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To improve the efficiency of high-density genotype data storage and imputation in bread wheat (Triticum aestivum L.), we applied the Practical Haplotype Graph (PHG) tool. The Wheat PHG database was built using whole-exome capture sequencing data from a diverse set of 65 wheat accessions. Population haplotypes were inferred for the reference genome intervals defined by the boundaries of the high-quality gene models. Missing genotypes in the inference panels, composed of wheat cultivars or recombinant inbred lines genotyped by exome capture, genotyping-by-sequencing (GBS), or whole-genome skim-seq sequencing approaches, were imputed using the Wheat PHG database. Though imputation accuracy varied depending on the method of sequencing and coverage depth, we found 92% imputation accuracy with 0.01× sequence coverage, which was slightly lower than the accuracy obtained using the 0.5× sequence coverage (96.6%). Compared to Beagle, on average, PHG imputation was ∼3.5% (P-value < 2 × 10-14) more accurate, and showed 27% higher accuracy at imputing a rare haplotype introgressed from a wild relative into wheat. We found reduced accuracy of imputation with independent 2× GBS data (88.6%), which increases to 89.2% with the inclusion of parental haplotypes in the database. The accuracy reduction with GBS is likely associated with the small overlap between GBS markers and the exome capture dataset, which was used for constructing PHG. The highest imputation accuracy was obtained with exome capture for the wheat D genome, which also showed the highest levels of linkage disequilibrium and proportion of identity-by-descent regions among accessions in the PHG database. We demonstrate that genetic mapping based on genotypes imputed using PHG identifies SNPs with a broader range of effect sizes that together explain a higher proportion of genetic variance for heading date and meiotic crossover rate compared to previous studies.

To improve the efficiency of high-density genotype data storage and imputation in bread wheat (Triticum aestivum L.), we applied the Practical Haplotype Graph (PHG) tool. The wheat PHG database was built using whole-exome capture sequencing data from a diverse set of 65 wheat accessions. Population haplotypes were inferred for the reference genome intervals defined by the boundaries of the high-quality gene models. Missing genotypes in the inference panels, composed of wheat cultivars or recombinant inbred lines genotyped by exome capture, genotyping-by-sequencing (GBS), or whole-genome skim-seq sequencing approaches, were imputed using the wheat PHG database. Though imputation accuracy varied depending on the method of sequencing and coverage depth, we found 92% imputation accuracy with 0.01x sequence coverage, which was slightly lower than the accuracy obtained using the 0.5x sequence coverage (96.6%). Compared to Beagle, on average, PHG imputation was ∼3.5% (p-value < 2 x 10-14) more accurate, and showed 27% higher accuracy at imputing a rare haplotype introgressed from a wild relative into wheat. We found reduced accuracy of imputation with independent 2x GBS data (88.6%), which increases to 89.2% with the inclusion of parental haplotypes in the database. The accuracy reduction with GBS is likely associated with the small overlap between GBS markers and the exome capture dataset, which was used for constructing PHG. The highest imputation accuracy was obtained with exome capture for the wheat D genome, which also showed the highest levels of linkage disequlibrium and proportion of identity-by-descent regions among accessions in the PHG database. We demonstrate that genetic mapping based on genotypes imputed using PHG identifies SNPs with a broader range of effect sizes that together explain a higher proportion of genetic variance for heading date and meiotic crossover rate compared to previous studies.

SUMMARY: Septoria nodorum blotch (SNB), caused by Parastagonospora nodorum, is a disease of durum and common wheat initiated by the recognition of pathogen‐produced necrotrophic effectors (NEs) by specific wheat genes. The wheat gene Snn1 was previously cloned, and it encodes a wall‐associated kinase that directly interacts with the NE SnTox1 leading to programmed cell death and ultimately the development of SNB. Here, sequence analysis of Snn1 from 114 accessions including diploid, tetraploid, and hexaploid wheat species revealed that some wheat lines possess two copies of Snn1 (designated Snn1‐B1 and Snn1‐B2) approximately 120 kb apart. Snn1‐B2 evolved relatively recently as a paralog of Snn1‐B1, and both genes have undergone diversifying selection. Three point mutations associated with the formation of the first SnTox1‐sensitive Snn1‐B1 allele from a primitive wild wheat were identified. Four subsequent and independent SNPs, three in Snn1‐B1 and one in Snn1‐B2, converted the sensitive alleles to insensitive forms. Protein modeling indicated these four mutations could abolish Snn1–SnTox1 compatibility either through destabilization of the Snn1 protein or direct disruption of the protein–protein interaction. A high‐throughput marker was developed for the absent allele of Snn1, and it was 100% accurate at predicting SnTox1‐insensitive lines in both durum and spring wheat. Results of this study increase our understanding of the evolution, diversity, and function of Snn1‐B1 and Snn1‐B2 genes and will be useful for marker‐assisted elimination of these genes for better host resistance. Significance Statement: Alleles of the wheat Snn1 gene that confer septoria nodorum blotch susceptibility through direct interaction with the pathogen‐produced necrotrophic effector SnTox1 arose through three point mutations and a gene duplication event, and four subsequent point mutations led to the formation of lack‐of‐function (resistance) alleles. Knowledge of the evolution, selection, and structural and functional nature of Snn1 alleles allowed for the development of an efficient marker‐based elimination assay for the development of disease resistant wheat. [ABSTRACT FROM AUTHOR]

Fusarium head blight (FHB) is a devastating fungal disease of wheat. Since early 1990s, frequent FHB epidemics in major wheat‐growing regions have caused massive economic losses. Developing FHB‐resistant varieties is key to minimize the loss caused by the disease. In durum wheat (Triticum turgidum L. ssp. durum), however, it is challenged by lack of resistant sources. Introgression of resistance genes from wild relatives and bread wheat has resulted in some durum wheat lines with moderate resistance. Due to its complex genetic nature, integrating more resistance genes with moderate and even minor effects promises to provide high and durable FHB resistance. In this study, a base population was developed using diverse resistant lines and elite durum wheat breeding lines as founders and went through three cycles of phenotypic selection from 2019 to 2022, with FHB severity decreased by 34%. Six S0:1 lines in Cycle 2 and Cycle 3 populations exhibited significantly lower FHB severity than the moderately susceptible check variety ND Riveland. The results suggested that recurrent phenotypic selection could effectively improve FHB resistance. Analysis of the founders and Cycle 2 and Cycle 3 populations with 2706 single nucleotide polymorphism markers indicated that there was little decrease in genetic variation due to selection. Genome‐wide association analysis found no markers significantly associated with FHB severity. Genomic prediction accuracies based on cross‐validation for FHB severity, plant height, and days‐to‐flowering were 0.51, 0.69, and 0.61, respectively. Recurrent genomic selection can shorten the select cycle to 4 months and therefore is promising to accelerate genetic improvement of FHB severity. Core Ideas: Recurrent phenotypic selection could effectively improve FHB resistance in durum wheat.A moderate prediction accuracy for FHB severity was found in the durum wheat recurrent selection population.Recurrent genomic selection can shorten select cycle and is promising to accelerate genetic improvement. [ABSTRACT FROM AUTHOR]

SUMMARY: Chloroplast biogenesis is critical for crop biomass and economic yield. However, chloroplast development is a very complicated process coordinated by cross‐communication between the nucleus and plastids, and the underlying mechanisms have not been fully revealed. To explore the regulatory machinery for chloroplast biogenesis, we conducted map‐based cloning of the Grandpa 1 (Gpa1) gene regulating chloroplast development in barley. The spontaneous mutation gpa1.a caused a variegation phenotype of the leaf, dwarfed growth, reduced grain yield, and increased tiller number. Genetic mapping anchored the Gpa1 gene onto 2H within a gene cluster functionally related to photosynthesis or chloroplast differentiation. One gene (HORVU.MOREX.r3.2HG0213170) in the delimited region encodes a putative plastid terminal oxidase (PTOX) in thylakoid membranes, which is homologous to IMMUTANS (IM) of Arabidopsis. The IM gene is required for chloroplast biogenesis and maintenance of functional thylakoids in Arabidopsis. Using CRISPR technology and gene transformation, we functionally validated that the PTOX‐encoding gene, HORVU.MOREX.r3.2HG0213170, is the causal gene of Gpa1. Gene expression and chemical analysis revealed that the carotenoid biosynthesis pathway is suppressed by the gpa1 mutation, rendering mutants vulnerable to photobleaching. Our results showed that the overtillering associated with the gpa1 mutation was caused by the lower accumulation of carotenoid‐derived strigolactones (SLs) in the mutant. The cloning of Gpa1 not only improves our understanding of the molecular mechanisms underlying chloroplast biosynthesis but also indicates that the PTOX activity is conserved between monocots and dicots for the establishment of the photosynthesis factory. Significance Statement: The Gpa1 gene encoding a plastid terminal oxidase is required for chloroplast biogenesis and tillering control in barley. [ABSTRACT FROM AUTHOR]

The USDA‐ARS and North Dakota State University Agricultural Experiment Station jointly released the Fusarium head blight (FHB)‐resistant spring wheat (Triticum aestivum L.) germplasm WGC002 (Reg. no. GP‐1089, PI 702949) in May 2023. WGC002 is a wheat‐Thinopyrum elongatum 7B‐7E translocation line, designated 7BS·7BL‐7EL, with the wheat chromosome 7BL terminal region replaced by the homoeologous counterpart of the Th. elongatum chromosome 7EL that contains the novel FHB resistance gene Fhb7The2. WGC002 was developed from the Chinese Spring (CS) wheat‐Th. elongatum disomic substitution line DS 7E(7B) using our genomics‐enabled chromosome engineering pipeline. The pedigree of WGC002 is DS 7E(7B)/2*CS ph1b mutant//DS 7E(7B). WGC002 has consistently exhibited resistance to FHB in inoculations of greenhouse grown plants. WGC002 does not contain the yellow flour pigment gene in the Fhb7The2 haplotype present on the terminal 7EL segment of the 7BS·7BL‐7EL translocation and has not exhibited any obvious linkage drag on the 7EL segment. Therefore, WGC002 is ready for immediate use in wheat breeding. One sequence‐tagged site (STS) and two polymerase chain reaction allelic competitive extension markers were developed specifically for Fhb7The2 and validated in different wheat genotypes. They are highly diagnostic for Fhb7The2 and extremely useful in marker‐assisted introgression of Fhb7The2 in wheat breeding. In summary, WGC002 is a new wild grass‐derived FHB‐resistant spring wheat germplasm with diagnostic DNA markers available to conduct marker‐assisted selection of Fhb7The2, that will enhance and diversify FHB resistance of wheat. Core Ideas: We developed an FHB‐resistant wheat germplasm, WGC002, which contains the wild grass‐derived resistance gene Fhb7The2.Fhb7The2 was incorporated into wheat through a 7B‐7E translocation by chromosome engineering. The chromosome 7E segment containing Fhb7The2 does not carry the gene for yellow flour pigment in WGC002.We developed the STS and PACE markers specific for Fhb7The2. [ABSTRACT FROM AUTHOR]

There is limited information regarding the morphometric relationships of panicle traits in oat (Avena sativa) and their contribution to phenology and growth, physiology, and pathology traits important for yield. To model panicle growth and development and identify genomic regions associated with corresponding traits, 10 diverse spring oat mapping populations (n=2,993) were evaluated in the field and 9 genotyped via genotyping-by-sequencing. Representative panicles from all progeny individuals, parents, and check lines were scanned, and images were analyzed using manual and automated techniques, resulting in over 60 unique panicle, rachis, and spikelet variables. Spatial modeling and days to heading were used to account for environmental and phenological variances, respectively. Panicle variables were intercorrelated, providing reproducible archetypal and growth models. Notably, adult plant resistance for oat crown rust was most prominent for taller, stiff stalked plants having a more open panicle structure. Within and among family variance for panicle traits reflected the moderate-to-high heritability and mutual genome-wide associations (hotspots) with numerous high-effect loci. Candidate genes and potential breeding applications are discussed. This work adds to the growing genetic resources for oat and provides a unique perspective on the genetic basis of panicle architecture in cereal crops. [ABSTRACT FROM AUTHOR]

Fusarium head blight is a destructive disease of small grains. The disease is predominantly caused by the haploid ascomycete fungus Fusarium graminearum in North America. To understand the genetics of quantitative traits for sensitivity to fungicides in this fungal pathogen, we conducted a genome-wide association study of sensitivity to two demethylation inhibition class fungicides, tebuconazole and prothioconazole, using an F. graminearum population of 183 isolates collected between 1981 and 2013 from North Dakota. Baseline sensitivity to tebuconazole and prothioconazole was established using 21 isolates collected between 1981 and 1994. Most fungal isolates were sensitive to both tebuconazole and prothioconazole; however, five isolates showed significantly reduced sensitivity to prothioconazole. The genome-wide association study identified one significant marker-trait association on chromosome 3 for tebuconazole resistance, whereas six significant marker-trait associations, one on chromosome 1, three on chromosome 2, and two on chromosome 4, were detected for prothioconazole resistance. Functional annotation of the marker-trait association for tebuconazole revealed a candidate gene encoding a basic helix-loop-helix domain-containing protein that reinforces sterol in the fungal membrane. Putative genes for prothioconazole resistance were also identified, which are involved in RNA interference, the detoxification by ubiquitin-proteasome pathway, and membrane integrity reinforcement. Considering the potential of the pathogen toward overcoming chemical control, continued monitoring of fungal sensitivities to commercially applied fungicides, especially those containing prothioconazole, is warranted to reduce risks of fungicide resistance in the pathogen populations. [ABSTRACT FROM AUTHOR]

Summary Aegilops umbellulata serve as an important reservoir for novel biotic and abiotic stress tolerance for wheat improvement. However, chromosomal rearrangements and evolutionary trajectory of this species remain to be elucidated. Here, we present a comprehensive investigation into Ae. umbellulata genome by generating a high‐quality near telomere‐to‐telomere genome assembly of PI 554389 and resequencing 20 additional Ae. umbellulata genomes representing diverse geographical and phenotypic variations. Our analysis unveils complex chromosomal rearrangements, most prominently in 4U and 6U chromosomes, delineating a distinct evolutionary trajectory of Ae. umbellulata from wheat and its relatives. Furthermore, our data rectified the erroneous naming of chromosomes 4U and 6U in the past and highlighted multiple major evolutionary events that led to the present‐day U‐genome. Resequencing of diverse Ae. umbellulata accessions revealed high genetic diversity within the species, partitioning into three distinct evolutionary sub‐populations and supported by extensive phenotypic variability in resistance against several races/pathotypes of five major wheat diseases. Disease evaluations indicated the presence of several novel resistance genes in the resequenced lines for future studies. Resequencing also resulted in the identification of six new haplotypes for Lr9, the first resistance gene cloned from Ae. umbellulata. The extensive genomic and phenotypic resources presented in this study will expedite the future genetic exploration of Ae. umbellulata, facilitating efforts aimed at enhancing resiliency and productivity in wheat. [ABSTRACT FROM AUTHOR]

Spot form net blotch (SFNB), caused by the necrotrophic fungal pathogen Pyrenophora teres f. maculata (Ptm), is a foliar disease of barley that results in significant yield losses in major growing regions worldwide. Understanding the host-parasite interactions between pathogen virulence/avirulence genes and the corresponding host susceptibility/resistance genes is important for the deployment of genetic resistance against SFNB. Two recombinant inbred mapping populations were developed to characterize genetic resistance/susceptibility to the Ptm isolate 13IM8.3, which was collected from Idaho (ID). An Illumina Infinium array was used to produce a genome-wide marker set. Quantitative trait loci (QTL) analysis identified ten significant resistance/susceptibility loci, with two of the QTL being common to both populations. One of the QTL on 5H appears to be novel, while the remaining loci have been reported previously. Single nucleotide polymorphisms (SNPs) closely linked to or delimiting the significant QTL have been converted to user-friendly markers. Loci and associated molecular markers identified in this study will be useful in genetic mapping and deployment of the genetic resistance to SFNB in barley. [ABSTRACT FROM AUTHOR]

The Hessian fly (HF), Mayetiola destructor (Diptera: Cecidomyiidae), is one of the most devastating insect pests of cereals including wheat, barley, and rye. Although wheat is the preferred host for HF, this continuously evolving pest has been emerging as a threat to barley production. However, characterization and identification of genetic resistance to HF has not been conducted in barley. In the present study, we used a genome-wide association study (GWAS) to identify barley resistance loci to HF using a geographically diverse set of 234 barley accessions. The results showed that around 90% of barley lines were highly susceptible, indicating a significant vulnerability to HF in barley, and a total of 29 accessions were resistant, serving as potential resistance resources. GWAS with a mixed linear model revealed two marker-trait associations, both on chromosome 4H. The resistance loci and associated markers will facilitate barley improvement and development for breeders. In addition, our results are fundamental for genetic studies to understand the HF resistance mechanism in barley. [ABSTRACT FROM AUTHOR]

To improve the efficiency of high-density genotype data storage and imputation in bread wheat (Triticum aestivum L.), we applied the Practical Haplotype Graph (PHG) tool. The Wheat PHG database was built using whole-exome capture sequencing data from a diverse set of 65 wheat accessions. Population haplotypes were inferred for the reference genome intervals defined by the boundaries of the high-quality gene models. Missing genotypes in the inference panels, composed of wheat cultivars or recombinant inbred lines genotyped by exome capture, genotyping-by-sequencing (GBS), or whole-genome skim-seq sequencing approaches, were imputed using the Wheat PHG database. Though imputation accuracy varied depending on the method of sequencing and coverage depth, we found 92% imputation accuracy with 0.01× sequence coverage, which was slightly lower than the accuracy obtained using the 0.5× sequence coverage (96.6%). Compared to Beagle, on average, PHG imputation was ∼3.5% (P-value < 2 × 10-14) more accurate, and showed 27% higher accuracy at imputing a rare haplotype introgressed from a wild relative into wheat. We found reduced accuracy of imputation with independent 2× GBS data (88.6%), which increases to 89.2% with the inclusion of parental haplotypes in the database. The accuracy reduction with GBS is likely associated with the small overlap between GBS markers and the exome capture dataset, which was used for constructing PHG. The highest imputation accuracy was obtained with exome capture for the wheat D genome, which also showed the highest levels of linkage disequilibrium and proportion of identity-by-descent regions among accessions in the PHG database. We demonstrate that genetic mapping based on genotypes imputed using PHG identifies SNPs with a broader range of effect sizes that together explain a higher proportion of genetic variance for heading date and meiotic crossover rate compared to previous studies., (© The Author(s) 2021. Published by Oxford University Press on behalf of Genetics Society of America.)