ReviewPlants (Basel, Switzerland)2023
Recent Trends and Advancements in CRISPR-Based Tools for Enhancing Resistance against Plant Pathogens.
Review in Plants (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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
11 citing papers in PubMed, 19 citations in OpenAlex.
- Predicted protein-protein interactions between sugar beet root maggot trypsins and sugar beet Kunitz trypsin inhibitors using deep learning.Data in brief · 2026Article
- Deep learning analysis of soybean cyst nematode effectors to proven soybean resistance genes and homolog identification in the sugar beet-sugar beet root maggot plant pathosystem.Data in brief · 2026Article
- Deep learning analysis of sugar beet (Data in brief · 2026Article
- Molecular mechanisms and evolutionary adaptations of transporters for photosynthates and specialized metabolites in plants.Plant cell reports · 2026Review
- Fostering plant protection against certain bacterial diseases through quorum-sensing signal molecules: a critical review.Frontiers in plant science · 2025Review
- Advances in Research on Southern Corn Rust, a Devasting Fungal Disease.International journal of molecular sciences · 2024Review
- Use of CRISPR Technology in Gene Editing for Tolerance to Biotic Factors in Plants: A Systematic Review.Current issues in molecular biology · 2024Review
- The annotation of genomic dataset sequences of the sugar beet root maggotData in brief · 2024Article
- AData in brief · 2024Article
- Improving the Traits ofPlants (Basel, Switzerland) · 2024Review
- Unveiling the Genetic Symphony: Harnessing CRISPR-Cas Genome Editing for Effective Insect Pest Management.Plants (Basel, Switzerland) · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors at 6 institutions in 5 countries.
Funding
Abstract
Targeted genome editing technologies are becoming the most important and widely used genetic tools in studies of phytopathology. The "clustered regularly interspaced short palindromic repeats (CRISPR)" and its accompanying proteins (Cas) have been first identified as a natural system associated with the adaptive immunity of prokaryotes that have been successfully used in various genome-editing techniques because of its flexibility, simplicity, and high efficiency in recent years. In this review, we have provided a general idea about different CRISPR/Cas systems and their uses in phytopathology. This review focuses on the benefits of knock-down technologies for targeting important genes involved in the susceptibility and gaining resistance against viral, bacterial, and fungal pathogens by targeting the negative regulators of defense pathways of hosts in crop plants via different CRISPR/Cas systems. Moreover, the possible strategies to employ CRISPR/Cas system for improving pathogen resistance in plants and studying plant-pathogen interactions have been discussed.
Indexed as
Identifiers
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.