Discovery of target genes and pathways at GWAS loci by pooled single-cell CRISPR screens

Morris, John A.; Caragine, Christina M.; Daniloski, Zharko; Domingo, Júlia; Barry, Timothy; Lu, Lu; Davis, Kyrie; Ziosi, Marcello; Glinos, Dafni A.; Hao, Stephanie; Mimitou, Eleni P.; Smibert, Peter; Roeder, Kathryn; Katsevich, Eugene; Lappalainen, Tuuli; Sanjana, Neville E.

doi:10.1126/science.adh7699

Cited by 74 publications

(50 citation statements)

References 126 publications

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“…Furthermore, it is unclear how required H3K9me3 is for disruption of CTCF binding. A recent study demonstrated better enhancer and promoter targeting with a KRAB-dCas9-MeCP2 system than with KRAB-dCas9 alone 38 , suggesting the importance of the repressive marks. In this work we targeted TF binding motifs directly, making it plausible that steric hindrance also contributed to TF displacement from chromatin.…”

Section: Discussionmentioning

confidence: 99%

Multi-locus CRISPRi targeting with a single truncated guide RNA

Moore,

Wekhande,

Issner

et al. 2023

Preprint

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A critical goal in functional genomics is evaluating which non-coding elements contribute to gene expression, cellular function, and disease. Functional characterization remains a challenge due to the abundance and complexity of candidate elements. Here, we develop a CRISPRi-based approach for multi-locus screening of putative transcription factor binding sites with a single truncated guide. A truncated guide with hundreds of sequence match sites can reliably disrupt enhancer activity, which expands the targeting scope of CRISPRi while maintaining repressive efficacy. We screen over 13,000 possible CTCF binding sites with 24 guides at 10 nucleotides in spacer length. These truncated guides direct CRISPRi-mediated deposition of repressive H3K9me3 marks and disrupt transcription factor binding at most sequence match target sites. This approach is valuable for elucidating functional transcription factor binding motifs or other repeated genomic sequences and is easily implementable with existing tools.

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Section: Discussionmentioning

confidence: 99%

Multi-locus CRISPRi targeting with a single truncated guide RNA

Moore,

Wekhande,

Issner

et al. 2023

Preprint

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“…To study pathway activity across multiple biological contexts, we aimed to perform Perturb-seq experiments in six different cancer cell lines from different tissues of origin: A549 (lung), MCF7 (breast), HT29 (colon), HAP1 (bone marrow), BxPC3 (pancreas), and K562 (bone marrow). To facilitate multiplexed gene knockdown screens, we modified each of these lines to express a CRISPR interference (CRISPRi) dCas9-KRAB-MeCP2 cassette 30,31 (Supplementary Methods). To explore different environmental signaling contexts, we exposed each cell line to five distinct stimuli representing wellestablished pathway regulators, each of which has been broadly implicated in cellular responses and disease pathogenesis.…”

Section: Scalable and Flexible Perturb-seq Across Cell Lines And Cond...mentioning

confidence: 99%

Systematic reconstruction of molecular pathway signatures using scalable single-cell perturbation screens

Jiang,

Dalgarno,

Papalexi

et al. 2024

Preprint

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Recent advancements in functional genomics have provided an unprecedented ability to measure diverse molecular modalities, but learning causal regulatory relationships from observational data remains challenging. Here, we leverage pooled genetic screens and single cell sequencing (i.e. Perturb-seq) to systematically identify the targets of signaling regulators in diverse biological contexts. We demonstrate how Perturb-seq is compatible with recent and commercially available advances in combinatorial indexing and next-generation sequencing, and perform more than 1,500 perturbations split across six cell lines and five biological signaling contexts. We introduce an improved computational framework (Mixscale) to address cellular variation in perturbation efficiency, alongside optimized statistical methods to learn differentially expressed gene lists and conserved molecular signatures. Finally, we demonstrate how our Perturb-seq derived gene lists can be used to precisely infer changes in signaling pathway activation for in-vivo and in-situ samples. Our work enhances our understanding of signaling regulators and their targets, and lays a computational framework towards the data-driven inference of an 'atlas' of perturbation signatures.

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“…For example, massively parallel CRISPR screens have been used to systematically disrupt noncoding GWAS loci, coupled with single-cell transcriptomics and proteomics to understand cis and trans-acting gene regulatory networks; similar approaches could likely be applied to vascular traits. 88 As multiomics technology continues to evolve, we anticipate that single-cell CRISPR screening will increasingly be combined with epigenomic, proteomic, and metabolomic readouts to holistically probe the molecular consequences of various single and combinatorial gene perturbations.…”

Section: Experimental Approaches For Target Validation Phenotypic Scr...mentioning

confidence: 99%

Using Genomics to Identify Novel Therapeutic Targets for Aortic Disease

Raghavan,

Pirruccello,

Ellinor

et al. 2024

ATVB

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Aortic disease, including dissection, aneurysm, and rupture, carries significant morbidity and mortality and is a notable cause of sudden cardiac death. Much of our knowledge regarding the genetic basis of aortic disease has relied on the study of individuals with Mendelian aortopathies and, until recently, the genetic determinants of population-level variance in aortic phenotypes remained unclear. However, the application of machine learning methodologies to large imaging datasets has enabled researchers to rapidly define aortic traits and mine dozens of novel genetic associations for phenotypes such as aortic diameter and distensibility. In this review, we highlight the emerging potential of genomics for identifying causal genes and candidate drug targets for aortic disease. We describe how deep learning technologies have accelerated the pace of genetic discovery in this field. We then provide a blueprint for translating genetic associations to biological insights, reviewing techniques for locus and cell type prioritization, high-throughput functional screening, and disease modeling using cellular and animal models of aortic disease.

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Discovery of target genes and pathways at GWAS loci by pooled single-cell CRISPR screens

Cited by 74 publications

References 126 publications

Multi-locus CRISPRi targeting with a single truncated guide RNA

Multi-locus CRISPRi targeting with a single truncated guide RNA

Systematic reconstruction of molecular pathway signatures using scalable single-cell perturbation screens

Using Genomics to Identify Novel Therapeutic Targets for Aortic Disease

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