Multicenter integrated analysis of noncoding CRISPRi screens.

The ENCODE Consortium's efforts to annotate noncoding cis-regulatory elements (CREs) have advanced our understanding of gene regulatory landscapes. Pooled, noncoding CRISPR screens offer a systematic approach to investigate cis-regulatory mechanisms. The ENCODE4 Functional Characterization Centers conducted 108 screens in human cell lines, comprising >540,000 perturbations across 24.85 megabases of the genome. Using 332 functionally confirmed CRE-gene links in K562 cells, we established guidelines for screening endogenous noncoding elements with CRISPR interference (CRISPRi), including accurate detection of CREs that exhibit variable, often low, transcriptional effects. Benchmarking five screen analysis tools, we find that CASA produces the most conservative CRE calls and is robust to artifacts of low-specificity single guide RNAs. We uncover a subtle DNA strand bias for CRISPRi in transcribed regions with implications for screen design and analysis. Together, we provide an accessible data resource, predesigned single guide RNAs for targeting 3,275,697 ENCODE SCREEN candidate CREs with CRISPRi and screening guidelines to accelerate functional characterization of the noncoding genome.

Epigenome editing technologies for discovery and medicine.

Epigenome editing has rapidly evolved in recent years, with diverse applications that include elucidating gene regulation mechanisms, annotating coding and noncoding genome functions and programming cell state and lineage specification. Importantly, given the ubiquitous role of epigenetics in complex phenotypes, epigenome editing has unique potential to impact a broad spectrum of diseases. By leveraging powerful DNA-targeting technologies, such as CRISPR, epigenome editing exploits the heritable and reversible mechanisms of epigenetics to alter gene expression without introducing DNA breaks, inducing DNA damage or relying on DNA repair pathways.

Activation of the imprinted Prader-Willi Syndrome locus by CRISPR-based epigenome editing.

Epigenome editing with DNA-targeting technologies such as CRISPR-dCas9 can be used to dissect gene regulatory mechanisms and potentially treat associated disorders. For example, Prader-Willi Syndrome (PWS) is caused by loss of paternally expressed imprinted genes on chromosome 15q11.2-q13.3, although the maternal allele is intact but epigenetically silenced. Using CRISPR repression and activation screens in human induced pluripotent stem cells (iPSCs), we identified genomic elements that control expression of the PWS gene SNRPN from the paternal and maternal chromosomes. We showed that either targeted transcriptional activation or DNA demethylation can activate the silenced maternal SNRPN and downstream PWS transcripts. However, these two approaches function at unique regions, preferentially activating different transcript variants and involving distinct epigenetic reprogramming mechanisms. Remarkably, transient expression of the targeted demethylase leads to stable, long-term maternal SNRPN expression in PWS iPSCs. This work uncovers targeted epigenetic manipulations to reprogram a disease-associated imprinted locus and suggests possible therapeutic interventions.

Respiratory characterization of a humanized Duchenne muscular dystrophy mouse model.

Duchenne muscular dystrophy (DMD) is the most common X-linked disease. DMD is caused by a lack of dystrophin, a critical structural protein in striated muscle. Dystrophin deficiency leads to inflammation, fibrosis, and muscle atrophy. Boys with DMD have progressive muscle weakness within the diaphragm that results in respiratory failure in the 2nd or 3rd decade of life. The most common DMD mouse model - the mdx mouse - is not sufficient for evaluating genetic medicines that specifically target the human DMD (hDMD) gene sequence. Therefore, a novel transgenic mouse carrying the hDMD gene with an exon 52 deletion was created (hDMDΔ52;mdx). We characterized the respiratory function and pathology in this model using whole body plethysmography, histology, and immunohistochemistry. At 6-months-old, hDMDΔ52;mdx mice have reduced maximal respiration, neuromuscular junction pathology, and fibrosis throughout the diaphragm, which worsens at 12-months-old. In conclusion, the hDMDΔ52;mdx exhibits moderate respiratory pathology, and serves as a relevant animal model to study the impact of novel genetic therapies, including gene editing, on respiratory function.

Machine learning methods for predicting guide RNA effects in CRISPR epigenome editing experiments.

CRISPR epigenomic editing technologies enable functional interrogation of non-coding elements. However, current computational methods for guide RNA (gRNA) design do not effectively predict the power potential, molecular and cellular impact to optimize for efficient gRNAs, which are crucial for successful applications of these technologies. We present "launch-dCas9" (machine LeArning based UNified CompreHensive framework for CRISPR-dCas9) to predict gRNA impact from multiple perspectives, including cell fitness, wildtype abundance (gauging power potential), and gene expression in single cells. Our launchdCas9, built and evaluated using experiments involving >1 million gRNAs targeted across the human genome, demonstrates relatively high prediction accuracy (AUC up to 0.81) and generalizes across cell lines. Method-prioritized top gRNA(s) are 4.6-fold more likely to exert effects, compared to other gRNAs in the same cis-regulatory region. Furthermore, launchdCas9 identifies the most critical sequence-related features and functional annotations from >40 features considered. Our results establish launch-dCas9 as a promising approach to design gRNAs for CRISPR epigenomic experiments.

Proximity analysis of native proteomes reveals phenotypic modifiers in a mouse model of autism and related neurodevelopmental conditions.

One of the main drivers of autism spectrum disorder is risk alleles within hundreds of genes, which may interact within shared but unknown protein complexes. Here we develop a scalable genome-editing-mediated approach to target 14 high-confidence autism risk genes within the mouse brain for proximity-based endogenous proteomics, achieving the identification of high-specificity spatial proteomes. The resulting native proximity proteomes are enriched for human genes dysregulated in the brain of autistic individuals, and reveal proximity interactions between proteins from high-confidence risk genes with those of lower-confidence that may provide new avenues to prioritize genetic risk. Importantly, the datasets are enriched for shared cellular functions and genetic interactions that may underlie the condition. We test this notion by spatial proteomics and CRISPR-based regulation of expression in two autism models, demonstrating functional interactions that modulate mechanisms of their dysregulation. Together, these results reveal native proteome networks in vivo relevant to autism, providing new inroads for understanding and manipulating the cellular drivers underpinning its etiology.

Mechanosensitive genomic enhancers potentiate the cellular response to matrix stiffness.

Epigenetic control of cellular transcription and phenotype is influenced by changes in the cellular microenvironment, yet how mechanical cues from these microenvironments precisely influence epigenetic state to regulate transcription remains largely unmapped. Here, we combine genome-wide epigenome profiling, epigenome editing, and phenotypic and single-cell RNA-seq CRISPR screening to identify a new class of genomic enhancers that responds to the mechanical microenvironment. These 'mechanoenhancers' could be active on either soft or stiff extracellular matrix contexts, and regulated transcription to influence critical cell functions including apoptosis, mechanotransduction, proliferation, and migration. Epigenetic editing of mechanoenhancers on rigid materials tuned gene expression to levels observed on softer materials, thereby reprogramming the cellular response to the mechanical microenvironment. These editing approaches may enable the precise alteration of mechanically-driven disease states.

A humanized mouse model for adeno-associated viral gene therapy.

Clinical translation of AAV-mediated gene therapy requires preclinical development across different experimental models, often confounded by variable transduction efficiency. Here, we describe a human liver chimeric transgene-free Il2rg-/-/Rag2-/-/Fah-/-/Aavr-/- (TIRFA) mouse model overcoming this translational roadblock, by combining liver humanization with AAV receptor (AAVR) ablation, rendering murine cells impermissive to AAV transduction. Using human liver chimeric TIRFA mice, we demonstrate increased transduction of clinically used AAV serotypes in primary human hepatocytes compared to humanized mice with wild-type AAVR. Further, we demonstrate AAV transduction in human teratoma-derived primary cells and liver cancer tissue, displaying the versatility of the humanized TIRFA mouse. From a mechanistic perspective, our results support the notion that AAVR functions as both an entry receptor and an intracellular receptor essential for transduction. The TIRFA mouse should allow prediction of AAV gene transfer efficiency and the study of AAV vector biology in a preclinical human setting.