Evidence map›Paper›PMID 40373016›Full record

ArticlePloS one2025

Success and limitations in adaptation of Fast-TrACC tissue culture-independent transformation in coffee, cotton, and tree tobacco.

Boaz Negin, Laura Daniela Martin-Lesmes, Georg Jander

Abstract read
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

3 authors.

Boaz NeginBoyce Thompson Institute, Ithaca, NY, United States of America.ORCID https://orcid.org/0000-0003-1890-9848
Laura Daniela Martin-LesmesUniversidad de los Andes, Bogotá, Colombia.ORCID https://orcid.org/0009-0005-1890-9065
Georg JanderBoyce Thompson Institute, Ithaca, NY, United States of America.ORCID https://orcid.org/0000-0002-9675-934X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Plant transformation is a critical process for generating transgenic and genome-edited plants for use in research and agriculture. For most plant species, this process has traditionally involved genomic insertion of DNA in tissue culture and regeneration of transformed plants through hormonal induction. Recently, methods for plant transformation in a tissue culture-independent manner, through the expression of growth regulators, have been published. We attempted to adapt this promising approach to three woody species, coffee (Coffea arabica), cotton (Gossypium hirsutum), and tree tobacco (Nicotiana glauca), using a combination of Agrobacterium strains, plasmid systems, and different promoters driving the expression of ZmWUS2 and AtIPT, which were originally adapted for this purpose in Nicotiana benthamiana. We found that tree tobacco was amenable to tissue culture-independent transformation but had difficulty developing transgenic seeds. Coffee was not receptive to this transformation method, and cotton was amenable to callus formation but did not exhibit gene insertions in the newly-formed shoots. These limitations are partially technical, such as maize WUS not affecting coffee similarly to other plants, but are in part fundamental setbacks in the use of growth regulators to drive tissue culture-independent transformation. We suggest how these drawbacks can be overcome in the future through the use of inducible or tissue-specific promoters and other means.

Indexed as

CoffeaCoffeeGossypiumNicotianaTissue Culture TechniquesTransformation, GeneticPlants, Genetically ModifiedPromoter Regions, GeneticSeedsCoffee

Identifiers

PMID40373016
PMCPMC12080836

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.