Dataset Information

In Vivo Target Gene Activation via CRISPR/Cas9-Mediated Trans-epigenetic Modulation.

ABSTRACT: Current genome-editing systems generally rely on inducing DNA double-strand breaks (DSBs). This may limit their utility in clinical therapies, as unwanted mutations caused by DSBs can have deleterious effects. CRISPR/Cas9 system has recently been repurposed to enable target gene activation, allowing regulation of endogenous gene expression without creating DSBs. However, in vivo implementation of this gain-of-function system has proven difficult. Here, we report a robust system for in vivo activation of endogenous target genes through trans-epigenetic remodeling. The system relies on recruitment of Cas9 and transcriptional activation complexes to target loci by modified single guide RNAs. As proof-of-concept, we used this technology to treat mouse models of diabetes, muscular dystrophy, and acute kidney disease. Results demonstrate that CRISPR/Cas9-mediated target gene activation can be achieved in vivo, leading to measurable phenotypes and amelioration of disease symptoms. This establishes new avenues for developing targeted epigenetic therapies against human diseases. VIDEO ABSTRACT.

SUBMITTER: Liao HK

PROVIDER: S-EPMC5732045 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature

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In Vivo Target Gene Activation via CRISPR/Cas9-Mediated Trans-epigenetic Modulation.

Liao Hsin-Kai HK Hatanaka Fumiyuki F Araoka Toshikazu T Reddy Pradeep P Wu Min-Zu MZ Sui Yinghui Y Yamauchi Takayoshi T Sakurai Masahiro M O'Keefe David D DD Núñez-Delicado Estrella E Guillen Pedro P Campistol Josep M JM Wu Cheng-Jang CJ Lu Li-Fan LF Esteban Concepcion Rodriguez CR Izpisua Belmonte Juan Carlos JC

Cell 20171207 7

Current genome-editing systems generally rely on inducing DNA double-strand breaks (DSBs). This may limit their utility in clinical therapies, as unwanted mutations caused by DSBs can have deleterious effects. CRISPR/Cas9 system has recently been repurposed to enable target gene activation, allowing regulation of endogenous gene expression without creating DSBs. However, in vivo implementation of this gain-of-function system has proven difficult. Here, we report a robust system for in vivo activ ...[more]

PMID: 29224783

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Project description:BackgroundA common issue in CRISPR-Cas9 genome editing is off-target activity, which prevents the widespread use of CRISPR-Cas9 in medical applications. Among other factors, primary chromatin structure and epigenetics may influence off-target activity.MethodsIn this work, we utilize crisprSQL, an off-target database, to analyze the effect of 19 epigenetic descriptors on CRISPR-Cas9 off-target activity. Termed as 19 epigenetic features/scores, they consist of 6 experimental epigenetic and 13 computed nucleosome organization-related features. In terms of novel features, 15 of the epigenetic scores are newly considered. The 15 newly considered scores consist of 13 freshly computed nucleosome occupancy/positioning scores and 2 experimental features (MNase and DRIP). The other 4 existing scores are experimental features (CTCF, DNase I, H3K4me3, RRBS) commonly used in deep learning models for off-target activity prediction. For data curation, MNase was aggregated from existing experimental nucleosome occupancy data. Based on the sequence context information available in crisprSQL, we also computed nucleosome occupancy/positioning scores for off-target sites.ResultsTo investigate the relationship between the 19 epigenetic features and off-target activity, we first conducted Spearman and Pearson correlation analysis. Such analysis shows that some computed scores derived from training-based models and training-free algorithms outperform all experimental epigenetic features. Next, we evaluated the contribution of all epigenetic features in two successful machine/deep learning models which predict off-target activity. We found that some computed scores, unlike all 6 experimental features, significantly contribute to the predictions of both models. As a practical research contribution, we make the off-target dataset containing all 19 epigenetic features available to the research community.ConclusionsOur comprehensive computational analysis helps the CRISPR-Cas9 community better understand the relationship between epigenetic features and CRISPR-Cas9 off-target activity.

Dataset Information

In Vivo Target Gene Activation via CRISPR/Cas9-Mediated Trans-epigenetic Modulation.

Publications

In Vivo Target Gene Activation via CRISPR/Cas9-Mediated Trans-epigenetic Modulation.

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