Site-specific manipulation of Arabidopsis loci using CRISPR-Cas9 SunTag systems
Understanding genomic functions requires site-specific manipulation of loci via efficient protein effector targeting systems. However, few approaches for targeted manipulation of the epigenome are available in plants. Here, we adapt the dCas9-SunTag system to engineer targeted gene activation and DN...
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Published in | Nature communications Vol. 10; no. 1; pp. 729 - 11 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
London
Nature Publishing Group UK
13.02.2019
Nature Publishing Group Nature Portfolio |
Subjects | |
Online Access | Get full text |
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Summary: | Understanding genomic functions requires site-specific manipulation of loci via efficient protein effector targeting systems. However, few approaches for targeted manipulation of the epigenome are available in plants. Here, we adapt the dCas9-SunTag system to engineer targeted gene activation and DNA methylation in
Arabidopsis
. We demonstrate that a dCas9-SunTag system utilizing the transcriptional activator VP64 drives robust and specific activation of several loci, including protein coding genes and transposable elements, in diverse chromatin contexts. In addition, we present a CRISPR-based methylation targeting system for plants, utilizing a SunTag system with the catalytic domain of the
Nicotiana tabacum
DRM methyltransferase, which efficiently targets DNA methylation to specific loci, including the
FWA
promoter, triggering a developmental phenotype, and the
SUPERMAN
promoter. These SunTag systems represent valuable tools for the site-specific manipulation of plant epigenomes.
Few approaches for targeted manipulation of the epigenome are available in plants. Here, the authors adapt the dCas9-SunTag system to engineer targeted gene activation and site-specific manipulation of DNA methylation in
Arabidopsis
. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 |
ISSN: | 2041-1723 2041-1723 |
DOI: | 10.1038/s41467-019-08736-7 |