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Application of new breeding techniques in fruit trees

Abstract Climate change and rapid adaption of invasive pathogens pose a constant pressure on the fruit industry to develop improved varieties. Aiming to accelerate the development of better-adapted cultivars, new breeding techniques have emerged as a promising alternative to meet the demand of a growing global population. Accelerated breeding, cisgenesis, and CRISPR/Cas genome editing hold significant potential for crop trait improvement and have proven to be useful in several plant species. This review focuses on the successful application of these technologies in fruit trees to confer pathogen resistance and tolerance to abiotic stress and improve quality traits. In addition, we review the optimization and diversification of CRISPR/Cas genome editing tools applied to fruit trees, such as multiplexing, CRISPR/Cas-mediated base editing and site-specific recombination systems. Advances in protoplast regeneration and delivery techniques, including the use of nanoparticles and viral-derived replicons, are described for the obtention of exogenous DNA-free fruit tree species. The regulatory landscape and broader social acceptability for cisgenesis and CRISPR/Cas genome editing are also discussed. Altogether, this review provides an overview of the versatility of applications for fruit crop improvement, as well as current challenges that deserve attention for further optimization and potential implementation of new breeding techniques.
- 4science Italy
- Stellenbosch University South Africa
- University of Trento Italy
- University of Trento Italy
- Fondazione Edmund Mach Italy
Gene Editing, Settore AGR/07 - GENETICA AGRARIA, 570, Plant Breeding, Fruit, Climate Change, 630, Trees
Gene Editing, Settore AGR/07 - GENETICA AGRARIA, 570, Plant Breeding, Fruit, Climate Change, 630, Trees
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).9 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
