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Plant pathogens represent a significant threat to crop production worldwide, as they can substantially reduce crop yield and quality, strongly impacting food safety. In the ongoing co-evolution between plants and pathogens, the emergence of new virulent strains is accelerated by current climate changes, resulting in the breakdown of established resistance genes in crop varieties. Furthermore, due to shifts in climate conditions, pathogens are able to spread to regions where they were previously absent. Agronomic management practices can help control pathogen attacks and their effects on crop performance, but chemical applications are not fully effective, and their use limits the environmental sustainability of agriculture. Therefore, developing genetically resistant varieties remains the most effective and environmentally friendly approach. Achieving this goal depends on a thorough understanding of the genetic basis of the plant-pathogen interaction.

Plant resistance to a pathogen can be complete, usually controlled by a single resistance gene, according to the gene-for-gene theory, in which one resistance gene in the host interacts with one avirulence gene in the pathogen. This interaction prevents infection due to an incompatible disease reaction in the host. Alternatively, quantitative disease resistance is characterized by a reduced—though not entirely prevented—disease response. Complete resistance based on gene-for-gene interactions is typically effective against one or a few isolates and can be overcome by single mutations in the pathogen, while quantitative resistance is more difficult for pathogens to overcome because it is often governed by the action of multiple genes and is effective against many isolates or pathogens. Nevertheless, so-called “magic genes”—single genes that are effective against all known isolates of different pathogen species—have been identified as a very promising tool for resistance breeding.

The objective of this Research Topic is to gather articles that update the status of new technologies in breeding for disease resistance. The aim is to provide an updated view of the science behind breeding for resistance and highlight the most recent and advanced tools that have become available in recent years. Topics of interest include:

• Use of genetic diversity and mapping populations to identify genomic loci controlling resistance, such as association mapping using genome-wide association (GWAS), nested association mapping (NAM), and multi-parent advanced generation intercross (MAGIC).

• Functional analysis of candidate genes (identification and analysis of mutants, knock-out or over-expressing lines)

• Identification of quantitative trait loci (QTLs) and using marker-assisted selection (MAS) and genomic selection (GS) approaches

• Use of new breeding technologies, including gene editing and cisgenesis

• New phenotyping tools aimed at increasing resolution and time-cost effectiveness in detecting disease reaction (near and remote sensing, and image analysis)

• Machine learning or artificial intelligence methods to improve both phenotyping and data analysis

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Advances in Breeding for Quantitative Disease Resistance - Volume II