Evidence map›Paper›PMID 41802064›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2026

Elucidating the design principles for engineering plant organ size.

Tawni Bull, Jared Van Blair, Sam Sutton, Hadley Colwell, Arjun Khakhar

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. The Promise of Synthetic Biology for Redesigning Plant Architecture.International journal of molecular sciences · 2026
    Review
  2. Article
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

5 authors.

Tawni BullDepartment of Biology, Colorado State University, Fort Collins, CO 80521.ORCID 0000-0001-9382-1075
Jared Van BlairDepartment of Biology, Colorado State University, Fort Collins, CO 80521.
Sam SuttonDepartment of Biology, Colorado State University, Fort Collins, CO 80521.
Hadley ColwellDepartment of Biology, Colorado State University, Fort Collins, CO 80521.ORCID 0009-0003-2396-2675
Arjun KhakharDepartment of Biology, Colorado State University, Fort Collins, CO 80521.ORCID 0000-0002-4676-6533

Funding

NSF (NSF) 2310396NSF (NSF) DBI-2019674
6 · The paper itself

Abstract

Enhancements to crop morphology, such as the semidwarfing that helped drive the green revolution, are often driven by changes in gene expression. These are challenging to translate across species, which slows the rate of crop improvement. Synthetic transcription factors (SynTFs) offer a rapid alternative to generate targeted alterations to gene expression. However, the complexity of developmental pathways makes it unclear how to best apply them to predictably engineer morphology. In this work, we explore whether mathematical modeling can guide SynTF-based gene expression modulation to help elucidate the design principles of engineering organ size. We targeted genes in the phytohormone, gibberellin (GA), signaling pathway, which is a central regulator of cell expansion. We demonstrate that modulation of GA signaling gene expression can generate consistent dwarfing across tissues and environments in

Indexed as

ArabidopsisArabidopsis ProteinsGene Expression Regulation, PlantGibberellinsModels, BiologicalOrgan SizePlant Growth RegulatorsPlants, Genetically ModifiedSignal TransductionTranscription FactorsArabidopsis ProteinsGibberellinsPlant Growth RegulatorsTranscription FactorsGibberellin signalingmathematical modelingplant organ sizesynthetic biologysynthetic transcription factors

Identifiers

PMID41802064
PMCPMC12994204

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.