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Pangenomes are collections of annotated genome sequences of multiple individuals of a species 1 . The structural variants uncovered by these datasets are a major asset to genetic analysis in crop plants 2 . Here we report a pangenome of barley comprising long-read sequence assemblies of 76 wild and domesticated genomes and short-read sequence data of 1,315 genotypes. An expanded catalogue of sequence variation in the crop includes structurally complex loci that are rich in gene copy number variation. To demonstrate the utility of the pangenome, we focus on four loci involved in disease resistance, plant architecture, nutrient release and trichome development. Novel allelic variation at a powdery mildew resistance locus and population-specific copy number gains in a regulator of vegetative branching were found. Expansion of a family of starch-cleaving enzymes in elite malting barleys was linked to shifts in enzymatic activity in micro-malting trials. Deletion of an enhancer motif is likely to change the developmental trajectory of the hairy appendages on barley grains. Our findings indicate that allelic diversity at structurally complex loci may have helped crop plants to adapt to new selective regimes in agricultural ecosystems., Competing Interests: Competing interests K.B., C.D., M.E.J., S.M.K., Q.L., E.M., P.R.P., B.S., H.C.T., M.T.S.N., C.V. and M.W.R. are current or previous Carlsberg A/S employees. P.A.P. and D.V. are SECOBRA Recherches employees. The other authors declare no competing interests., (© 2024. The Author(s).)

Bread wheat (Triticum aestivum) is a globally dominant crop and major source of calories and proteins for the human diet. Compared with its wild ancestors, modern bread wheat shows lower genetic diversity, caused by polyploidisation, domestication and breeding bottlenecks 1,2 . Wild wheat relatives represent genetic reservoirs, and harbour diversity and beneficial alleles that have not been incorporated into bread wheat. Here we establish and analyse extensive genome resources for Tausch's goatgrass (Aegilops tauschii), the donor of the bread wheat D genome. Our analysis of 46 Ae. tauschii genomes enabled us to clone a disease resistance gene and perform haplotype analysis across a complex disease resistance locus, allowing us to discern alleles from paralogous gene copies. We also reveal the complex genetic composition and history of the bread wheat D genome, which involves contributions from genetically and geographically discrete Ae. tauschii subpopulations. Together, our results reveal the complex history of the bread wheat D genome and demonstrate the potential of wild relatives in crop improvement., (© 2024. The Author(s).)

Key Message: Genetic dissection of a QTL from wild emmer wheat, QGpc.huj.uh-5B.2, introgressed into bread wheat, identified candidate genes associated with tolerance to nitrogen deficiency, and potentially useful for improving nitrogen-use efficiency. Nitrogen (N) is an important macronutrient critical to wheat growth and development; its deficiency is one of the main factors causing reductions in grain yield and quality. N availability is significantly affected by drought or flooding, that are dependent on additional factors including soil type or duration and severity of stress. In a previous study, we identified a high grain protein content QTL (QGpc.huj.uh-5B.2) derived from the 5B chromosome of wild emmer wheat, that showed a higher proportion of explained variation under water-stress conditions. We hypothesized that this QTL is associated with tolerance to N deficiency as a possible mechanism underlying the higher effect under stress. To validate this hypothesis, we introgressed the QTL into the elite bread wheat var. Ruta, and showed that under N-deficient field conditions the introgression IL99 had a 33% increase in GPC (p < 0.05) compared to the recipient parent. Furthermore, evaluation of IL99 response to severe N deficiency (10% N) for 14 days, applied using a semi-hydroponic system under controlled conditions, confirmed its tolerance to N deficiency. Fine-mapping of the QTL resulted in 26 homozygous near-isogenic lines (BC 4 F 5 ) segregating to N-deficiency tolerance. The QTL was delimited from - 28.28 to - 1.29 Mb and included 13 candidate genes, most associated with N-stress response, N transport, and abiotic stress responses. These genes may improve N-use efficiency under severely N-deficient environments. Our study demonstrates the importance of WEW as a source of novel candidate genes for sustainable improvement in tolerance to N deficiency in wheat., (© 2024. The Author(s).)

Background: Fusarium head blight (FHB) infection results in Fusarium damaged kernels (FDK) and deoxynivalenol (DON) contamination that are downgrading factors at the Canadian elevators. Durum wheat (Triticum turgidum L. var. durum Desf.) is particularly susceptible to FHB and most of the adapted Canadian durum wheat cultivars are susceptible to moderately susceptible to this disease. However, the durum line DT696 is less susceptible to FHB than commercially grown cultivars. Little is known about genetic variation for durum wheat ability to resist FDK infection and DON accumulation. This study was undertaken to map genetic loci conferring resistance to DON and FDK resistance using a SNP high-density genetic map of a DT707/DT696 DH population and to identify SNP markers useful in marker-assisted breeding. One hundred twenty lines were grown in corn spawn inoculated nurseries near Morden, MB in 2015, 2016 and 2017 and the harvested seeds were evaluated for DON. The genetic map of the population was used in quantitative trait locus analysis performed with MapQTL.6® software., Results: Four DON accumulation resistance QTL detected in two of the three years were identified on chromosomes 1 A, 5 A (2 loci) and 7 A and two FDK resistance QTL were identified on chromosomes 5 and 7 A in single environments. Although not declared significant due to marginal LOD values, the QTL for FDK on the 5 and 7 A were showing in other years suggesting their effects were real. DT696 contributed the favourable alleles for low DON and FDK on all the chromosomes. Although no resistance loci contributed by DT707, transgressive segregant lines were identified resulting in greater resistance than DT696. Breeder-friendly KASP markers were developed for two of the DON and FDK QTL detected on chromosomes 5 and 7 A. Markers flanking each QTL were physically mapped against the durum wheat reference sequence and candidate genes which might be involved in FDK and DON resistance were identified within the QTL intervals., Conclusions: The DH lines harboring the desired resistance QTL will serve as useful resources in breeding for FDK and DON resistance in durum wheat. Furthermore, breeder-friendly KASP markers developed during this study will be useful for the selection of durum wheat varieties with low FDK and DON levels in durum wheat breeding programs., (© 2024. Crown.)

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., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

Tetraploid wheats (Triticum turgidum L.), including durum wheat (T. turgidum ssp. durum (Desf.) Husn.), are important crops with high nutritional and cultural values. However, their production is constrained by sensitivity to environmental conditions. In search of adaptive genetic signatures tracing historical selection and hybridization events, we performed genome scans on two datasets: (1) Durum Global Diversity Panel comprising a total of 442 tetraploid wheat and wild progenitor accessions including durum landraces (n = 286), domesticated emmer (T. turgidum ssp. dicoccum (Schrank) Thell.; n = 103) and wild emmer (T. turgidum ssp. dicoccoides (Korn. ex Asch. & Graebn.) Thell.; n = 53) wheats genotyped using the 90K single nucleotide polymorphism (SNP) array, and (2) a second dataset comprising a total 121 accessions of nine T. turgidum subspecies including wild emmer genotyped with >100 M SNPs from whole-genome resequencing. The genome scan on the first dataset detected six outlier loci on chromosomes 1A, 1B, 3A (n = 2), 6A, and 7A. These loci harbored important genes for adaptation to abiotic stresses, phenological responses, such as seed dormancy, circadian clock, flowering time, and key yield-related traits, including pleiotropic genes, such as HAT1, KUODA1, CBL1, and ZFN1. The scan on the second dataset captured a highly differentiated region on chromosome 2B that shows significant differentiation between two groups: one group consists of Georgian (T. turgidum ssp. paleocolchicum A. Love & D. Love) and Persian (T. turgidum ssp. carthlicum (Nevski) A. Love & D. Love) wheat accessions, while the other group comprises all the remaining tetraploids including wild emmer. This is consistent with a previously reported introgression in this genomic region from T. timopheevii Zhuk. which naturally cohabit in the Georgian and neighboring areas. This region harbored several adaptive genes, including the thermomorphogenesis gene PIF4, which confers temperature-resilient disease resistance and regulates other biological processes. Genome scans can be used to fast-track germplasm housed in gene banks and in situ; which helps to identify environmentally resilient accessions for breeding and/or to prioritize them for conservation., (© 2023 National Research Council Canada and The Authors. The Plant Genome published by Wiley Periodicals LLC on behalf of Crop Science Society of America. Reproduced with the permission of the Minister of Innovation, Science and Industry.)

Durum wheat is more susceptible to Fusarium head blight (FHB) than other types or classes of wheat. The disease is one of the most devastating in wheat; it reduces yield and end-use quality and contaminates the grain with fungal mycotoxins such as deoxynivalenol (DON). A panel of 265 Canadian and European durum wheat cultivars, as well as breeding and experimental lines, were tested in artificially inoculated field environments (2019-2022, inclusive) and two greenhouse trials (2019 and 2020). The trials were assessed for FHB severity and incidence, visual rating index, Fusarium -damaged kernels, DON accumulation, anthesis or heading date, maturity date, and plant height. In addition, yellow pigment and protein content were analyzed for the 2020 field season. To capture loci underlying FHB resistance and related traits, GWAS was performed using single-locus and several multi-locus models, employing 13,504 SNPs. Thirty-one QTL significantly associated with one or more FHB-related traits were identified, of which nine were consistent across environments and associated with multiple FHB-related traits. Although many of the QTL were identified in regions previously reported to affect FHB, the QTL QFhb-3B.2 , associated with FHB severity, incidence, and DON accumulation, appears to be novel. We developed KASP markers for six FHB-associated QTL that were consistently detected across multiple environments and validated them on the Global Durum Panel (GDP). Analysis of allelic diversity and the frequencies of these revealed that the lines in the GDP harbor between zero and six resistance alleles. This study provides a comprehensive assessment of the genetic basis of FHB resistance and DON accumulation in durum wheat. Accessions with multiple favorable alleles were identified and will be useful genetic resources to improve FHB resistance in durum breeding programs through marker-assisted recurrent selection and gene stacking., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Haile, Sertse, N’Diaye, Klymiuk, Wiebe, Ruan, Chawla, Henriquez, Wang, Kutcher, Steiner, Buerstmayr and Pozniak.)

Wheat is an important contributor to global food security, and further improvements are required to feed a growing human population. Functional genetics and genomics tools can help us to understand the function of different genes and to engineer beneficial changes. In this study, we used a promoter capture assay to sequence 2-kb regions upstream of all high-confidence annotated genes from 1,513 mutagenized plants from the tetraploid wheat variety Kronos. We identified 4.3 million induced mutations with an accuracy of 99.8%, resulting in a mutation density of 41.9 mutations per kb. We also remapped Kronos exome capture reads to Chinese Spring RefSeq v1.1, identified 4.7 million mutations, and predicted their effects on annotated genes. Using these predictions, we identified 59% more nonsynonymous substitutions and 49% more truncation mutations than in the original study. To show the biological value of the promoter dataset, we selected two mutations within the promoter of the VRN-A1 vernalization gene. Both mutations, located within transcription factor binding sites, significantly altered VRN-A1 expression, and one reduced the number of spikelets per spike. These publicly available sequenced mutant datasets provide rapid and inexpensive access to induced variation in the promoters and coding regions of most wheat genes. These mutations can be used to understand and modulate gene expression and phenotypes for both basic and commercial applications, where limited governmental regulations can facilitate deployment. These mutant collections, together with gene editing, provide valuable tools to accelerate functional genetic studies in this economically important crop.

Fusarium head blight (FHB) is one the most globally destructive fungal diseases in wheat and other small grains, causing a reduction in grain yield by 10-70%. The present study was conducted in a panel of historical and modern Canadian spring wheat ( Triticum aestivum L.) varieties and lines to identify new sources of FHB resistance and map associated quantitative trait loci (QTLs). We evaluated 249 varieties and lines for reaction to disease incidence, severity, and visual rating index (VRI) in seven environments by artificially spraying a mixture of four Fusarium graminearum isolates. A subset of 198 them were genotyped with the Wheat 90K iSelect single nucleotide polymorphisms (SNPs) array. Genome-wide association mapping performed on the overall best linear unbiased estimators (BLUE) computed from all seven environments and the International Wheat Genome Sequencing Consortium (IWGSC) RefSeq v2.0 physical map of 26,449 polymorphic SNPs out of the 90K identified sixteen FHB resistance QTLs that individually accounted for 5.7-10.2% of the phenotypic variance. The positions of two of the FHB resistance QTLs overlapped with plant height and flowering time QTLs. Four of the QTLs ( QFhb.dms-3B.1 , QFhb.dms-5A.5 , QFhb.dms-5A.7 , and QFhb.dms-6A.4 ) were simultaneously associated with disease incidence, severity, and VRI, which accounted for 27.0-33.2% of the total phenotypic variance in the combined environments. Three of the QTLs ( QFhb.dms-2A.2 , QFhb.dms-2D.2 , and QFhb.dms-5B.8 ) were associated with both incidence and VRI and accounted for 20.5-22.1% of the total phenotypic variance. In comparison with the VRI of the checks, we identified four highly resistant and thirty-three moderately resistant lines and varieties. The new FHB sources of resistance and the physical map of the associated QTLs would provide wheat breeders valuable information towards their efforts in developing improved varieties in western Canada., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Semagn, Henriquez, Iqbal, Brûlé-Babel, Strenzke, Ciechanowska, Navabi, N’Diaye, Pozniak and Spaner.)

Double haploid (DH) population development is widely used in many crops, including wheat (Triticum aestivum L.), to rapidly produce fixed germplasm for breeding and genetic studies. The genome shock that takes place during DH induction could induce chromosomal aberrations that can impact genome integrity and subsequently plant fitness and agronomic performance. To evaluate the extent of chromosomal aberrations that exist as a result of the DH process, we studied two wheat DH populations: CDC Stanley×CDC Landmark and KS13H9×SYMonument. We utilized high-throughput skim sequencing to construct digital karyotypes of these populations to quantify deletions and aneuploidy with high resolution and accuracy, which was confirmed in selected plants by cytological analysis. The two populations studied showed high proportion of abnormal primary DH lines, 55 and 45%, respectively, based on at least one abnormality per progeny. The chromosomal abnormalities are genetically unstable and were observed segregating in the subsequent generations. These observations have important implications for the use of DH lines in genetics and breeding., (© 2023 The Authors. The Plant Genome published by Wiley Periodicals LLC on behalf of Crop Science Society of America.)

Fusarium head blight (FHB) has rapidly become a major challenge to successful wheat production and competitive end-use quality in western Canada. Continuous effort is required to develop germplasm with improved FHB resistance and understand how to incorporate the material into crossing schemes for marker-assisted selection and genomic selection. The aim of this study was to map quantitative trait loci (QTL) responsible for the expression of FHB resistance in two adapted cultivars and to evaluate their co-localization with plant height, days to maturity, days to heading, and awnedness. A large doubled haploid population of 775 lines developed from cultivars Carberry and AC Cadillac was assessed for FHB incidence and severity in nurseries near Portage la Prairie, Brandon, and Morden in different years, and for plant height, awnedness, days to heading, and days to maturity near Swift Current. An initial linkage map using a subset of 261 lines was constructed using 634 polymorphic DArT and SSR markers. QTL analysis revealed five resistance QTL on chromosomes 2A, 3B (two loci), 4B, and 5A. A second genetic map with increased marker density was constructed using the Infinium iSelect 90k SNP wheat array in addition to the previous DArT and SSR markers, which revealed two additional QTL on 6A and 6D. The complete population was genotyped, and a total of 6,806 Infinium iSelect 90k SNP polymorphic markers were used to identify 17 putative resistance QTL on 14 different chromosomes. As with the smaller population size and fewer markers, large-effect QTL were detected on 3B, 4B, and 5A that were consistently expressed across environments. FHB resistance QTL were co-localized with plant height QTL on chromosomes 4B, 6D, and 7D; days to heading on 2B, 3A, 4A, 4B, and 5A; and maturity on 3A, 4B, and 7D. A major QTL for awnedness was identified as being associated with FHB resistance on chromosome 5A. Nine small-effect QTL were not associated with any of the agronomic traits, whereas 13 QTL that were associated with agronomic traits did not co-localize with any of the FHB traits. There is an opportunity to select for improved FHB resistance within adapted cultivars by using markers associated with complementary QTL., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (© 2023 Arti Singh, Ron DePauw, Curtis J. Pozniak, Amidou N’Diaye and His Majesty the King in Right of Canada, as represented by the Minister of Agriculture and Agri-Food Canada for the contribution of Samia Berraies, Richard D. Cuthbert, Ron E. Knox, Yuefeng Ruan, Firdissa E. Bokore, Maria Antonia Henriquez, Santosh Kumar, Andrew James Burt, Brad Meyer.)

Wheat was one of the crops domesticated in the Fertile Crescent region approximately 10,000 years ago. Despite undergoing recent polyploidization, hull-to-free-thresh transition events, and domestication bottlenecks, wheat is now grown in over 130 countries and accounts for a quarter of the world's cereal production. The main reason for its widespread success is its broad genetic diversity that allows it to thrive in different environments. To trace historical selection and hybridization signatures, genome scans were performed on two datasets: approximately 113K SNPs from 921 predominantly bread wheat accessions and approximately 110K SNPs from about 400 wheat accessions representing all ploidy levels. To identify environmental factors associated with the loci, a genome-environment association (GEA) was also performed. The genome scans on both datasets identified a highly differentiated region on chromosome 4A where accessions in the first dataset were dichotomized into a group (n = 691), comprising nearly all cultivars, wild emmer, and most landraces, and a second group (n = 230), dominated by landraces and spelt accessions. The grouping of cultivars is likely linked to their potential ancestor, bread wheat cv. Norin-10. The 4A region harbored important genes involved in adaptations to environmental conditions. The GEA detected loci associated with latitude and temperature. The genetic signatures detected in this study provide insight into the historical selection and hybridization events in the wheat genome that shaped its current genetic structure and facilitated its success in a wide spectrum of environmental conditions. The genome scans and GEA approaches applied in this study can help in screening the germplasm housed in gene banks for breeding, and for conservation purposes.

Crop breeding has traditionally ignored the plant-associated microbial communities. Considering the interactions between plant genotype and associated microbiota is of value since different genotypes of the same crop often harbor distinct microbial communities which can influence the plant phenotype. However, recent studies have reported contrasting results, which led us to hypothesize that the effect of genotype is constrained by growth stages, sampling year and plant compartment. To test this hypothesis, we sampled bulk soil, rhizosphere soil and roots of 10 field-grown wheat genotypes, twice per year, for 4 years. DNA was extracted and regions of the bacterial 16 S rRNA and CPN60 genes and the fungal ITS region were amplified and sequenced. The effect of genotype was highly contingent on the time of sampling and on the plant compartment sampled. Only for a few sampling dates, were the microbial communities significantly different across genotypes. The effect of genotype was most often significant for root microbial communities. The three marker genes used provided a highly coherent picture of the effect of genotype. Taken together, our results confirm that microbial communities in the plant environment strongly vary across compartments, growth stages, and years, and that this can mask the effect of genotype., (© 2023. The Author(s).)

Reproductive success hinges on precisely coordinated meiosis, yet our understanding of how structural rearrangements of chromatin and phase transitions during meiosis are transcriptionally regulated is limited. In crop plants, detailed analysis of the meiotic transcriptome could identify regulatory genes and epigenetic regulators that can be targeted to increase recombination rates and broaden genetic variation, as well as provide a resource for comparison among eukaryotes of different taxa to answer outstanding questions about meiosis. We conducted a meiotic stage-specific analysis of messenger RNA (mRNA), small non-coding RNA (sncRNA), and long intervening/intergenic non-coding RNA (lincRNA) in wheat (Triticum aestivum L.) and revealed novel mechanisms of meiotic transcriptional regulation and meiosis-specific transcripts. Amidst general repression of mRNA expression, significant enrichment of ncRNAs was identified during prophase I relative to vegetative cells. The core meiotic transcriptome was comprised of 9309 meiosis-specific transcripts, 48 134 previously unannotated meiotic transcripts, and many known and novel ncRNAs differentially expressed at specific stages. The abundant meiotic sncRNAs controlled the reprogramming of central metabolic pathways by targeting genes involved in photosynthesis, glycolysis, hormone biosynthesis, and cellular homeostasis, and lincRNAs enhanced the expression of nearby genes. Alternative splicing was not evident in this polyploid species, but isoforms were switched at phase transitions. The novel, stage-specific regulatory controls uncovered here challenge the conventional understanding of this crucial biological process and provide a new resource of requisite knowledge for those aiming to directly modulate meiosis to improve crop plants. The wheat meiosis transcriptome dataset can be queried for genes of interest using an eFP browser located at https://bar.utoronto.ca/efp&#95;wheat/cgi-bin/efpWeb.cgi?dataSource=Wheat&#95;Meiosis., (© 2023 National Research Council Canada and The Authors. The Plant Journal published by Society for Experimental Biology and John Wiley & Sons Ltd. Reproduced with the permission of the Minister of Innovation, Science, and Economic Development.)

The Canada Western Red Spring wheat ( Triticum aestivum L.) cultivars AAC Concord, AAC Prevail, CDC Hughes, Lillian, Glenlea, and elite line BW961 express a spectrum of resistance to leaf rust caused by Puccinia triticina Eriks. This study aimed to identify and map the leaf rust resistance of the cultivars using three doubled haploid populations, AAC Prevail/BW961 (PB), CDC Hughes/AAC Concord (HC), and Lillian/Glenlea (LG). The populations were evaluated for seedling resistance in the greenhouse and adult plant disease response in the field at Morden, MB for 3 years and genotyped with the 90K wheat Infinium iSelect SNP array. Genetic maps were constructed to perform QTL analysis on the seedling and field leaf rust data. A total of three field leaf rust resistance QTL segregated in the PB population, five in the HC, and six in the LG population. In the PB population, BW961 contributed two QTL on chromosomes 2DS and 7DS, and AAC Prevail contributed a QTL on 4AL consistent across trials. Of the five QTL in HC, AAC Concord contributed two QTL on 4AL and 7AL consistent across trials and a QTL on 3DL.1 that provided seedling resistance only. CDC Hughes contributed two QTL on 1DS and 3DL.2. Lillian contributed four QTL significant in at least two of the three trials on 2BS, 4AL, 5AL, and 7AL, and Glenlea two QTL on 4BL and 7BL. The 1DS QTL from CDC Hughes, the 2DS from BW961, the 4AL from the AAC Prevail, AAC Concord, and Lillian, and the 7AL from AAC Concord and Lillian conferred seedling leaf rust resistance. The QTL on 4AL corresponded with Lr30 and was the same across cultivars AAC Prevail, AAC Concord, and Lillian, whereas the 7AL corresponding with LrCen was coincident between AAC Concord and Lillian. The 7DS and 2DS QTL in BW961 corresponded with Lr34 and Lr2a , respectively, and the 1DS QTL in CDC Hughes with Lr21 . The QTL identified on 5AL could represent a novel gene. The results of this study will widen our knowledge of leaf rust resistance genes in Canadian wheat and their utilization in resistance breeding., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Curtis J. Pozniak, Pierre Hucl and His Majesty the King in Right of Canada, as represented by the Minister of Agriculture and Agri-Food Canada for the contribution of Firdissa E. Bokore, Richard D. Cuthbert, Ron E. Knox, Colin W. Hiebert, Samia Berraies, Yuefeng Ruan, Brad Meyer, Brent D. McCallum.)

Introduction: Wheat rust diseases are widespread and affect all wheat growing areas around the globe. Breeding strategies focus on incorporating genetic disease resistance. However, pathogens can quickly evolve and overcome the resistance genes deployed in commercial cultivars, creating a constant need for identifying new sources of resistance., Methods: We have assembled a diverse tetraploid wheat panel comprised of 447 accessions of three Triticum turgidum subspecies and performed a genome-wide association study (GWAS) for resistance to wheat stem, stripe, and leaf rusts. The panel was genotyped with the 90K Wheat iSelect single nucleotide polymorphism (SNP) array and subsequent filtering resulted in a set of 6,410 non-redundant SNP markers with known physical positions., Results: Population structure and phylogenetic analyses revealed that the diversity panel could be divided into three subpopulations based on phylogenetic/geographic relatedness. Marker-trait associations (MTAs) were detected for two stem rust, two stripe rust and one leaf rust resistance loci. Of them, three MTAs coincide with the known rust resistance genes Sr13, Yr15 and Yr67, while the other two may harbor undescribed resistance genes., Discussion: The tetraploid wheat diversity panel, developed and characterized herein, captures wide geographic origins, genetic diversity, and evolutionary history since domestication making it a useful community resource for mapping of other agronomically important traits and for conducting evolutionary studies., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Klymiuk, Haile, Ens, Wiebe, N’Diaye, Fatiukha, Krugman, Ben-David, Hübner, Cloutier and Pozniak.)

Key Message: rAMP-seq based genomic selection for agronomic traits has been shown to be a useful tool for winter wheat breeding programs by increasing the rate of genetic gain. Genomic selection (GS) is an effective strategy to employ in a breeding program that focuses on optimizing quantitative traits, which results in the ability for breeders to select the best genotypes. GS was incorporated into a breeding program to determine the potential for implementation on an annual basis, with emphasis on selecting optimal parents and decreasing the time and costs associated with phenotyping large numbers of genotypes. The design options for applying repeat amplification sequencing (rAMP-seq) in bread wheat were explored, and a low-cost single primer pair strategy was implemented. A total of 1870 winter wheat genotypes were phenotyped and genotyped using rAMP-seq. The optimization of training to testing population size showed that the 70:30 ratio provided the most consistent prediction accuracy. Three GS models were tested, rrBLUP, RKHS and feed-forward neural networks using the University of Guelph Winter Wheat Breeding Program (UGWWBP) and Elite-UGWWBP populations. The models performed equally well for both populations and did not differ in prediction accuracy (r) for most agronomic traits, with the exception of yield, where RKHS performed the best with an r = 0.34 and 0.39 for each population, respectively. The ability to operate a breeding program where multiple selection strategies, including GS, are utilized will lead to higher efficiency in the program and ultimately lead to a higher rate of genetic gain., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Background: As complete and accurate genome sequences are becoming easier to obtain, more researchers wish to get one or more of them to support their research endeavors. Reliable and well-documented sequence assembly workflows find use in reference or pangenome projects., Results: We describe modifications to the TRITEX genome assembly workflow motivated by the rise of fast and easy long-read contig assembly of inbred plant genomes and the routine deployment of the toolchains in pangenome projects. New features include the use as surrogates of or complements to dense genetic maps and the introduction of user-editable tables to make the curation of contig placements easier and more intuitive., Conclusion: Even maximally contiguous sequence assemblies of the telomere-to-telomere sort, and to a yet greater extent, the fragmented kind require validation, correction, and comparison to reference standards. As pangenomics is burgeoning, these tasks are bound to become more widespread and TRITEX is one tool to get them done. This technical guide is supported by a step-by-step computational tutorial accessible under https://tritexassembly.bitbucket.io/ . The TRITEX source code is hosted under this URL: https://bitbucket.org/tritexassembly ., (© 2022. The Author(s).)

Semidwarfing genes have greatly increased wheat yields globally, yet the widely used gibberellin (GA)-insensitive genes Rht-B1b and Rht-D1b have disadvantages for seedling emergence. Use of the GA-sensitive semidwarfing gene Rht13 avoids this pleiotropic effect. Here, we show that Rht13 encodes a nucleotide-binding site/leucine-rich repeat ( NB-LRR ) gene. A point mutation in the semidwarf Rht-B13b allele autoactivates the NB-LRR gene and causes a height reduction comparable with Rht-B1b and Rht-D1b in diverse genetic backgrounds. The autoactive Rht-B13b allele leads to transcriptional up-regulation of pathogenesis-related genes including class III peroxidases associated with cell wall remodeling. Rht13 represents a new class of reduced height ( Rht ) gene, unlike other Rht genes, which encode components of the GA signaling or metabolic pathways. This discovery opens avenues to use autoactive NB-LRR genes as semidwarfing genes in a range of crop species, and to apply Rht13 in wheat breeding programs using a perfect genetic marker.

The likelihood of success in developing modern cultivars depend on multiple factors, including the identification of suitable parents to initiate new crosses, and characterizations of genomic regions associated with target traits. The objectives of the present study were to (a) determine the best economic weights of four major wheat diseases (leaf spot, common bunt, leaf rust, and stripe rust) and grain yield for multi-trait restrictive linear phenotypic selection index (RLPSI), (b) select the top 10% cultivars and lines (hereafter referred as genotypes) with better resistance to combinations of the four diseases and acceptable grain yield as potential parents, and (c) map genomic regions associated with resistance to each disease using genome-wide association study (GWAS). A diversity panel of 196 spring wheat genotypes was evaluated for their reaction to stripe rust at eight environments, leaf rust at four environments, leaf spot at three environments, common bunt at two environments, and grain yield at five environments. The panel was genotyped with the Wheat 90K SNP array and a few KASP SNPs of which we used 23,342 markers for statistical analyses. The RLPSI analysis performed by restricting the expected genetic gain for yield displayed significant (p < 0.05) differences among the 3125 economic weights. Using the best four economic weights, a subset of 22 of the 196 genotypes were selected as potential parents with resistance to the four diseases and acceptable grain yield. GWAS identified 37 genomic regions, which included 12 for common bunt, 13 for leaf rust, 5 for stripe rust, and 7 for leaf spot. Each genomic region explained from 6.6 to 16.9% and together accounted for 39.4% of the stripe rust, 49.1% of the leaf spot, 94.0% of the leaf rust, and 97.9% of the common bunt phenotypic variance combined across all environments. Results from this study provide valuable information for wheat breeders selecting parental combinations for new crosses to develop improved germplasm with enhanced resistance to the four diseases as well as the physical positions of genomic regions that confer resistance, which facilitates direct comparisons for independent mapping studies in the future.

The development of next-generation sequencing (NGS) enabled a shift from array-based genotyping to directly sequencing genomic libraries for high-throughput genotyping. Even though whole-genome sequencing was initially too costly for routine analysis in large populations such as breeding or genetic studies, continued advancements in genome sequencing and bioinformatics have provided the opportunity to capitalize on whole-genome information. As new sequencing platforms can routinely provide high-quality sequencing data for sufficient genome coverage to genotype various breeding populations, a limitation comes in the time and cost of library construction when multiplexing a large number of samples. Here we describe a high-throughput whole-genome skim-sequencing (skim-seq) approach that can be utilized for a broad range of genotyping and genomic characterization. Using optimized low-volume Illumina Nextera chemistry, we developed a skim-seq method and combined up to 960 samples in one multiplex library using dual index barcoding. With the dual-index barcoding, the number of samples for multiplexing can be adjusted depending on the amount of data required, and could be extended to 3,072 samples or more. Panels of doubled haploid wheat lines (Triticum aestivum, CDC Stanley x CDC Landmark), wheat-barley (T. aestivum x Hordeum vulgare) and wheat-wheatgrass (Triticum durum x Thinopyrum intermedium) introgression lines as well as known monosomic wheat stocks were genotyped using the skim-seq approach. Bioinformatics pipelines were developed for various applications where sequencing coverage ranged from 1 × down to 0.01 × per sample. Using reference genomes, we detected chromosome dosage, identified aneuploidy, and karyotyped introgression lines from the skim-seq data. Leveraging the recent advancements in genome sequencing, skim-seq provides an effective and low-cost tool for routine genotyping and genetic analysis, which can track and identify introgressions and genomic regions of interest in genetics research and applied breeding programs., (© 2022. The Author(s).)

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., (© 2022. The Author(s).)

Key Message: This study performed comprehensive analyses on the predictive abilities of single-trait and two multi-trait models in three populations. Our results demonstrated the superiority of multi-traits over single-trait models across seven agronomic and four to seven disease resistance traits of different genetic architecture. The predictive ability of multi-trait and single-trait prediction models has not been investigated on diverse traits evaluated under organic and conventional management systems. Here, we compared the predictive abilities of 25% of a testing set that has not been evaluated for a single trait (ST), not evaluated for multi-traits (MT1), and evaluated for some traits but not others (MT2) in three spring wheat populations genotyped either with the wheat 90K single nucleotide polymorphisms array or DArTseq. Analyses were performed on seven agronomic traits evaluated under conventional and organic management systems, four to seven disease resistance traits, and all agronomic and disease resistance traits simultaneously. The average prediction accuracies of the ST, MT1, and MT2 models varied from 0.03 to 0.78 (mean 0.41), from 0.05 to 0.82 (mean 0.47), and from 0.05 to 0.92 (mean 0.67), respectively. The predictive ability of the MT2 model was significantly greater than the ST model in all traits and populations except common bunt with the MT1 model being intermediate between them. The MT2 model increased prediction accuracies over the ST and MT1 models in all traits by 9.0-82.4% (mean 37.3%) and 2.9-82.5% (mean 25.7%), respectively, except common bunt that showed up to 7.7% smaller accuracies in two populations. A joint analysis of all agronomic and disease resistance traits further improved accuracies within the MT1 and MT2 models on average by 21.4% and 17.4%, respectively, as compared to either the agronomic or disease resistance traits, demonstrating the high potential of the multi-traits models in improving prediction accuracies., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Some previous studies have assessed the predictive ability of genome-wide selection on stripe (yellow) rust resistance in wheat, but the effect of genotype by environment interaction (GEI) in prediction accuracies has not been well studied in diverse genetic backgrounds. Here, we compared the predictive ability of a model based on phenotypic data only (M1), the main effect of phenotype and molecular markers (M2), and a model that incorporated GEI (M3) using three cross-validations (CV1, CV2, and CV0) scenarios of interest to breeders in six spring wheat populations. Each population was evaluated at three to eight field nurseries and genotyped with either the DArTseq technology or the wheat 90K single nucleotide polymorphism arrays, of which a subset of 1,058- 23,795 polymorphic markers were used for the analyses. In the CV1 scenario, the mean prediction accuracies of the M1, M2, and M3 models across the six populations varied from -0.11 to -0.07, from 0.22 to 0.49, and from 0.19 to 0.48, respectively. Mean accuracies obtained using the M3 model in the CV1 scenario were significantly greater than the M2 model in two populations, the same in three populations, and smaller in one population. In both the CV2 and CV0 scenarios, the mean prediction accuracies of the three models varied from 0.53 to 0.84 and were not significantly different in all populations, except the Attila/CDC Go in the CV2, where the M3 model gave greater accuracy than both the M1 and M2 models. Overall, the M3 model increased prediction accuracies in some populations by up to 12.4% and decreased accuracy in others by up to 17.4%, demonstrating inconsistent results among genetic backgrounds that require considering each population separately. This is the first comprehensive genome-wide prediction study that investigated details of the effect of GEI on stripe rust resistance across diverse spring wheat populations.

Aegilops is a close relative of wheat (Triticum spp.), and Aegilops species in the section Sitopsis represent a rich reservoir of genetic diversity for the improvement of wheat. To understand their diversity and advance their utilization, we produced whole-genome assemblies of Aegilops longissima and Aegilops speltoides. Whole-genome comparative analysis, along with the recently sequenced Aegilops sharonensis genome, showed that the Ae. longissima and Ae. sharonensis genomes are highly similar and are most closely related to the wheat D subgenome. By contrast, the Ae. speltoides genome is more closely related to the B subgenome. Haplotype block analysis supported the idea that Ae. speltoides genome is closest to the wheat B subgenome, and highlighted variable and similar genomic regions between the three Aegilops species and wheat. Genome-wide analysis of nucleotide-binding leucine-rich repeat (NLR) genes revealed species-specific and lineage-specific NLR genes and variants, demonstrating the potential of Aegilops genomes for wheat improvement., (© 2022 The Authors. The Plant Journal published by Society for Experimental Biology and John Wiley & Sons Ltd.)

Key Message: A major QTL on chromosome arm 4BS was associated with reduced spike shattering and reduced plant height in coupling phase, and a second major QTL associated with reduced spike shattering was detected on chromosome arm 5AL in the same wheat variety Carberry. Spike shattering can cause severe grain yield loss in wheat. Development of cultivars with reduced shattering but having easy mechanical threshability is the target of wheat breeding programs. This study was conducted to determine quantitative trait loci (QTL) associated with shattering resistance, and epistasis among QTL in the populations Carberry/AC Cadillac and Carberry/Thatcher. Response of the populations to spike shattering was evaluated near Swift Current, SK, in four to five environments. Plant height data recorded in different locations and years were used to determine the relationship of the trait with spike shattering. Each population was genotyped and mapped with the wheat 90 K Illumina iSelect SNP array. Main effect QTL were analyzed by MapQTL 6, and epistatic interactions between main effect QTL were determined by QTLNetwork 2.0. Correlations between height and shattering ranged from 0.15 to 0.49. Carberry contributed two major QTL associated with spike shattering on chromosome arms 4BS and 5AL, detected in both populations. Carberry also contributed two minor QTL on 7AS and 7AL. AC Cadillac contributed five minor QTL on 1AL, 2DL, 3AL, 3DL and 7DS. Nine epistatic QTL interactions were identified, out of which the most consistent and synergistic interaction, that reduced the expression of shattering, occurred between 4BS and 5AL QTL. The 4BS QTL was consistently associated with reduced shattering and reduced plant height in the coupling phase. The present findings shed light on the inheritance of shattering resistance and provide genetic markers for manipulating the trait to develop wheat cultivars., (© 2022. Crown.)

The wild relatives and progenitors of wheat have been widely used as sources of disease resistance (R) genes. Molecular identification and characterization of these R genes facilitates their manipulation and tracking in breeding programmes. Here, we develop a reference-quality genome assembly of the wild diploid wheat relative Aegilops sharonensis and use positional mapping, mutagenesis, RNA-Seq and transgenesis to identify the stem rust resistance gene Sr62, which has also been transferred to common wheat. This gene encodes a tandem kinase, homologues of which exist across multiple taxa in the plant kingdom. Stable Sr62 transgenic wheat lines show high levels of resistance against diverse isolates of the stem rust pathogen, highlighting the utility of Sr62 for deployment as part of a polygenic stack to maximize the durability of stem rust resistance., (© 2022. The Author(s).)

Some studies have investigated the potential of genomic selection (GS) on stripe rust, leaf rust, Fusarium head blight (FHB), and leaf spot in wheat, but none of them have assessed the effect of the reaction norm model that incorporated GE interactions. In addition, the prediction accuracy on common bunt has not previously been studied. Here, we investigated within-population prediction accuracies using the baseline M1 model and two reaction norm models (M2 and M3) with three random cross-validation (CV1, CV2, and CV0) schemes. Three Canadian spring wheat populations were evaluated in up to eight field environments and genotyped with 3158, 5732, and 23,795 polymorphic markers. The M3 model that incorporated GE interactions reduced residual variance by an average of 10.2% as compared with the main effect M2 model and increased prediction accuracies on average by 2-6%. In some traits, the M3 model increased prediction accuracies up to 54% as compared with the M2 model. The average prediction accuracies of the M3 model with CV1, CV2, and CV0 schemes varied from 0.02 to 0.48, from 0.25 to 0.84, and from 0.14 to 0.87, respectively. In both CV2 and CV0 schemes, stripe rust in all three populations, common bunt and leaf rust in two populations, as well as FHB severity, FHB index, and leaf spot in one population had high to very high (0.54-0.87) prediction accuracies. This is the first comprehensive genomic selection study on five major diseases in spring wheat.

Key Message: Using phenotype data of three spring wheat populations evaluated at 6-15 environments under two management systems, we found moderate to very high prediction accuracies across seven traits. The phenotype data collected under an organic management system effectively predicted the performance of lines in the conventional management and vice versa. There is growing interest in developing wheat cultivars specifically for organic agriculture, but we are not aware of the effect of organic management on the predictive ability of genomic selection (GS). Here, we evaluated within populations prediction accuracies of four GS models, four combinations of training and testing sets, three reaction norm models, and three random cross-validations (CV) schemes in three populations phenotyped under organic and conventional management systems. Our study was based on a total of 578 recombinant inbred lines and varieties from three spring wheat populations, which were evaluated for seven traits at 3-9 conventionally and 3-6 organically managed field environments and genotyped either with the wheat 90 K SNP array or DArTseq. We predicted the management systems (CV0 M ) or environments (CV0), a subset of lines that have been evaluated in either management (CV2 M ) or some environments (CV2), and the performance of newly developed lines in either management (CV1 M ) or environments (CV1). The average prediction accuracies of the model that incorporated genotype × environment interactions with CV0 and CV2 schemes varied from 0.69 to 0.97. In the CV1 and CV1M schemes, prediction accuracies ranged from - 0.12 to 0.77 depending on the reaction norm models, the traits, and populations. In most cases, grain protein showed the highest prediction accuracies. The phenotype data collected under the organic management effectively predicted the performance of lines under conventional management and vice versa. This is the first comprehensive GS study that investigated the effect of the organic management system in wheat., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The hexaploid spring wheat cultivar, Carberry, was registered in Canada in 2009, and has since been grown over an extensive area on the Canadian Prairies. Carberry has maintained a very high level of leaf rust ( Puccinia triticina Eriks.) resistance since its release. To understand the genetic basis of Carberry's leaf rust resistance, Carberry was crossed with the susceptible cultivar, Thatcher, and a doubled haploid (DH) population of 297 lines was generated. The DH population was evaluated for leaf rust in seven field environments at the adult plant stage. Seedling and adult plant resistance (APR) to multiple virulence phenotypes of P. triticina was evaluated on the parents and the progeny population in controlled greenhouse studies. The population was genotyped with the wheat 90 K iSelect single nucleotide polymorphism (SNP) array, and quantitative trait loci (QTL) analysis was performed. The analysis using field leaf rust response indicated that Carberry contributed nine QTL located on chromosomes 1B, 2B (2 loci), 2D, 4A, 4B, 5A, 5B, and 7D. The QTL located on 1B, 2B, 5B, and 7D chromosomes were observed in two or more environments, whereas the remainder were detected in single environments. The resistance on 1B, detected in five environments, was attributed to Lr46 and on 7D, detected in seven environments to Lr34 . The first 2B QTL corresponded with the adult plant gene, Lr13 , while the second QTL corresponded with Lr16 . The seedling analysis showed that Carberry carries Lr2a , Lr16 , and Lr23 . Five epistatic effects were identified in the population, with synergistic interactions being observed for Lr34 with Lr46 , Lr16 , and Lr2a . The durable rust resistance of Carberry is attributed to Lr34 and Lr46 in combination with these other resistance genes, because the resistance has remained effective even though the P. triticina population has evolved virulent to Lr2a, Lr13, Lr16 , and Lr23 ., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Amidou N’Diaye, Curtis J. Pozniak and Her Majesty the Queen in Right of Canada, as represented by the Minister of Agriculture and Agri-Food Canada for the contribution of Firdissa E. Bokore, Ron E. Knox, Colin W. Hiebert, Richard D. Cuthbert, Ron M. DePauw, Brad Meyer, and Brent D. McCallum.)

Previous molecular characterization studies conducted in Canadian wheat cultivars shed some light on the impact of plant breeding on genetic diversity, but the number of varieties and markers used was small. Here, we used 28,798 markers of the wheat 90K single nucleotide polymorphisms to (a) assess the extent of genetic diversity, relationship, population structure, and divergence among 174 historical and modern Canadian spring wheat varieties registered from 1905 to 2018 and 22 unregistered lines (hereinafter referred to as cultivars), and (b) identify genomic regions that had undergone selection. About 91% of the pairs of cultivars differed by 20-40% of the scored alleles, but only 7% of the pairs had kinship coefficients of < 0.250, suggesting the presence of a high proportion of redundancy in allelic composition. Although the 196 cultivars represented eight wheat classes, our results from phylogenetic, principal component, and the model-based population structure analyses revealed three groups, with no clear structure among most wheat classes, breeding programs, and breeding periods. F ST statistics computed among different categorical variables showed little genetic differentiation (< 0.05) among breeding periods and breeding programs, but a diverse level of genetic differentiation among wheat classes and predicted groups. Diversity indices were the highest and lowest among cultivars registered from 1970 to 1980 and from 2011 to 2018, respectively. Using two outlier detection methods, we identified from 524 to 2314 SNPs and 41 selective sweeps of which some are close to genes with known phenotype, including plant height, photoperiodism, vernalization, gluten strength, and disease resistance., (© 2021. The Author(s).)

Wheat has one of the largest and most repetitive genomes among major crop plants, containing over 85% transposable elements (TEs). TEs populate genomes much in the way that individuals populate ecosystems, diversifying into different lineages, sub-families and sub-populations. The recent availability of high-quality, chromosome-scale genome sequences from ten wheat lines enables a detailed analysis how TEs evolved in allohexaploid wheat, its diploids progenitors, and in various chromosomal haplotype segments. LTR retrotransposon families evolved into distinct sub-populations and sub-families that were active in waves lasting several hundred thousand years. Furthermore, It is shown that different retrotransposon sub-families were active in the three wheat sub-genomes, making them useful markers to study and date polyploidization events and chromosomal rearrangements. Additionally, haplotype-specific TE sub-families are used to characterize chromosomal introgressions in different wheat lines. Additionally, populations of non-autonomous TEs co-evolved over millions of years with their autonomous partners, leading to complex systems with multiple types of autonomous, semi-autonomous and non-autonomous elements. Phylogenetic and TE population analyses revealed the relationships between non-autonomous elements and their mobilizing autonomous partners. TE population analysis provided insights into genome evolution of allohexaploid wheat and genetic diversity of species, and may have implication for future crop breeding., Competing Interests: The authors declare no conflict of interest., (© 2021 The Authors. Advanced Genetics published by Wiley Periodicals LLC.)

Key Message: Using phenotypic data of four biparental spring wheat populations evaluated at multiple environments under two management systems, we discovered 152 QTL and 22 QTL hotspots, of which two QTL accounted for up to 37% and 58% of the phenotypic variance, consistently detected in all environments, and fell within genomic regions harboring known genes. Identification of the physical positions of quantitative trait loci (QTL) would be highly useful for developing functional markers and comparing QTL results across multiple independent studies. The objectives of the present study were to map and characterize QTL associated with nine agronomic and end-use quality traits (tillering ability, plant height, lodging, grain yield, grain protein content, thousand kernel weight, test weight, sedimentation volume, and falling number) in hard red spring wheat recombinant inbred lines (RILs) using the International Wheat Genome Sequencing Consortium (IWGSC) RefSeq v2.0 physical map. We evaluated a total of 698 RILs from four populations derived from crosses involving seven parents at 3-8 conventionally (high N) and organically (low N) managed field environments. Using the phenotypic data combined across all environments per management, and the physical map between 1058 and 6526 markers per population, we identified 152 QTL associated with the nine traits, of which 29 had moderate and 2 with major effects. Forty-nine of the 152 QTL mapped across 22 QTL hotspot regions with each region coincident to 2-6 traits. Some of the QTL hotspots were physically located close to known genes. QSv.dms-1A and QPht.dms-4B.1 individually explained up to 37% and 58% of the variation in sedimentation volume and plant height, respectively, and had very large LOD scores that varied from 19.0 to 35.7 and from 16.7 to 55.9, respectively. We consistently detected both QTL in the combined and all individual environments, laying solid ground for further characterization and possibly for cloning., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Plant-pathogen interactions result in disease development in a susceptible host. Plants actively resist pathogens via a complex immune system comprising both surface-localized receptors that sense the extracellular space as well as intracellular receptors recognizing pathogen effectors. To date, the majority of cloned resistance genes encode intracellular nucleotide-binding leucine-rich repeat receptor proteins. Recent discoveries have revealed tandem kinase proteins (TKPs) as another important family of intracellular proteins involved in plant immune responses. Five TKP genes-barley Rpg1 and wheat WTK1 ( Yr15 ), WTK2 ( Sr60 ), WTK3 ( Pm24 ), and WTK4 -protect against devastating fungal diseases. Moreover, a large diversity and numerous putative TKPs exist across the plant kingdom. This review explores our current knowledge of TKPs and serves as a basis for future studies that aim to develop and exploit a deeper understanding of innate plant immunity receptor proteins.[Formula: see text] Copyright © 2021 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

The Global Wheat Head Detection (GWHD) dataset was created in 2020 and has assembled 193,634 labelled wheat heads from 4700 RGB images acquired from various acquisition platforms and 7 countries/institutions. With an associated competition hosted in Kaggle, GWHD&#95;2020 has successfully attracted attention from both the computer vision and agricultural science communities. From this first experience, a few avenues for improvements have been identified regarding data size, head diversity, and label reliability. To address these issues, the 2020 dataset has been reexamined, relabeled, and complemented by adding 1722 images from 5 additional countries, allowing for 81,553 additional wheat heads. We now release in 2021 a new version of the Global Wheat Head Detection dataset, which is bigger, more diverse, and less noisy than the GWHD&#95;2020 version., Competing Interests: The authors declare that there is no conflict of interest regarding the publication of this article., (Copyright © 2021 Etienne David et al.)

Among polyploid species with complex genomic architecture, variations in the regulation of alternative splicing (AS) provide opportunities for transcriptional and proteomic plasticity and the potential for generating trait diversities. However, the evolution of AS and its influence on grain development in diploid grass and valuable polyploid wheat crops are poorly understood. To address this knowledge gap, we developed a pipeline for the analysis of alternatively spliced transcript isoforms, which takes the high sequence similarity among polyploid wheat subgenomes into account. Through analysis of synteny and detection of collinearity of homoeologous subgenomes, conserved and specific AS events across five wheat and grass species were identified. A global analysis of the regulation of AS in diploid grass and polyploid wheat grains revealed diversity in AS events not only between the endosperm, pericarp and embryo overdevelopment, but also between subgenomes. Analysis of AS in homoeologous triads of polyploid wheats revealed evolutionary divergence between gene-level and transcript-level regulation of embryogenesis. Evolutionary age analysis indicated that the generation of novel transcript isoforms has occurred in young genes at a more rapid rate than in ancient genes. These findings, together with the development of comprehensive AS resources for wheat and grass species, advance understanding of the evolution of regulatory features of AS during embryogenesis and grain development in wheat., (© 2021 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.)

Sequence assembly of large and repeat-rich plant genomes has been challenging, requiring substantial computational resources and often several complementary sequence assembly and genome mapping approaches. The recent development of fast and accurate long-read sequencing by circular consensus sequencing (CCS) on the PacBio platform may greatly increase the scope of plant pan-genome projects. Here, we compare current long-read sequencing platforms regarding their ability to rapidly generate contiguous sequence assemblies in pan-genome studies of barley (Hordeum vulgare). Most long-read assemblies are clearly superior to the current barley reference sequence based on short-reads. Assemblies derived from accurate long reads excel in most metrics, but the CCS approach was the most cost-effective strategy for assembling tens of barley genomes. A downsampling analysis indicated that 20-fold CCS coverage can yield very good sequence assemblies, while even five-fold CCS data may capture the complete sequence of most genes. We present an updated reference genome assembly for barley with near-complete representation of the repeat-rich intergenic space. Long-read assembly can underpin the construction of accurate and complete sequences of multiple genomes of a species to build pan-genome infrastructures in Triticeae crops and their wild relatives., (© American Society of Plant Biologists 2021.)

Cultivated germplasm provides an opportunity to investigate how crop agronomic traits, selection for major genes, and differences in crossing-over rates drive patterns of allelic variation. To identify how these factors correlated with allelic variation within a collection of cultivated bread wheat (Triticum aestivum L.), we generated genotypes for 388 accessions grown in Canada over the past 170 yr using filtered single nucleotide polymorphism (SNP) calls from an Illumina Wheat iSelect 90K SNP-array. Entries' breeding program, era of release, grain texture, kernel color, and growth habit contributed to allelic differentiation. Allelic diversity and linkage disequilibrium (LD) of markers flanking some major loci known to affect traits such as gluten strength, growth habit, and grain color were consistent with selective sweeps. Nonetheless, some flanking markers of major loci had low LD and high allelic diversity. Positive selection may have acted upon homoeologous genes that had significant enrichment for the gene ontology terms 'response-to-auxin' and 'response-to-wounding.' Long regions of LD, spanning approximately one-third the length of entire chromosomes, were associated with many pericentromeric regions. These regions were also characterized by low diversity. Enhancing recombination across these regions could generate novel allele combinations to accelerate Canadian wheat improvement., (© 2021 The Authors. The Plant Genome published by Wiley Periodicals LLC on behalf of Crop Science Society of America.)

It is thought that modern wheat genotypes have lost their capacity to associate with soil microbes that would help them acquire nutrients from the soil. To test this hypothesis, ten ancestral and modern wheat genotypes were seeded in a field experiment under low fertilization conditions. The rhizosphere soil was collected, its DNA extracted and submitted to shotgun metagenomic sequencing. In contrast to our hypothesis, there was no significant difference in the global rhizosphere metagenomes of the different genotypes, and this held true when focusing the analyses on specific taxonomic or functional categories of genes. Some genes were significantly more abundant in the rhizosphere of one genotype or another, but they comprised only a small portion of the total genes identified and did not affect the global rhizosphere metagenomes. Our study shows for the first time that the rhizosphere metagenome of wheat is stable across a wide variety of genotypes when growing under nutrient poor conditions., (© The Author(s) 2021. Published by Oxford University Press on behalf of FEMS. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

In previous studies, we reported quantitative trait loci (QTL) associated with the heading, flowering, and maturity time in four hard red spring wheat recombinant inbred line (RIL) populations but the results are scattered in population-specific genetic maps, which is challenging to exploit efficiently in breeding. Here, we mapped and characterized QTL associated with these three earliness traits using the International Wheat Genome Sequencing Consortium (IWGSC) RefSeq v2.0 physical map. Our data consisted of (i) 6526 single nucleotide polymorphisms (SNPs) and two traits evaluated at five conventionally managed environments in the 'Cutler' × 'AC Barrie' population; (ii) 3158 SNPs and two traits evaluated across three organic and seven conventional managements in the 'Attila' × 'CDC Go' population; (iii) 5731 SilicoDArT and SNP markers and the three traits evaluated at four conventional and organic management systems in the 'Peace' × 'Carberry' population; and (iv) 1058 SNPs and two traits evaluated across two conventionally and organically managed environments in the 'Peace' × 'CDC Stanley' population. Using composite interval mapping, the phenotypic data across all environments, and the IWGSC RefSeq v2.0 physical maps, we identified a total of 44 QTL associated with days to heading (11), flowering (10), and maturity (23). Fifteen of the 44 QTL were common to both conventional and organic management systems, and the remaining QTL were specific to either the conventional (21) or organic (8) management systems. Some QTL harbor known genes, including the Vrn-A1 , Vrn-B1 , Rht-A1 , and Rht-B1 that regulate photoperiodism, flowering time, and plant height in wheat, which lays a solid basis for cloning and further characterization.

Rye (Secale cereale L.) is an exceptionally climate-resilient cereal crop, used extensively to produce improved wheat varieties via introgressive hybridization and possessing the entire repertoire of genes necessary to enable hybrid breeding. Rye is allogamous and only recently domesticated, thus giving cultivated ryes access to a diverse and exploitable wild gene pool. To further enhance the agronomic potential of rye, we produced a chromosome-scale annotated assembly of the 7.9-gigabase rye genome and extensively validated its quality by using a suite of molecular genetic resources. We demonstrate applications of this resource with a broad range of investigations. We present findings on cultivated rye's incomplete genetic isolation from wild relatives, mechanisms of genome structural evolution, pathogen resistance, low-temperature tolerance, fertility control systems for hybrid breeding and the yield benefits of rye-wheat introgressions.

Human population growth has increased the demand for food crops, animal feed, biofuel and biomaterials, all the while climate change is impacting environmental growth conditions. There is an urgent need to develop crop varieties which tolerate adverse growth conditions while requiring fewer inputs. Plant breeding is critical to global food security and, while it has benefited from modern technologies, it remains constrained by a lack of valuable genetic diversity, linkage drag, and an effective way to combine multiple favourable alleles for complex traits. CRISPR/Cas technology has transformed genome editing across biological systems and promises to transform agriculture with its high precision, ease of design, multiplexing ability and low cost. We discuss the integration of CRISPR/Cas-based gene editing into crop breeding to advance domestication and refine inbred crop varieties for various applications and growth environments. We highlight the use of CRISPR/Cas-based gene editing to fix desirable allelic variants, generate novel alleles, break deleterious genetic linkages, support pre-breeding and for introgression of favourable loci into elite lines., (© 2021 Her Majesty the Queen in Right of Canada. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd. Reproduced with the permission of the Minister of National Research Council Canada.)

Bread wheat is a major crop that has long been the focus of basic and breeding research. Assembly of its genome has been difficult because of its large size and allohexaploid nature (AABBDD genome). Following the first reported assembly of the genome of the experimental strain Chinese Spring (CS), the 10+ Wheat Genomes Project was launched to produce multiple assemblies of worldwide modern cultivars. The only Asian cultivar in the project is Norin 61, a representative Japanese cultivar adapted to grow across a broad latitudinal range, mostly characterized by a wet climate and a short growing season. Here, we characterize the key aspects of its chromosome-scale genome assembly spanning 15 Gb with a raw scaffold N50 of 22 Mb. Analysis of the repetitive elements identified chromosomal regions unique to Norin 61 that encompass a tandem array of the pathogenesis-related 13 family. We report novel copy-number variations in the B homeolog of the florigen gene FT1/VRN3, pseudogenization of its D homeolog and the association of its A homeologous alleles with the spring/winter growth habit. Furthermore, the Norin 61 genome carries typical East Asian functional variants different from CS, ranging from a single nucleotide to multi-Mb scale. Examples of such variation are the Fhb1 locus, which confers Fusarium head-blight resistance, Ppd-D1a, which confers early flowering, Glu-D1f for Asian noodle quality and Rht-D1b, which introduced semi-dwarfism during the green revolution. The adoption of Norin 61 as a reference assembly for functional and evolutionary studies will enable comprehensive characterization of the underexploited Asian bread wheat diversity., (� The Author(s) 2021. Published by Oxford University Press on behalf of Japanese Society of Plant Physiologists.)

Key Message: The first cytological characterization of the 2N v S segment in hexaploid wheat; complete de novo assembly and annotation of 2N v S segment; 2N v S frequency is increasing 2N v S and is associated with higher yield. The Aegilops ventricosa 2N v S translocation segment has been utilized in breeding disease-resistant wheat crops since the early 1990s. This segment is known to possess several important resistance genes against multiple wheat diseases including root knot nematode, stripe rust, leaf rust and stem rust. More recently, this segment has been associated with resistance to wheat blast, an emerging and devastating wheat disease in South America and Asia. To date, full characterization of the segment including its size, gene content and its association with grain yield is lacking. Here, we present a complete cytological and physical characterization of this agronomically important translocation in bread wheat. We de novo assembled the 2N v S segment in two wheat varieties, 'Jagger' and 'CDC Stanley,' and delineated the segment to be approximately 33 Mb. A total of 535 high-confidence genes were annotated within the 2N v S region, with > 10% belonging to the nucleotide-binding leucine-rich repeat (NLR) gene families. Identification of groups of NLR genes that are potentially N genome-specific and expressed in specific tissues can fast-track testing of candidate genes playing roles in various disease resistances. We also show the increasing frequency of 2N v S among spring and winter wheat breeding programs over two and a half decades, and the positive impact of 2N v S on wheat grain yield based on historical datasets. The significance of the 2N v S segment in wheat breeding due to resistance to multiple diseases and a positive impact on yield highlights the importance of understanding and characterizing the wheat pan-genome for better insights into molecular breeding for wheat improvement.

Key Message: A major QTL for oviposition deterrence to orange wheat blossom midge was detected on chromosome 1A in the Canadian breeding line BW278 that was inherited from the Chinese variety Sumai-3. Orange wheat blossom midge (OWBM, Sitodiplosis mosellana Géhin, Diptera: Cecidomyiidae) is an important insect pest of wheat (Triticum aestivum L.) that reduces both grain yield and quality. Oviposition deterrence results in a reduction of eggs deposited on spikes relative to that observed on a wheat line preferred by OWBM. Quantification of oviposition deterrence is labor-intensive, so wheat breeders require efficient DNA markers for the selection of this trait. The objective of this study was to identify quantitative trait loci (QTL) for oviposition deterrence in a doubled haploid (DH) population developed from the spring wheat cross Superb/BW278. The DH population and check varieties were evaluated for OWBM kernel damage from five field nurseries over three growing seasons. QTL analysis identified major effect loci on chromosomes 1A (QSm.mrc-1A) and 5A (QSm.mrc-5A). Reduced kernel damage was contributed by BW278 at QSm.mrc-1A and Superb at QSm.mrc-5A. QSm.mrc-1A mapped to the approximate location of the oviposition deterrence QTL previously found in the American variety Reeder. However, haplotype analysis revealed that BW278 inherited this oviposition deterrence allele from the Chinese spring wheat variety Sumai-3. QSm.mrc-5A mapped to the location of awn inhibitor gene B1, suggesting that awns hinder OWBM oviposition. Single-nucleotide polymorphisms (SNPs) were identified for predicting the presence or absence of QSm.mrc-1A based upon haplotype. Functional annotation of candidate genes in 1A QTL intervals revealed eleven potential candidate genes, including a gene involved in terpenoid biosynthesis. SNPs for QSm.mrc-1A and fully awned spikes provide a basis for the selection of oviposition deterrence to OWBM.

Fusarium head blight (FHB) is a serious fungal disease affecting wheat and other cereals worldwide. This fungus causes severe yield and quality losses from a reduction in grain quality and contamination of grain with mycotoxins. Intensive breeding efforts led to the release of AAC Tenacious, which was the first spring wheat cultivar registered in Canada with a resistant (R) rating to FHB. To elucidate the physiological mechanisms of resistance, we performed histological and transcriptomic analyses of AAC Tenacious and a susceptible control Roblin after inoculation with Fusarium graminearum ( Fg ). The spikelet and rachis of infected wheat spikes were hand sectioned and monitored by confocal and fluorescent microscopy. Visible hyphae were observed within the inoculated spikelets for AAC Tenacious; however, the infection was largely restricted to the point of inoculation (POI), whereas the adjacent florets in Roblin were heavily infected. Significant cell wall thickening within the rachis node below the POI was evident in AAC Tenacious compared to Roblin in response to Fg inoculation. Rachis node and rachilla tissues from the POI and the rachis node below the POI were collected at 5 days post inoculation for RNAseq. Significant changes in gene expression were detected in both cultivars in response to infection. The rachis node below the POI in AAC Tenacious had fewer differentially expressed genes (DEGs) when compared to the uninoculated control, likely due to its increased disease resistance. Analysis of DEGs in Roblin and AAC Tenacious revealed the activation of genes and pathways in response to infection, including those putatively involved in cell wall modification and defense response., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Nilsen, Walkowiak, Kumar, Molina, Randhawa, Dhariwal, Byrns, Pozniak and Henriquez.)

Key Message: Genomic predictions across environments and within populations resulted in moderate to high accuracies but across-population genomic prediction should not be considered in wheat for small population size. Genomic selection (GS) is a marker-based selection suggested to improve the genetic gain of quantitative traits in plant breeding programs. We evaluated the effects of training population (TP) composition, cross-validation design, and genetic relationship between the training and breeding populations on the accuracy of GS in spring wheat (Triticum aestivum L.). Two populations of 231 and 304 spring hexaploid wheat lines that were phenotyped for six agronomic traits and genotyped with the wheat 90 K array were used to assess the accuracy of seven GS models (RR-BLUP, G-BLUP, BayesB, BL, RKHS, GS + de novo GWAS, and reaction norm) using different cross-validation designs. BayesB outperformed the other models for within-population genomic predictions in the presence of few quantitative trait loci (QTL) with large effects. However, including fixed-effect marker covariates gave better performance for an across-population prediction when the same QTL underlie traits in both populations. The accuracy of prediction was highly variable based on the cross-validation design, which suggests the importance to use a design that resembles the variation within a breeding program. Moderate to high accuracies were obtained when predictions were made within populations. In contrast, across-population genomic prediction accuracies were very low, suggesting that the evaluated models are not suitable for prediction across independent populations. On the other hand, across-environment prediction and forward prediction designs using the reaction norm model resulted in moderate to high accuracies, suggesting that GS can be applied in wheat to predict the performance of newly developed lines and lines in incomplete field trials.

Representative, broad and diverse collections are a primary resource to dissect genetic diversity and meet pre-breeding and breeding goals through the identification of beneficial alleles for target traits. From 2,500 tetraploid wheat accessions obtained through an international collaborative effort, a Global Durum wheat Panel (GDP) of 1,011 genotypes was assembled that captured 94-97% of the original diversity. The GDP consists of a wide representation of Triticum turgidum ssp. durum modern germplasm and landraces, along with a selection of emmer and primitive tetraploid wheats to maximize diversity. GDP accessions were genotyped using the wheat iSelect 90K SNP array. Among modern durum accessions, breeding programs from Italy, France and Central Asia provided the highest level of genetic diversity, with only a moderate decrease in genetic diversity observed across nearly 50 years of breeding (1970-2018). Further, the breeding programs from Europe had the largest sets of unique alleles. LD was lower in the landraces (0.4 Mbp) than in modern germplasm (1.8 Mbp) at r 2 = 0.5. ADMIXTURE analysis of modern germplasm defined a minimum of 13 distinct genetic clusters ( k ), which could be traced to the breeding program of origin. Chromosome regions putatively subjected to strong selection pressure were identified from fixation index ( F st ) and diversity reduction index ( DRI ) metrics in pairwise comparisons among decades of release and breeding programs. Clusters of putative selection sweeps (PSW) were identified as co-localized with major loci controlling phenology ( Ppd and Vrn ), plant height ( Rht ) and quality (gliadins and glutenins), underlining the role of the corresponding genes as driving elements in modern breeding. Public seed availability and deep genetic characterization of the GDP make this collection a unique and ideal resource to identify and map useful genetic diversity at loci of interest to any breeding program., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The reviewer MR declared a past co-authorship with several of the authors DM and FL to the handling editor., (Copyright © 2020 Mazzucotelli, Sciara, Mastrangelo, Desiderio, Xu, Faris, Hayden, Tricker, Ozkan, Echenique, Steffenson, Knox, Niane, Udupa, Longin, Marone, Petruzzino, Corneti, Ormanbekova, Pozniak, Roncallo, Mather, Able, Amri, Braun, Ammar, Baum, Cattivelli, Maccaferri, Tuberosa and Bassi.)