barrel proteins. Purified MTCH2 was sufficient to mediate insertion into reconstituted proteoliposomes. Functional and mutational studies suggested that MTCH2 has evolved from a solute carrier transporter. MTCH2 uses membrane-embedded hydrophilic residues to function as a gatekeeper for the outer membrane, controlling mislocalization of TAs into the endoplasmic reticulum and modulating the sensitivity of leukemia cells to apoptosis. Our identification of MTCH2 as an insertase provides a mechanistic explanation for the diverse phenotypes and disease states associated with MTCH2 dysfunction.

Dual genome-wide coding and lncRNA screens in neural induction of induced pluripotent stem cells.

Human chromosomes are pervasively transcribed, but systematic understanding of coding and lncRNA genome function in cell differentiation is lacking. Using CRISPR interference (CRISPRi) in human induced pluripotent stem cells, we performed dual genome-wide screens - assessing 18,905 protein-coding and 10,678 lncRNA loci - and identified 419 coding and 201 lncRNA genes that regulate neural induction. Integrative analyses revealed distinct properties of coding and lncRNA genome function, including a 10-fold enrichment of lncRNA genes for roles in differentiation compared to proliferation. Further, we applied Perturb-seq to obtain granular insights into neural induction phenotypes. While most coding hits stalled or aborted differentiation, lncRNA hits were enriched for the genesis of diverse cellular states, including those outside the neural lineage. In addition to providing a rich resource (danlimlab.shinyapps.io/dualgenomewide) for understanding coding and lncRNA gene function in development, these results indicate that the lncRNA genome regulates lineage commitment in a manner fundamentally distinct from coding genes.

Maximizing CRISPRi efficacy and accessibility with dual-sgRNA libraries and optimal effectors.

CRISPR interference (CRISPRi) enables programmable, reversible, and titratable repression of gene expression (knockdown) in mammalian cells. Initial CRISPRi-mediated genetic screens have showcased the potential to address basic questions in cell biology, genetics, and biotechnology, but wider deployment of CRISPRi screening has been constrained by the large size of single guide RNA (sgRNA) libraries and challenges in generating cell models with consistent CRISPRi-mediated knockdown. Here, we present next-generation CRISPRi sgRNA libraries and effector expression constructs that enable strong and consistent knockdown across mammalian cell models. First, we combine empirical sgRNA selection with a dual-sgRNA library design to generate an ultra-compact (1-3 elements per gene), highly active CRISPRi sgRNA library. Next, we compare CRISPRi effectors to show that the recently published Zim3-dCas9 provides an excellent balance between strong on-target knockdown and minimal non-specific effects on cell growth or the transcriptome. Finally, we engineer a suite of cell lines with stable expression of Zim3-dCas9 and robust on-target knockdown. Our results and publicly available reagents establish best practices for CRISPRi genetic screening.