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Coupled single-cell epigenome editing and profiling reveals causal gene regulatory networks [Perturb-ATAC (GBC/sgRNA)]

ABSTRACT: Coupled single-cell epigenome editing and profiling reveals causal gene regulatory networks [Perturb-ATAC (GBC/sgRNA)]

PROVIDER: PRJNA478048 | ENA |

REPOSITORIES: ENA

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Coupled single-cell epigenome editing and profiling reveals causal gene regulatory networks [Perturb-ATAC (GBC/sgRNA)]

Project description:Here we present Perturb-ATAC, a method which combines multiplexed CRISPR interference or knockout with genome-wide chromatin accessibility profiling in single cells, based on the simultaneous detection of CRISPR guide RNAs and open chromatin sites by Assay of Transposase-accessible Chromatin with sequencing (ATAC-seq). We applied Perturb-ATAC to transcription factors (TFs), chromatin-modifying factors, and noncoding RNAs (ncRNAs) in ~3,700 single cells, encompassing more than 75 unique genotype-phenotype relationships.

2018-12-20 | GSE116285 | GEO

Coupled single-cell epigenome editing and profiling reveals causal gene regulatory networks [Perturb-ATAC (ATAC)]

Project description:Coupled single-cell epigenome editing and profiling reveals causal gene regulatory networks [Perturb-ATAC (ATAC)]

| PRJNA478045 | ENA

Coupled single-cell epigenome editing and profiling reveals causal gene regulatory networks [Perturb-ATAC (ATAC)]

2018-12-20 | GSE116249 | GEO

Coupled single-cell epigenome editing and profiling reveals causal gene regulatory networks [scATAC-seq]

2018-12-20 | GSE116248 | GEO

Coupled single-cell epigenome editing and profiling reveals causal gene regulatory networks [Bulk ATAC-seq]

2018-12-20 | GSE116247 | GEO

Coupled single-cell epigenome editing and profiling reveals causal gene regulatory networks [scATAC-seq]

Project description:Coupled single-cell epigenome editing and profiling reveals causal gene regulatory networks [scATAC-seq]

| PRJNA478037 | ENA

Coupled single-cell epigenome editing and profiling reveals causal gene regulatory networks [Bulk ATAC-seq]

Project description:Coupled single-cell epigenome editing and profiling reveals causal gene regulatory networks [Bulk ATAC-seq]

| PRJNA478036 | ENA

Comparison of dual sgRNA library versus Dolcetto by Perturb-seq

Project description:CRISPR interference (CRISPRi) genetic screens use programmable repression of gene expression to systematically explore questions in cell biology and genetics. However, wider adoption of CRISPRi screening has been constrained by the large size of single guide RNA (sgRNA) libraries and lack of consensus on the choice of CRISPRi effector proteins. Here, we address these challenges to present next-generation CRISPRi sgRNA libraries and effectors. First, we combine empiric sgRNA selection with a dual sgRNA library design to generate an ultra-compact, highly active CRISPRi sgRNA library. Next, we rigorously compare CRISPRi effectors to show that the recently published Zim3-dCas9 provides an optimal balance between strong on-target knockdown and minimal nonspecific effects on cell growth or the transcriptome. Finally, we engineer a suite of cell lines which stably express Zim3-dCas9 and demonstrate robust on-target knockdown across these cell lines. Our results and publicly available reagents establish best practices for CRISPRi genetic screening.

2022-06-04 | GSE205310 | GEO

Coupled single-cell CRISPR screening and epigenomic profiling reveals causal gene regulatory networks

Project description:Coupled single-cell CRISPR screening and epigenomic profiling reveals causal gene regulatory networks

| PRJNA478043 | ENA

Perturb-map coupled with spatial transcriptomics identifies mutation associated gene signatures in a mouse model of lung adenocarcinoma

Project description:The cellular architecture of a tumor has a major impact on cancer outcome, and thus there is interest in identifying genes controlling the tumor microenvironment (TME). While CRISPR screens are helping uncover genes regulating many cell-intrinsic processes, existing approaches are suboptimal for identifying gene functions operating extracellularly or within a tissue context. To address this, we developed an approach for spatial functional genomics called Perturb-map, which utilizes protein barcodes (Pro-Code) to enable spatial detection of barcoded cells within tissue. We applied Perturb-map to knockout dozens of genes in parallel in a mouse model of lung cancer and simultaneously assessed how each knockout influenced tumor growth, histopathology, and immune composition. Additionally, we paired Perturb-map and spatial transcriptomics for unbiased molecular analysis of Pro-Code/CRISPR lesions. Our studies found in Tgfbr2 knockout lesions, the TME was converted to a fibro-mucinous state and T-cells excluded, concomitant with upregulated TGFb and TGFb-mediated stroma activation, suggesting Tgfbr2 loss on lung cancer cells increased TGFb bioavailability and enhanced its suppressive effects on the TME. These studies establish Perturb-map for functional genomics within a tissue at single cell-resolution with spatial architecture preserved.

2022-01-15 | GSE193460 | GEO

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