Mismatch tolerance of a gRNA for CRISPR-based gene activation confers broad activity critical for cell reprogramming

CRISPR activation and interference systems (CRISPRa/i) are widely used for programmable transcriptional control. Although these technologies are capable of highly specific single-gene activity, some applications of transcriptional network reprogramming require broad, genome-wide effects. Here, we identify a CRISPRa gRNA that robustly reprograms astrocyte transcriptional state. Unexpectedly, this activity arises from extensive off-target binding that induces expression changes in thousands of genes, unlike neighboring gRNAs targeting the same intended on-target site. We leverage this promiscuous gRNA to dissect determinants of gRNA-driven off-target dCas9 binding in the context of transcriptional reprogramming. Using ChIP-seq, high-throughput protein-binding microarrays, and gRNA-variant library screening in cells, we demonstrate that PAM-proximal bases are primary determinants of genomic binding, mismatch tolerance is both gRNA- and base-specific, and targeted mutations within the PAM-proximal region can tune gRNA specificity. We further demonstrate that CRISPRa-driven phenotypes can reflect combined contributions from widespread off-target activity and dose-dependent on-target effects. These findings highlight the potentially widespread impacts of CRISPRa off-target activity, underscore the need to account for cryptic effects when selecting and evaluating gRNAs for programming cell phenotypes, and demonstrate that multi-site binding by CRISPRa systems can be exploited as a feature for network-level perturbations in cell reprogramming.

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Publication Details

Journal
bioRxiv (Cold Spring Harbor Laboratory)
Published
2026-02-03
DOI
https://doi.org/10.64898/2026.02.01.703129
Primary Topic
CRISPR and Genetic Engineering
Type
article
Field-Weighted Citation Impact
0.00

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article

Mismatch tolerance of a gRNA for CRISPR-based gene activation confers broad activity critical for cell reprogramming

Dahlia Halabi, Samuel Reisman, Nicholas Sangvai, Samantha E Miller et al.
bioRxiv (Cold Spring Harbor Laboratory)
CRISPR and Genetic Engineering
article

Mismatch tolerance of a gRNA for CRISPR-based gene activation confers broad activity critical for cell reprogramming

Dahlia Halabi, Samuel Reisman, Nicholas Sangvai, Samantha E Miller, Wei Zhu, Raluca Gordan, Charles A. Gersbach, Gregory E Crawford
article en

Abstract

CRISPR activation and interference systems (CRISPRa/i) are widely used for programmable transcriptional control. Although these technologies are capable of highly specific single-gene activity, some applications of transcriptional network reprogramming require broad, genome-wide effects. Here, we identify a CRISPRa gRNA that robustly reprograms astrocyte transcriptional state. Unexpectedly, this activity arises from extensive off-target binding that induces expression changes in thousands of genes, unlike neighboring gRNAs targeting the same intended on-target site. We leverage this promiscuous gRNA to dissect determinants of gRNA-driven off-target dCas9 binding in the context of transcriptional reprogramming. Using ChIP-seq, high-throughput protein-binding microarrays, and gRNA-variant library screening in cells, we demonstrate that PAM-proximal bases are primary determinants of genomic binding, mismatch tolerance is both gRNA- and base-specific, and targeted mutations within the PAM-proximal region can tune gRNA specificity. We further demonstrate that CRISPRa-driven phenotypes can reflect combined contributions from widespread off-target activity and dose-dependent on-target effects. These findings highlight the potentially widespread impacts of CRISPRa off-target activity, underscore the need to account for cryptic effects when selecting and evaluating gRNAs for programming cell phenotypes, and demonstrate that multi-site binding by CRISPRa systems can be exploited as a feature for network-level perturbations in cell reprogramming.

bioRxiv (Cold Spring Harbor Laboratory)
University of Massachusetts Chan Medical School (US), Duke University (US), Duke Medical Center (US), Duke University Hospital (US), Applied Genetic Technologies (United States) (US)
National Science Foundation, National Institutes of Health
Openalex Percentile: Top 69%
CRISPR and Genetic Engineering
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