Evidence map›Paper›PMID 42645592›Full record

ReviewPlant cell reports2026

Synthetic transcriptional repression systems in plants.

Lindsey A Clark, Alexander C Pfotenhauer, Scott C Lenaghan, C Neal Stewart

Abstract readReview
PubMed Publisher
In one paragraph

Review in Plant cell reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Lindsey A ClarkCenter for Agricultural Synthetic Biology, The University of Tennessee, Knoxville, TN, USA.
Alexander C PfotenhauerCenter for Agricultural Synthetic Biology, The University of Tennessee, Knoxville, TN, USA.
Scott C LenaghanCenter for Agricultural Synthetic Biology, The University of Tennessee, Knoxville, TN, USA.
C Neal StewartCenter for Agricultural Synthetic Biology, The University of Tennessee, Knoxville, TN, USA. nealstewart@utk.edu.ORCID http://orcid.org/0000-0003-3026-9193

Funding

Defense Advanced Research Projects Agency D24AC00001
6 · The paper itself

Abstract

Transcriptional repression is a fundamental regulatory mechanism that enables precise control of gene expression in response to developmental signals and environmental stimuli. Synthetic biology can leverage this process within plants to engineer programmable transgene repression systems. This review examines strategies for harnessing prokaryotic repressors in eukaryotic systems to develop synthetic repression systems in plants. These systems utilize modular promoter and repressor architectures that can be tuned through operator placement and repression-domain fusion, respectively, to adjust transcriptional regulation. Chemically dependent inducibility can also be introduced either through use of native derepression mechanisms of the prokaryotic repressors or the incorporation of ligand-binding domains. Finally, this review explores key challenges in designing synthetic repression systems, including kinetics constraints, balancing ON and OFF states, and differences between transient and transgenic expression contexts. Overall, this review highlights modular design frameworks for tunable transgene expression in plants.

Indexed as

Gene Expression Regulation, PlantPlantsSynthetic BiologyTranscription, GeneticPlants, Genetically ModifiedPromoter Regions, GeneticRepressor ProteinsTranscription FactorsTransgenesRepressor ProteinsTranscription FactorsRepression domainsSynthetic biologySynthetic promotersSynthetic transcription factorsTranscriptional regulation

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.