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Compressed Perturb-seq: highly efficient screens for regulatory circuits using random composite perturbations

ABSTRACT: Compressed Perturb-seq: highly efficient screens for regulatory circuits using random composite perturbations

PROVIDER: PRJNA913903 | ENA |

REPOSITORIES: ENA

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Compressed Perturb-seq: highly efficient screens for regulatory circuits using random composite perturbations

Project description:Pooled CRISPR screens with single-cell RNA-seq readout (Perturb-seq) have emerged as a key technique in functional genomics, but are limited in scale by cost and combinatorial complexity. Here, we reimagine Perturb-seq’s design through the lens of algorithms applied to random, low-dimensional observations. We present compressed Perturb-seq, in which we measure multiple perturbations per cell or multiple cells per droplet, and decompress these measurements by leveraging the sparse structure of regulatory circuits. Applying compressed Perturb-seq to 598 genes in the immune response to bacterial lipopolysaccharide, we achieve the same accuracy as conventional Perturb-seq at 4 to 20-fold reduced cost, with greater power to learn genetic interactions. We identify known and novel regulators of immune responses and uncover evolutionarily constrained genes with downstream targets enriched for immune disease heritability, including many missed by existing GWAS or trans-eQTL studies. Our framework enables new scales of interrogation for a foundational method in functional genomics.

2023-01-01 | GSE221321 | GEO

Perturb-seq: Dissecting molecular circuits with scalable single cell RNA profiling of pooled genetic screens

Project description:Methods: We create a CRISPR vector containing a polyadenylated RNA barcode and couple it with droplet scRNA-seq to get a large scale transcriptional measurements of perturbations Results: We were able to perform regulatory inference of gene function, observe nonlinear interactions, and perform downsampling analysis to show that gene signature effects can be seen with as few as 10's of cells while gene level phenotypes, depending on effects size would require 100's of cells Conclusion: Perturb-seq presents a scalable paradigm for obtaining rich genomic profiles of perturbations

2016-12-16 | GSE90063 | GEO

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Project description:We develop a system for bidirectional epigenetic editing (CRISPRai), in which orthogonal activating (CRISPRa) and repressive (CRISPRi) perturbations are applied simultaneously to multiple loci the same cell. We perform Perturb-seq, a method for single-cell RNA-seq paired with CRISPR guide RNA (gRNA) detection, on cells perturbed using CRISPRai for a panel of pairwise combinations of genes in K562 cells.

2024-03-14 | GSE220974 | GEO

Perturb-seq: Dissecting molecular circuits with scalable single cell RNA profiling of pooled genetic screens

Project description:Perturb-seq: Dissecting molecular circuits with scalable single cell RNA profiling of pooled genetic screens

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Centralized control of dynamic gene regulatory circuits governs human T cell rest and activation [Perturb-CITE-seq]

Project description:Centralized control of dynamic gene regulatory circuits governs human T cell rest and activation [Perturb-CITE-seq]

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Transcriptome-wide characterization of genetic perturbations

Project description:Single cell CRISPR screens such as Perturb-seq enable transcriptomic profiling of cellular perturbations at scale. However, the data produced by these screens are inherently noisy, 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.

2024-05-05 | GSE264667 | GEO

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

Project description: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 array which 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.

2022-09-29 | GSE213957 | GEO

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Project description:DNA storage of digital media using composite DNA

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A new pipeline SPICE identifies novel JUN-IKZF1 composite elements

Project description:Transcription factor partners can cooperatively bind to DNA composite elements to augment gene transcription. Here, we report a novel protein-DNA binding screening pipeline, termed Spacing Preference Identification of Composite Elements (SPICE), that can systematically predict protein binding partners and DNA motif spacing preferences. SPICE de novo predicted known composite elements, including AP1-IRF composite elements (AICE) and STAT5 tetramers, and also predicted a range of novel binding partners, including JUN-IKZF1 composite elements. We confirmed cooperative binding of JUN and IKZF1 to an upstream conserved noncoding region, CNS9, in the human IL10 gene, that contains a non-canonical IKZF1 site, and the activity of an IL10-luciferase reporter construct depended on both this site and the AP1 binding site within this composite element in primary B and T cells. Our findings reveal an unappreciated global association of IKZF1 and AP1, and establish SPICE as a valuable new pipeline for predicting novel transcription binding complexes.

2023-11-05 | GSE230035 | GEO

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