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Grain hardness is an important end-use quality trait which can significantly affect milling and processing quality of wheat. It is controlled by Puroindoline (Pin) genes in wheat, of which Pina-D1and Pinb-D1control major phenotypic variation, while Pinb-B2explain moderate variation. We analyzed the allelic variation of three Pingenes in a panel of 227 synthetic hexaploid wheats (SHWs) using allele-specific markers either previously available or newly developed in this study to identify new alleles and facilitate their introgression. Eight different alleles were identified in Pina-D1gene using six newly developed markers. The wild-type alleles, Pina-D1aand Pinb-D1a, were identified in 11.6 and 24.2% of accessions, respectively. It was found that Pina-D1cwas most frequent (30.7%), followed by Pina-D1eallele (18%) at Pina-D1. For Pinb-D1, three new markers were developed which classified synthetic wheats into four haplotype groups, of which Hap-IV (Pinb-D1j/Pinb-D1o) was most frequent (52.8%). A cleaved amplified polymorphic site (CAPS) marker using ApoIrestriction enzyme successfully classified accessions into wild-type and non-wild-type groups. At Pinb-B2gene, the frequency of Pinb-B2ballele was higher (76.2%) which is associated with relatively hard texture compared to Pinb-B2aallele. The results provide a deeper insight into the allelic composition of grain of grain texture genes in SHWs which can be introgressed to develop required texture market class using allele-specific markers developed in this study.

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 bottlenecks1,2. 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. tauschiigenomes 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. tauschiisubpopulations. Together, our results reveal the complex history of the bread wheat D genome and demonstrate the potential of wild relatives in crop improvement.

Sustainable wheat production is challenged by climate change events such as drought, salinity, and heat stress. Senescence is a gradual programmed cell death trait occurring post anthesis in wheat (Triticum aestivum), with significant affecting stability of yield and quality‐related traits under climate severities. Phenotyping of complex traits is increasingly perceived as a bottleneck due to elevated labor costs and time in large field conditions. Unmanned aerial vehicle (UAV)‐based platforms using RGB imagery and ground phenotyping–based novel traits can facilitate the repeated nondestructive measurements of crop canopy traits cost‐effectively. Here, we described combined application of UAV‐based RGB imaging and ground measurements based novel trait to quantify canopy senescence in wheat. We reported senescence related traits with high heritability in a recombinant inbred line population derived from the cross Zhongmai 175/Lunxuan 987. Our results showed that the selection of slow senescence genotypes using UAV‐based vegetation indices (VIs) was equally effective as ground‐based traits and illustrated significant variations among the genotypes. We also identified five quantitative trait loci (QTL) for canopy senescence in both UAV and ground‐based datasets using a 50K single‐nucleotide polymorphism array. QTL for UAV‐based VIs from RGB imaging and ground measurements based traits were mapped on chromosomes 1B, 2B, 3A, and 4B. The integration of both datasets with genetic analysis identified an important slow senescence/stay‐green related locus on chromosome 4B that explained phenotypic variation up to 23.07% for both UAV and ground traits at late grain‐ filling stage. Three QTL (QTL‐caas.1B, QTL‐caas.3A, and QTL‐caas.4B2) on chromosomes 1B, 3A, and 4B were also validated for slow senescence with high chlorophyll level and cool canopy temperature in a natural population of 160 lines by developing kompetitive allele‐specific PCR markers. QTL‐caas.4B1was validated not only for senescence but also for plant height. Our findings suggest that UAV‐based RGB imagery is advantageous for precise and rapid assessment of senescence related traits and genetic studies of senescence in wheat. Unmanned aerial vehicle (UAV)‐based phenotyping platforms using RGB imagery can facilitate the repeated nondestructive measurements of canopy greenness and senescence cost‐effectively.We have integrated vegetation indices derived from UAV‐based RGB pixels and ground measurements with quantitative genetic analysis to identify loci controlling canopy senescence in wheat.We have developed kompetitive allele‐specific PCR (KASP) markers based on identified loci that contribute to variations in wheat senescence.

Spike number (SN) per unit area is one of the major determinants of grain yield in wheat. Development of high-throughput techniques to count SN from large populations enables rapid and cost-effective selection and facilitates genetic studies. In the present study, we used a deep-learning algorithm, i.e., Faster Region-based Convolutional Neural Networks (Faster R-CNN) on Red-Green-Blue (RGB) images to explore the possibility of image-based detection of SN and its application to identify the loci underlying SN. A doubled haploid population of 101 lines derived from the Yangmai 16/Zhongmai 895 cross was grown at two sites for SN phenotyping and genotyped using the high-density wheat 660K SNP array. Analysis of manual spike number (MSN) in the field, image-based spike number (ISN), and verification of spike number (VSN) by Faster R-CNN revealed significant variation (P < 0.001) among genotypes, with high heritability ranged from 0.71 to 0.96. The coefficients of determination (R2) between ISN and VSN was 0.83, which was higher than that between ISN and MSN (R2 = 0.51), and between VSN and MSN (R2 = 0.50). Results showed that VSN data can effectively predict wheat spikes with an average accuracy of 86.7% when validated using MSN data. Three QTL Qsnyz.caas-4DS, Qsnyz.caas-7DS, and QSnyz.caas-7DLwere identified based on MSN, ISN and VSN data, while QSnyz.caas-7DSwas detected in all the three data sets. These results indicate that using Faster R-CNN model for image-based identification of SN per unit area is a precise and rapid phenotyping method, which can be used for genetic studies of SN in wheat.

It is important to understand the genetic gain achieved through selection of key yield traits for planning future breeding strategies in developing high yielding wheat (Triticum aestivumL.) cultivars. The aim of this study was to characterize the genetic changes and genotype × environment (G×E) interaction by additive main effect and multiplicative interactions (AMMI) for morphological, physiological, and yield component traits under five environments using 24 wheat cultivars released from 1911 to 2016 in Pakistan. There was a significant increase in grain yield (9.03 kg ha−1yr−1, 0.37%), and plant height was reduced linearly (−0.26 cm yr−1, −0.33%). The traits waxiness, leaf rolling, harvest index, spike length, and grains per spike significantly increased but the gain was only 0.16–0.2% per year. Analysis of variance revealed that genotype, environment, and G×E interaction were highly significant (P< .01) for all traits except relative chlorophyll content, biomass, days to maturity, and number of spikes. Gene‐specific markers identified the durable resistance gene Lr67/Yr46/Sr55/Pm46in obsolete cultivars as early as 1911, whereas the photoperiod‐insensitive allele Ppd‐D1aand reduced height alleles Rht‐B1band Rht‐D1bwere present only in the post‐1965 cultivars. Diversity analysis based on a 50K single nucleotide polymorphism genotyping array clearly differentiated temporal patterns in 24 cultivars, which was correlated with the agronomic performance of the cultivars. This dataset provided detailed insight into the performance of historical wheat cultivars and could help in devising wheat breeding strategies to focus on the traits contributing to grain yield and have slower rate of genetic progress. The genetic gain in morphology of Pakistani bread wheat cultivars over 105 yr areas was assessed.Leaf rolling, waxiness, and grains/spikes associated with genetic gains in grain yield were achieved by breeding.The performance and stability of yield and yield‐related traits was analyzed for the different cultivars.

Tajikistan is rich in genetic resources and one of a few countries where farmers still grow wheat (Triticumspp) landraces, which are important for production and breeding. This study undertook morphological description and agronomic and genomic characterization of wheat landraces collected in Tajikistan in 2013 and 2014 to develop opportunities for their use in breeding and on‐farm maintenance. In total, 60 wheat landraces were collected from 40 villages in 14 administrative districts and four regions. They were evaluated for agronomic traits in field trials in Turkey. The study identified six distinct regions where landraces are still grown. The villages growing the landraces were remote, with the distance to the nearest market being 30–100 km. The area allocated to wheat landraces varied from 0.01 to 2 ha. The main reason for maintaining the wheat landraces was their suitability for homemade bread and specific adaptation to high altitude. Overall, 68 distinct lines originating from landraces were identified using morphological and genomic descriptions. A core set of 30 lines was selected and field phenotyped under rain‐fed conditions. Several landraces (Joydori, Safedak, Surkhaki besuk, Shukhak, Surkh‐suk, and Kilaki bartang) that exceeded local check for grain yield and size were identified. Cluster analysis using single nucleotide polymorphism (SNP) array kinship matrix demonstrated relatedness between the landraces from different regions of Tajikistan and from neighboring regions of Uzbekistan. The value of this study for the international community is in conservation of rare and unique wheat landraces that could have been lost in the future. Wheat landraces are cultivated in Tajikistan in mountains because of their adaptation and quality.Overall, 68 unique landraces were identified using morphological and genomic tools.Field evaluation of the core set of 30 landraces identified superior genotypes.

Black point, a black discoloration of the grain embryo, downgrades the grain quality and commodity grade. Identification of the underlying genetic loci can facilitate the improvement of black point resistance in wheat. Here, 262 recombinant inbred lines (RILs) from the cross of Zhongmai 578/Jimai 22 were evaluated for black point reaction in five environments. A high-density genetic linkage map of the RIL population was constructed with the wheat 50K single nucleotide polymorphism (SNP) array. Six stable QTLs for black point resistance, QBp.caas-2A, QBp.caas-2B1, QBp.caas-2B2, QBp.caas-2D, QBp.caas-3Aand QBp.caas-5Bwere detected, explaining 2.1-28.8% of the phenotypic variances. The resistance alleles of QBp.caas-2B1and QBp.caas-2B2were contributed by Zhongmai 578 while the others were from Jimai 22. QBp.caas-2B2, QBp.caas-2Dand QBp.caas-3Aare overlapped with previously reported loci, whereas QBp.caas-2A, QBp.caas-2B1and QBp.caas-5Bare likely to be new. Five KASP markers, Kasp_2A_BP, Kasp_2B1_BP, Kasp_2B2_BP, Kasp_3A_BPand Kasp_5B_BPwere validated in a natural population of 165 cultivars. The findings provide useful QTL and molecular markers for improvement of black point in wheat resistance in marker-assisted breeding.

The wheat gene pool has a tremendous amount of genetic diversity for salinity tolerance. During the last few decades, several wheat genetic stocks have been developed showing all three types of tolerance mechanisms, i.e., tissue tolerance, osmotic tolerance and ion (Na+) exclusion. However, delivery of improved crop varieties adapted to saline conditions has been lagging behind due to several reasons including the huge knowledge gap in understanding genetic basis of salinity tolerance in wheat, and then applying the available knowledge to deliver salt-resilient crop varieties. We review the research around salinity tolerance in wheat in context of historical and rapidly evolving breeding technologies and discuss the future prospects. The extensive research on identifying promising resources of salinity tolerance in durum wheat, synthetic hexaploid wheats and tertiary gene pool species such as those of Thinopyrumhave been explored to transfer salinity tolerance traits to bread wheat. As the last few years witnessed leading-edge transformations where we have now (i) new and improved genotyping assays in form of SNP arrays and next-generation sequencing to facilitate gene discovery, (ii) new generation turn-over methods to get five to six generations per year by “speed breeding” facilitating gene deployment, (iii) gene-editing tools to precisely manipulate the effects of causal genes, and (iv) new phenomic platforms for capturing salinity effects in field and glass-house conditions. Integration of all these technologies will help in understanding the complex genetic architecture of wheat adaptability in saline soils and will accelerate the delivery of our future potential wheat cultivars.

Adaptation of wheat (Triticum aestivumL.) to high temperature could be improved by introgressions from wild relatives. The response of 137 D genome synthetic hexaploid wheats (SHWs) to high temperature was evaluated to determine their potential for wheat improvement. Field experiments were conducted in two temperature scenarios (normal sowing time [NOR] and late sowing time to expose the plants to heat stress [HS]) for 2 yr at three locations to assess the effect of terminal high temperature on yield‐related traits. High temperature stress overall led to a 46.9% reduction in grain yield and significant reductions of 25.2% in days to heading, 26.6% in plant height, 16.1% in grain number per square meter, and 18.3% in thousand grain weight. In ridge regression analysis, agronomic traits explained 8.74 to 35.2% of the variation in grain yield in the HS treatments with an average of 30.47%. In NOR treatments, agronomic traits explained 8.85 to 45.5% of the variation in grain yield, with an average of 34.5%. Days to heading was negatively correlated with grain yield in the heat‐stressed environments but did not explain significant variation in grain yield in optimal environments. Thousand‐grain weight explained the highest variation in grain yield in all environments, followed by grain number per square meter. The top ten highest grain‐yielding SHWs in the HS treatment were also tolerant to heat stress, with a heat susceptibility index ranging from 0.33 to 0.40. These SHWs could be a promising source to introduce yield‐related traits to develop high‐yielding wheat cultivars for heat‐stressed environments.

Understanding the key characteristics associated with genetic gains achieved through breeding is essential for improving yield‐limiting factors and designing future breeding strategies in bread wheat (Triticum aestivumL.) cultivars. The objective of the present study was to investigate the genetic progress in yield‐related and physiological traits in cultivars released from 1950 to 2012 for irrigated conditions in the southern Yellow and Huai Valleys Winter Wheat Zone. Field trials including 26 leading cultivars from 1950 to the present time were conducted at Zhengzhou and Zhoukou in Henan Province, during the 2013–2014 and 2014–2015 cropping seasons, providing data from four environments. Grain yield (GY) was significantly increased by the linear rate of 57.5 kg ha−1yr−1or 0.70% (R2= 0.66, P< 0.01) and significantly correlated with increased thousand‐kernel weight (TKW) (r= 0.48, P< 0.05), spike number m−2(r= 0.44, P< 0.05), kernels m−2(r= 0.56, P< 0.01), aboveground biomass (AGBM) (r= 0.80, P< 0.01), harvest index (HI) (r= 0.84, P< 0.01), water‐soluble carbohydrate at 10 d postanthesis (WSC‐10) (r= 0.80, P< 0.01), and reduced plant height (PH) (r= −0.85, P< 0.01). There was no significant change in kernel number per spike, heading date, normalized difference in vegetation index at anthesis and at 10 d postanthesis, leaf area index at anthesis and at 10 d postanthesis, and canopy temperature depression at anthesis during the past 60 yr. Soil plant analysis development (SPAD) estimates of chlorophyll content at 10 d postanthesis (Chl‐10) increased with year of release and were significantly correlated with GY (r= 0.69, P< 0.01), PH (r= −0.76, P< 0.01), AGBM (r= 0.52, P< 0.01), HI (r= 0.71, P< 0.01), and WSC‐10 (r= 0.73, P< 0.01). Cultivars conferring Rht‐D1band Rht‐D1b+ Rht8cshowed increased GY, TKW, AGBM, HI, WSC‐10, and Chl‐10. Stem water solubility content can be used as a selection criterion for further improving yield potential.

Synthetic hexaploid wheat and their advanced derivatives (SYN-DERs) are promising sources for introducing novel genetic diversity to develop climate-resilient cultivars. In a series of field and laboratory experiments, we measured biochemical, physiological and agronomic traits in a diversity panel of SYN-DERs evaluated under well-watered (WW) and water-limited (WL) conditions. Analysis of variance revealed significant differences among genotypes, treatments and their interaction for all agronomic and physiological traits. Grain yield (GY) was reduced by 62.75% under WL, with a reduction of 38.10% in grains per spike (GS) and 19.42% in 1000-grain weight (TGW). In a Pearson’s coefficient correlation, GY was significantly correlated with GS, number of tillers per plant and TGW in both conditions. Path coefficient analysis showed that TGW and GS made the highest contribution to GY in WW and WL conditions, respectively. The traits examined in this experiment explained 59.6% and 63.01% of the variation in GY under WL and WW conditions, respectively; TGW, canopy temperature at spike and superoxide dismutase were major determinants of GY under WL conditions. The major flowering-time determinant gene Ppd-D1 was fixed in the diversity panel, with presence of the photoperiod-insensitive allele (Ppd-D1a) in 99% accessions. Wild-type alleles at Rht-B1 and Rht-D1, and presence of the rye translocation (1B.1R), favoured GY under WL conditions. Continuous variation for the important traits indicated the potential use of genome-wide association studies to identify favourable alleles for drought adaptation in the SYN-DERs. This study showed sufficient genetic variation in the SYN-DERs diversity panel to improve yields during droughts because of better adaptability than bread wheat.

Wheat (Triticum aestivum) is one of the most essential human energy and protein sources. However, wheat production is threatened by devastating fungal diseases such as stripe rust, caused by Puccinia striiformisWestend. f. sp. tritici(Pst). Here, we reveal that the alternations in chloroplast lipid profiles and the accumulation of jasmonate (JA) in the necrosis region activate JA signaling and trigger the host defense. The collapse of chloroplasts in the necrosis region results in accumulations of polyunsaturated membrane lipids and the lipid-derived phytohormone JA in transgenic lines of Yr36 that encodes Wheat Kinase START 1 (WKS1), a high-temperature-dependent adult plant resistance protein. WKS1.1, a protein encoded by a full-length splicing variant of WKS1, phosphorylates and enhances the activity of keto-acyl thiolase (KAT-2B), a critical enzyme catalyzing the β-oxidation reaction in JA biosynthesis. The premature stop mutant, kat-2b, accumulates less JA and shows defects in the host defense against Pst. Conversely, overexpression of KAT-2Bresults in a higher level of JA and limits the growth of Pst. Moreover, JA inhibits the growth and reduces pustule densities of Pst. This study illustrates the WKS1.1‒KAT-2B‒JA pathway for enhancing wheat defense against fungal pathogens to attenuate yield loss.

We investigated alleles at 31 loci associated with adaptability, yield, and end‐use quality in 107 wheat (Triticum aestivumL.) landraces (WLRs) and 121 improved historical wheat cultivars (HWCs) from Pakistan. The WLRs were categorized into two further subgroups: 36 pre‐Green‐Revolution landraces released as cultivars and 71 geographically spread landraces from all over Pakistan. Alleles Vrn‐A1a, TaGW2‐6A‐A, TaCKX6‐D1b, Pinb‐D1b, Psy‐A1b, and Wx‐D1bwere absent in WLRs, whereas ample diversity was observed at all other loci. In HWCs, only Wx‐D1band Glu‐A3ewere absent among the alleles tested, whereas the alleles Ppd‐D1a(90%), Rht‐B1bor Rht‐D1b(83.4%), TaCwi‐A1a(95%), TaGW2‐6A‐G(76%), TaCKX6‐D1a(77.3%), Glu‐A1b(66.1%), Glu‐D1d(61.3%), Pina‐D1b(88.2%), Pinb‐D1a(90%), Psy‐A1a(66.1%), Psy‐B1b(81.8%), Psy‐D1a(86.5%), Ppo‐A1a(70%), TaZds‐D1b(73.9%), TaLox‐B1b(80.1%), and Wx‐D1a(100%) predominated, indicating significant improvement in adaptability, yield potential, and end‐use quality and unconscious selection for favored alleles. Higher frequencies of favored alleles at the TaCwi‐A1and TaCKX6‐D1loci influencing 1000‐kernel weight (TKW) in HWCs indicated that selection pressure on these alleles during breeding successfully contributed to cultivar improvement. Wright's pairwise fixation index (Fst) statistics indicated greater genetic divergence between HWC and WLR collections (0.16) than HWC and WLR cultivars (0.14). Population structure based on functional markers (FMs) using principal component analysis partitioned the germplasm into two distinct groups. High genetic divergence and low admixture between HWCs and WLRs indicated limited use of landraces in wheat breeding in Pakistan. Our results suggested these collections as rich reservoirs of alleles and haplotype combinations that may be useful in future breeding programs.

The recently published reference genome of Aegilops tauschiiprovides new insights into the originator of the D genome donor of hexaploid wheat. This will be a foundation for exploring the genomic diversity underpinning adaptive traits in wheat, and ultimately advance wheat improvement efforts.