Genome editing of susceptibility gene StDND2 enhances Phytophthora resistance in Solanum tuberosum
Monday, 22-06-2026 | 15:21
Potato (Solanum tuberosum L.) cultivation is severely constrained by multiple pathogens, among which late blight caused by the oomycete P. infestans remains the most destructive disease. Developing pathogen-resistant cultivars can enhance productivity and reduce fungicide use in potato, where R-gene-based resistance is often overcome by evolving pathogen populations. Targeting susceptibility (S) genes represents a promising alternative strategy for improving disease resistance.
Scientific news
IRRI joins global effort to modernize GHG measurement guidelines for rice
IRRI joins global effort to modernize GHG measurement guidelines for rice
The participation of the International Rice Research Institute (IRRI) in a landmark GHG Measurement Practices in Rice-Based Systems writeshop is helping advance new global guidelines for measuring greenhouse gas emissions (GHG) from rice systems, positioning the institute to play a pivotal role in future climate mitigation and monitoring, reporting, and verification (MRV) initiatives for rice.
Genome editing of susceptibility gene StDND2 enhances Phytophthora resistance in Solanum tuberosum
Genome editing of susceptibility gene StDND2 enhances Phytophthora resistance in Solanum tuberosum
Potato (Solanum tuberosum L.) cultivation is severely constrained by multiple pathogens, among which late blight caused by the oomycete P. infestans remains the most destructive disease. Developing pathogen-resistant cultivars can enhance productivity and reduce fungicide use in potato, where R-gene-based resistance is often overcome by evolving pathogen populations. Targeting susceptibility (S) genes represents a promising alternative strategy for improving disease resistance.
AI Model Maps How Gene Switches Control Plant Traits and Crop Stress Response
AI Model Maps How Gene Switches Control Plant Traits and Crop Stress Response
An international research team led by Forschungszentrum Jülich and the IPK Leibniz Institute has developed an artificial intelligence (AI) model that predicts how regulatory proteins bind to plant DNA to control gene activity. The study, published in Nature Communications, was trained on genomic data from Arabidopsis thaliana and successfully applied to crops such as maize.

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