Multiplexed single-cell characterization of alternative polyadenylation regulators.

Most mammalian genes have multiple polyA sites, representing a substantial source of transcript diversity regulated by the cleavage and polyadenylation (CPA) machinery. To better understand how these proteins govern polyA site choice, we introduce CPA-Perturb-seq, a multiplexed perturbation screen dataset of 42 CPA regulators with a 3' scRNA-seq readout that enables transcriptome-wide inference of polyA site usage. We develop a framework to detect perturbation-dependent changes in polyadenylation and characterize modules of co-regulated polyA sites. We find groups of intronic polyA sites regulated by distinct components of the nuclear RNA life cycle, including elongation, splicing, termination, and surveillance. We train and validate a deep neural network (APARENT-Perturb) for tandem polyA site usage, delineating a cis-regulatory code that predicts perturbation response and reveals interactions between regulatory complexes. Our work highlights the potential for multiplexed single-cell perturbation screens to further our understanding of post-transcriptional regulation.

Low copy CRISPR-Cas13d mitigates collateral RNA cleavage.

While CRISPR-Cas13 systems excel in accurately targeting RNA, the potential for collateral RNA degradation poses a concern for therapeutic applications and limits broader adoption for transcriptome perturbations. We evaluate the extent to which collateral RNA cleavage occurs when Rfx Cas13d is delivered via plasmid transfection or lentiviral transduction and find that collateral activity only occurs with high levels of Rfx Cas13d expression. Using transcriptome-scale and combinatorial CRISPR pooled screens in cell lines with low-copy Rfx Cas13d, we find high on-target knockdown, without extensive collateral activity regardless of the expression level of the target gene. In contrast, transfection of Rfx Cas13d, which yields higher nuclease expression, results in collateral RNA degradation. Further, our analysis of a high-fidelity Cas13 variant uncovers a marked decrease in on-target efficiency, suggesting that its reduced collateral activity may be due to an overall diminished nuclease capability.

Prediction of on-target and off-target activity of CRISPR-Cas13d guide RNAs using deep learning.

Transcriptome engineering applications in living cells with RNA-targeting CRISPR effectors depend on accurate prediction of on-target activity and off-target avoidance. Here we design and test ~200,000 RfxCas13d guide RNAs targeting essential genes in human cells with systematically designed mismatches and insertions and deletions (indels). We find that mismatches and indels have a position- and context-dependent impact on Cas13d activity, and mismatches that result in G-U wobble pairings are better tolerated than other single-base mismatches. Using this large-scale dataset, we train a convolutional neural network that we term targeted inhibition of gene expression via gRNA design (TIGER) to predict efficacy from guide sequence and context. TIGER outperforms the existing models at predicting on-target and off-target activity on our dataset and published datasets. We show that TIGER scoring combined with specific mismatches yields the first general framework to modulate transcript expression, enabling the use of RNA-targeting CRISPRs to precisely control gene dosage.

Cas13d-mediated isoform-specific RNA knockdown with a unified computational and experimental toolbox.

Alternative splicing is an essential mechanism for diversifying proteins, in which mature RNA isoforms produce proteins with potentially distinct functions. Two major challenges in characterizing the cellular function of isoforms are the lack of experimental methods to specifically and efficiently modulate isoform expression and computational tools for complex experimental design. To address these gaps, we developed and methodically tested a strategy which pairs the RNA-targeting CRISPR/Cas13d system with guide RNAs that span exon-exon junctions in the mature RNA. We performed a high-throughput essentiality screen, quantitative RT-PCR assays, and PacBio long read sequencing to affirm our ability to specifically target and robustly knockdown individual RNA isoforms. In parallel, we provide computational tools for experimental design and screen analysis. Considering all possible splice junctions annotated in GENCODE for multi-isoform genes and our gRNA efficacy predictions, we estimate that our junction-centric strategy can uniquely target up to 89% of human RNA isoforms, including 50,066 protein-coding and 11,415 lncRNA isoforms. Importantly, this specificity spans all splicing and transcriptional events, including exon skipping and inclusion, alternative 5' and 3' splice sites, and alternative starts and ends.

CPA-Perturb-seq: Multiplexed single-cell characterization of alternative polyadenylation regulators.

Most mammalian genes have multiple polyA sites, representing a substantial source of transcript diversity that is governed by the cleavage and polyadenylation (CPA) regulatory machinery. To better understand how these proteins govern polyA site choice we introduce CPA-Perturb-seq, a multiplexed perturbation screen dataset of 42 known CPA regulators with a 3' scRNA-seq readout that enables transcriptome-wide inference of polyA site usage. We develop a statistical framework to specifically identify perturbation-dependent changes in intronic and tandem polyadenylation, and discover modules of co-regulated polyA sites exhibiting distinct functional properties. By training a multi-task deep neural network (APARENT-Perturb) on our dataset, we delineate a cis-regulatory code that predicts responsiveness to perturbation and reveals interactions between distinct regulatory complexes. Finally, we leverage our framework to re-analyze published scRNA-seq datasets, identifying new regulators that affect the relative abundance of alternatively polyadenylated transcripts, and characterizing extensive cellular heterogeneity in 3' UTR length amongst antibody-producing cells. Our work highlights the potential for multiplexed single-cell perturbation screens to further our understanding of post-transcriptional regulation in vitro and in vivo.

Efficient combinatorial targeting of RNA transcripts in single cells with Cas13 RNA Perturb-seq.

Pooled CRISPR screens coupled with single-cell RNA-sequencing have enabled systematic interrogation of gene function and regulatory networks. Here, we introduce Cas13 RNA Perturb-seq (CaRPool-seq), which leverages the RNA-targeting CRISPR-Cas13d system and enables efficient combinatorial perturbations alongside multimodal single-cell profiling. CaRPool-seq encodes multiple perturbations on a cleavable CRISPR array that is associated with a detectable barcode sequence, allowing for the simultaneous targeting of multiple genes. We compared CaRPool-seq to existing Cas9-based methods, highlighting its unique strength to efficiently profile combinatorially perturbed cells. Finally, we apply CaRPool-seq to perform multiplexed combinatorial perturbations of myeloid differentiation regulators in an acute myeloid leukemia (AML) model system and identify extensive interactions between different chromatin regulators that can enhance or suppress AML differentiation phenotypes.

Chemically modified guide RNAs enhance CRISPR-Cas13 knockdown in human cells.

RNA-targeting CRISPR-Cas13 proteins have recently emerged as a powerful platform to modulate gene expression outcomes. However, protein and CRISPR RNA (crRNA) delivery in human cells can be challenging with rapid crRNA degradation yielding transient knockdown. Here we compare several chemical RNA modifications at different positions to identify synthetic crRNAs that improve RNA targeting efficiency and half-life in human cells. We show that co-delivery of modified crRNAs and recombinant Cas13 enzyme in ribonucleoprotein (RNP) complexes can alter gene expression in primary CD4+ and CD8+ T cells. This system represents a robust and efficient method to modulate transcripts without genetic manipulation.

Profiling the genetic determinants of chromatin accessibility with scalable single-cell CRISPR screens.

CRISPR screens have been used to connect genetic perturbations with changes in gene expression and phenotypes. Here we describe a CRISPR-based, single-cell combinatorial indexing assay for transposase-accessible chromatin (CRISPR-sciATAC) to link genetic perturbations to genome-wide chromatin accessibility in a large number of cells. In human myelogenous leukemia cells, we apply CRISPR-sciATAC to target 105 chromatin-related genes, generating chromatin accessibility data for ~30,000 single cells. We correlate the loss of specific chromatin remodelers with changes in accessibility globally and at the binding sites of individual transcription factors (TFs). For example, we show that loss of the H3K27 methyltransferase EZH2 increases accessibility at heterochromatic regions involved in embryonic development and triggers expression of genes in the HOXA and HOXD clusters. At a subset of regulatory sites, we also analyze changes in nucleosome spacing following the loss of chromatin remodelers. CRISPR-sciATAC is a high-throughput, single-cell method for studying the effect of genetic perturbations on chromatin in normal and disease states.

Characterizing the molecular regulation of inhibitory immune checkpoints with multimodal single-cell screens.

The expression of inhibitory immune checkpoint molecules, such as programmed death-ligand (PD-L)1, is frequently observed in human cancers and can lead to the suppression of T cell-mediated immune responses. Here, we apply expanded CRISPR-compatible (EC)CITE-seq, a technology that combines pooled CRISPR screens with single-cell mRNA and surface protein measurements, to explore the molecular networks that regulate PD-L1 expression. We also develop a computational framework, mixscape, that substantially improves the signal-to-noise ratio in single-cell perturbation screens by identifying and removing confounding sources of variation. Applying these tools, we identify and validate regulators of PD-L1 and leverage our multimodal data to identify both transcriptional and post-transcriptional modes of regulation. Specifically, we discover that the Kelch-like protein KEAP1 and the transcriptional activator NRF2 mediate the upregulation of PD-L1 after interferon (IFN)-γ stimulation. Our results identify a new mechanism for the regulation of immune checkpoints and present a powerful analytical framework for the analysis of multimodal single-cell perturbation screens.

Ythdf is a N6-methyladenosine reader that modulates Fmr1 target mRNA selection and restricts axonal growth in Drosophila.

N6-methyladenosine (m6 A) regulates a variety of physiological processes through modulation of RNA metabolism. This modification is particularly enriched in the nervous system of several species, and its dysregulation has been associated with neurodevelopmental defects and neural dysfunctions. In Drosophila, loss of m6 A alters fly behavior, albeit the underlying molecular mechanism and the role of m6 A during nervous system development have remained elusive. Here we find that impairment of the m6 A pathway leads to axonal overgrowth and misguidance at larval neuromuscular junctions as well as in the adult mushroom bodies. We identify Ythdf as the main m6 A reader in the nervous system, being required to limit axonal growth. Mechanistically, we show that the m6 A reader Ythdf directly interacts with Fmr1, the fly homolog of Fragile X mental retardation RNA binding protein (FMRP), to inhibit the translation of key transcripts involved in axonal growth regulation. Altogether, this study demonstrates that the m6 A pathway controls development of the nervous system and modulates Fmr1 target transcript selection.

Transcriptome-wide Cas13 guide RNA design for model organisms and viral RNA pathogens.

The recent characterization of RNA-targeting CRISPR nucleases has enabled diverse transcriptome engineering and screening applications that depend crucially on prediction and selection of optimized CRISPR guide RNAs (gRNAs). Previously, we developed a computational model to predict RfxCas13d gRNA activity for all human protein-coding genes. Here, we extend this framework to six model organisms (human, mouse, zebrafish, fly, nematode, and flowering plants) for protein-coding genes and noncoding RNAs (ncRNAs) and also to four RNA virus families (severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2], HIV-1, H1N1 influenza, and Middle East respiratory syndrome [MERS]). We include experimental validation of predictions by testing knockdown of multiple ncRNAs (MALAT1, HOTAIRM1, Gas5, and Pvt1) in human and mouse cells. We developed a freely available web-based platform (cas13design) with pre-scored gRNAs for transcriptome-wide targeting in several organisms and an interactive design tool to predict optimal gRNAs for custom RNA targets entered by the user. This resource will facilitate CRISPR-Cas13 RNA targeting in model organisms, emerging viral threats to human health.

Identification of Required Host Factors for SARS-CoV-2 Infection in Human Cells.

To better understand host-virus genetic dependencies and find potential therapeutic targets for COVID-19, we performed a genome-scale CRISPR loss-of-function screen to identify host factors required for SARS-CoV-2 viral infection of human alveolar epithelial cells. Top-ranked genes cluster into distinct pathways, including the vacuolar ATPase proton pump, Retromer, and Commander complexes. We validate these gene targets using several orthogonal methods such as CRISPR knockout, RNA interference knockdown, and small-molecule inhibitors. Using single-cell RNA-sequencing, we identify shared transcriptional changes in cholesterol biosynthesis upon loss of top-ranked genes. In addition, given the key role of the ACE2 receptor in the early stages of viral entry, we show that loss of RAB7A reduces viral entry by sequestering the ACE2 receptor inside cells. Overall, this work provides a genome-scale, quantitative resource of the impact of the loss of each host gene on fitness/response to viral infection.

Massively parallel Cas13 screens reveal principles for guide RNA design.

Type VI CRISPR enzymes are RNA-targeting proteins with nuclease activity that enable specific and robust target gene knockdown without altering the genome. To define rules for the design of Cas13d guide RNAs (gRNAs), we conducted massively parallel screens targeting messenger RNAs (mRNAs) of a green fluorescent protein transgene, and CD46, CD55 and CD71 cell-surface proteins in human cells. In total, we measured the activity of 24,460 gRNAs with and without mismatches relative to the target sequences. Knockdown efficacy is driven by gRNA-specific features and target site context. Single mismatches generally reduce knockdown to a modest degree, but spacer nucleotides 15-21 are largely intolerant of target site mismatches. We developed a computational model to identify optimal gRNAs and confirm their generalizability, testing 3,979 guides targeting mRNAs of 48 endogenous genes. We show that Cas13 can be used in forward transcriptomic pooled screens and, using our model, predict optimized Cas13 gRNAs for all protein-coding transcripts in the human genome.

High-Throughput Screens of PAM-Flexible Cas9 Variants for Gene Knockout and Transcriptional Modulation.

A key limitation of the widely used CRISPR enzyme S. pyogenes Cas9 is the strict requirement of an NGG protospacer-adjacent motif (PAM) at the target site. This constraint can be limiting for genome editing applications that require precise Cas9 positioning. Recently, two Cas9 variants with a relaxed PAM requirement (NG) have been developed (xCas9 and Cas9-NG), but their activity has been measured at only a small number of endogenous sites. Here, we devise a high-throughput Cas9 pooled competition screen to compare the performance of Cas9 variants at thousands of genomic loci for gene knockout, transcriptional activation, and inhibition. We show that PAM flexibility comes at a substantial cost of decreased DNA targeting and cleavage. Of the PAM-flexible variants, we find that Cas9-NG outperforms xCas9 regardless of genome engineering modality or PAM. Finally, we combine xCas9 mutations with those of Cas9-NG, creating a stronger transcriptional modulator than existing PAM-flexible Cas9 variants.

Global identification of functional microRNA-mRNA interactions in Drosophila.

MicroRNAs (miRNAs) are key mediators of post-transcriptional gene expression silencing. So far, no comprehensive experimental annotation of functional miRNA target sites exists in Drosophila. Here, we generated a transcriptome-wide in vivo map of miRNA-mRNA interactions in Drosophila melanogaster, making use of single nucleotide resolution in Argonaute1 (AGO1) crosslinking and immunoprecipitation (CLIP) data. Absolute quantification of cellular miRNA levels presents the miRNA pool in Drosophila cell lines to be more diverse than previously reported. Benchmarking two CLIP approaches, we identify a similar predictive potential to unambiguously assign thousands of miRNA-mRNA pairs from AGO1 interaction data at unprecedented depth, achieving higher signal-to-noise ratios than with computational methods alone. Quantitative RNA-seq and sub-codon resolution ribosomal footprinting data upon AGO1 depletion enabled the determination of miRNA-mediated effects on target expression and translation. We thus provide the first comprehensive resource of miRNA target sites and their quantitative functional impact in Drosophila.

Deciphering human ribonucleoprotein regulatory networks.

RNA-binding proteins (RBPs) control and coordinate each stage in the life cycle of RNAs. Although in vivo binding sites of RBPs can now be determined genome-wide, most studies typically focused on individual RBPs. Here, we examined a large compendium of 114 high-quality transcriptome-wide in vivo RBP-RNA cross-linking interaction datasets generated by the same protocol in the same cell line and representing 64 distinct RBPs. Comparative analysis of categories of target RNA binding preference, sequence preference, and transcript region specificity was performed, and identified potential posttranscriptional regulatory modules, i.e. specific combinations of RBPs that bind to specific sets of RNAs and targeted regions. These regulatory modules represented functionally related proteins and exhibited distinct differences in RNA metabolism, expression variance, as well as subcellular localization. This integrative investigation of experimental RBP-RNA interaction evidence and RBP regulatory function in a human cell line will be a valuable resource for understanding the complexity of post-transcriptional regulation.

omniCLIP: probabilistic identification of protein-RNA interactions from CLIP-seq data.

CLIP-seq methods allow the generation of genome-wide maps of RNA binding protein - RNA interaction sites. However, due to differences between different CLIP-seq assays, existing computational approaches to analyze the data can only be applied to a subset of assays. Here, we present a probabilistic model called omniCLIP that can detect regulatory elements in RNAs from data of all CLIP-seq assays. omniCLIP jointly models data across replicates and can integrate background information. Therefore, omniCLIP greatly simplifies the data analysis, increases the reliability of results and paves the way for integrative studies based on data from different assays.

The mRNA-bound proteome of the early fly embryo.

Early embryogenesis is characterized by the maternal to zygotic transition (MZT), in which maternally deposited messenger RNAs are degraded while zygotic transcription begins. Before the MZT, post-transcriptional gene regulation by RNA-binding proteins (RBPs) is the dominant force in embryo patterning. We used two mRNA interactome capture methods to identify RBPs bound to polyadenylated transcripts within the first 2 h of Drosophila melanogaster embryogenesis. We identified a high-confidence set of 476 putative RBPs and confirmed RNA-binding activities for most of 24 tested candidates. Most proteins in the interactome are known RBPs or harbor canonical RBP features, but 99 exhibited previously uncharacterized RNA-binding activity. mRNA-bound RBPs and TFs exhibit distinct expression dynamics, in which the newly identified RBPs dominate the first 2 h of embryonic development. Integrating our resource with in situ hybridization data from existing databases showed that mRNAs encoding RBPs are enriched in posterior regions of the early embryo, suggesting their general importance in posterior patterning and germ cell maturation.

miR-184 Regulates Pancreatic ß-Cell Function According to Glucose Metabolism.

In response to fasting or hyperglycemia, the pancreatic ß-cell alters its output of secreted insulin; however, the pathways governing this adaptive response are not entirely established. Although the precise role of microRNAs (miRNAs) is also unclear, a recurring theme emphasizes their function in cellular stress responses. We recently showed that miR-184, an abundant miRNA in the ß-cell, regulates compensatory proliferation and secretion during insulin resistance. Consistent with previous studies showing miR-184 suppresses insulin release, expression of this miRNA was increased in islets after fasting, demonstrating an active role in the ß-cell as glucose levels lower and the insulin demand ceases. Additionally, miR-184 was negatively regulated upon the administration of a sucrose-rich diet in Drosophila, demonstrating strong conservation of this pathway through evolution. Furthermore, miR-184 and its target Argonaute2 remained inversely correlated as concentrations of extracellular glucose increased, underlining a functional relationship between this miRNA and its targets. Lastly, restoration of Argonaute2 in the presence of miR-184 rescued suppression of miR-375-targeted genes, suggesting these genes act in a coordinated manner during changes in the metabolic context. Together, these results highlight the adaptive role of miR-184 according to glucose metabolism and suggest the regulatory role of this miRNA in energy homeostasis is highly conserved.

Regnase-1 and Roquin Regulate a Common Element in Inflammatory mRNAs by Spatiotemporally Distinct Mechanisms.

Regnase-1 and Roquin are RNA binding proteins essential for degradation of inflammation-related mRNAs and maintenance of immune homeostasis. However, their mechanistic relationship has yet to be clarified. Here, we show that, although Regnase-1 and Roquin regulate an overlapping set of mRNAs via a common stem-loop structure, they function in distinct subcellular locations: ribosome/endoplasmic reticulum and processing-body/stress granules, respectively. Moreover, Regnase-1 specifically cleaves and degrades translationally active mRNAs and requires the helicase activity of UPF1, similar to the decay mechanisms of nonsense mRNAs. In contrast, Roquin controls translationally inactive mRNAs, independent of UPF1. Defects in both Regnase-1 and Roquin lead to large increases in their target mRNAs, although Regnase-1 tends to control the early phase of inflammation when mRNAs are more actively translated. Our findings reveal that differential regulation of mRNAs by Regnase-1 and Roquin depends on their translation status and enables elaborate control of inflammation.