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Wheat stands as the foremost cultivated crop in Pakistan, dominating in terms of acreage and production among cereals. The morphology of wheat grains has been a target of selection since the dawn of agriculture and remains a paramount focus in contemporary breeding efforts. This study sought to examine alterations in grain morphology using digital imaging across 64 bread wheat cultivars grown in Pakistan under both well-watered and water-limited conditions, while also exploring their link with the TaCWI gene. The analysis revealed a substantial range of variation in grain morphology encompassing more than 15fifteen descriptors among the cultivars. Historically significant wheat cultivars, including T9 and C-271, which predate 1930, exhibited the smallest grain area, while contemporary counterparts like, Pirsabak-2013 and Markaz-2019 showcased the largest grain area. Significantly, the wheat cell wall invertase gene, TaCwi-A1, displayed a strong association with grain size. The TaCwi-A1a allele was identified in 31 out of the 64 cultivars and was notably correlated with larger grain size. This research unveils a comprehensive understanding of variations in grain size and shape among historical wheat cultivars in Pakistan and emphasizes that modern Pakistani wheat cultivars tend to exhibit larger grain size. Furthermore, it underscores the necessity of evaluating the allelic influence of additional genes related to grain size and weight, paving the way for more targeted breeding efforts in the future. [ABSTRACT FROM AUTHOR]

Key message: Three stable QTL for grain zinc concentration were identified in wheat landrace Chinese Spring. Favorable alleles were more frequent in landraces than in modern wheat cultivars. Wheat is a major source of dietary energy for the growing world population. Developing cultivars with enriched zinc and iron can potentially alleviate human micronutrient deficiency. In this study, a recombinant inbred line (RIL) population with 245 lines derived from cross Zhou 8425B/Chinese Spring was used to detect quantitative trait loci (QTL) for grain zinc concentration (GZnC) and grain iron concentration (GFeC) across four environments. Three stable QTL for GZnC with all favorable alleles from Chinese Spring were identified on chromosomes 3BL, 5AL, and 5BL. These QTL explaining maxima of 8.7%, 5.8%, and 7.1% of phenotypic variances were validated in 125 resequenced wheat accessions encompassing both landraces and modern cultivars using six kompetitive allele specific PCR (KASP) assays. The frequencies of favorable alleles for QGZnCzc.caas-3BL, QGZnCzc.caas-5AL and QGZnCzc.caas-5BL were higher in landraces (90.4%, 68.0%, and 100.0%, respectively) compared to modern cultivars (45.9%, 35.4%, and 40.9%), suggesting they were not selected in breeding programs. Candidate gene association studies on GZnC in the cultivar panel further delimited the QTL into 8.5 Mb, 4.1 Mb, and 47.8 Mb regions containing 46, 4, and 199 candidate genes, respectively. The 5BL QTL located in a region where recombination was suppressed. Two stable and three less stable QTL for GFeC with favorable alleles also from Chinese Spring were identified on chromosomes 4BS (Rht-B1a), 4DS (Rht-D1a), 1DS, 3AS, and 6DS. This study sheds light on the genetic basis of GZnC and GFeC in Chinese Spring and provides useful molecular markers for wheat biofortification. [ABSTRACT FROM AUTHOR]

In this study, Levinson-type inequalities for the class of n-convex (n ≥ 3 ) functions are generalized using new Green functions and the Hermite interpolating polynomial involving two types of data points. Some estimations for novel functionals are derived using f-divergence. Furthermore, different inequalities involving Shannon entropies are presented. [ABSTRACT FROM AUTHOR]

Background: Hexaploid bread wheat underwent a series of polyploidization events through interspecific hybridizations that conferred adaptive plasticity and resulted in duplication and neofunctionalization of major agronomic genes. The genetic architecture of polyploid wheat not only confers adaptive plasticity but also offers huge genetic diversity. However, the contribution of different gene copies (homeologs) encoded from different subgenomes (A, B, D) at different growth stages remained unexplored. Methods: In this study, hybrid of elite cultivars of wheat were developed via reciprocal crosses (cytoplasm swapping) and phenotypically evaluated. We assessed differential expression profiles of yield-related negative regulators in these cultivars and their F1 hybrids and identified various cis-regulatory signatures by employing bioinformatics tools. Furthermore, the preferential expression patterns of the syntenic triads encoded from A, B, and D subgenomes were assessed to decipher their functional redundancy at six different growth stages. Results: Hybrid progenies showed better heterosis such as up to 17% increase in the average number of grains and up to 50% increase in average thousand grains weight as compared to mid-parents. Based on the expression profiling, our results indicated significant dynamic transcriptional expression patterns, portraying the different homeolog-dominance at the same stage in the different cultivars and their hybrids. Albeit belonging to same syntenic triads, a dynamic trend was observed in the regulatory signatures of these genes that might be influencing their expression profiles. Conclusion: These findings can substantially contribute and provide insights for the selective introduction of better cultivars into traditional and hybrid breeding programs which can be harnessed for the improvement of future wheat. [ABSTRACT FROM AUTHOR]

Background: SnRK2 plays vital role in responding to adverse abiotic stimuli. The applicability of TaSnRK2.4 and TaSnRK2.9 was investigated to leverage the potential of these genes in indigenous wheat breeding programs. Methods: Genetic diversity was assessed using pre-existing markers for TaSnRK2.4 and TaSnRK2.9. Furthermore, new markers were also developed to enhance their broader applicability. KASP markers were designed for TaSnRK2.4, while CAPS-based markers were tailored for TaSnRK2.9. Results: Analysis revealed lack of polymorphism in TaSnRK2.4 among Pakistani wheat germplasm under study. To validate this finding, available gel-based markers for TaSnRK2.4 were employed, producing consistent results and offering limited potential for application in marker-assisted wheat breeding with Pakistani wheat material. For TaSnRK2.9-5A, CAPS2.9-5A-1 and CAPS2.9-5A-2 markers were designed to target SNP positions at 308 nt and 1700 nt revealing four distinct haplotypes. Association analysis highlighted the significance of Hap-5A-1 of TaSnRK2.9-5A, which exhibited association with an increased number of productive tillers (NPT), grains per spike (GPS), and reduced plant height (PH) under well-watered (WW) conditions. Moreover, it showed positive influence on NPT under WW conditions, GPS under water-limited (WL) conditions, and PH under both WW and WL conditions. High selection intensity observed for Hap-5A-1 underscores the valuable role it has played in Pakistani wheat breeding programs. Gene expression studies of TaSnRK2.9-5A revealed the involvement of this gene in response to PEG, NaCl, low temperature and ABA treatments. Conclusion: These findings propose that TaSnRK2.9 can be effectively employed for improving wheat through marker-assisted selection in wheat breeding efforts. [ABSTRACT FROM AUTHOR]

Achieving high yield and good quality in crops is essential for human food security and health. However, there is usually disharmony between yield and quality. Seed storage protein (SSP) and starch, the predominant components in cereal grains, determine yield and quality, and their coupled synthesis causes a yield–quality trade‐off. Therefore, dissection of the underlying regulatory mechanism facilitates simultaneous improvement of yield and quality. Here, we summarize current findings about the synergistic molecular machinery underpinning SSP and starch synthesis in the leading staple cereal crops, including maize, rice and wheat. We further evaluate the functional conservation and differentiation of key regulators and specify feasible research approaches to identify additional regulators and expand insights. We also present major strategies to leverage resultant information for simultaneous improvement of yield and quality by molecular breeding. Finally, future perspectives on major challenges are proposed. [ABSTRACT FROM AUTHOR]

Background: SnRK2 plays vital role in responding to adverse abiotic stimuli. The applicability of TaSnRK2.4 and TaSnRK2.9 was investigated to leverage the potential of these genes in indigenous wheat breeding programs. Methods: Genetic diversity was assessed using pre-existing markers for TaSnRK2.4 and TaSnRK2.9. Furthermore, new markers were also developed to enhance their broader applicability. KASP markers were designed for TaSnRK2.4, while CAPS-based markers were tailored for TaSnRK2.9. Results: Analysis revealed lack of polymorphism in TaSnRK2.4 among Pakistani wheat germplasm under study. To validate this finding, available gel-based markers for TaSnRK2.4 were employed, producing consistent results and offering limited potential for application in marker-assisted wheat breeding with Pakistani wheat material. For TaSnRK2.9-5A, CAPS2.9-5A-1 and CAPS2.9-5A-2 markers were designed to target SNP positions at 308 nt and 1700 nt revealing four distinct haplotypes. Association analysis highlighted the significance of Hap-5A-1 of TaSnRK2.9-5A, which exhibited association with an increased number of productive tillers (NPT), grains per spike (GPS), and reduced plant height (PH) under well-watered (WW) conditions. Moreover, it showed positive influence on NPT under WW conditions, GPS under water-limited (WL) conditions, and PH under both WW and WL conditions. High selection intensity observed for Hap-5A-1 underscores the valuable role it has played in Pakistani wheat breeding programs. Gene expression studies of TaSnRK2.9-5A revealed the involvement of this gene in response to PEG, NaCl, low temperature and ABA treatments. Conclusion: These findings propose that TaSnRK2.9 can be effectively employed for improving wheat through marker-assisted selection in wheat breeding efforts. [ABSTRACT FROM AUTHOR]

Background: Hexaploid bread wheat underwent a series of polyploidization events through interspecific hybridizations that conferred adaptive plasticity and resulted in duplication and neofunctionalization of major agronomic genes. The genetic architecture of polyploid wheat not only confers adaptive plasticity but also offers huge genetic diversity. However, the contribution of different gene copies (homeologs) encoded from different subgenomes (A, B, D) at different growth stages remained unexplored. Methods: In this study, hybrid of elite cultivars of wheat were developed via reciprocal crosses (cytoplasm swapping) and phenotypically evaluated. We assessed differential expression profiles of yield-related negative regulators in these cultivars and their F1 hybrids and identified various cis-regulatory signatures by employing bioinformatics tools. Furthermore, the preferential expression patterns of the syntenic triads encoded from A, B, and D subgenomes were assessed to decipher their functional redundancy at six different growth stages. Results: Hybrid progenies showed better heterosis such as up to 17% increase in the average number of grains and up to 50% increase in average thousand grains weight as compared to mid-parents. Based on the expression profiling, our results indicated significant dynamic transcriptional expression patterns, portraying the different homeolog-dominance at the same stage in the different cultivars and their hybrids. Albeit belonging to same syntenic triads, a dynamic trend was observed in the regulatory signatures of these genes that might be influencing their expression profiles. Conclusion: These findings can substantially contribute and provide insights for the selective introduction of better cultivars into traditional and hybrid breeding programs which can be harnessed for the improvement of future wheat. [ABSTRACT FROM AUTHOR]

The Kazakhstan-Siberia Network for Spring Wheat Improvement (KASIB) was established in 2000, forming a collaboration between breeding and research programs through biannual yield trials. A core set of 142 genotypes from 15 breeding programs was selected, genotyped for 81 DNA functional markers and phenotyped for 10 agronomic traits at three sites in Kazakhstan (Karabalyk, Shortandy and Shagalaly) and one site in Russia (Omsk) in 2020–2022. The study aim was to identify markers demonstrating significant effects on agronomic traits. The average grain yield of individual trials varied from 118 to 569 g/m2. Grain yield was positively associated with the number of days to heading, plant height, number of grains per spike and 1000-kernel weight. Eight DNA markers demonstrated significant effects. The spring-type allele of the Vrn-A1 gene accelerated heading by two days (5.6%) and was present in 80% of the germplasm. The winter allele of the Vrn-A1 gene significantly increased grain yield by 2.7%. The late allele of the earliness marker per se, TaMOT1-D1, delayed development by 1.9% and increased yield by 4.5%. Translocation of 1B.1R was present in 21.8% of the material, which resulted in a 6.2% yield advantage compared to 1B.1B germplasm and a reduction in stem rust severity from 27.6 to 6.6%. The favorable allele of TaGS-D1 increased both kernel weight and yield by 2–3%. Four markers identified in ICARDA germplasm, ISBW2-GY (Kukri_c3243_1065, 3B), ISBW3-BM (TA004946-0577, 1B), ISBW10-SM2 (BS00076246_51, 5A), ISBW11-GY (wsnp_Ex_c12812_20324622, 4A), showed an improved yield in this study of 3–4%. The study recommends simultaneous validation and use of selected markers in KASIB's network. [ABSTRACT FROM AUTHOR]

Roots are the main sensing organ, initiating multiple signaling pathways in response to abiotic factors, including nutrients, drought, and salt stress. A focus on improving the root system architecture is a key strategy to mitigate these stresses in wheat crop. In the present study, a diversity panel comprising indigenous landraces and historical cultivars from Pakistan was characterized for the root system architecture (RSA) and important loci were identified using a genome‐wide association study (GWAS). RSA of the diversity panel was characterized 30 days after sowing in brunch tubes, and root images were taken. A high‐throughput root imaging analysis using Rhizovision software was performed by setting the scale to extract the eight RSA traits and four plant biomass‐related traits. GWAS identified 323 association signals for 12 root and biomass traits present on all wheat chromosomes, while the most important and reliable genetic loci (based on pleotropic loci and candidate genes) were identified on chromosomes 2A, 2B, 5A, 5D, 6A, 7B, and 7D for RSA. SNP annotation and transcriptome profiling identified nine candidate genes regulating the RSA and plant biomass traits, including ROOTLESS WITH UNDETECTABLE MERISTEM1, MYB TRANSCRIPTION FACTOR4, BRASSINOSTEROID INSENSITIVE1, SLENDER RICE1, AUXIN‐RESPONSIVE FACTOR25, SCARECROW, NARROW LEAF2, PIN‐FORMED1 AND PHOSPHATE TRANSCRIPTION FACTOR1. This study provided pre‐breeding information for deep‐rooting genotypes and associated markers that will accelerate the incorporation of such traits in breeding. [ABSTRACT FROM AUTHOR]

Background: Durum wheat is one of the most important crops, especially in the Mediterranean region. Insight into the genetic diversity of germplasm can improve the breeding program management in various traits. This study was done using single nucleotide polymorphisms (SNP) markers to characterize the genetic distinctiveness and differentiation of tetraploid wheat landraces collected from nine European and Asian countries. A sum of 23,334 polymorphic SNPs was detected in 126 tetraploid wheat landraces in relation to the reference genome. Results: The number of identified SNPs was 11,613 and 11,721 in A and B genomes, respectively. The highest and lowest diversity was on 6B and 6 A chromosomes, respectively. Structure analysis classified the landraces into two distinct subpopulations (K = 2). Evaluating the principal coordinate analysis (PCoA) and weighted pair-group method using arithmetic averages (WPGMA) clustering results demonstrated that landraces (99.2%) are categorized into one of the two chief subpopulations. Therefore, the grouping pattern did not clearly show the presence of a clear pattern of relationships between genetic diversity and their geographical derivation. Part of this result could be due to the historical exchange between different germplasms. Although the result did not separate landraces based on their region of origin, the landraces collected from Iran were classified into the same group and cluster. Analysis of molecular variance (AMOVA) also confirmed the results of population structure. Finally, Durum wheat landraces in some countries, including Turkey, Russia, Ukraine, and Afghanistan, were highly diverse, while others, including Iran and China, were low-diversity. Conclusion: The recent study concluded that the 126 tetraploid wheat genotypes and their GBS-SNP markers are very appropriate for quantitative trait loci (QTLs) mapping and genome-wide association studies (GWAS). The core collection comprises two distinct subpopulations. Subpopulation II genotypes are the most diverse genotypes, and if they possess desired traits, they may be used in future breeding programs. The degree of diversity in the landraces of countries can provide the ground for the improvement of new cultivars with international cooperation. linkage disequilibrium (LD) hotspot distribution across the genome was investigated, which provides useful information about the genomic regions that contain intriguing genes. [ABSTRACT FROM AUTHOR]

Digital signal processing (DSP) is one of the most effective tools that have influenced science, engineering, and technology in the twenty-first century. Since 1970, advancements in the expansive field of DSP have made it a crucial tool in many applications. Many in-depth investigations on the filters and the extraction of helpful information have been conducted by researchers in a variety of scientific domains. In this paper, digital filters have been applied on radon (thereafter called to be as 222Rn) and thoron (thereafter to be called as 220Rn) time series signals to extract meaningful information from the original signals. By employing finite impulse response (FIR) equiripple and infinite impulse response (IIR) Butterworth filters to the soil 222Rn and 220Rn signals, the extracted features have been examined to obtain the improved output of the signal. The Persistence spectrums and spectrograms of FIR and IIR filtered 222Rn and 220Rn are constructed to check the anomalous shift in frequency, power and amplitude of the signals, due to the seismic events, if any, that took place during the research period. Finding of study shows that FIR and IIR filtered 220Rn indicates the anomalous behavior, nine and eleven days, before the seismic event of M 4.3 and M 2.5 occurred during the study period on 21st and 23rd of March 2017. Radon and thoron also shows anomalous nature twelve and nine days, before the earthquake of magnitude M 4.8 occurred during the study. Some anomalies appearing in the original 222Rn and 220Rn time series are found to have no connection with seismic events rather meteorological factors are believed to be responsible for them. [ABSTRACT FROM AUTHOR]

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.4B1 was 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. Core Ideas: 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. [ABSTRACT FROM AUTHOR]

Key message: Major QTL for grain zinc and iron concentrations were identified on the long arm of chromosomes 2D and 6D. Gene-based KASP markers were developed for putative candidate genes TaIPK1-2D and TaNAS10-6D. Micronutrient malnutrition is one of the most common public health problems in the world. Biofortification, the most attractive and sustainable solution to surmount malnutrition requires the development of micronutrient enriched new crop cultivars. In this study, two recombinant inbred line (RIL) populations, ZM175/XY60 and ZM175/LX987, were used to identify QTL for grain zinc concentration (GZnC), grain iron concentration (GFeC) and thousand grain weight (TGW). Eight QTL for GZnC, six QTL for GFeC and five QTL for TGW were detected. Three QTL on chromosomes 2DL and 4BS and chromosome 6A showed pleiotropic effects on all three traits. The 4BS and 6A QTL also increased plant height and might be Rht-B1a and Rht25a, respectively. The 2DL locus within a suppressed recombination region was identified in both RIL populations and the favorable allele simultaneously increasing GZnC, GFeC and TGW was contributed by XY60 and LX987. A QTL on chromosome 6DL associated only with GZnC was detected in ZM175/XY60 and was validated in JD8/AK58 RILs using kompetitive allele-specific PCR (KASP) marker K_AX-110119937. Both the 2DL and 6DL QTL were new loci for GZnC. Based on gene annotations, sequence variations and expression profiles, the phytic acid biosynthesis gene TaIPK1-2D and nicotianamine synthase gene TaNAS10-6D were predicted as candidate genes. Their gene-based KASP markers were developed and validated in a cultivar panel of 343 wheat accessions. This study investigated the genetic basis of GZnC and GFeC and provided valuable candidate genes and markers for breeding Zn- and Fe-enriched wheat. [ABSTRACT FROM AUTHOR]

In this paper, four new Green functions are used to generalize Levinson-type inequalities for the class of 3-convex functions. The f-divergence, Renyi entropy, Renyi divergence, Shannon entropy, and the Zipf–Mandelbrot law are also used to apply the main results to information theory. [ABSTRACT FROM AUTHOR]

Summary: Wheat fixes CO2 by photosynthesis into kernels to nourish humankind. Improving the photosynthesis rate is a major driving force in assimilating atmospheric CO2 and guaranteeing food supply for human beings. Strategies for achieving the above goal need to be improved. Here, we report the cloning and mechanism of CO2ASSIMILATION RATE AND KERNEL‐ENHANCED 1 (CAKE1) from durum wheat (Triticum turgidum L. var. durum). The cake1 mutant displayed a lower photosynthesis rate with smaller grains. Genetic studies identified CAKE1 as HSP90.2‐B, encoding cytosolic molecular chaperone folding nascent preproteins. The disturbance of HSP90.2 decreased leaf photosynthesis rate, kernel weight (KW) and yield. Nevertheless, HSP90.2 over‐expression increased KW. HSP90.2 recruited and was essential for the chloroplast localization of nuclear‐encoded photosynthesis units, for example PsbO. Actin microfilaments docked on the chloroplast surface interacted with HSP90.2 as a subcellular track towards chloroplasts. A natural variation in the hexaploid wheat HSP90.2‐B promoter increased its transcription activity, enhanced photosynthesis rate and improved KW and yield. Our study illustrated an HSP90.2–Actin complex sorting client preproteins towards chloroplasts to promote CO2 assimilation and crop production. The beneficial haplotype of Hsp90.2 is rare in modern varieties and could be an excellent molecular switch promoting photosynthesis rate to increase yield in future elite wheat varieties. [ABSTRACT FROM AUTHOR]

Main conclusion: The study provided an insight toward better understanding of stay-green mechanisms for drought tolerance improvement and identified that synthetic-derived wheats proved as a promising germplasm for improved tolerance against water stress. Stay-green (SG) trait is considered to be related with the ability of wheat plants to maintain photosynthesis and CO2 assimilation. The present study explored the interaction of water stress with SG expression through physio-biochemical, agronomic and phenotypic responses among diverse wheat germplasm comprising of 200 synthetic hexaploids, 12 synthetic derivatives, 97 landraces and 16 conventional bread wheat varieties, for 2 years. The study established that variation of SG trait existed in the studied wheat germplasm and there was positive association between SG trait and tolerance to water stress. The relationship of SG trait with chlorophyll content (r = 0.97), ETR (r = 0.28), GNS (r = 0.44), BMP (r = 0.34) and GYP (r = 0.44) was particularly promising under water stress environment. Regarding chlorophyll fluorescence, the positive correlation of фPSII (r = 0.21), qP (r = 0.27) and ETR (r = 0.44) with grain yield per plant was noted. The improved ΦPSII and Fv/Fm of PSII photochemistry resulted in the high photosynthesis activity in SG wheat genotypes. Regarding relative water content and photochemical quenching coefficient, synthetic-derived wheats were better by maintaining 20.9, 9.8 and 16.1% more RWC and exhibiting 30.2, 13.5 and 17.9% more qP when compared with landraces, varieties and synthetic hexaploids, respectively, under water stress environment. Synthetic derived wheats also exhibited relatively more SG character with good yield and were more tolerant to water stress in terms of grain yield, grain weight per plant, better photosynthetic performance through chlorophyll fluorescence measurement, high leaf chlorophyll and proline content, and hence, may be used as novel sources for breeding drought tolerant materials. The study will further facilitate research on wheat leaf senescence and will add to better understanding of SG mechanisms for drought tolerance improvement. [ABSTRACT FROM AUTHOR]

Genomic prediction is an effective way to accelerate the rate of agronomic trait improvement in plants. Traditional methods typically use linear regression models with clear assumptions; such methods are unable to capture the complex relationships between genotypes and phenotypes. Non-linear models (e.g., deep neural networks) have been proposed as a superior alternative to linear models because they can capture complex non-additive effects. Here we introduce a deep learning (DL) method, deep neural network genomic prediction (DNNGP), for integration of multi-omics data in plants. We trained DNNGP on four datasets and compared its performance with methods built with five classic models: genomic best linear unbiased prediction (GBLUP); two methods based on a machine learning (ML) framework, light gradient boosting machine (LightGBM) and support vector regression (SVR); and two methods based on a DL framework, deep learning genomic selection (DeepGS) and deep learning genome-wide association study (DLGWAS). DNNGP is novel in five ways. First, it can be applied to a variety of omics data to predict phenotypes. Second, the multilayered hierarchical structure of DNNGP dynamically learns features from raw data, avoiding overfitting and improving the convergence rate using a batch normalization layer and early stopping and rectified linear activation (rectified linear unit) functions. Third, when small datasets were used, DNNGP produced results that are competitive with results from the other five methods, showing greater prediction accuracy than the other methods when large-scale breeding data were used. Fourth, the computation time required by DNNGP was comparable with that of commonly used methods, up to 10 times faster than DeepGS. Fifth, hyperparameters can easily be batch tuned on a local machine. Compared with GBLUP, LightGBM, SVR, DeepGS and DLGWAS, DNNGP is superior to these existing widely used genomic selection (GS) methods. Moreover, DNNGP can generate robust assessments from diverse datasets, including omics data, and quickly incorporate complex and large datasets into usable models, making it a promising and practical approach for straightforward integration into existing GS platforms. The application of deep learning to plant breeding is an active area of research. This work reports a new method, DNNGP, for prediction of quantitative traits from multi-omics data in the context of genomic selection in plants. DNNGP performs as well as or better than several commonly used methods in a broad range of tasks. The insights gained through the development, testing, and application of DNNGP can benefit genomics applications of deep learning in the future. [ABSTRACT FROM AUTHOR]

We evaluated root system architecture (RSA) of a set of 58 historical spring wheat cultivars from Pakistan representing 105 years of selection breeding. The evaluations were carried out under control and water-limited conditions using a high-throughput phenotyping system coupled with RhizoVision Explorer software. The cultivars were classified into three groups based on release year as cultivars released pre-1965, released between 1965 and 2000, and cultivars released post-2000. Under water-limited conditions a decline in 20 out of 25 RSA component traits was observed in pre-1965 cultivars group. Whereas cultivars released after the 1965, so-called green revolution period, showed a decline in 17 traits with significant increments in root length, depth, and steep angle frequency which are important root traits for resource-uptake under water-limited conditions. Similarly, cultivars released after 2000 indicated an increase in the number of roots, depth, diameter, surface area, and steep angle frequency. The coefficient of correlation analysis showed a positive correlation between root depth and yield-related traits under water-limited conditions. We also investigated the effects of green-revolution genes (Rht1) and some phenology-related genes such as DRO1, TaMOR, TaLTPs, TaSus-2B on RSA and identified significant associations of these genes with important root traits. There was strong selection pressure on DRO1 gene in cultivated wheat indicating the allele fixed in modern wheat cultivars is different from landraces. The expression of DRO1, and TaMOR were retrieved from an RNAseq experiment, and results were validated using qRT-PCR. The highest expression of DRO1 and TaMOR was found in Chakwal-50, a rainfed cultivar released in 2008, and MaxiPak-65 released in 1965. We conclude that there is a positive historic change in RSA after 1965 that might be attributed to genetic factors associated with favored RSA traits. Furthermore, we suggest root depth and steep angle as promising traits to withstand water-limited environments and may have implications in selection for breeding. [ABSTRACT FROM AUTHOR]

Crop wild resources are excellent sources of new genetic variation for resilience against climate extremes. However, detailed characterization of the desirable phenotypes is essential before using these crop wild resources in breeding programs. This current study was, therefore, conducted to investigate the water stress responses of eight wild Elymus species and two wheat cultivars. The experiment was carried out under varying levels of osmotic stress induced by polyethylene glycol and progressive water stress through different field capacities. Water stress significantly reduced both physiological and biochemical traits compared to control, ranging from7.1% (protein content) to 34.5% (chlorophyll) under moderate stress and 9.1-45.8% under severe stress. The anatomical features were also affected under progressive water stress, including a reduction in xylem vessel diameter (7.92 and 16.50%), phloem length (4.36 and 7.18%), vascular bundle length (3.09 and 6.04%), and ground tissue thickness (2.36 and 5.52%), respectively. Conclusively, Elymus borianus (endemic to Swat, Pakistan), E. russelli, E. caninus, E. longioristatus, and E. dauhuricus outperformed the check wheat cultivar, Pirsabak 2005, which is a rainfed variety. The results revealed that Elymus species belonging to the tertiary gene pool of bread wheat could be an excellent drought tolerance source for use in a breeding program. [ABSTRACT FROM AUTHOR]

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-7DL were identified based on MSN, ISN and VSN data, while QSnyz.caas-7DS was 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. [ABSTRACT FROM AUTHOR]

Increasing global temperature has adverse effects on crop health and productivity at both seedling and reproductivity stages. It is paramount to develop heat tolerant wheat cultivars able to sustain under high and fluctuating temperature conditions. An experiment was conducted to characterize 194 historical wheat cultivars of Pakistan under high temperature at seedling stage to identify loci associated with heat tolerance using genome-wide association studies (GWAS). A quantitative trait locus, TaHST1, on chr4A was also characterized to identify the haplotypes at this locus associated with heat tolerance in wheat from Pakistan. Initially, the diversity panel was planted under control conditions (25°C/20°C day and night temperature) in a glass house. At three leaf stage, plants were subjected to heat stress (HS) by increasing temperature (40°C/35°C day and night), while one treatment was kept at control condition. After 7days of HS, data were collected for seedling morphology. Heat stress reduced these traits by 25% (root weight) to 40% (shoot weight), and shoot biomass was largely affected by heat stress. A GWAS model, fixed and random model circulating probability unification (FarmCPU), identified 43 quantitative trait nucleotides (QTNs) on all chromosomes, except chr7B, were associated under both HS and control conditions. Thirteen QTNs were identified in control, while 30 QTNs were identified in HS condition. In total, 24 haplotypes were identified at TaHST1 locus, and most of the heat tolerant genotypes were assigned to Hap-20 and Hap-21. Eleven QTNs were identified within 0.3-3.1Mb proximity of heat shock protein (HSP). Conclusively, this study provided a detailed genetic framework of heat tolerance in wheat at the seedling stage and identify potential genetic regions associated with heat tolerance which can be used for marker assisted selection (MAS) in breeding for heat stress tolerance. [ABSTRACT FROM AUTHOR]

Key Message: A genetic framework underpinning salinity tolerance at reproductive stage was revealed by genome-wide SNP markers and major adaptability genes in synthetic-derived wheats, and trait-associated loci were used to predict phenotypes. Using wild relatives of crops to identify genes related to improved productivity and resilience to climate extremes is a prioritized area of crop genetic improvement. High salinity is a widespread crop production constraint, and development of salt-tolerant cultivars is a sustainable solution. We evaluated a panel of 294 wheat accessions comprising synthetic-derived wheat lines (SYN-DERs) and modern bread wheat advanced lines under control and high salinity conditions at two locations. The GWAS analysis revealed a quantitative genetic framework of more than 200 loci with minor effect underlying salinity tolerance at reproductive stage. The significant trait-associated SNPs were used to predict phenotypes using a GBLUP model, and the prediction accuracy (r2) ranged between 0.57 and 0.74. The r2 values for flag leaf weight, days to flowering, biomass, and number of spikes per plant were all above 0.70, validating the phenotypic effects of the loci discovered in this study. Furthermore, the germplasm sets were compared to identify selection sweeps associated with salt tolerance loci in SYN-DERs. Six loci associated with salinity tolerance were found to be differentially selected in the SYN-DERs (12.4 Mb on chromosome (chr)1B, 7.1 Mb on chr2A, 11.2 Mb on chr2D, 200 Mb on chr3D, 600 Mb on chr6B, and 700.9 Mb on chr7B). A total of 228 reported markers and genes, including 17 well-characterized genes, were uncovered using GWAS and EigenGWAS. A linkage disequilibrium (LD) block on chr5A, including the Vrn-A1 gene at 575 Mb and its homeologs on chr5D, were strongly associated with multiple yield-related traits and flowering time under salinity stress conditions. The diversity panel was screened with more than 68 kompetitive allele-specific PCR (KASP) markers of functional genes in wheat, and the pleiotropic effects of superior alleles of Rht-1, TaGASR-A1, and TaCwi-A1 were revealed under salinity stress. To effectively utilize the extensive genetic information obtained from the GWAS analysis, a genetic interaction network was constructed to reveal correlations among the investigated traits. The genetic network data combined with GWAS, selective sweeps, and the functional gene survey provided a quantitative genetic framework for identifying differentially retained loci associated with salinity tolerance in wheat. [ABSTRACT FROM AUTHOR]

Root hairs play an important role in absorbing water and nutrients in crop plants. Here we optimized high-throughput root hair length (RHL) and root hair density (RHD) phenotyping in wheat using a portable Dinolite™ microscope. A collection of 24 century wide spring wheat cultivars released between 1911 and 2016 were phenotyped for RHL and RHD. The results revealed significant variations for both traits with five and six-fold variation for RHL and RHD, respectively. RHL ranged from 1.01 mm to 1.77 mm with an average of 1.39 mm, and RHD ranged from 17.08 mm−2 to 20.8 mm−2 with an average of 19.6 mm−2. Agronomic and physiological traits collected from five different environments and their best linear unbiased predictions (BLUPs) were correlated with RHL and RHD, and results revealed that relative-water contents (RWC), biomass and grain per spike (GpS) were positively correlated with RHL in both water-limited and well-watered conditions. While RHD was negatively correlated with grain yield (GY) in four environments and their BLUPs. Both RHL and RHD had positive correlation indicating the possibility of simultaneous selection of both phenotypes during wheat breeding. The expression pattern of TaRSL4 gene involved in regulation of root hair length was determined in all 24 wheat cultivars based on RNA-seq data, which indicated the differentially higher expression of the A- and D- homeologues of the gene in roots, while B-homeologue was consistently expressed in both leaf and roots. The results were validated by qRT-PCR and the expression of TaRSL4 was consistently high in rainfed cultivars such as Chakwal-50, Rawal-87, and Margallah-99. Overall, the new phenotyping method for RHL and RHD along with correlations with morphological and physiological traits in spring wheat cultivars improved our understanding for selection of these phenotypes in wheat breeding. [ABSTRACT FROM AUTHOR]

Grain yield (GY) prediction for wheat based on canopy spectral reflectance can improve selection efficiency in breeding programs. Time-series spectral information from different growth stages such as flowering to maturity is considered to have high accuracy in predicting GY and combining this information from multiple growth stages could effectively improve prediction accuracy. For this, 207 wheat cultivars and breeding lines were grown in full and limited irrigation treatments, and their canopy spectral reflectance was measured at the flowering, early, middle, and late grain fill stages. The potential of temporal spectral information at multiple growth stages for GY prediction was evaluated by a new method based on stacking the multiple growth stages data. Twenty VIs derived from spectral reflectance were used as the input feature of a support vector regression (SVR) to predict GY at each growth stage. The predicted GY values at multiple growth stages were trained by multiple linear regression (MLR) to establish a second-level prediction model. Results suggested that the prediction accuracy (R2) of VIs data from single growth stages ranged from 0.60 to 0.66 and 0.35 to 0.42 in the full and limited irrigation treatments, respectively. The prediction accuracy was increased by an average of 0.06, 0.07, and 0.07 after stacking the VIs of two, three, and four growth stages, respectively, under full irrigation. Similarly, under limited irrigation, the prediction accuracy was increased by 0.03, 0.04, and 0.04 by stacking the VIs of two, three, and four growth stages, respectively. Stacking of VIs of multiple important growth stages can increase the accuracy of GY prediction and application of a stable stacking model could increase the usefulness of data obtained from different phenotyping platforms. [ABSTRACT FROM AUTHOR]

Increasing global temperature has adverse effects on crop health and productivity at both seedling and reproductivity stages. It is paramount to develop heat tolerant wheat cultivars able to sustain under high and fluctuating temperature conditions. An experiment was conducted to characterize 194 historical wheat cultivars of Pakistan under high temperature at seedling stage to identify loci associated with heat tolerance using genome-wide association studies (GWAS). A quantitative trait locus, TaHST1, on chr4A was also characterized to identify the haplotypes at this locus associated with heat tolerance in wheat from Pakistan. Initially, the diversity panel was planted under control conditions (25°C/20°C day and night temperature) in a glass house. At three leaf stage, plants were subjected to heat stress (HS) by increasing temperature (40°C/35°C day and night), while one treatment was kept at control condition. After 7days of HS, data were collected for seedling morphology. Heat stress reduced these traits by 25% (root weight) to 40% (shoot weight), and shoot biomass was largely affected by heat stress. A GWAS model, fixed and random model circulating probability unification (FarmCPU), identified 43 quantitative trait nucleotides (QTNs) on all chromosomes, except chr7B, were associated under both HS and control conditions. Thirteen QTNs were identified in control, while 30 QTNs were identified in HS condition. In total, 24 haplotypes were identified at TaHST1 locus, and most of the heat tolerant genotypes were assigned to Hap-20 and Hap-21. Eleven QTNs were identified within 0.3-3.1Mb proximity of heat shock protein (HSP). Conclusively, this study provided a detailed genetic framework of heat tolerance in wheat at the seedling stage and identify potential genetic regions associated with heat tolerance which can be used for marker assisted selection (MAS) in breeding for heat stress tolerance. [ABSTRACT FROM AUTHOR]

Synthetic hexaploid wheats and their derived advanced lines were subject to empirical selection in developing genetically superior cultivars. To investigate genetic diversity, patterns of nucleotide diversity, population structure, and selection signatures during wheat breeding, we tested 422 wheat accessions, including 145 synthetic-derived wheats, 128 spring wheat cultivars, and 149 advanced breeding lines from Pakistan. A total of 18,589 high-quality GBS-SNPs were identified that were distributed across the A (40%), B (49%), and D (11%) genomes. Values of population diversity parameters were estimated across chromosomes and genomes. Genome-wide average values of genetic diversity and polymorphic information content were estimated to be 0.30 and 0.25, respectively. Neighbor-joining (NJ) tree, principal component analysis (PCA), and kinship analyses revealed that synthetic-derived wheats and advanced breeding lines were genetically diverse. The 422 accessions were not separated into distinct groups by NJ analysis and confirmed using the PCA. This conclusion was validated with both relative kinship and Rogers' genetic distance analyses. EigenGWAS analysis revealed that 32 unique genome regions had undergone selection. We found that 50% of the selected regions were located in the B-genome, 29% in the D-genome, and 21% in the A-genome. Previously known functional genes or QTL were found within the selection regions associated with phenology-related traits such as vernalization, adaptability, disease resistance, and yield-related traits. The selection signatures identified in the present investigation will be useful for understanding the targets of modern wheat breeding in Pakistan. [ABSTRACT FROM AUTHOR]

SUMMARY: Roots are essential multifunctional plant organs involved in water and nutrient uptake, metabolite storage, anchorage, mechanical support, and interaction with the soil environment. Understanding of this 'hidden half' provides potential for manipulation of root system architecture (RSA) traits to optimize resource use efficiency and grain yield in cereal crops. Unfortunately, root traits are highly neglected in breeding due to the challenges of phenotyping, but could have large rewards if the variability in RSA traits can be fully exploited. Until now, a plethora of genes have been characterized in detail for their potential role in improving RSA. The use of forward genetics approaches to find sequence variations in genes underpinning desirable RSA would be highly beneficial. Advances in computer vision applications have allowed image‐based approaches for high‐throughput phenotyping of RSA traits that can be used by any laboratory worldwide to make progress in understanding root function and dissection of the genetics. At the same time, the frontiers of root measurement include non‐invasive methods like X‐ray computer tomography and magnetic resonance imaging that facilitate new types of temporal studies. Root physiology and ecology are further supported by spatiotemporal root simulation modeling. The discovery of component traits providing improved resilience and yield advantage in target environments is a key necessity for mainstreaming root‐based cereal breeding. The integrated use of pan‐genome resources, now available in most cereals, coupled with new in‐field phenotyping platforms has the potential for precise selection of superior genotypes with improved RSA. Significance Statement: We reviewed the current status of genetics underpinning root system architecture in cereals and presented a comprehensive genetic framework. We further provided a comparative analysis of the phenotyping methods, different root phenes and their interaction with the environment, and breeding applications. [ABSTRACT FROM AUTHOR]

Biofortification is a sustainable strategy to alleviate micronutrient deficiency in humans. It is necessary to improve grain zinc (GZnC) and iron concentrations (GFeC) in wheat based on genetic knowledge. However, the precise dissection of the genetic architecture underlying GZnC and GFeC remains challenging. In this study, high-resolution genome-wide association studies were conducted for GZnC and GFeC by three different models using 166 wheat cultivars and 373,106 polymorphic markers from the wheat 660K and 90K single nucleotide polymorphism (SNP) arrays. Totally, 25 and 16 stable loci were detected for GZnC and GFeC, respectively. Among them, 17 loci for GZnC and 8 for GFeC are likely to be new quantitative trait locus/loci (QTL). Based on gene annotations and expression profiles, 28 promising candidate genes were identified for Zn/Fe uptake (8), transport (11), storage (3), and regulations (6). Of them, 11 genes were putative wheat orthologs of known Arabidopsis and rice genes related to Zn/Fe homeostasis. A brief model, such as genes related to Zn/Fe homeostasis from root uptake, xylem transport to the final seed storage was proposed in wheat. Kompetitive allele-specific PCR (KASP) markers were successfully developed for two major QTL of GZnC on chromosome arms 3AL and 7AL, respectively, which were independent of thousand kernel weight and plant height. The 3AL QTL was further validated in a bi-parental population under multi-environments. A wheat multidrug and toxic compound extrusion (MATE) transporter TraesCS3A01G499300 , the ortholog of rice gene OsPEZ2 , was identified as a potential candidate gene. This study has advanced our knowledge of the genetic basis underlying GZnC and GFeC in wheat and provides valuable markers and candidate genes for wheat biofortification. [ABSTRACT FROM AUTHOR]

Karnal bunt caused by Tilletia indica is a quarantine disease of wheat causing huge economic losses due to the ban on the import of bunted grains. This study was designed to characterize pathogenicity, aggressiveness and genetic diversity of 68 Tilletia indica isolates collected from different geographic regions of Pakistan. Forty-six isolates were tested for their pathogenicity on eight wheat varieties, out of which three were non-aggressive. The coefficient of infection (CI) ranged from 15.73% (PB-25) to 10% (PB-68, PB-60, and PB-43). The isolates collected from central Punjab showed higher infestation compared to other isolates. Among the wheat varieties used for the aggressiveness study, WL-711 showed susceptible reaction with 10.88% CI, while NIFA-Barsat, HD-29, Janbaz, Bakhtawar-92, Tatara, and AARI 2011 showed resistance to the highly resistant response. These isolates were amplified using 31 random amplified polymorphic DNA (RAPD) markers and 32 inter-simple sequence repeat (ISSR) markers for diversity analysis. The principal component analysis (PCA) and analysis of molecular variance (AMOVA) showed greater divergence among isolates collected from Punjab and Khyber Pakhtunkhwa (KPK), with a moderate level of admixture. The isolates from Faisalabad (Punjab) were more aggressive compared to isolates from KPK and were clearly separated based on PCA, indicating the significant genetic distance in the populations. Our findings will assist breeders and pathologists in better understanding the pathogenic variability in Tilletia indica and in subsequent disease management. [ABSTRACT FROM AUTHOR]

Stripe rust caused by Puccnina striiformis (Pst) is an economically important disease attacking wheat all over the world. Identifying and deploying new genes for Pst resistance is an economical and long-term strategy for controlling Pst. A genome-wide association study (GWAS) using single nucleotide polymorphisms (SNPs) and functional haplotypes were used to identify loci associated with stripe rust resistance in synthetic-derived (SYN-DER) wheats in four environments. In total, 92 quantitative trait nucleotides (QTNs) distributed over 65 different loci were associated with resistance to Pst at seedling and adult plant stages. Nine additional loci were discovered by the linkage disequilibrium-based haplotype-GWAS approach. The durable rust-resistant gene Lr34/Yr18 provided resistance in all four environments, and against all the five Pst races used in this study. The analysis identified several SYN-DER accessions that carried major genes: either Yr24/Yr26 or Yr32. New loci were also identified on chr2B, chr5B, and chr7D, and 14 QTNs and three haplotypes identified on the D-genome possibly carry new alleles of the known genes contributed by the Ae. tauschii founders. We also evaluated eleven different models for genomic prediction of Pst resistance, and a prediction accuracy up to 0.85 was achieved for an adult plant resistance, however, genomic prediction for seedling resistance remained very low. A meta-analysis based on a large number of existing GWAS would enhance the identification of new genes and loci for stripe rust resistance in wheat. The genetic framework elucidated here for stripe rust resistance in SYN-DER identified the novel loci for resistance to Pst assembled in adapted genetic backgrounds. [ABSTRACT FROM AUTHOR]

Background: The COBL genes encode a plant-specific glycosylphosphatidylinositol (GPI)-anchored protein. Recently identified COBRA genes are supposed as a key regulator of the orientation of cell expansion in the root indicating that COBRA gene family members are likely to be important players at the plasma membrane-cell wall interface. Methods and results: Five COBL gene namely, TaCOBL 1, TaCOBL 2, TaCOBL 3, TaCOBL 4 and TaCOBL 5 were identified using database search and domain predictions. Chromosomal location of each gene was mapped on karyotype. Structure of genes, promoter analysis and phylogenetic analysis were performed using different bioinformatics tools. Set of novel SNPs were also predicted. Gene ontologies were analyzed, and the processes and pathways were identified in which COBRA genes were involved. The molecular weight all the cobra proteins was in range of 50–75 KDa with 429–461 amino acid residues. The COBL genes were mapped on homeologous groups 2, 4, 5, 6 and 7. Gene ontology analysis revealed that TaCOBL genes were involved in cellulose microfibril organization, mucilage biosynthetic process involved in seed coat development, plant-type cell wall biogenesis plant-type cell wall cellulose biosynthetic process, seed coat development and seed development. Three drought responsive cis-elements (WRKY, ABRE and DRE) were found nearby COBL genes The qRT-PCR revealed TaCOBL genes are drought responsive and can be further explored to understand their role in drought tolerance in wheat. Conclusion: The comprehensive annotation and expression profiling of COBL genes revealed that all five COBL genes are drought response. The promoter cis-regulatory element analysis revealed that COBL genes had stress related WRKY, ABRE and DRE cis-regulatory elements. This evidence suggest that TaCOBL genes are involved in drought stress tolerance. [ABSTRACT FROM AUTHOR]

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 aestivum L.) 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−1 yr−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/Pm46 in obsolete cultivars as early as 1911, whereas the photoperiod‐insensitive allele Ppd‐D1a and reduced height alleles Rht‐B1b and Rht‐D1b were 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. Core Ideas: 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. [ABSTRACT FROM AUTHOR]

Tajikistan is rich in genetic resources and one of a few countries where farmers still grow wheat (Triticum spp) 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. Core Ideas: 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. [ABSTRACT FROM AUTHOR]

Popcorn (Zea mays L. var. Everta) is the most ancient type of cultivated maize. However, there is little known about the genetics of popping-related traits based on genotyping-by-sequencing (GBS) technology. Here, we characterized the phenotypic variation for seven popping-related traits in maize kernels among 526 CIMMYT inbred lines (CMLs). In total, 155 083 high-quality single nucleotide polymorphism (SNP) markers were identified by a GBS approach. Several trait-associated loci were detected by genome-wide association study for color, popping expansion volume, shape, pericarp, flotation index, floury/vitreous, and protein content, explaining a majority of the observed phenotypic variance, and these were validated by a diverse panel comprising 764 tropical landrace accessions. Sixty two of the identified loci were recognized to have undergone selection. On average, there was a 55.27% frequency for alleles that promote popping in CMLs. Our work not only pinpoints previously unknown loci for popping-related traits, but also reveals that many of these loci have undergone selection. Beyond establishing a new benchmark for the genetics of popcorn, our study provides a foundation for gene discovery and breeding. It also presents evidence to investigate the role of a gradual loss of popping ability as a by-product of diversification of culinary uses throughout the evolution of teosinte–to–modern maize. [ABSTRACT FROM AUTHOR]

Kazakhstan-Siberia Network for Spring Wheat Improvement (KASIB) was established in 2000 to conduct multi-location cooperative yield trials for the exchange of breeding material and to evaluate agronomic traits such as grain yield and disease resistance. In 2016, aggregated KASIB data were analyzed and 120 cultivars and breeding lines demonstrating different degrees of resistance to leaf rust selected. They were tested for leaf rust and agronomic traits in Omsk, Russia; Almaty, Kazakhstan and Sakarya, Turkey in 2017–2019. This germplasm was grouped into four categories based on leaf rust reaction: 31 resistant (R), 27 moderately resistant (MR), 37 intermediate (M) and 25 moderately susceptible (MS) entries. Lr genes were postulated based on tests using pathotypes with known virulence profiles and molecular markers. The most frequent Lr genes alone or in combination were Lr10 (31 entries), Lr26 (24), Lr9 (23), Lr1 (18), Lr17 (11), Lr34 (11) and Lr19 (7). Genes Lr1, Lr9, Lr10 and Lr17 reduced the leaf rust severity to M or MS across environments. The presence of Lr26 alone or in combination with other major genes reduced the leaf rust severity to MR-M in Omsk and R in Sakarya. The only gene with the large effect on leaf rust was Lr19, which provided a high level of resistance at all sites both alone and in combination with Lr26. Leaf rust severity in 52 entries with adult plant resistance (APR) was compared to 68 entries possessing effective seedling resistance genes. The leaf rust severity in entries with APR compared to seedling resistance was similar at low infection pressure at Sakarya, 2018 and Omsk, 2019. However, at higher leaf rust infection pressure at Omsk in 2017 and 2018, Almaty in 2019, there was a clear advantage for the germplasm possessing major genes. High level of stem rust infection in Omsk in 2019 confirmed effectiveness of the Sr31/Lr26 gene. A set of 33 genotypes was selected combining resistance to leaf and stem rust with superior agronomic performance. [ABSTRACT FROM AUTHOR]

Key message: GWAS identified 36 potentially new loci for wheat stem water-soluble carbohydrate (WSC) contents and 13 pleiotropic loci affecting WSC and thousand-kernel weight. Five KASP markers were developed and validated. Water-soluble carbohydrates (WSC) reserved in stems contribute significantly to grain yield (GY) in wheat. However, knowledge of the genetic architecture underlying stem WSC content (SWSCC) is limited. In the present study, 166 diverse wheat accessions from the Yellow and Huai Valleys Winter Wheat Zone of China and five other countries were grown in four well-watered environments. SWSCC at 10 days post-anthesis (10DPA), 20DPA and 30DPA, referred as WSC10, WSC20 and WSC30, respectively, and thousand-kernel weight (TKW) were assessed. Correlation analysis showed that TKW was significantly and positively correlated with WSC10 and WSC20. Genome-wide association study was performed on SWSCC and TKW with 373,106 markers from the wheat 660 K and 90 K SNP arrays. Totally, 62 stable loci were detected for SWSCC, with 36, 24 and 19 loci for WSC10, WSC20 and WSC30, respectively; among these, 36 are potentially new, 16 affected SWSCC at two or three time-points, and 13 showed pleiotropic effects on both SWSCC and TKW. Linear regression showed clear cumulative effects of favorable alleles for increasing SWSCC and TKW. Genetic gain analyses indicated that pyramiding favorable alleles of SWSCC had simultaneously improved TKW. Kompetitive allele-specific PCR markers for five pleiotropic loci associated with both SWSCC and TKW were developed and validated. This study provided a genome-wide landscape of the genetic architecture of SWSCC, gave a perspective for understanding the relationship between WSC and GY and explored the theoretical basis for co-improvement of WSC and GY. It also provided valuable loci and markers for future breeding. [ABSTRACT FROM AUTHOR]

Unmanned aerial vehicle (UAV) based remote sensing is a promising approach for non-destructive and high-throughput assessment of crop water and nitrogen (N) efficiencies. In this study, UAV was used to evaluate two field trials using four water (T0 = 0 mm, T1 = 80 mm, T2 = 120 mm, and T3 = 160 mm), and four N (T0 = 0, T1 = 120 kg ha–1, T2 = 180 kg ha–1, and T3 = 240 kg ha–1) treatments, respectively, conducted on three wheat genotypes at two locations. Ground-based destructive data of water and N indictors such as biomass and N contents were also measured to validate the aerial surveillance results. Multispectral traits including red normalized difference vegetation index (RNDVI), green normalized difference vegetation index (GNDVI), normalized difference red-edge index (NDRE), red-edge chlorophyll index (RECI) and normalized green red difference index (NGRDI) were recorded using UAV as reliable replacement of destructive measurements by showing high r values up to 0.90. NGRDI was identified as the most efficient non-destructive indicator through strong prediction values ranged from R 2 = 0.69 to 0.89 for water use efficiencies (WUE) calculated from biomass (WUE.BM), and R 2 = 0.80 to 0.86 from grain yield (WUE.GY). RNDVI was better in predicting the phenotypic variations for N use efficiency calculated from nitrogen contents of plant samples (NUE.NC) with high R 2 values ranging from 0.72 to 0.94, while NDRE was consistent in predicting both NUE.NC and NUE.GY by 0.73 to 0.84 with low root mean square errors. UAV-based remote sensing demonstrates that treatment T2 in both water 120 mm and N 180 kg ha–1 supply trials was most appropriate dosages for optimum uptake of water and N with high GY. Among three cultivars, Zhongmai 895 was highly efficient in WUE and NUE across the water and N treatments. Conclusively, UAV can be used to predict time-series WUE and NUE across the season for selection of elite genotypes, and to monitor crop efficiency under varying N and water dosages. [ABSTRACT FROM AUTHOR]

Key message: We discussed the most recent efforts in wheat functional genomics to discover new genes and their deployment in breeding with special emphasis on advances in Asian countries. Wheat research community is making significant progress to bridge genotype-to-phenotype gap and then applying this knowledge in genetic improvement. The advances in genomics and phenomics have intrigued wheat researchers in Asia to make best use of this knowledge in gene and trait discovery. These advancements include, but not limited to, map-based gene cloning, translational genomics, gene mapping, association genetics, gene editing and genomic selection. We reviewed more than 57 homeologous genes discovered underpinning important traits and multiple strategies used for their discovery. Further, the complementary advancements in wheat phenomics and analytical approaches to understand the genetics of wheat adaptability, resilience to climate extremes and resistance to pest and diseases were discussed. The challenge to build a gold standard reference genome sequence of bread wheat is now achieved and several de novo reference sequences from the cultivars representing different gene pools will be available soon. New pan-genome sequencing resources of wheat will strengthen the foundation required for accelerated gene discovery and provide more opportunities to practice the knowledge-based breeding. [ABSTRACT FROM AUTHOR]

Fusarium head blight (FHB) is a devastating wheat disease worldwide. To decipher the genetic architecture of FHB resistance in Chinese germplasm, a Wheat Association Panel for Scab Research (WAPS) consisting of 240 leading Chinese wheat cultivars and elite lines was genotyped using the 90K single nucleotide polymorphism (SNP) arrays. The FHB response was evaluated in the field nurseries in Wuhan in Hubei Province over four consecutive years from 2014 to 2017. Five quantitative trait loci (QTL) were consistently identified on chromosome arms 1AS, 2DL, 5AS, 5AL, and 7DS using a mixed linear model (MLM), explaining 5.6, 10.3, 5.7, 5.4, and 5.6% of phenotypic variation, respectively. The QTL on 5AS, 5AL, and 7DS QTL are probably novel. The allelic frequency analysis indicated that cultivars from the Middle and Lower Yangtze River Valleys harbored more favorable alleles and were therefore more resistant than those from other regions. To facilitate in-house germplasm screening and marker-assisted selection (MAS), SNP-derived PCR markers were developed for the QTL regions on 1AS, 5AS, and 5AL QTL. In addition to the above five QTL, the WAPS population had a very low frequency of Fhb1, confirming that the gene is not widely used in Chinese wheat breeding programs. The resistant lines and molecular markers developed in this study are resources and information for enhancing FHB resistance in breeding populations by marker-assisted recurrent selection and gene stacking. [ABSTRACT FROM AUTHOR]

Key message: Genetic diversity, population structure, LD decay, and selective sweeps in 687 wheat accessions were analyzed, providing relevant guidelines to facilitate the use of the germplasm in wheat breeding. Common wheat (Triticum aestivum L.) is one of the most widely grown crops in the world. Landraces were subjected to strong human-mediated selection in developing high-yielding, good quality, and widely adapted cultivars. To investigate the genome-wide patterns of allelic variation, population structure and patterns of selective sweeps during modern wheat breeding, we tested 687 wheat accessions, including landraces (148) and cultivars (539) mainly from China and Pakistan in a wheat 90 K single nucleotide polymorphism array. Population structure analysis revealed that cultivars and landraces from China and Pakistan comprised three relatively independent genetic clusters. Cultivars displayed lower nucleotide diversity and a wider average LD decay across whole genome, indicating allelic erosion and a diversity bottleneck due to the modern breeding. Analysis of genetic differentiation between landraces and cultivars from China and Pakistan identified allelic variants subjected to selection during modern breeding. In total, 477 unique genome regions showed signatures of selection, where 109 were identified in both China and Pakistan germplasm. The majority of genomic regions were located in the B genome (225), followed by the A genome (175), and only 77 regions were located in the D genome. EigenGWAS was further used to identify key selection loci in modern wheat cultivars from China and Pakistan by comparing with global winter wheat and spring wheat diversity panels, respectively. A few known functional genes or loci found within these genome regions corresponded to known phenotypes for disease resistance, vernalization, quality, adaptability and yield-related traits. This study uncovered molecular footprints of modern wheat breeding and explained the genetic basis of polygenic adaptation in wheat. The results will be useful for understanding targets of modern wheat breeding, and in devising future breeding strategies to target beneficial alleles currently not pursued. [ABSTRACT FROM AUTHOR]

Understanding the genomic basis of adaptation in maize is important for gene discovery and the improvement of breeding germplasm, but much remains a mystery in spite of significant population genetics and archaeological research. Identifying the signals underpinning adaptation are challenging as adaptation often coincided with genetic drift, and the base genomic diversity of the species in massive. In this study, tGBS technology was used to genotype 1,143 diverse maize accessions including landraces collected from 20 countries and elite breeding lines of tropical lowland, highland, subtropical/midaltitude and temperate ecological zones. Based on 355,442 high‐quality single nucleotide polymorphisms, 13 genomic regions were detected as being under selection using the bottom‐up searching strategy, EigenGWAS. Of the 13 selection regions, 10 were first reported, two were associated with environmental parameters via EnvGWAS, and 146 genes were enriched. Combining large‐scale genomic and ecological data in this diverse maize panel, our study supports a polygenic adaptation model of maize and offers a framework to enhance our understanding of both the mechanistic basis and the evolutionary consequences of maize domestication and adaptation. The regions identified here are promising candidates for further, targeted exploration to identify beneficial alleles and haplotypes for deployment in maize breeding. [ABSTRACT FROM AUTHOR]

Modern breeding imposed selection for improved productivity that largely influenced the frequency of superior alleles underpinning traits of breeding interest. Therefore, molecular diagnosis for the allelic variations of such genes is important to manipulate beneficial alleles in wheat molecular breeding. We analyzed a diversity panel largely consisted of advanced lines derived from synthetic hexaploid wheats for allelic variation at 87 functional genes or loci of breeding importance using 124 high-throughput KASP markers. We also developed two KASP markers for water-soluble carbohydrate genes (TaSST-D1 and TaSST-A1) associated with plant height and thousand grain weight (TGW) in the diversity panel. KASP genotyping results indicated that beneficial alleles for genes underpinning flowering time (Ppd-D1 and Vrn-D3), thousand grain weight (TaCKX-D1, TaTGW6-A1, TaSus1-7B , and TaCwi-D1), water-soluble carbohydrates (TaSST-A1), yellow-pigment content (Psy-B1 and Zds-D1), and root lesion nematodes (Rlnn1) were fixed in diversity panel with frequency ranged from 96.4 to 100%. The association analysis of functional genes with agronomic and biochemical traits under well-watered (WW) and water-limited (WL) conditions revealed that 21 marker-trait associations (MTAs) were consistently detected in both moisture conditions. The major developmental genes such as Vrn-A1, Rht-D1 , and Ppd-B1 had the confounding effect on several agronomic traits including plant height, grain size and weight, and grain yield in both WW and WL conditions. The accumulation of favorable alleles for grain size and weight genes additively enhanced grain weight in the diversity panel. Graphical genotyping approach was used to identify accessions with maximum number of favorable alleles, thus likely to have high breeding value. These results improved our knowledge on the selection of favorable and unfavorable alleles through unconscious selection breeding and identified the opportunities to deploy alleles with effects in wheat breeding. [ABSTRACT FROM AUTHOR]

Key message: Recent technological advances in wheat genomics provide new opportunities to uncover genetic variation in traits of breeding interest and enable genome-based breeding to deliver wheat cultivars for the projected food requirements for 2050. There has been tremendous progress in development of whole-genome sequencing resources in wheat and its progenitor species during the last 5 years. High-throughput genotyping is now possible in wheat not only for routine gene introgression but also for high-density genome-wide genotyping. This is a major transition phase to enable genome-based breeding to achieve progressive genetic gains to parallel to projected wheat production demands. These advances have intrigued wheat researchers to practice less pursued analytical approaches which were not practiced due to the short history of genome sequence availability. Such approaches have been successful in gene discovery and breeding applications in other crops and animals for which genome sequences have been available for much longer. These strategies include, (i) environmental genome-wide association studies in wheat genetic resources stored in genbanks to identify genes for local adaptation by using agroclimatic traits as phenotypes, (ii) haplotype-based analyses to improve the statistical power and resolution of genomic selection and gene mapping experiments, (iii) new breeding strategies for genome-based prediction of heterosis patterns in wheat, and (iv) ultimate use of genomics information to develop more efficient and robust genome-wide genotyping platforms to precisely predict higher yield potential and stability with greater precision. Genome-based breeding has potential to achieve the ultimate objective of ensuring sustainable wheat production through developing high yielding, climate-resilient wheat cultivars with high nutritional quality. [ABSTRACT FROM AUTHOR]

Drought stress ‘particularly at seedling stage’ causes morpho-physiological differences in wheat which are crucial for its survival and adaptability. In the present study, 209 recombinant inbred lines (RILs) from synthetic wheat (W7984)× ‘Opata’ (also known as SynOpRIL) population were investigated under well-watered and water-limited conditions to identify quantitative trait loci (QTL) for morphological traits at seedling stage. Analysis of variance revealed significant differences (P < 0.01) among RILs, and water treatments for all traits with moderate to high broad sense heritability. Pearson's coefficient of correlation revealed positive correlation among all traits except dry root weight that showed poor correlation with fresh shoot weight (FSW) under water-limited conditions. A high-density linkage map was constructed with 2639 genotyping-by-sequencing markers and covering 5047 cM with an average marker density of 2 markers/cM. Composite interval mapping identified 16 QTL distributed over nine chromosomes, of which six were identified under well-watered and 10 in water-limited conditions. These QTL explained from 4 to 59% of the phenotypic variance. Six QTL were identified on chromosome 7B; three for shoot length under water-limited conditions (QSL.nust-7B) at 64, 104 and 221 cM, two for fresh root weight (QFRW.nust-7B) at 124 and 128 cM, and one for root length (QRL.nust-7B) at 122 cM positions. QFSW.nust-7B appeared to be the most significant QTL explaining 59% of the phenotypic variance and also associated with FSW at well-watered conditions. These QTL could serve as target regions for candidate gene discovery and marker-assisted selection in wheat breeding. [ABSTRACT FROM AUTHOR]

Background: Wheat genetic resources have been used for genetic improvement since 1876, when Stephen Wilson (Transactions and Proceedings of the Botanical Society of Edinburgh 12: 286) consciously made the first wide hybrid involving wheat and rye in Scotland. Wide crossing continued with sporadic attempts in the first half of 19th century and became a sophisticated scientific discipline during the last few decades with considerable impact in farmers' fields. However, a large diversity of untapped genetic resources could contribute in meeting future wheat production challenges. Perspectives and Conclusion: Recently the complete reference genome of hexaploid (Chinese Spring) and tetraploid (Triticum turgidum ssp. dicoccoides) wheat became publicly available coupled with on-going international efforts on wheat pan-genome sequencing. We anticipate that an objective appraisal is required in the post-genomics era to prioritize genetic resources for use in the improvement of wheat production if the goal of doubling yield by 2050 is to be met. Advances in genomics have resulted in the development of high-throughput genotyping arrays, improved and efficient methods of gene discovery, genomics-assisted selection and gene editing using endonucleases. Likewise, ongoing advances in rapid generation turnover, improved phenotyping, envirotyping and analytical methods will significantly accelerate exploitation of exotic genes and increase the rate of genetic gain in breeding. We argue that the integration of these advances will significantly improve the precision and targeted identification of potentially useful variation in the wild relatives of wheat, providing new opportunities to contribute to yield and quality improvement, tolerance to abiotic stresses, resistance to emerging biotic stresses and resilience to weather extremes. [ABSTRACT FROM AUTHOR]

Background and aims: Chromium (Cr) toxicity is a rapidly increasing environmental concern and poses a major threat to plant growth as well as food chain. This study was carried out to screen spring wheat diversity panel against Cr toxicity to assess yield reduction, grain contamination extents and genomic regions associated with tolerance to Cr toxicity.Methods: The diversity panel was planted in control and Cr stress (26 mg Cr/kg soil) in paved plots, and several morphological and physiological traits were recorded. Wheat 90 K Infinium iSelect SNP array was used to identify genomic regions underpinning tolerance to Cr toxicity.Results: Some wheat cultivars (Khosar-95, Miraj-08, Millet-11, Sarsabaz and NARC-11) had Cr concentration within international edible threshold limit (1 ppm), but showed greater reduction to grain yield (63–95%) due to higher leaf Cr concentrations (2.35–8.95 ppm). Contrastingly, wheat cultivars Auqab-00 and Pakistan-13 had lower yield reduction up to 9% and 39%, respectively but had higher concentration of Cr in seeds (2.1 and 3.5 ppm, respectively). Genome-wide association studies identified 71 loci linked with yield related traits under Cr stress and 48 loci for differences between control and Cr stress treatments. Further, gene ontology of trait-associated SNPs revealed proteins with significant importance in plant development and tolerance against heavy metal stress.Conclusion: To our knowledge, this is the first study for identification of genomic regions linked to Cr stress, suggesting that this could be useful to identify complex architecture of genetic factors as well as molecular breeding opportunities for tolerance to Cr stress. [ABSTRACT FROM AUTHOR]