Integrating genomics, phenomics, and deep learning improves the predictive ability for Fusarium head blight-related traits in winter wheat.

Fusarium head blight (FHB) remains one of the most destructive diseases of wheat (Triticum aestivum L.), causing considerable losses in yield and end-use quality. Phenotyping of FHB resistance traits, Fusarium-damaged kernels (FDK), and deoxynivalenol (DON), is either prone to human biases or resource expensive, hindering the progress in breeding for FHB-resistant cultivars. Though genomic selection (GS) can be an effective way to select these traits, inaccurate phenotyping remains a hurdle in exploiting this approach. Here, we used an artificial intelligence (AI)-based precise FDK estimation that exhibits high heritability and correlation with DON. Further, GS using AI-based FDK (FDK_QVIS/FDK_QNIR) showed a two-fold increase in predictive ability (PA) compared to GS for traditionally estimated FDK (FDK_V). Next, the AI-based FDK was evaluated along with other traits in multi-trait (MT) GS models to predict DON. The inclusion of FDK_QNIR and FDK_QVIS with days to heading as covariates improved the PA for DON by 58% over the baseline single-trait GS model. We next used hyperspectral imaging of FHB-infected wheat kernels as a novel avenue to improve the MT GS for DON. The PA for DON using selected wavebands derived from hyperspectral imaging in MT GS models surpassed the single-trait GS model by around 40%. Finally, we evaluated phenomic prediction for DON by integrating hyperspectral imaging with deep learning to directly predict DON in FHB-infected wheat kernels and observed an accuracy (R2 = 0.45) comparable to best-performing MT GS models. This study demonstrates the potential application of AI and vision-based platforms to improve PA for FHB-related traits using genomic and phenomic selection.

Enhancing the potential of phenomic and genomic prediction in winter wheat breeding using high-throughput phenotyping and deep learning.

Integrating high-throughput phenotyping (HTP) based traits into phenomic and genomic selection (GS) can accelerate the breeding of high-yielding and climate-resilient wheat cultivars. In this study, we explored the applicability of Unmanned Aerial Vehicles (UAV)-assisted HTP combined with deep learning (DL) for the phenomic or multi-trait (MT) genomic prediction of grain yield (GY), test weight (TW), and grain protein content (GPC) in winter wheat. Significant correlations were observed between agronomic traits and HTP-based traits across different growth stages of winter wheat. Using a deep neural network (DNN) model, HTP-based phenomic predictions showed robust prediction accuracies for GY, TW, and GPC for a single location with R2 of 0.71, 0.62, and 0.49, respectively. Further prediction accuracies increased (R2 of 0.76, 0.64, and 0.75) for GY, TW, and GPC, respectively when advanced breeding lines from multi-locations were used in the DNN model. Prediction accuracies for GY varied across growth stages, with the highest accuracy at the Feekes 11 (Milky ripe) stage. Furthermore, forward prediction of GY in preliminary breeding lines using DNN trained on multi-location data from advanced breeding lines improved the prediction accuracy by 32% compared to single-location data. Next, we evaluated the potential of incorporating HTP-based traits in multi-trait genomic selection (MT-GS) models in the prediction of GY, TW, and GPC. MT-GS, models including UAV data-based anthocyanin reflectance index (ARI), green chlorophyll index (GCI), and ratio vegetation index 2 (RVI_2) as covariates demonstrated higher predictive ability (0.40, 0.40, and 0.37, respectively) as compared to single-trait model (0.23) for GY. Overall, this study demonstrates the potential of integrating HTP traits into DL-based phenomic or MT-GS models for enhancing breeding efficiency.

Pm57 from Aegilops searsii encodes a tandem kinase protein and confers wheat powdery mildew resistance.

Powdery mildew is a devastating disease that affects wheat yield and quality. Wheat wild relatives represent valuable sources of disease resistance genes. Cloning and characterization of these genes will facilitate their incorporation into wheat breeding programs. Here, we report the cloning of Pm57, a wheat powdery mildew resistance gene from Aegilops searsii. It encodes a tandem kinase protein with putative kinase-pseudokinase domains followed by a von Willebrand factor A domain (WTK-vWA), being ortholog of Lr9 that mediates wheat leaf rust resistance. The resistance function of Pm57 is validated via independent mutants, gene silencing, and transgenic assays. Stable Pm57 transgenic wheat lines and introgression lines exhibit high levels of all-stage resistance to diverse isolates of the Bgt fungus, and no negative impacts on agronomic parameters are observed in our experimental set-up. Our findings highlight the emerging role of kinase fusion proteins in plant disease resistance and provide a valuable gene for wheat breeding.

Wheat powdery mildew resistance gene Pm13 encodes a mixed lineage kinase domain-like protein.

Wheat powdery mildew is one of the most destructive diseases threatening global wheat production. The wild relatives of wheat constitute rich sources of diversity for powdery mildew resistance. Here, we report the map-based cloning of the powdery mildew resistance gene Pm13 from the wild wheat species Aegilops longissima. Pm13 encodes a mixed lineage kinase domain-like (MLKL) protein that contains an N-terminal-domain of MLKL (MLKL_NTD) domain in its N-terminus and a C-terminal serine/threonine kinase (STK) domain. The resistance function of Pm13 is validated by mutagenesis, gene silencing, transgenic assay, and allelic association analyses. The development of introgression lines with significantly reduced chromosome segments of Ae. longissima encompassing Pm13 enables widespread deployment of this gene into wheat cultivars. The cloning of Pm13 may provide valuable insights into the molecular mechanisms underlying Pm13-mediated powdery mildew resistance and highlight the important roles of kinase fusion proteins (KFPs) in wheat immunity.

Genetic Mapping of a Novel Gene PmAege7M from Aegilops geniculata Conferring Resistance to Wheat Powdery Mildew.

Powdery mildew, caused by Blumeria graminis f. sp. tritici (Bgt), is one of the most damaging foliage diseases of wheat across the world. Aegilops geniculata Roth is a valuable gene resource for enhancing wheat resistance to powdery mildew. This study identified Ae. geniculata accession PI 487224 as immune and PI 487228 as susceptible to powdery mildew. Genetic analysis of the F1, F2, and F2:3 progeny derived from PI 487224 × PI 487228 showed that powdery mildew resistance in PI 487224 was controlled by two independent dominant genes located on two different nonhomologous chromosomes. By combing bulked segregant RNA-Seq, genetic linkage analysis of a single resistance gene segregation population, and marker analysis of a set of 14 wheat-Ae. geniculata chromosome addition lines, one of the resistance genes, temperately designated PmAege7M, was mapped to a 4.9-cM interval flanked by markers STS7-55926 and SNP7-45792/STS7-65911 on the long arm of chromosome 7 Mg of PI 487224, spanning 604.73 to 622.82 Mb on the 7D long arm based on the Ae. tauschii reference genome (Aet_v4.0). The map and closely linked markers of PmAege7M from Ae. geniculata in this study will facilitate the transfer of PmAege7M into common wheat and fine mapping of the gene.

Multi-trait genomic selection improves the prediction accuracy of end-use quality traits in hard winter wheat.

Improvement of end-use quality remains one of the most important goals in hard winter wheat (HWW) breeding. Nevertheless, the evaluation of end-use quality traits is confined to later development generations owing to resource-intensive phenotyping. Genomic selection (GS) has shown promise in facilitating selection for end-use quality; however, lower prediction accuracy (PA) for complex traits remains a challenge in GS implementation. Multi-trait genomic prediction (MTGP) models can improve PA for complex traits by incorporating information on correlated secondary traits, but these models remain to be optimized in HWW. A set of advanced breeding lines from 2015 to 2021 were genotyped with 8725 single-nucleotide polymorphisms and was used to evaluate MTGP to predict various end-use quality traits that are otherwise difficult to phenotype in earlier generations. The MTGP model outperformed the ST model with up to a twofold increase in PA. For instance, PA was improved from 0.38 to 0.75 for bake absorption and from 0.32 to 0.52 for loaf volume. Further, we compared MTGP models by including different combinations of easy-to-score traits as covariates to predict end-use quality traits. Incorporation of simple traits, such as flour protein (FLRPRO) and sedimentation weight value (FLRSDS), substantially improved the PA of MT models. Thus, the rapid low-cost measurement of traits like FLRPRO and FLRSDS can facilitate the use of GP to predict mixograph and baking traits in earlier generations and provide breeders an opportunity for selection on end-use quality traits by culling inferior lines to increase selection accuracy and genetic gains.

Identification of leaf rust resistance loci in a geographically diverse panel of wheat using genome-wide association analysis.

Leaf rust, caused by Puccinia triticina (Pt) is among the most devastating diseases posing a significant threat to global wheat production. The continuously evolving virulent Pt races in North America calls for exploring new sources of leaf rust resistance. A diversity panel of 365 bread wheat accessions selected from a worldwide population of landraces and cultivars was evaluated at the seedling stage against four Pt races (TDBJQ, TBBGS, MNPSD and, TNBJS). A wide distribution of seedling responses against the four Pt races was observed. Majority of the genotypes displayed a susceptible response with only 28 (9.8%), 59 (13.5%), 45 (12.5%), and 29 (8.1%) wheat accessions exhibiting a highly resistant response to TDBJQ, TBBGS, MNPSD and, TNBJS, respectively. Further, we conducted a high-resolution multi-locus genome-wide association study (GWAS) using a set of 302,524 high-quality single nucleotide polymorphisms (SNPs). The GWAS analysis identified 27 marker-trait associations (MTAs) for leaf rust resistance on different wheat chromosomes of which 20 MTAs were found in the vicinity of known Lr genes, MTAs, or quantitative traits loci (QTLs) identified in previous studies. The remaining seven significant MTAs identified represent genomic regions that harbor potentially novel genes for leaf rust resistance. Furthermore, the candidate gene analysis for the significant MTAs identified various genes of interest that may be involved in disease resistance. The identified resistant lines and SNPs linked to the QTLs in this study will serve as valuable resources in wheat rust resistance breeding programs.

Genome-wide association analysis of spike and kernel traits in the U.S. hard winter wheat.

A better understanding of the genetic control of spike and kernel traits that have higher heritability can help in the development of high-yielding wheat varieties. Here, we identified the marker-trait associations (MTAs) for various spike- and kernel-related traits in winter wheat (Triticum aestivum L.) through genome-wide association studies (GWAS). An association mapping panel comprising 297 hard winter wheat accessions from the U.S. Great Plains was evaluated for eight spike- and kernel-related traits in three different environments. A GWAS using 15,590 single-nucleotide polymorphisms (SNPs) identified a total of 53 MTAs for seven spike- and kernel-related traits, where the highest number of MTAs were identified for spike length (16) followed by the number of spikelets per spike (15) and spikelet density (11). Out of 53 MTAs, 14 were considered to represent stable quantitative trait loci (QTL) as they were identified in multiple environments. Five multi-trait MTAs were identified for various traits including the number of spikelets per spike (NSPS), spikelet density (SD), kernel width (KW), and kernel area (KA) that could facilitate the pyramiding of yield-contributing traits. Further, a significant additive effect of accumulated favorable alleles on the phenotype of four spike-related traits suggested that breeding lines and cultivars with a higher number of favorable alleles could be a valuable resource for breeders to improve yield-related traits. This study improves the understanding of the genetic basis of yield-related traits in hard winter wheat and provides reliable molecular markers that will facilitate marker-assisted selection (MAS) in wheat breeding programs.

Multi-Locus Genome-Wide Association Studies to Characterize Fusarium Head Blight (FHB) Resistance in Hard Winter Wheat.

Fusarium head blight (FHB), caused by the fungus Fusarium graminearum Schwabe is an important disease of wheat that causes severe yield losses along with serious quality concerns. Incorporating the host resistance from either wild relatives, landraces, or exotic materials remains challenging and has shown limited success. Therefore, a better understanding of the genetic basis of native FHB resistance in hard winter wheat (HWW) and combining it with major quantitative trait loci (QTLs) can facilitate the development of FHB-resistant cultivars. In this study, we evaluated a set of 257 breeding lines from the South Dakota State University (SDSU) breeding program to uncover the genetic basis of native FHB resistance in the US hard winter wheat. We conducted a multi-locus genome-wide association study (ML-GWAS) with 9,321 high-quality single-nucleotide polymorphisms (SNPs). A total of six distinct marker-trait associations (MTAs) were identified for the FHB disease index (DIS) on five different chromosomes including 2A, 2B, 3B, 4B, and 7A. Further, eight MTAs were identified for Fusarium-damaged kernels (FDK) on six chromosomes including 3B, 5A, 6B, 6D, 7A, and 7B. Out of the 14 significant MTAs, 10 were found in the proximity of previously reported regions for FHB resistance in different wheat classes and were validated in HWW, while four MTAs represent likely novel loci for FHB resistance. Accumulation of favorable alleles of reported MTAs resulted in significantly lower mean DIS and FDK score, demonstrating the additive effect of FHB resistance alleles. Candidate gene analysis for two important MTAs identified several genes with putative proteins of interest; however, further investigation of these regions is needed to identify genes conferring FHB resistance. The current study sheds light on the genetic basis of native FHB resistance in the US HWW germplasm and the resistant lines and MTAs identified in this study will be useful resources for FHB resistance breeding via marker-assisted selection.

Whole-genome analysis of hard winter wheat germplasm identifies genomic regions associated with spike and kernel traits.

Genetic dissection of yield component traits including spike and kernel characteristics is essential for the continuous improvement in wheat yield. Genome-wide association studies (GWAS) have been frequently used to identify genetic determinants for spike and kernel-related traits in wheat, though none have been employed in hard winter wheat (HWW) which represents a major class in US wheat acreage. Further, most of these studies relied on assembled diversity panels instead of adapted breeding lines, limiting the transferability of results to practical wheat breeding. Here we assembled a population of advanced/elite breeding lines and well-adapted cultivars and evaluated over four environments for phenotypic analysis of spike and kernel traits. GWAS identified 17 significant multi-environment marker-trait associations (MTAs) for various traits, representing 12 putative quantitative trait loci (QTLs), with five QTLs affecting multiple traits. Four of these QTLs mapped on three chromosomes 1A, 5B, and 7A for spike length, number of spikelets per spike (NSPS), and kernel length are likely novel. Further, a highly significant QTL was detected on chromosome 7AS that has not been previously associated with NSPS and putative candidate genes were identified in this region. The allelic frequencies of important quantitative trait nucleotides (QTNs) were deduced in a larger set of 1,124 accessions which revealed the importance of identified MTAs in the US HWW breeding programs. The results from this study could be directly used by the breeders to select the lines with favorable alleles for making crosses, and reported markers will facilitate marker-assisted selection of stable QTLs for yield components in wheat breeding.

Mapping of the novel powdery mildew resistance gene Pm2Mb from Aegilops biuncialis based on ph1b-induced homoeologous recombination.

KEY MESSAGE: A novel powdery mildew resistance gene Pm2Mb from Aegilops biuncialis was transferred into common wheat and mapped to chromosome 2MbL bin FL 0.49-0.66 by molecular cytogenetic analysis of 2Mb recombinants. Aegilops biuncialis, a wild relative of common wheat, is highly resistant to powdery mildew. Previous studies identified that chromosome 2Mb in Chinese Spring (CS)-Ae. biuncialis 2Mb disomic addition line TA7733 conferred high resistance to powdery mildew, and the resistance gene was temporarily designated as Pm2Mb. In this study, a total of 65 CS-Ae. biuncialis 2Mb recombinants were developed by ph1b-induced homoeologous recombination and they were grouped into 12 different types based on the presence of different markers of 2Mb-specificity. Segment sizes and breakpoints of each 2Mb recombinant type were further characterized using in situ hybridization and molecular marker analyses. Powdery mildew responses of each type were assessed by inoculation of each 2Mb recombinant-derived F2 progenies using the isolate E05. Combined analyses of in situ hybridization, molecular markers and powdery mildew resistance data of the 2Mb recombinants, the gene Pm2Mb was cytologically located to an interval of FL 0.49-0.66 in the long arm of 2Mb, where 19 2Mb-specific markers were located. Among the 65 2Mb recombinants, T-11 (T2DS.2DL-2MbL) and T-12 (Ti2DS.2DL-2MbL-2DL) contained a small 2MbL segment harboring Pm2Mb. Besides, a physical map of chromosome 2Mb was constructed with 70 2Mb-specific markers in 10 chromosomal bins and the map showed that submetacentric chromosome 2Mb of Ae. biuncialis was rearranged by a terminal intrachromosomal translocation. The newly developed 2Mb recombinants with powdery mildew resistance, the 2Mb-specific molecular markers and the physical map of chromosome 2Mb will benefit wheat disease breeding as well as fine mapping and cloning of Pm2Mb.

Cloning of the broadly effective wheat leaf rust resistance gene Lr42 transferred from Aegilops tauschii.

The wheat wild relative Aegilops tauschii was previously used to transfer the Lr42 leaf rust resistance gene into bread wheat. Lr42 confers resistance at both seedling and adult stages, and it is broadly effective against all leaf rust races tested to date. Lr42 has been used extensively in the CIMMYT international wheat breeding program with resulting cultivars deployed in several countries. Here, using a bulked segregant RNA-Seq (BSR-Seq) mapping strategy, we identify three candidate genes for Lr42. Overexpression of a nucleotide-binding site leucine-rich repeat (NLR) gene AET1Gv20040300 induces strong resistance to leaf rust in wheat and a mutation of the gene disrupted the resistance. The Lr42 resistance allele is rare in Ae. tauschii and likely arose from ectopic recombination. Cloning of Lr42 provides diagnostic markers and over 1000 CIMMYT wheat lines carrying Lr42 have been developed documenting its widespread use and impact in crop improvement.

Development and Characterization of Triticum aestivum-Aegilops longissima 6Sl Recombinants Harboring a Novel Powdery Mildew Resistance Gene Pm6Sl.

Powdery mildew of wheat is a foliar disease that is spread worldwide. Cultivation of resistant varieties is the most effective, economical, and environmentally friendly strategy to curb this disease. Powdery mildew resistance genes (Pm) are the primary resources for resistance breeding, and new Pm genes are in constant demand. Previously, we identified Aegilops longissima chromosome 6Sl#3 as a carrier of powdery mildew resistance and designated the resistance gene as Pm6Sl. Here, we reported the design of 24 markers specific to 6Sl#3 on the basis of the full-length cDNA sequences of 6Sl#3 donor Ae. longissma accession TA1910, and the development of wheat-Ae. longissima 6Sl#3 introgression stocks by ph1b-induced homoeologous recombination. Further, 6Sl#3 introgression lines were identified and characterized by integration analysis of powdery mildew responses, in situ hybridization, and molecular markers and Pm6Sl was mapped to a distal interval of 42.80 Mb between markers Ael58410 and Ael57699 in the long arm of 6Sl#3. Two resistant recombinants, R43 (T6BS.6BL-6Sl#3L) and T27 (Ti6AS.6AL-6Sl#3L-6AL), contained segments harboring Pm6Sl with less than 8% of 6Sl#3 genomic length, and two markers were diagnostic for Pm6Sl. This study broadened powdery mildew resistance gene resources for wheat improvement and provided a fundamental basis for fine mapping and cloning of Pm6Sl to further understand its molecular mechanism of disease resistance.

Multi-Trait Multi-Environment Genomic Prediction of Agronomic Traits in Advanced Breeding Lines of Winter Wheat.

Genomic prediction is a promising approach for accelerating the genetic gain of complex traits in wheat breeding. However, increasing the prediction accuracy (PA) of genomic prediction (GP) models remains a challenge in the successful implementation of this approach. Multivariate models have shown promise when evaluated using diverse panels of unrelated accessions; however, limited information is available on their performance in advanced breeding trials. Here, we used multivariate GP models to predict multiple agronomic traits using 314 advanced and elite breeding lines of winter wheat evaluated in 10 site-year environments. We evaluated a multi-trait (MT) model with two cross-validation schemes representing different breeding scenarios (CV1, prediction of completely unphenotyped lines; and CV2, prediction of partially phenotyped lines for correlated traits). Moreover, extensive data from multi-environment trials (METs) were used to cross-validate a Bayesian multi-trait multi-environment (MTME) model that integrates the analysis of multiple-traits, such as G × E interaction. The MT-CV2 model outperformed all the other models for predicting grain yield with significant improvement in PA over the single-trait (ST-CV1) model. The MTME model performed better for all traits, with average improvement over the ST-CV1 reaching up to 19, 71, 17, 48, and 51% for grain yield, grain protein content, test weight, plant height, and days to heading, respectively. Overall, the empirical analyses elucidate the potential of both the MT-CV2 and MTME models when advanced breeding lines are used as a training population to predict related preliminary breeding lines. Further, we evaluated the practical application of the MTME model in the breeding program to reduce phenotyping cost using a sparse testing design. This showed that complementing METs with GP can substantially enhance resource efficiency. Our results demonstrate that multivariate GS models have a great potential in implementing GS in breeding programs.

Genome-wide association analysis permits characterization of Stagonospora nodorum blotch (SNB) resistance in hard winter wheat.

Stagonospora nodorum blotch (SNB) is an economically important wheat disease caused by the necrotrophic fungus Parastagonospora nodorum. SNB resistance in wheat is controlled by several quantitative trait loci (QTLs). Thus, identifying novel resistance/susceptibility QTLs is crucial for continuous improvement of the SNB resistance. Here, the hard winter wheat association mapping panel (HWWAMP) comprising accessions from breeding programs in the Great Plains region of the US, was evaluated for SNB resistance and necrotrophic effectors (NEs) sensitivity at the seedling stage. A genome-wide association study (GWAS) was performed to identify single-nucleotide polymorphism (SNP) markers associated with SNB resistance and effectors sensitivity. We found seven significant associations for SNB resistance/susceptibility distributed over chromosomes 1B, 2AL, 2DS, 4AL, 5BL, 6BS, and 7AL. Two new QTLs for SNB resistance/susceptibility at the seedling stage were identified on chromosomes 6BS and 7AL, whereas five QTLs previously reported in diverse germplasms were validated. Allele stacking analysis at seven QTLs explained the additive and complex nature of SNB resistance. We identified accessions ('Pioneer-2180' and 'Shocker') with favorable alleles at five of the seven identified loci, exhibiting a high level of resistance against SNB. Further, GWAS for sensitivity to NEs uncovered significant associations for SnToxA and SnTox3, co-locating with previously identified host sensitivity genes (Tsn1 and Snn3). Candidate region analysis for SNB resistance revealed 35 genes of putative interest with plant defense response-related functions. The QTLs identified and validated in this study could be easily employed in breeding programs using the associated markers to enhance the SNB resistance in hard winter wheat.

Development of Novel Wheat-Aegilops longissima 3S1 Translocations Conferring Powdery Mildew Resistance and Specific Molecular Markers for Chromosome 3S1.

Powdery mildew of wheat, caused by Blumeria graminis f. sp. tritici, is a destructive disease of common wheat. Cultivation of resistant varieties is the most cost-effective disease management strategy. Previous studies reported that chromosome 3Sl#2 present in Chinese Spring (CS)-Aegilops longissima 3Sl#2(3B) disomic substitution line TA3575 conferred resistance to powdery mildew. In this study, we further located the powdery mildew resistance gene(s) to the short arm of chromosome 3Sl#2 (3Sl#2S) by evaluating for B. graminis f. sp. tritici resistance of newly developed CS-Ae. longissima 3Sl#2 translocation lines. Meanwhile, TA7545, a previously designated CS-Ae. longissima 3Sl#3 disomic addition line, was reidentified as an isochromosome 3Sl#3S addition line and evaluated to confer resistance to powdery mildew, thus locating the resistance gene(s) to the short arm of chromosome 3Sl#3 (3Sl#3S). Based on transcriptome sequences of TA3575, 10 novel chromosome 3SlS-specific markers were developed, of which 5 could be used to distinguish between 3Sl#2S and 3Sl#3S derived from Ae. longissima accessions TL20 and TA1910 (TAM4) and the remaining 5 could identify both 3Sl#2S and 3Sl#3S. Also, CL897, one of five markers specific to both 3Sl#2S and 3Sl#3S, could be used to detect Pm13 located at chromosome 3Sl#1S from Ae. longissima accession TL01 in diverse wheat genetic backgrounds. The powdery mildew resistance genes on chromosomes 3Sl#2S and 3Sl#3S, the CS-Ae. longissima 3Sl#2 translocation lines, and the 3SlS-specific markers developed in this study will facilitate the transfer of B. graminis f. sp. tritici resistance genes into common wheat and provide new germplasm resources for powdery mildew resistance breeding.

Artificial selection in breeding extensively enriched a functional allelic variation in TaPHS1 for pre-harvest sprouting resistance in wheat.

Pre-harvest sprouting (PHS) causes significant losses in wheat yield and quality worldwide. Previously, we cloned a PHS resistance gene, TaPHS1, and identified two causal mutations for reduced seed dormancy (SD) and increased PHS susceptibility. Here we identified a novel allelic variation of C to T transition in 3'-UTR of TaPHS1, which associated with reduced SD and PHS resistance. The T allele occurred in wild wheat progenitors and was likely the earliest functional mutation in TaPHS1 for PHS susceptibility. Allele frequency analysis revealed low frequency of the T allele in wild diploid and tetraploid wheat progenitors, but very high frequency in modern wheat cultivars and breeding lines, indicating that artificial selection quickly enriched the T allele during modern breeding. The T allele was significantly associated with short SD in both T. aestivum and T. durum, the two most cultivated species of wheat. This variation together with previously reported functional sequence variations co-regulated TaPHS1 expression levels and PHS resistance in different germplasms. Haplotype analysis of the four functional variations identified the best PHS resistance haplotype of TaPHS1. The resistance haplotype can be used in marker-assisted selection to transfer TaPHS1 to new wheat cultivars.

Physical Mapping of Pm57, a Powdery Mildew Resistance Gene Derived from Aegilops searsii.

Powdery mildew caused by Blumeria graminis f. sp. tritici (Bgt) is one of many severe diseases that threaten bread wheat (Triticum aestivum L.) yield and quality worldwide. The discovery and deployment of powdery mildew resistance genes (Pm) can prevent this disease epidemic in wheat. In a previous study, we transferred the powdery mildew resistance gene Pm57 from Aegilops searsii into common wheat and cytogenetically mapped the gene in a chromosome region with the fraction length (FL) 0.75-0.87, which represents 12% segment of the long arm of chromosome 2Ss#1. In this study, we performed RNA-seq using RNA extracted from leaf samples of three infected and mock-infected wheat-Ae. searsii 2Ss#1 introgression lines at 0, 12, 24, and 48 h after inoculation with Bgt isolates. Then we designed 79 molecular markers based on transcriptome sequences and physically mapped them to Ae. searsii chromosome 2Ss#1- in seven intervals. We used these markers to identify 46 wheat-Ae. searsii 2Ss#1 recombinants induced by ph1b, a deletion mutant of pairing homologous (Ph) genes. After analyzing the 46 ph1b-induced 2Ss#1L recombinants in the region where Pm57 is located with different Bgt-responses, we physically mapped Pm57 gene on the long arm of 2Ss#1 in a 5.13 Mb genomic region, which was flanked by markers X67593 (773.72 Mb) and X62492 (778.85 Mb). By comparative synteny analysis of the corresponding region on chromosome 2B in Chinese Spring (T. aestivum L.) with other model species, we identified ten genes that are putative plant defense-related (R) genes which includes six coiled-coil nucleotide-binding site-leucine-rich repeat (CNL), three nucleotide-binding site-leucine-rich repeat (NL) and a leucine-rich receptor-like repeat (RLP) encoding proteins. This study will lay a foundation for cloning of Pm57, and benefit the understanding of interactions between resistance genes of wheat and powdery mildew pathogens.

Mining and genomic characterization of resistance to tan spot, Stagonospora nodorum blotch (SNB), and Fusarium head blight in Watkins core collection of wheat landraces.

BACKGROUND: In the late 1920s, A. E. Watkins collected about 7000 landrace cultivars (LCs) of bread wheat (Triticum aestivum L.) from 32 different countries around the world. Among which 826 LCs remain viable and could be a valuable source of superior/favorable alleles to enhance disease resistance in wheat. In the present study, a core set of 121 LCs, which captures the majority of the genetic diversity of Watkins collection, was evaluated for identifying novel sources of resistance against tan spot, Stagonospora nodorum blotch (SNB), and Fusarium Head Blight (FHB). RESULTS: A diverse response was observed in 121 LCs for all three diseases. The majority of LCs were moderately susceptible to susceptible to tan spot Ptr race 1 (84%) and FHB (96%) whereas a large number of LCs were resistant or moderately resistant against tan spot Ptr race 5 (95%) and SNB (54%). Thirteen LCs were identified in this study could be a valuable source for multiple resistance to tan spot Ptr races 1 and 5, and SNB, and another five LCs could be a potential source for FHB resistance. GWAS analysis was carried out using disease phenotyping score and 8807 SNPs data of 118 LCs, which identified 30 significant marker-trait associations (MTAs) with -log10 (p-value) > 3.0. Ten, five, and five genomic regions were found to be associated with resistance to tan spot Ptr race 1, race 5, and SNB, respectively in this study. In addition to Tsn1, several novel genomic regions Q.Ts1.sdsu-4BS and Q.Ts1.sdsu-5BS (tan spot Ptr race 1) and Q.Ts5.sdsu-1BL, Q.Ts5.sdsu-2DL, Q.Ts5.sdsu-3AL, and Q.Ts5.sdsu-6BL (tan spot Ptr race 5) were also identified. Our results indicate that these putative genomic regions contain several genes that play an important role in plant defense mechanisms. CONCLUSION: Our results suggest the existence of valuable resistant alleles against leaf spot diseases in Watkins LCs. The single-nucleotide polymorphism (SNP) markers linked to the quantitative trait loci (QTLs) for tan spot and SNB resistance along with LCs harboring multiple disease resistance could be useful for future wheat breeding.

Molecular characterization of bacterial leaf streak resistance in hard winter wheat.

Bacterial leaf streak (BLS) caused by Xanthomonas campestris pv. translucens is one of the major bacterial diseases threatening wheat production in the United States Northern Great Plains (NGP) region. It is a sporadic but widespread wheat disease that can cause significant loss in grain yield and quality. Identification and characterization of genomic regions in wheat that confer resistance to BLS will help track resistance genes/QTLs in future wheat breeding. In this study, we evaluated a hard winter wheat association mapping panel (HWWAMP) containing 299 hard winter wheat lines from the US hard winter wheat growing region for their reactions to BLS. We observed a range of BLS responses among the lines, importantly, we identified ten genotypes that showed a resistant reaction both in greenhouse and field evaluation. -Genome-wide association analysis with 15,990 SNPs was conducted using an exponentially compressed mixed linear model. Five genomic regions (p < 0.001) that regulate the resistance to BLS were identified on chromosomes 1AL, 1BS, 3AL, 4AL, and 7AS. The QTLs Q.bls.sdsu-1AL, Q.bls.sdsu-1BS, Q.bls.sdsu-3AL, Q.bls.sdsu-4AL, and Q.bls.sdsu-7AS explain a total of 42% of the variation. In silico analysis of sequences in the candidate regions on chromosomes 1AL, 1BS, 3AL, 4AL, and 7AS identified 10, 25, 22, eight, and nine genes, respectively with known plant defense-related functions. Comparative analysis with rice showed two syntenic regions in rice that harbor genes for bacterial leaf streak resistance. The ten BLS resistant genotypes and SNP markers linked to the QTLs identified in our study could facilitate breeding for BLS resistance in winter wheat.