Evidence map›Paper›PMID 41354981›Full record

ReviewProtoplasma2026

Precision editing to improve fruit traits: CRISPR/Cas into the picture.

Tuyelee Das, Tanay Barman, Ashish Prasad

Abstract readReview
PubMed Publisher
In one paragraph

Review in Protoplasma, 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

3 authors.

Tuyelee DasUniversity Centre of Research and Development, Chandigarh University, Mohali, Punjab, 140413, India.
Tanay BarmanCentre of Excellence on Sustainable Land Management, Indian Council of Forestry Research and Education, Dehradun, India.
Ashish PrasadDepartment of Botany, Kurukshetra University, Kurukshetra, India. ashishprasad0411@kuk.ac.in.ORCID http://orcid.org/0000-0002-6682-4294

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Crop growth, quality, and yield can be adversely affected by various biotic and abiotic stresses. Crop characteristics can be improved with conventional breeding and other variation-based breeding strategies. However, these strategies are time as well as resource consuming and to overcome this, novel approaches are necessary. CRISPR/Cas technique allows to improve desired traits more efficiently and accurately by targeting specific genes. Genome editing has become more versatile with CRISPR/Cas systems and is a valuable tool to protect food security by developing commercial crops optimized for yield and nutritional quality. Researchers are able to target and edit stress response pathway genes to develop crops with increased tolerance to stress. A lack of regeneration protocols and sufficient genome sequencing data has restricted fruit editing to only a few fruits (tomatoes, citrus, apple, kiwi, banana, grapes, strawberries, watermelon, etc.). This review is focused on CRISPR/Cas applications on the nutritional aspects of fruit engineering along with the challenges and opportunities. Another aspect which will be covered is the use of CRISPR/Cas technology to improve fruit resilience to biotic and abiotic stress, but not at the cost of yield. We discuss the pros and cons of using this technology, such as unintended effects on fruit traits or public concerns about GMOs. We conclude that the application of CRISPR/Cas9 technology has the potential to be of great benefit to the agricultural industry not only to improve nutritional aspects but also to help reduce crop losses.

Indexed as

CRISPR-Cas SystemsFruitGene EditingCrops, AgriculturalPlant BreedingCRISPR/Cas9Fruit breedingGenome editingMetabolic engineeringSecondary metabolitesTrait improvement

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.