ReviewFrontiers in plant science2021
Applications and Major Achievements of Genome Editing in Vegetable Crops: A Review.
Review in Frontiers in plant science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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.
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.
Who cites it
7 citing papers in PubMed, 31 citations in OpenAlex.
- Genome editing in vegetable crops: a new era of sustainable agriculture.Molecular biology reports · 2025Review
- Genetic amelioration of fruit and vegetable crops to increase biotic and abiotic stress resistance through CRISPR Genome Editing.Frontiers in plant science · 2023Review
- Low-Carbohydrate High-Fat Diet: A SWOC Analysis.Metabolites · 2022Review
- Molecular Bases of Heat Stress Responses in Vegetable Crops With Focusing on Heat Shock Factors and Heat Shock Proteins.Frontiers in plant science · 2022Review
- Understanding the molecular mechanism of leaf morphogenesis in vegetable crops conduces to breeding process.Frontiers in plant science · 2022Review
- Knockout of phytoene desaturase gene using CRISPR/Cas9 in highbush blueberry.Frontiers in plant science · 2022Article
- New approaches to improve crop tolerance to biotic and abiotic stresses.Physiologia plantarum · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The emergence of genome-editing technology has allowed manipulation of DNA sequences in genomes to precisely remove or replace specific sequences in organisms resulting in targeted mutations. In plants, genome editing is an attractive method to alter gene functions to generate improved crop varieties. Genome editing is thought to be simple to use and has a lower risk of off-target effects compared to classical mutation breeding. Furthermore, genome-editing technology tools can also be applied directly to crops that contain complex genomes and/or are not easily bred using traditional methods. Currently, highly versatile genome-editing tools for precise and predictable editing of almost any locus in the plant genome make it possible to extend the range of application, including functional genomics research and molecular crop breeding. Vegetables are essential nutrient sources for humans and provide vitamins, minerals, and fiber to diets, thereby contributing to human health. In this review, we provide an overview of the brief history of genome-editing technologies and the components of genome-editing tool boxes, and illustrate basic modes of operation in representative systems. We describe the current and potential practical application of genome editing for the development of improved nutritious vegetables and present several case studies demonstrating the potential of the technology. Finally, we highlight future directions and challenges in applying genome-editing systems to vegetable crops for research and product development.
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What OpenQuestion holds
Registered trials
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.