Genome-wide programmable transcriptional memory by CRISPR-based epigenome editing

Nuñez, James K.; Jin, Chen; Pommier, Greg C.; Cogan, J. Zachery; Replogle, Joseph M.; Adriaens, Carmen; Ramadoss, Gokul N.; Shi, Quanming; Hung, King L.; Samelson, Avi J.; Pogson, Angela N; Kim, James Y. S.; Chung, Amanda; Leonetti, Manuel D.; Chang, Howard Y.; Kampmann, Martin; Bernstein, B; Hovestadt, Volker; Gilbert, Luke A.; Weissman, Jonathan S.

doi:10.1016/j.cell.2021.03.025

Cited by 357 publications

(354 citation statements)

References 68 publications

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“…DNA demethylation of the DGKA enhancer by the dCas9-VPR-TET3 system in HEK293T cells was accompanied by enrichment of the activating histone marks H3K4me1 and H3K27ac [ 54 , 55 ] and enhanced DGKA expression after irradiation. Strong synergistic effects of the VPR transactivation domain or similar activation domains and the TET enzyme have been observed [ 56 , 57 ], therefore the transcriptional activation and deposition of activating histone markers might not only be caused by demethylation and EGR1 binding but partly also due to VPR-TET3 recruitment at the demethylated DGKA enhancer. In addition, an enrichment of the repressive histone mark H3K27me3 was observed after cumate treatment.…”

Section: Discussionmentioning

confidence: 99%

Epigenetic Modulation of Radiation-Induced Diacylglycerol Kinase Alpha Expression Prevents Pro-Fibrotic Fibroblast Response

Liu

Tóth

Bakr

et al. 2021

Cancers

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Radiotherapy, a common component in cancer treatment, can induce adverse effects including fibrosis in co-irradiated tissues. We previously showed that differential DNA methylation at an enhancer of diacylglycerol kinase alpha (DGKA) in normal dermal fibroblasts is associated with radiation-induced fibrosis. After irradiation, the transcription factor EGR1 is induced and binds to the hypomethylated enhancer, leading to increased DGKA and pro-fibrotic marker expression. We now modulated this DGKA induction by targeted epigenomic and genomic editing of the DGKA enhancer and administering epigenetic drugs. Targeted DNA demethylation of the DGKA enhancer in HEK293T cells resulted in enrichment of enhancer-related histone activation marks and radiation-induced DGKA expression. Mutations of the EGR1-binding motifs decreased radiation-induced DGKA expression in BJ fibroblasts and caused dysregulation of multiple fibrosis-related pathways. EZH2 inhibitors (GSK126, EPZ6438) did not change radiation-induced DGKA increase. Bromodomain inhibitors (CBP30, JQ1) suppressed radiation-induced DGKA and pro-fibrotic marker expression. Similar drug effects were observed in donor-derived fibroblasts with low DNA methylation. Overall, epigenomic manipulation of DGKA expression may offer novel options for a personalized treatment to prevent or attenuate radiotherapy-induced fibrosis.

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Section: Discussionmentioning

confidence: 99%

Epigenetic Modulation of Radiation-Induced Diacylglycerol Kinase Alpha Expression Prevents Pro-Fibrotic Fibroblast Response

Liu

Tóth

Bakr

et al. 2021

Cancers

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“…AltumAge provides a detailed relationship between each one of 21368 CpG sites and age, showing that while most CpG sites are mostly linearly related with age, some important ones are not. Given recent advances in epigenetic editing [1], finding the sweet spot for DNA methylation to delay or reverse aging may be necessary for future interventions to tackle the disease. AltumAge allied with other deep learning inference methods can provide information on highly interacting CpG sites.…”

Section: Discussionmentioning

confidence: 99%

AltumAge: A Pan-Tissue DNA-Methylation Epigenetic Clock Based on Deep Learning

Camillo

Lapierre

Singh

2021

Preprint

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Several age predictors based on DNA methylation, dubbed epigenetic clocks, have been created in recent years. Their accuracy and potential for generalization vary widely based on the training data. Here, we gathered 143 publicly available data sets from several human tissues to develop AltumAge, a highly accurate and precise age predictor based on deep learning. Compared to Horvath's 2013 model, AltumAge performs better across both normal and malignant tissues and is more generalizable to new data sets. Interestingly, it can predict gestational week from placental tissue with low error. Lastly, we used deep learning interpretation methods to learn which methylation sites contributed to the final model predictions. We observed that while most important CpG sites are linearly related to age, some highly-interacting CpG sites can influence the relevance of such relationships. We studied the associated genes of these CpG sites and found literary evidence of their involvement in age-related gene regulation. Using chromatin annotations, we observed that the CpG sites with the highest contribution to the model predictions were related to heterochromatin and gene regulatory regions in the genome. We also found age-related KEGG pathways for genes containing these CpG sites. In general, neural networks are better predictors due to their ability to capture complex feature interactions compared to the typically used regularized linear regression. Altogether, our neural network approach provides significant improvement and flexibility to current epigenetic clocks without sacrificing model interpretability.

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“…Epigenome engineering strategies include chromatin editing, namely histone acetylation and methylation and DNA methylation [ 37 ]. Remarkably, the epigenetic changes are maintained through cell divisions [ 38 ]. Dead Cas9 proteins fused to enzymes mediating DNA methylation of repressive histone modifications established the CRISPRoff system able to silence most genes in a heritable manner.…”

Section: Extensions Of the Crispr/cas9 Systemmentioning

confidence: 99%

“…Dead Cas9 proteins fused to enzymes mediating DNA methylation of repressive histone modifications established the CRISPRoff system able to silence most genes in a heritable manner. The epigenetic modifications were even kept when human iPSCs (induced pluripotent stem cells) were differentiated into neurons [ 38 ]. In addition, the CRISPRoff tools can be used to study general rules for heritable gene silencing.…”

Section: Extensions Of the Crispr/cas9 Systemmentioning

confidence: 99%

CRISPR/Cas9: Principle, Applications, and Delivery through Extracellular Vesicles

Horodecka

Duechler

2021

IJMS

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The establishment of CRISPR/Cas9 (clustered regularly interspaced short palindromic repeats/CRISPR-associated protein 9) technology for eukaryotic gene editing opened up new avenues not only for the analysis of gene function but also for therapeutic interventions. While the original methodology allowed for targeted gene disruption, recent technological advancements yielded a rich assortment of tools to modify genes and gene expression in various ways. Currently, clinical applications of this technology fell short of expectations mainly due to problems with the efficient and safe delivery of CRISPR/Cas9 components to living organisms. The targeted in vivo delivery of therapeutic nucleic acids and proteins remain technically challenging and further limitations emerge, for instance, by unwanted off-target effects, immune reactions, toxicity, or rapid degradation of the transfer vehicles. One approach that might overcome many of these limitations employs extracellular vesicles as intercellular delivery devices. In this review, we first introduce the CRISPR/Cas9 system and its latest advancements, outline major applications, and summarize the current state of the art technology using exosomes or microvesicles for transporting CRISPR/Cas9 constituents into eukaryotic cells.

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Genome-wide programmable transcriptional memory by CRISPR-based epigenome editing

Cited by 357 publications

References 68 publications

Epigenetic Modulation of Radiation-Induced Diacylglycerol Kinase Alpha Expression Prevents Pro-Fibrotic Fibroblast Response

Epigenetic Modulation of Radiation-Induced Diacylglycerol Kinase Alpha Expression Prevents Pro-Fibrotic Fibroblast Response

AltumAge: A Pan-Tissue DNA-Methylation Epigenetic Clock Based on Deep Learning

CRISPR/Cas9: Principle, Applications, and Delivery through Extracellular Vesicles

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