Intracellular Reactive Oxygen Species-Aided Localized Cell Death Contributing to Immune Responses Against Wheat Powdery Mildew Pathogen.

Reactive oxygen species (ROS)- and hypersensitive response (HR)-mediated cell death have long been known to play critical roles in plant immunity to pathogens. Wheat powdery mildew caused by Blumeria graminis f. sp. tritici (Bgt) is a destructive wheat pathogen. Here, we report a quantitative analysis of the proportion of infected cells with local apoplastic ROS (apoROS) versus intracellular ROS (intraROS) accumulation in various wheat accessions that carry different disease resistance genes (R genes) at a series of time points postinfection. The proportion of apoROS accumulation was 70 to 80% of the infected wheat cells detected in both compatible and incompatible host-pathogen interactions. However, intensive intraROS accumulation followed by localized cell death responses was detected in 11 to 15% of the infected wheat cells, mainly in wheat lines that carried nucleotide-binding leucine-rich repeat R genes (e.g., Pm3F, Pm41, TdPm60, MIIW72, and Pm69). The lines that carry unconventional R genes, Pm24 (Wheat Tandem Kinase 3) and pm42 (a recessive R gene), showed fewer intraROS responses, whereas 11% of Pm24 line-infected epidermis cells still showed HR cell death, suggesting that different resistance pathways are activated there. Here, we also demonstrated that ROS could not act as a strong systemic signal for inducing high resistance to Bgt in wheat, although it induced the expression of pathogenesis-related genes. These results provide new insights into the contribution of intraROS and localized cell death to immune responses against wheat powdery mildew.

Dissection of a rapidly evolving wheat resistance gene cluster by long-read genome sequencing accelerated the cloning of Pm69.

Gene cloning in repeat-rich polyploid genomes remains challenging. Here, we describe a strategy for overcoming major bottlenecks in cloning of the powdery mildew resistance gene (R-gene) Pm69 derived from tetraploid wild emmer wheat. A conventional positional cloning approach was not effective owing to suppressed recombination. Chromosome sorting was compromised by insufficient purity. A Pm69 physical map, constructed by assembling Oxford Nanopore Technology (ONT) long-read genome sequences, revealed a rapidly evolving nucleotide-binding leucine-rich repeat (NLR) R-gene cluster with structural variations. A single candidate NLR was identified by anchoring RNA sequencing reads from susceptible mutants to ONT contigs and was validated by virus-induced gene silencing. Pm69 is likely a newly evolved NLR and was discovered in only one location across the wild emmer wheat distribution range in Israel. Pm69 was successfully introgressed into cultivated wheat, and a diagnostic molecular marker was used to accelerate its deployment and pyramiding with other R-genes.

Discovery of stripe rust resistance with incomplete dominance in wild emmer wheat using bulked segregant analysis sequencing.

Durable crop disease resistance is an essential component of global food security. Continuous pathogen evolution leads to a breakdown of resistance and there is a pressing need to characterize new resistance genes for use in plant breeding. Here we identified an accession of wild emmer wheat (Triticum turgidum ssp. dicoccoides), PI 487260, that is highly resistant to multiple stripe rust isolates. Genetic analysis revealed resistance was conferred by a single, incompletely dominant gene designated as Yr84. Through bulked segregant analysis sequencing (BSA-Seq) we identified a 52.7 Mb resistance-associated interval on chromosome 1BS. Detected variants were used to design genetic markers for recombinant screening, further refining the interval of Yr84 to a 2.3-3.3 Mb in tetraploid wheat genomes. This interval contains 34 candidate genes encoding for protein domains involved in disease resistance responses. Furthermore, KASP markers closely-linked to Yr84 were developed to facilitate marker-assisted selection for rust resistance breeding.

Capturing Wheat Phenotypes at the Genome Level.

Recent technological advances in next-generation sequencing (NGS) technologies have dramatically reduced the cost of DNA sequencing, allowing species with large and complex genomes to be sequenced. Although bread wheat (Triticum aestivum L.) is one of the world's most important food crops, efficient exploitation of molecular marker-assisted breeding approaches has lagged behind that achieved in other crop species, due to its large polyploid genome. However, an international public-private effort spanning 9 years reported over 65% draft genome of bread wheat in 2014, and finally, after more than a decade culminated in the release of a gold-standard, fully annotated reference wheat-genome assembly in 2018. Shortly thereafter, in 2020, the genome of assemblies of additional 15 global wheat accessions was released. As a result, wheat has now entered into the pan-genomic era, where basic resources can be efficiently exploited. Wheat genotyping with a few hundred markers has been replaced by genotyping arrays, capable of characterizing hundreds of wheat lines, using thousands of markers, providing fast, relatively inexpensive, and reliable data for exploitation in wheat breeding. These advances have opened up new opportunities for marker-assisted selection (MAS) and genomic selection (GS) in wheat. Herein, we review the advances and perspectives in wheat genetics and genomics, with a focus on key traits, including grain yield, yield-related traits, end-use quality, and resistance to biotic and abiotic stresses. We also focus on reported candidate genes cloned and linked to traits of interest. Furthermore, we report on the improvement in the aforementioned quantitative traits, through the use of (i) clustered regularly interspaced short-palindromic repeats/CRISPR-associated protein 9 (CRISPR/Cas9)-mediated gene-editing and (ii) positional cloning methods, and of genomic selection. Finally, we examine the utilization of genomics for the next-generation wheat breeding, providing a practical example of using in silico bioinformatics tools that are based on the wheat reference-genome sequence.