Cookies?
Library Header Image
LSE Research Online LSE Library Services

Massively parallel characterization of CRISPR activator efficacy in human induced pluripotent stem cells and neurons

Wu, Qianxin, Wu, Junjing, Abdul Karim, Muhammad Kaiser, Chen, Xi, Wang, Tengyao ORCID: 0000-0003-2072-6645, Iwama, Sho, Carobbio, Stefania, Keen, Peter, Vidal-Puig, Antonio, Kotter, Mark R. and Bassett, Andrew (2023) Massively parallel characterization of CRISPR activator efficacy in human induced pluripotent stem cells and neurons. Molecular Cell, 83 (7). 1125 - 1139. ISSN 1097-2765

[img] Text (Massively parallel characterization of CRISPR activator efficacy in human induced pluripotent stem cells and neuron) - Published Version
Available under License Creative Commons Attribution.

Download (37MB)

Identification Number: 10.1016/j.molcel.2023.02.011

Abstract

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.

Item Type: Article
Official URL: https://www.cell.com/molecular-cell/home
Additional Information: © 2023 The Authors
Divisions: Statistics
Subjects: Q Science > QH Natural history > QH426 Genetics
Q Science > QH Natural history > QH301 Biology
Q Science
Date Deposited: 09 Mar 2023 10:33
Last Modified: 28 Oct 2024 07:33
URI: http://eprints.lse.ac.uk/id/eprint/118367

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics