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A fire blight resistance QTL explaining 34.3%-46.6% of the phenotypic variation was recently identified on linkage group 7 of apple cultivar 'Fiesta' (F7). However, markers flanking this QTL were AFLP and RAPD markers unsuitable for marker-assisted selection (MAS). Two RAPD markers bracketing the QTL have been transformed into SCAR (sequence-characterized amplified region) markers, and an SSR marker specific for the region was developed. Pedigree analysis of 'Fiesta' with these markers enabled tracking of the F7 QTL allele back to 'Cox's Orange Pippin'. Stability of the effect of this QTL allele in different backgrounds was analyzed by inoculating progeny plants of a cross between 'Milwa', a susceptible cultivar, and '1217', a moderately resistant cultivar, and a set of cultivars that carry or lack the allele conferring increased fire blight resistance. Progenies and cultivars that carried both markers were significantly more resistant than those that did not carry both markers, indicating high stability of the F7 QTL allele in different backgrounds. This stability and the availability of reproducible markers bracketing the QTL make this locus promising for use in MAS.

A major resistance quantitative trait locus, qRfg1, significantly enhances maize resistance to Gibberella stalk rot, a devastating disease caused by Fusarium graminearum. However, the underlying molecular mechanism remains unknown. We adopted a map-based cloning approach to identify the resistance gene at qRfg1 and examined the dynamic epigenetic changes during qRfg1-mediated maize resistance to the disease. A CCT domain-containing gene, ZmCCT, is the causal gene at the qRfg1 locus and a polymorphic CACTA-like transposable element (TE1) c. 2.4 kb upstream of ZmCCT is the genetic determinant of allelic variation. The non-TE1 ZmCCT allele is in a poised state, with predictive bivalent chromatin enriched for both repressive (H3K27me3/H3K9me3) and active (H3K4me3) histone marks. Upon pathogen challenge, this non-TE1 ZmCCT allele was promptly induced by a rapid yet transient reduction in H3K27me3/H3K9me3 and a progressive decrease in H3K4me3, leading to disease resistance. However, TE1 insertion in ZmCCT caused selective depletion of H3K4me3 and enrichment of methylated GC to suppress the pathogen-induced ZmCCT expression, resulting in disease susceptibility. Moreover, ZmCCT- mediated resistance to Gibberella stalk rot is not affected by photoperiod sensitivity. This chromatin-based regulatory mechanism enables ZmCCT to be more precise and timely in defense against F. graminearum infection.

Sclerotinia sclerotiorum (Lib.) de Bary is an unusual pathogen which has the broad host range, diverse infection modes, and potential double feeding lifestyles of both biotroph and necrotroph. It is capable of infecting over 400 plant species found worldwide and more than 60 names have agriculturally been used to refer to diseases caused by this pathogen. Plant defense to S. sclerotiorum is a complex biological process and exhibits a typical quantitative disease resistance (QDR) response. Recent studies using Arabidopsis thaliana and crop plants have obtained new advances in mechanisms used by plants to cope with S. sclerotiorum infection. In this review, we focused on our current understanding on plant defense mechanisms against this pathogen, and set up a model for the defense process including three stages: recognition of this pathogen, signal transduction and defense response. We also have a particular interest in defense signaling mediated by diverse signaling molecules. We highlight the current challenges and unanswered questions in both the defense process and defense signaling. Essentially, we discussed candidate resistance genes newly mapped by using high-throughput experiments in important crops, and classified these potential gene targets into different stages of the defense process, which will broaden our understanding of the genetic architecture underlying quantitative resistance to S. sclerotiorum . We proposed that more powerful mapping population(s) will be required for accurate and reliable QDR gene identification.

Rice (Oryza sativa) is a crucial staple crop for global food security, particularly in Asia. However, rice production faces significant challenges from various diseases that can cause substantial yield losses. This review explores the role of genetic resistance in rice disease management, focusing on the molecular mechanisms underlying plant–pathogen interactions and strategies for developing resistant varieties. The paper discusses qualitative and quantitative resistance, emphasizing the importance of resistance (R) genes, defense-regulator genes, and quantitative trait loci (QTLs) in conferring broad-spectrum disease resistance. Gene-for-gene relationships in rice–pathogen interactions are examined, particularly for Xanthomonas oryzae pv. oryzae and Magnaporthe oryzae. The review also covers recent advancements in breeding techniques, including marker-assisted selection, genetic engineering, and genome editing technologies like CRISPR-Cas. These approaches offer promising avenues for enhancing disease resistance in rice while maintaining yield potential. Understanding and exploiting genetic resistance mechanisms is crucial for developing durable and broad-spectrum disease-resistant rice varieties, essential for ensuring sustainable rice production and global food security in the face of evolving pathogen threats and changing environmental conditions.

• Quantitative disease resistance, often influenced by environmental factors, is thought to be the result of DNA sequence variants segregating at multiple loci. However, heritable differences in DNA methylation, so-called transgenerational epigenetic variants, also could contribute to quantitative traits. Here, we tested this possibility using the well-characterized quantitative resistance of Arabidopsis to clubroot, a Brassica major disease caused by Plasmodiophora brassicae. • For that, we used the epigenetic recombinant inbred lines (epiRIL) derived from the cross ddm1-2 ✕ Col-0, which show extensive epigenetic variation but limited DNA sequence variation. Quantitative loci under epigenetic control (QTLepi) mapping was carried out on 123 epiRIL infected with P. brassicae and using various disease-related traits. • EpiRIL displayed a wide range of continuous phenotypic responses. Twenty QTLepi were detected across the five chromosomes, with a bona fide epigenetic origin for 16 of them. The effect of five QTLepi was dependent on temperature conditions. Six QTLepi co-localized with previously identified clubroot resistance genes and QTL in Arabidopsis. • Co-localization of clubroot resistance QTLepi with previously detected DNA-based QTL reveals a complex model in which a combination of allelic and epiallelic variations interacts with the environment to lead to variation in clubroot quantitative resistance.

Despite the recognized social and economic importance of common beans (Phaseolus vulgaris L.), the average grain yield is far below the productive potential of cultivars. This situation is explained by several factors, such as the large number of diseases and pests that affect the crop, some of which cause significant damage. It is estimated that approximately 200 diseases can significantly affect common beans. These can be bacterial, viral, fungal, and nematode-induced. The main bean fungal diseases include anthracnose, angular leaf spot, powdery mildew, gray mold, Fusarium wilt, dry root rot, Pythium root rot, southern blight, white mold, charcoal rot and rust. This review provides a comprehensive overview of eleven major fungal diseases affecting common bean, describing their associated damage, characteristic symptomatology, and the epidemiological factors that favor disease development. It further synthesizes current knowledge on host resistance mechanisms that can be exploited to develop molecularly informed resistant genotypes. The compilation includes characterized resistance genes and mapped quantitative trait loci (QTLs), with details on their chromosomal locations, genetic effects, and potential for use in breeding. Moreover, the review highlights successful applications of molecular breeding approaches targeting fungal resistance. Finally, it discusses conclusions and future perspectives for integrating advanced genetic improvement strategies—such as marker-assisted selection, genomic selection, gene editing, and pyramiding—to enhance durable resistance to fungal pathogens in common bean. This work serves as both a reference for forthcoming resistance-mapping studies and a guide for the strategic selection of resistance loci in breeding programs aimed at developing cultivars with stable and long-lasting fungal resistance.

Cultivar-strain specificity in the wheat–Zymoseptoria tritici pathosystem determines the infection outcome and is controlled by resistance genes on the host side, many of which have been identified. On the pathogen side, however, the molecular determinants of specificity remain largely unknown. We used genetic mapping, targeted gene disruption and allele swapping to characterise the recognition of the new avirulence factor Avr3D1. We then combined population genetic and comparative genomic analyses to characterise the evolutionary trajectory of Avr3D1. Avr3D1 is specifically recognised by wheat cultivars harbouring the Stb7 resistance gene, triggering a strong defence response without preventing pathogen infection and reproduction. Avr3D1 resides in a cluster of putative effector genes located in a genome region populated by independent transposable element insertions. The gene was present in all 132 investigated strains and is highly polymorphic, with 30 different protein variants identified. We demonstrated that specific amino acid substitutions in Avr3D1 led to evasion of recognition. These results demonstrate that quantitative resistance and gene-for-gene interactions are not mutually exclusive. Localising avirulence genes in highly plastic genomic regions probably facilitates accelerated evolution that enables escape from recognition by resistance proteins.

Summary Fusarium head blight (FHB) resistance in wheat is considered to be polygenic in nature. Cell wall fortification is one of the best resistance mechanisms in wheat against Fusarium graminearum which causes FHB. Metabolomics approach in our study led to the identification of a wide array of resistance‐related (RR) metabolites, among which hydroxycinnamic acid amides (HCAAs), such as coumaroylagmatine and coumaroylputrescine, were the highest fold change RR metabolites in the rachis of a resistant near‐isogenic line (NIL‐R) upon F. graminearum infection. Placement of these metabolites in the secondary metabolic pathway led to the identification of a gene encoding agmatine coumaroyl transferase, herein referred to as TaACT, as a candidate gene. Based on wheat survey sequence, TaACT was located within a FHB quantitative trait loci on chromosome 2DL (FHB QTL‐2DL) between the flanking markers WMC245 and GWM608. Phylogenetic analysis suggested that TaACT shared closest phylogenetic relationship with an ACT ortholog in barley. Sequence analysis of TaACT in resistant and susceptible NILs, with contrasting levels of resistance to FHB, led to the identification of several single nucleotide polymorphisms (SNPs) and two inversions that may be important for gene function. Further, a role for TaACT in FHB resistance was functionally validated by virus‐induced gene silencing (VIGS) in wheat NIL‐R and based on complementation studies in Arabidopsis with act mutant background. The disease severity, fungal biomass and RR metabolite analysis confirmed TaACT as an important gene in wheat FHB QTL‐2DL, conferring resistance to F. graminearum.

Plant disease resistance is often under quantitative genetic control. Thus, in a given interaction, plant cellular responses to infection are influenced by resistance or susceptibility alleles at different loci. In this study, a genetic linkage analysis was used to address the complexity of the metabolic responses of Brassica napus roots to infection by Plasmodiophora brassicae. Metabolome profiling and pathogen quantification in a segregating progeny allowed a comparative mapping of quantitative trait loci (QTLs) involved in resistance and in metabolic adjustments. Distinct metabolic modules were associated with each resistance QTL, suggesting the involvement of different underlying cellular mechanisms. This approach highlighted the possible role of gluconasturtiin and two unknown metabolites in the resistance conferred by two QTLs on chromosomes C03 and C09, respectively. Only two susceptibility biomarkers (glycine and glutathione) were simultaneously linked to the three main resistance QTLs, suggesting the central role of these compounds in the interaction. By contrast, several genotype-specific metabolic responses to infection were genetically unconnected to resistance or susceptibility. Likewise, variations of root sugar profiles, which might have influenced pathogen nutrition, were not found to be related to resistance QTLs. This work illustrates how genetic metabolomics can help to understand plant stress responses and their possible links with disease.

Summary Evolutionary processes during plant polyploidization and speciation have led to extensive presence–absence variation (PAV) in crop genomes, and there is increasing evidence that PAV associates with important traits. Today, high‐resolution genetic analysis in major crops frequently implements simple, cost‐effective, high‐throughput genotyping from single nucleotide polymorphism (SNP) hybridization arrays; however, these are normally not designed to distinguish PAV from failed SNP calls caused by hybridization artefacts. Here, we describe a strategy to recover valuable information from single nucleotide absence polymorphisms (SNaPs) by population‐based quality filtering of SNP hybridization data to distinguish patterns associated with genuine deletions from those caused by technical failures. We reveal that including SNaPs in genetic analyses elucidate segregation of small to large‐scale structural variants in nested association mapping populations of oilseed rape (Brassica napus), a recent polyploid crop with widespread structural variation. Including SNaP markers in genomewide association studies identified numerous quantitative trait loci, invisible using SNP markers alone, for resistance to two major fungal diseases of oilseed rape, Sclerotinia stem rot and blackleg disease. Our results indicate that PAV has a strong influence on quantitative disease resistance in B. napus and that SNaP analysis using cost‐effective SNP array data can provide extensive added value from ‘missing data’. This strategy might also be applicable for improving the precision of genetic mapping in many important crop species.