Robust Transcriptional Activation in Plants Using Multiplexed CRISPR-Act2.0 and mTALE-Act Systems
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User-friendly tools for robust transcriptional activation of endogenous genes are highly demanded in plants. We previously showed that a dCas9-VP64 system consisting of the deactivated CRISPR-associated protein 9 (dCas9) fused with four tandem repeats of the transcriptional activator VP16 (VP64) could be used for transcriptional activation of endogenous genes in plants. In this study, we developed a second generation of vector systems for enhanced transcriptional activation in plants. We tested multiple strategies for dCas9-based transcriptional activation, and found that simultaneous recruitment of VP64 by dCas9 and a modified guide RNA scaffold gRNA2.0 (designated CRISPR-Act2.0) yielded stronger transcriptional activation than the dCas9-VP64 system. Moreover, we developed a multiplex transcription activator-like effector activation (mTALE-Act) system for simultaneous activation of up to four genes in plants. Our results suggest that mTALE-Act is even more effective than CRISPR-Act2.0 in most cases tested. In addition, we explored tissue-specific gene activation using positive feedback loops. Interestingly, our study revealed that certain endogenous genes are more amenable than others to transcriptional activation, and tightly regulated genes may cause target gene silencing when perturbed by activation probes. Hence, these new tools could be used to investigate gene regulatory networks and their control mechanisms. Assembly of multiplex CRISPR-Act2.0 and mTALE-Act systems are both based on streamlined and PCR-independent Golden Gate and Gateway cloning strategies, which will facilitate transcriptional activation applications in both dicots and monocots.
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In rice, simultaneous multigene activation is possible using the CRISPR activation (CRISPRa) system.
“In rice, simultaneous multigene activation is possible using the CRISPR activation (CRISPRa) system (Lowder et al., 2018).”
From Genetic resources and precise gene editing for targeted improvement of barley abiotic stress tolerance (2023) · cites this paper as Lowder et al., 2018
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- Authors
- Lowder, L. G., Zhou, J., Zhang, Y., Malzahn, A., Zhong, Z., Hsieh, T.-F., Voytas, D. F., Zhang, Y., & Qi, Y.
- Affiliations
- East Carolina University (US)
- University of Electronic Science and Technology of China (CN)
- University of Maryland, College Park (US)
- North Carolina State University (US)
- University of Minnesota (US)
- Corresponding author
- Qi, Yiping
- Venue
- Molecular Plant
- Publisher
- Elsevier BV
- Published
- 2018-02
- Volume
- 11
- Issue
- 2
- Pages
- 245-256
- ISSN
- 1674-2052 (ISSN-L)
- OpenAlex
- W2768119869
- Cited by
- 232
- References
- 81
- Citations by year
- 2026: 20 · 2025: 22 · 2024: 13 · 2023: 28 · 2022: 45 · 2021: 29 · 2020: 32 · 2019: 36 · 2018: 7
- FWCI
- 8.37
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Molecular Plant (publishedVersion)
- PubMed (publishedVersion)
- Funders
- East Carolina University
- University of Maryland-College Park
- North Carolina Biotechnology Center
- Syngenta Biotechnology (2016-CFG-8003)
- Sichuan Youth Science and Technology Foundation (2017JQ0005)
- National Science Foundation of China (31771486)
- Fundamental Research Funds for the Central Universities (ZYGX2016J119)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › CRISPR and Genetic Engineering
- Life Sciences › Agricultural and Biological Sciences › Plant Science › Plant Molecular Biology Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Biotechnology › Transgenic Plants and Applications
- Keywords
- transcriptional activation, transcription activator-like effectors, positive feedback loop, gene regulatory networks, Golden Gate cloning, Gateway cloning, plant genome editing
- MeSH terms
- Transcription Factors, Transcriptional Activation, Gene Expression Regulation, Plant, Clustered Regularly Interspaced Short Palindromic Repeats, CRISPR-Cas Systems
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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