Massively parallel characterization of CRISPR activator efficacy in human induced pluripotent stem cells and neurons.
CRISPR activation (CRISPRa) is an important tool to perturb transcription, but its effectiveness varies between target genes. We employ human pluripotent stem cells with thousands of randomly integrated barcoded reporters to assess epigenetic features that influence CRISPRa efficacy. Basal expressio...
| Autores: | , , , , , , , , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2023 |
| País: | España |
| Institución: | Centro de Investigación Principe Felipe (CIPF) |
| Repositorio: | r-CIPF. Repositorio Institucional Producción Científica del Centro de Investigación Principe Felipe (CIPF) |
| OAI Identifier: | oai:cipf.fundanetsuite.com:p4116 |
| Acceso en línea: | https://cipf.fundanetsuite.com/Publicaciones/ProdCientif/PublicacionFrw.aspx?id=4116 |
| Access Level: | acceso abierto |
| Palabra clave: | CRISPR activation, CRISPRa, VPR, chromatin, epigenetic, hiPSC, iNeurons, p300, single cell, stem cells |
| Sumario: | CRISPR activation (CRISPRa) is an important tool to perturb transcription, but its effectiveness varies between target genes. We employ human pluripotent stem cells with thousands of randomly integrated barcoded reporters to assess epigenetic features that influence CRISPRa efficacy. Basal expression levels are influenced by genomic context and dramatically change during differentiation to neurons. Gene activation by dCas9-VPR is successful in most genomic contexts, including developmentally repressed regions, and activation level is anti-correlated with basal gene expression, whereas dCas9-p300 is ineffective in stem cells. Certain chromatin states, such as bivalent chromatin, are particularly sensitive to dCas9-VPR, whereas constitutive heterochromatin is less responsive. We validate these rules at endogenous genes and show that activation of certain genes elicits a change in the stem cell transcriptome, sometimes showing features of differentiated cells. Our data provide rules to predict CRISPRa outcome and highlight its utility to screen for factors driving stem cell differentiation. |
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