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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.

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.

Key messageWe discovered a natural FT-A2 allele that increases grain number per spike in both pasta and bread wheat with limited effect on heading time. Increases in wheat grain yield are necessary to meet future global food demands. A previous study showed that loss-of-function mutations in FLOWERING LOCUS T2 (FT2) increase spikelet number per spike (SNS), an important grain yield component. However, these mutations were also associated with reduced fertility, offsetting the beneficial effect of the increases in SNS on grain number. Here, we report a natural mutation resulting in an aspartic acid to alanine change at position 10 (D10A) associated with significant increases in SNS and no negative effects on fertility. Using a high-density genetic map, we delimited the SNS candidate region to a 5.2-Mb region on chromosome 3AS including 28 genes. Among them, only FT-A2 showed a non-synonymous polymorphism (D10A) present in two different populations segregating for the SNS QTL on chromosome arm 3AS. These results, together with the known effect of the ft-A2 mutations on SNS, suggest that variation in FT-A2 is the most likely cause of the observed differences in SNS. We validated the positive effects of the A10 allele on SNS, grain number, and grain yield per spike in near-isogenic tetraploid wheat lines and in an hexaploid winter wheat population. The A10 allele is present at very low frequency in durum wheat and at much higher frequency in hexaploid wheat, particularly in winter and fall-planted spring varieties. These results suggest that the FT-A2 A10 allele may be particularly useful for improving grain yield in durum wheat and fall-planted common wheat varieties.

Allopolyploidy greatly expands the range of possible regulatory interactions among functionally redundant homoeologous genes. However, connection between the emerging regulatory complexity and expression and phenotypic diversity in polyploid crops remains elusive. Here, we use diverse wheat accessions to map expression quantitative trait loci (eQTL) and evaluate their effects on the population-scale variation in homoeolog expression dosage. The relative contribution of cis- and trans-eQTL to homoeolog expression variation is strongly affected by both selection and demographic events. Though trans-acting effects play major role in expression regulation, the expression dosage of homoeologs is largely influenced by cis-acting variants, which appear to be subjected to selection. The frequency and expression of homoeologous gene alleles showing strong expression dosage bias are predictive of variation in yield-related traits, and have likely been impacted by breeding for increased productivity. Our study highlights the importance of genomic variants affecting homoeolog expression dosage in shaping agronomic phenotypes and points at their potential utility for improving yield in polyploid crops.

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.

Nucleotide-binding leucine-rich repeat receptors (NLRs) are the most abundant type of immune receptors in plants and can trigger a rapid cell-death (hypersensitive) response upon sensing pathogens. We previously cloned the wheat NLR Sr35, which encodes a coiled-coil (CC) NLR that confers resistance to the virulent wheat stem rust race Ug99. Here, we investigated Sr35 signaling after Agrobacterium-mediated transient expression in Nicotiana benthamiana. Expression of Sr35 in N. benthamiana leaves triggered a mild cell-death response, which is enhanced in the autoactive mutant Sr35 D503V. The N-terminal tagging of Sr35 with green fluorescent protein (GFP) blocked the induction of cell death, whereas a C-terminal GFP tag did not. No domain truncations of Sr35 generated cell-death responses as strong as the wild type, but a truncation including the NB-ARC (nucleotide binding adaptor) shared by APAF-1, R proteins, and CED-4 domains in combination with the D503V autoactive mutation triggered cell death. In addition, coexpression of Sr35 with the matching pathogen effector protein AvrSr35 resulted in robust cell death and electrolyte leakage levels that were similar to autoactive Sr35 and significantly higher than Sr35 alone. Coexpression of Sr35-CC-NB-ARC and AvrSr35 did not induce cell death, confirming the importance of the leucine-rich repeat (LRR) domain for AvrSr35 recognition. These findings were confirmed through Agrobacterium-mediated transient expression in barley. Taken together, these results implicate the CC-NB-ARC domains of Sr35 in inducing cell death and the LRR domain in AvrSr35 recognition.[Formula: see text] Copyright © 2020 The Author(s). This is an open access article distributed under the CC BY 4.0 International license.

Key messageA high-resolution genetic map combined with haplotype analyses identified a wheat ortholog of rice gene APO1 as the best candidate gene for a 7AL locus affecting spikelet number per spike. A better understanding of the genes controlling differences in wheat grain yield components can accelerate the improvements required to satisfy future food demands. In this study, we identified a promising candidate gene underlying a quantitative trait locus (QTL) on wheat chromosome arm 7AL regulating spikelet number per spike (SNS). We used large heterogeneous inbred families ( > 10,000 plants) from two crosses to map the 7AL QTL to an 87-kb region (674,019,191-674,106,327 bp, RefSeq v1.0) containing two complete and two partial genes. In this region, we found three major haplotypes that were designated as H1, H2 and H3. The H2 haplotype contributed the high-SNS allele in both H1 × H2 and H2 × H3 segregating populations. The ancestral H3 haplotype is frequent in wild emmer (48%) but rare (~ 1%) in cultivated wheats. By contrast, the H1 and H2 haplotypes became predominant in modern cultivated durum and common wheat, respectively. Among the four candidate genes, only TraesCS7A02G481600 showed a non-synonymous polymorphism that differentiated H2 from the other two haplotypes. This gene, designated here as WHEAT ORTHOLOG OF APO1 (WAPO1), is an ortholog of the rice gene ABERRANT PANICLE ORGANIZATION 1 (APO1), which affects spikelet number. Taken together, the high-resolution genetic map, the association between polymorphisms in the different mapping populations with differences in SNS, and the known role of orthologous genes in other grass species suggest that WAPO-A1 is the most likely candidate gene for the 7AL SNS QTL among the four genes identified in the candidate gene region.

Recombination affects the fate of alleles in populations by imposing constraints on the reshuffling of genetic information. Understanding the genetic basis of these constraints is critical for manipulating the recombination process to improve the resolution of genetic mapping, and reducing the negative effects of linkage drag and deleterious genetic load in breeding. Using sequence-based genotyping of a wheat nested association mapping (NAM) population of 2,100 recombinant inbred lines created by crossing 29 diverse lines, we mapped QTL affecting the distribution and frequency of 102 000 crossovers (CO). Genome-wide recombination rate variation was mostly defined by rare alleles with small effects together explaining up to 48.6% of variation. Most QTL were additive and showed predominantly trans-acting effects. The QTL affecting the proximal COs also acted additively without increasing the frequency of distal COs. We showed that the regions with decreased recombination carry more single nucleotide polymorphisms (SNPs) with possible deleterious effects than the regions with a high recombination rate. Therefore, our study offers insights into the genetic basis of recombination rate variation in wheat and its effect on the distribution of deleterious SNPs across the genome. The identified trans-acting additive QTL can be utilized to manipulate CO frequency and distribution in the large polyploid wheat genome opening the possibility to improve the efficiency of gene pyramiding and reducing the deleterious genetic load in the low-recombining pericentromeric regions of chromosomes.

KEY MESSAGE:Chromosome regions affecting grain yield, grain yield components and plant water status were identified and validated in fall-sown spring wheats grown under full and limited irrigation. Increases in wheat production are required to feed a growing human population. To understand the genetic basis of grain yield in fall-sown spring wheats, we performed a genome-wide association study (GWAS) including 262 photoperiod-insensitive spring wheat accessions grown under full and limited irrigation treatments. Analysis of molecular variance showed that 4.1% of the total variation in the panel was partitioned among accessions originally developed under fall-sowing or spring-sowing conditions, 11.7% among breeding programs within sowing times and 84.2% among accessions within breeding programs. We first identified QTL for grain yield, yield components and plant water status that were significant in at least three environments in the GWAS, and then selected those that were also significant in at least two environments in a panel of eight biparental mapping populations. We identified and validated 14 QTL for grain yield, 15 for number of spikelets per spike, one for kernel number per spike, 11 for kernel weight and 9 for water status, which were not associated with differences in plant height or heading date. We detected significant correlations among traits and colocated QTL that were consistent with those correlations. Among those, grain yield and plant water status were negatively correlated in all environments, and six QTL for these traits were colocated or tightly linked (

Puccinia graminis f. sp. tritici (Pgt) causes wheat stem rust, a devastating fungal disease. The Sr35 resistance gene confers immunity against this pathogen's most virulent races, including Ug99. We used comparative whole-genome sequencing of chemically mutagenized and natural Pgt isolates to identify a fungal gene named AvrSr35 that is required for Sr35 avirulence. The AvrSr35 gene encodes a secreted protein capable of interacting with Sr35 and triggering the immune response. We show that the origin of Pgt isolates virulent on Sr35 is associated with the nonfunctionalization of the AvrSr35 gene by the insertion of a mobile element. The discovery of AvrSr35 provides a new tool for Pgt surveillance, identification of host susceptibility targets, and characterization of the molecular determinants of immunity in wheat.

Summary: Wheat immunotoxicity is associated with abnormal reaction to gluten‐derived peptides. Attempts to reduce immunotoxicity using breeding and biotechnology often affect dough quality. Here, the multiplexed CRISPR‐Cas9 editing of cultivar Fielder was used to modify gluten‐encoding genes, specifically focusing on ω‐ and γ‐gliadin gene copies, which were identified to be abundant in immunoreactive peptides based on the analysis of wheat genomes assembled using the long‐read sequencing technologies. The whole‐genome sequencing of an edited line showed mutation or deletion of nearly all ω‐gliadin and half of the γ‐gliadin gene copies and confirmed the lack of editing in the α/β‐gliadin genes. The estimated 75% and 64% reduction in ω‐ and γ‐gliadin content, respectively, had no negative impact on the end‐use quality characteristics of grain protein and dough. A 47‐fold immunoreactivity reduction compared to a non‐edited line was demonstrated using antibodies against immunotoxic peptides. Our results indicate that the targeted CRISPR‐based modification of the ω‐ and γ‐gliadin gene copies determined to be abundant in immunoreactive peptides by analysing high‐quality genome assemblies is an effective mean for reducing immunotoxicity of wheat cultivars while minimizing the impact of editing on protein quality. [ABSTRACT FROM AUTHOR]

BackgroundBread wheat is an allopolyploid species with a large, highly repetitive genome. To investigate the impact of selection on variants distributed among homoeologous wheat genomes and to build a foundation for understanding genotype-phenotype relationships, we performed population-scale re-sequencing of a diverse panel of wheat lines.ResultsA sample of 62 diverse lines was re-sequenced using the whole exome capture and genotyping-by-sequencing approaches. We describe the allele frequency, functional significance, and chromosomal distribution of 1.57 million single nucleotide polymorphisms and 161,719 small indels. Our results suggest that duplicated homoeologous genes are under purifying selection. We find contrasting patterns of variation and inter-variant associations among wheat genomes; this, in addition to demographic factors, could be explained by differences in the effect of directional selection on duplicated homoeologs. Only a small fraction of the homoeologous regions harboring selected variants overlapped among the wheat genomes in any given wheat line. These selected regions are enriched for loci associated with agronomic traits detected in genome-wide association studies.ConclusionsEvidence suggests that directional selection in allopolyploids rarely acted on multiple parallel advantageous mutations across homoeologous regions, likely indicating that a fitness benefit could be obtained by a mutation at any one of the homoeologs. Additional advantageous variants in other homoelogs probably either contributed little benefit, or were unavailable in populations subjected to directional selection. We hypothesize that allopolyploidy may have increased the likelihood of beneficial allele recovery by broadening the set of possible selection targets.

Wheat varieties with a winter growth habit require long exposures to low temperatures (vernalization) to accelerate flowering. Natural variation in four vernalization genes regulating this requirement has favored wheat adaptation to different environments. The first three genes (VRN1-VRN3) have been cloned and characterized before. Here we show that the fourth gene, VRN-D4, originated by the insertion of a ∼290-kb region from chromosome arm 5AL into the proximal region of chromosome arm 5DS. The inserted 5AL region includes a copy of VRN-A1 that carries distinctive mutations in its coding and regulatory regions. Three lines of evidence confirmed that this gene is VRN-D4: it cosegregated with VRN-D4 in a high-density mapping population; it was expressed earlier than other VRN1 genes in the absence of vernalization; and induced mutations in this gene resulted in delayed flowering. VRN-D4 was found in most accessions of the ancient subspecies Triticum aestivum ssp. sphaerococcum from South Asia. This subspecies showed a significant reduction of genetic diversity and increased genetic differentiation in the centromeric region of chromosome 5D, suggesting that VRN-D4 likely contributed to local adaptation and was favored by positive selection. Three adjacent SNPs in a regulatory region of the VRN-D4 first intron disrupt the binding of GLYCINE-RICH RNA-BINDING PROTEIN 2 (TaGRP2), a known repressor of VRN1 expression. The same SNPs were identified in VRN-A1 alleles previously associated with reduced vernalization requirement. These alleles can be used to modulate vernalization requirements and to develop wheat varieties better adapted to different or changing environments.

Consensus linkage maps are important tools in crop genomics. We have assembled a high-density tetraploid wheat consensus map by integrating 13 data sets from independent biparental populations involving durum wheat cultivars (Triticum turgidum ssp. durum), cultivated emmer (T. turgidum ssp. dicoccum) and their ancestor (wild emmer, T. turgidum ssp. dicoccoides). The consensus map harboured 30 144 markers (including 26 626 SNPs and 791 SSRs) half of which were present in at least two component maps. The final map spanned 2631 cM of all 14 durum wheat chromosomes and, differently from the individual component maps, all markers fell within the 14 linkage groups. Marker density per genetic distance unit peaked at centromeric regions, likely due to a combination of low recombination rate in the centromeric regions and even gene distribution along the chromosomes. Comparisons with bread wheat indicated fewer regions with recombination suppression, making this consensus map valuable for mapping in the A and B genomes of both durum and bread wheat. Sequence similarity analysis allowed us to relate mapped gene-derived SNPs to chromosome-specific transcripts. Dense patterns of homeologous relationships have been established between the A- and B-genome maps and between nonsyntenic homeologous chromosome regions as well, the latter tracing to ancient translocation events. The gene-based homeologous relationships are valuable to infer the map location of homeologs of target loci/QTLs. Because most SNP and SSR markers were previously mapped in bread wheat, this consensus map will facilitate a more effective integration and exploitation of genes and QTL for wheat breeding purposes.

Key messageThe diploid wheat stem rust resistance gene Sr21 confers temperature-sensitive resistance to isolates of the Ug99 group and maps to the middle of the long arm of chromosome 2A (m). A race of Puccinia graminis f. sp. tritici, the causal pathogen of stem rust of wheat, known as Ug99, and its variants, are virulent to plants carrying stem rust resistance genes currently deployed in most wheat cultivars worldwide. Therefore, identification, mapping and deployment of effective resistance genes are critical to reduce this threat. Resistance gene Sr21 identified in diploid wheat T. monococcum can be effective against races from the Ug99 race group, but both susceptible and partial resistant reactions have been reported in previous studies. To clarify this conflicting information we screened four monogenic lines with Sr21 and four susceptible controls with 16 Pgt isolates including five isolates of the Ug99 race group under three different temperatures and three different photoperiods. We observed that, temperature influences the interaction between monogenic lines with Sr21 and Ug99 race group isolates, and may be one source of previous inconsistencies. This result indicates that, although Sr21 confers partial resistance against Ug99, its effectiveness can be modulated by environmental conditions and should not be deployed alone. Using two large diploid wheat-mapping populations (total 3,788 F2 plants) we mapped Sr21 approximately 50 cM from the centromere on the long arm of chromosome 2A(m) within a 0.20 cM interval flanked by sequence-based markers FD527726 and EX594406. The closely linked markers identified in this study will be useful to reduce the T. monococcum segments introgressed into common wheat, accelerate Sr21 deployment in wheat breeding programs, and facilitate the map-based cloning of this gene.

High-density single nucleotide polymorphism (SNP) genotyping arrays are a powerful tool for studying genomic patterns of diversity, inferring ancestral relationships between individuals in populations and studying marker-trait associations in mapping experiments. We developed a genotyping array including about 90,000 gene-associated SNPs and used it to characterize genetic variation in allohexaploid and allotetraploid wheat populations. The array includes a significant fraction of common genome-wide distributed SNPs that are represented in populations of diverse geographical origin. We used density-based spatial clustering algorithms to enable high-throughput genotype calling in complex data sets obtained for polyploid wheat. We show that these model-free clustering algorithms provide accurate genotype calling in the presence of multiple clusters including clusters with low signal intensity resulting from significant sequence divergence at the target SNP site or gene deletions. Assays that detect low-intensity clusters can provide insight into the distribution of presence-absence variation (PAV) in wheat populations. A total of 46 977 SNPs from the wheat 90K array were genetically mapped using a combination of eight mapping populations. The developed array and cluster identification algorithms provide an opportunity to infer detailed haplotype structure in polyploid wheat and will serve as an invaluable resource for diversity studies and investigating the genetic basis of trait variation in wheat.

High-density single nucleotide polymorphism (SNP) genotyping arrays are a powerful tool for studying genomic patterns of diversity, inferring ancestral relationships between individuals in populations and studying marker-trait associations in mapping experiments. We developed a genotyping array including about 90,000 gene-associated SNPs and used it to characterize genetic variation in allohexaploid and allotetraploid wheat populations. The array includes a significant fraction of common genome-wide distributed SNPs that are represented in populations of diverse geographical origin. We used density-based spatial clustering algorithms to enable high-throughput genotype calling in complex data sets obtained for polyploid wheat. We show that these model-free clustering algorithms provide accurate genotype calling in the presence of multiple clusters including clusters with low signal intensity resulting from significant sequence divergence at the target SNP site or gene deletions. Assays that detect low-intensity clusters can provide insight into the distribution of presence-absence variation (PAV) in wheat populations. A total of 46 977 SNPs from the wheat 90K array were genetically mapped using a combination of eight mapping populations. The developed array and cluster identification algorithms provide an opportunity to infer detailed haplotype structure in polyploid wheat and will serve as an invaluable resource for diversity studies and investigating the genetic basis of trait variation in wheat.

An ordered draft sequence of the 17-gigabase hexaploid bread wheat (Triticum aestivum) genome has been produced by sequencing isolated chromosome arms. We have annotated 124,201 gene loci distributed nearly evenly across the homeologous chromosomes and subgenomes. Comparative gene analysis of wheat subgenomes and extant diploid and tetraploid wheat relatives showed that high sequence similarity and structural conservation are retained, with limited gene loss, after polyploidization. However, across the genomes there was evidence of dynamic gene gain, loss, and duplication since the divergence of the wheat lineages. A high degree of transcriptional autonomy and no global dominance was found for the subgenomes. These insights into the genome biology of a polyploid crop provide a springboard for faster gene isolation, rapid genetic marker development, and precise breeding to meet the needs of increasing food demand worldwide.

Chemical mutagenesis efficiently generates phenotypic variation in otherwise homogeneous genetic backgrounds, enabling functional analysis of genes. Advances in mutation detection have brought the utility of induced mutant populations on par with those produced by insertional mutagenesis, but systematic cataloguing of mutations would further increase their utility. We examined the suitability of multiplexed global exome capture and sequencing coupled with custom-developed bioinformatics tools to identify mutations in well-characterized mutant populations of rice (Oryza sativa) and wheat (Triticum aestivum). In rice, we identified ∼18,000 induced mutations from 72 independent M2 individuals. Functional evaluation indicated the recovery of potentially deleterious mutations for >2600 genes. We further observed that specific sequence and cytosine methylation patterns surrounding the targeted guanine residues strongly affect their probability to be alkylated by ethyl methanesulfonate. Application of these methods to six independent M2 lines of tetraploid wheat demonstrated that our bioinformatics pipeline is applicable to polyploids. In conclusion, we provide a method for developing large-scale induced mutation resources with relatively small investments that is applicable to resource-poor organisms. Furthermore, our results demonstrate that large libraries of sequenced mutations can be readily generated, providing enhanced opportunities to study gene function and assess the effect of sequence and chromatin context on mutations.

Wheat stem rust, caused by Puccinia graminis f. sp. tritici (Pgt), is a devastating disease that can cause severe yield losses. A previously uncharacterized Pgt race, designated Ug99, has overcome most of the widely used resistance genes and is threatening major wheat production areas. Here, we demonstrate that the Sr35 gene from Triticum monococcum is a coiled-coil, nucleotide-binding, leucine-rich repeat gene that confers near immunity to Ug99 and related races. This gene is absent in the A-genome diploid donor and in polyploid wheat but is effective when transferred from T. monococcum to polyploid wheat. The cloning of Sr35 opens the door to the use of biotechnological approaches to control this devastating disease and to analyses of the molecular interactions that define the wheat-rust pathosystem.

Abstract Background The high level of identity among duplicated homoeologous genomes in tetraploid pasta wheat presents substantial challenges for de novo transcriptome assembly. To solve this problem, we develop a specialized bioinformatics workflow that optimizes transcriptome assembly and separation of merged homoeologs. To evaluate our strategy, we sequence and assemble the transcriptome of one of the diploid ancestors of pasta wheat, and compare both assemblies with a benchmark set of 13,472 full-length, non-redundant bread wheat cDNAs. Results A total of 489 million 100 bp paired-end reads from tetraploid wheat assemble in 140,118 contigs, including 96% of the benchmark cDNAs. We used a comparative genomics approach to annotate 66,633 open reading frames. The multiple k-mer assembly strategy increases the proportion of cDNAs assembled full-length in a single contig by 22% relative to the best single k-mer size. Homoeologs are separated using a post-assembly pipeline that includes polymorphism identification, phasing of SNPs, read sorting, and re-assembly of phased reads. Using a reference set of genes, we determine that 98.7% of SNPs analyzed are correctly separated by phasing. Conclusions Our study shows that de novo transcriptome assembly of tetraploid wheat benefit from multiple k-mer assembly strategies more than diploid wheat. Our results also demonstrate that phasing approaches originally designed for heterozygous diploid organisms can be used to separate the close homoeologous genomes of tetraploid wheat. The predicted tetraploid wheat proteome and gene models provide a valuable tool for the wheat research community and for those interested in comparative genomic studies.

Domesticated crops experience strong human-mediated selection aimed at developing high-yielding varieties adapted to local conditions. To detect regions of the wheat genome subject to selection during improvement, we developed a high-throughput array to interrogate 9,000 gene-associated single-nucleotide polymorphisms (SNP) in a worldwide sample of 2,994 accessions of hexaploid wheat including landraces and modern cultivars. Using a SNP-based diversity map we characterized the impact of crop improvement on genomic and geographic patterns of genetic diversity. We found evidence of a small population bottleneck and extensive use of ancestral variation often traceable to founders of cultivars from diverse geographic regions. Analyzing genetic differentiation among populations and the extent of haplotype sharing, we identified allelic variants subjected to selection during improvement. Selective sweeps were found around genes involved in the regulation of flowering time and phenology. An introgression of a wild relative-derived gene conferring resistance to a fungal pathogen was detected by haplotype-based analysis. Comparing selective sweeps identified in different populations, we show that selection likely acts on distinct targets or multiple functionally equivalent alleles in different portions of the geographic range of wheat. The majority of the selected alleles were present at low frequency in local populations, suggesting either weak selection pressure or temporal variation in the targets of directional selection during breeding probably associated with changing agricultural practices or environmental conditions. The developed SNP chip and map of genetic variation provide a resource for advancing wheat breeding and supporting future population genomic and genome-wide association studies in wheat.

Abstract Background Increasing the nutrient concentration of wheat grains is important to ameliorate nutritional deficiencies in many parts of the world. Proteins and nutrients in the wheat grain are largely derived from the remobilization of degraded leaf molecules during monocarpic senescence. The down-regulation of the NAC transcription factor Grain Protein Content (GPC) in transgenic wheat plants delays senescence (>3 weeks) and reduces the concentration of protein, Zn and Fe in the grain (>30%), linking senescence and nutrient remobilization. Based on the early and rapid up-regulation of GPC in wheat flag leaves after anthesis, we hypothesized that this transcription factor is an early regulator of monocarpic senescence. To test this hypothesis, we used high-throughput mRNA-seq technologies to characterize the effect of the GPC down-regulation on the wheat flag-leaf transcriptome 12 days after anthesis. At this early stage of senescence GPC transcript levels are significantly lower in transgenic GPC-RNAi plants than in the wild type, but there are still no visible phenotypic differences between genotypes. Results We generated 1.4 million 454 reads from early senescing flag leaves (average ~350 nt) and assembled 1.2 million into 30,497 contigs that were used as a reference to map 145 million Illumina reads from three wild type and four GPC-RNAi plants. Following normalization and statistical testing, we identified a set of 691 genes differentially regulated by GPC (431 ≥ 2-fold change). Transcript level ratios between transgenic and wild type plants showed a high correlation (R = 0.83) between qRT-PCR and Illumina results, providing independent validation of the mRNA-seq approach. A set of differentially expressed genes were analyzed across an early senescence time-course. Conclusions Monocarpic senescence is an active process characterized by large-scale changes in gene expression which begins considerably before the appearance of visual symptoms of senescence. The mRNA-seq approach used here was able to detect small differences in transcript levels during the early stages of senescence. This resulted in an extensive list of GPC-regulated genes, which includes transporters, hormone regulated genes, and transcription factors. These GPC-regulated genes, particularly those up-regulated during senescence, provide valuable entry points to dissect the early stages of monocarpic senescence and nutrient remobilization in wheat.

Abstract Background Single nucleotide polymorphisms (SNPs) are ideally suited for the construction of high-resolution genetic maps, studying population evolutionary history and performing genome-wide association mapping experiments. Here, we used a genome-wide set of 1536 SNPs to study linkage disequilibrium (LD) and population structure in a panel of 478 spring and winter wheat cultivars (Triticum aestivum) from 17 populations across the United States and Mexico. Results Most of the wheat oligo pool assay (OPA) SNPs that were polymorphic within the complete set of 478 cultivars were also polymorphic in all subpopulations. Higher levels of genetic differentiation were observed among wheat lines within populations than among populations. A total of nine genetically distinct clusters were identified, suggesting that some of the pre-defined populations shared significant proportion of genetic ancestry. Estimates of population structure (FST) at individual loci showed a high level of heterogeneity across the genome. In addition, seven genomic regions with elevated FST were detected between the spring and winter wheat populations. Some of these regions overlapped with previously mapped flowering time QTL. Across all populations, the highest extent of significant LD was observed in the wheat D-genome, followed by lower LD in the A- and B-genomes. The differences in the extent of LD among populations and genomes were mostly driven by differences in long-range LD ( > 10 cM). Conclusions Genome- and population-specific patterns of genetic differentiation and LD were discovered in the populations of wheat cultivars from different geographic regions. Our study demonstrated that the estimates of population structure between spring and winter wheat lines can identify genomic regions harboring candidate genes involved in the regulation of growth habit. Variation in LD suggests that breeding and selection had a different impact on each wheat genome both within and among populations. The higher extent of LD in the wheat D-genome versus the A- and B-genomes likely reflects the episodes of recent introgression and population bottleneck accompanying the origin of hexaploid wheat. The assessment of LD and population structure in this assembled panel of diverse lines provides critical information for the development of genetic resources for genome-wide association mapping of agronomically important traits in wheat.

Abstract Background A genome-wide assessment of nucleotide diversity in a polyploid species must minimize the inclusion of homoeologous sequences into diversity estimates and reliably allocate individual haplotypes into their respective genomes. The same requirements complicate the development and deployment of single nucleotide polymorphism (SNP) markers in polyploid species. We report here a strategy that satisfies these requirements and deploy it in the sequencing of genes in cultivated hexaploid wheat (Triticum aestivum, genomes AABBDD) and wild tetraploid wheat (Triticum turgidum ssp. dicoccoides, genomes AABB) from the putative site of wheat domestication in Turkey. Data are used to assess the distribution of diversity among and within wheat genomes and to develop a panel of SNP markers for polyploid wheat. Results Nucleotide diversity was estimated in 2114 wheat genes and was similar between the A and B genomes and reduced in the D genome. Within a genome, diversity was diminished on some chromosomes. Low diversity was always accompanied by an excess of rare alleles. A total of 5,471 SNPs was discovered in 1791 wheat genes. Totals of 1,271, 1,218, and 2,203 SNPs were discovered in 488, 463, and 641 genes of wheat putative diploid ancestors, T. urartu, Aegilops speltoides, and Ae. tauschii, respectively. A public database containing genome-specific primers, SNPs, and other information was constructed. A total of 987 genes with nucleotide diversity estimated in one or more of the wheat genomes was placed on an Ae. tauschii genetic map, and the map was superimposed on wheat deletion-bin maps. The agreement between the maps was assessed. Conclusions In a young polyploid, exemplified by T. aestivum, ancestral species are the primary source of genetic diversity. Low effective recombination due to self-pollination and a genetic mechanism precluding homoeologous chromosome pairing during polyploid meiosis can lead to the loss of diversity from large chromosomal regions. The net effect of these factors in T. aestivum is large variation in diversity among genomes and chromosomes, which impacts the development of SNP markers and their practical utility. Accumulation of new mutations in older polyploid species, such as wild emmer, results in increased diversity and its more uniform distribution across the genome.

Puccinia graminis f. sp. tritici is the causal agent of stem rust of wheat. A new race designated TTKSK (also known as Ug99) and its variants (TTKST and TTTSK) are virulent to most of the stem rust resistance genes currently deployed in wheat cultivars worldwide. Therefore, identification, mapping, and deployment of effective resistance genes are critical components of global efforts to mitigate this threat. Multipathotype seedling tests demonstrated that resistance gene Sr35 is effective against the three TTKS variants and another broadly virulent race from Yemen, TRTTF. Two genetic maps of Sr35 are presented in diploid (Triticum monococcum) and two in hexaploid wheat (T. aestivum). The Sr35 resistance to TRTTF and RKQQC races was mapped in diploid wheat within a 2.2 to 3.1 cM interval on the long arm of chromosome 3Aᵐ between markers XBF483299 and XCJ656351 This interval corresponds to a 174-kb region in Brachypodium that includes 16 annotated genes. The Sr35 map location was confirmed in two backcross-derived hexaploid populations segregating for Sr35 Recombination between diploid and hexaploid chromosomes was 10-fold lower than between homologous chromosomes, but was sufficient to reduce the introgressed diploid segment. These maps provide markers closely linked to Sr35 that will be useful to accelerate its deployment and pyramiding with other stem rust resistance genes.

Single nucleotide polymorphisms (SNPs) are indispensable in such applications as association mapping and construction of high-density genetic maps. These applications usually require genotyping of thousands of SNPs in a large number of individuals. Although a number of SNP genotyping assays are available, most of them are designed for SNP genotyping in diploid individuals. Here, we demonstrate that the Illumina GoldenGate assay could be used for SNP genotyping of homozygous tetraploid and hexaploid wheat lines. Genotyping reactions could be carried out directly on genomic DNA without the necessity of preliminary PCR amplification. A total of 53 tetraploid and 38 hexaploid homozygous wheat lines were genotyped at 96 SNP loci. The genotyping error rate estimated after removal of low-quality data was 0 and 1% for tetraploid and hexaploid wheat, respectively. Developed SNP genotyping assays were shown to be useful for genotyping wheat cultivars. This study demonstrated that the GoldenGate assay is a very efficient tool for high-throughput genotyping of polyploid wheat, opening new possibilities for the analysis of genetic variation in wheat and dissection of genetic basis of complex traits using association mapping approach.

In this study, we developed 359 detection primers for single nucleotide polymorphisms (SNPs) previously discovered within intron sequences of wheat genes and used them to evaluate SNP polymorphism in common wheat (Triticum aestivum L.). These SNPs showed an average polymorphism information content (PIC) of 0.18 among 20 US elite wheat cultivars, representing seven market classes. This value increased to 0.23 when SNPs were pre-selected for polymorphisms among a diverse set of 13 hexaploid wheat accessions (excluding synthetic wheats) used in the wheat SNP discovery project (http://wheat.pw.usda.gov/SNP). PIC values for SNP markers in the D genome were approximately half of those for the A and B genomes. D genome SNPs also showed a larger PIC reduction relative to the other genomes (P < 0.05) when US cultivars were compared with the more diverse set of 13 wheat accessions. Within those accessions, D genome SNPs show a higher proportion of alleles with low minor allele frequencies (