Genome-wide association study and genetic diversity analysis on nitrogen use efficiency in a Central European winter wheat (Triticum aestivum L.) collection

Nitrogen fertilizer application rate affects the dynamic metabolism of nitrogen and carbohydrates in kernels of waxy maize

Introduction

Nitrogen (N) plays a pivotal role in the growth, development, and yield of maize. An optimal N application rate is crucial for enhancing N and carbohydrate (C) accumulation in waxy maize grains, which in turn synergistically improves grain weight.

Methods

A 2-year field experiment was conducted to evaluate the impact of different N application rates on two waxy maize varieties, Jinnuo20 (JN20) and Jindannuo41 (JDN41), during various grain filling stages. The applied N rates were 0 (N0), 120 (N1), 240 (N2), and 360 (N3) kg N ha-1.

Results

The study revealed that N application significantly influenced nitrogen accumulation, protein components (gliadin, albumin, globulin, and glutelin), carbohydrate contents (soluble sugars, amylose, and amylopectin), and activities of enzymes related to N and C metabolism in waxy maize grains. Notable varietal differences in these parameters were observed. In both varieties, the N2 treatment consistently resulted in the highest values for almost all measured traits compared to the other N treatments. Specifically, the N2 treatment yielded an average increase in grain dry matter of 21.78% for JN20 and 17.11% for JDN41 compared to N0. The application of N positively influenced the activities of enzymes involved in C and N metabolism, enhancing the biosynthesis of grain protein, amylose, and amylopectin while decreasing the accumulation of soluble sugars. This modulation of the C/N ratio in the grains directly contributed to an increase in grain dry weight.

Conclusion

Collectively, our findings underscore the critical role of N in regulating kernel N and C metabolism, thereby influencing dry matter accumulation in waxy maize grains during the grain filling stage.

Nitrogen use efficiency in bread wheat: Genetic variation and prospects for improvement

Nitrogen (N) is one of the primary macronutrients required for crop growth and yield. This nutrient is especially limiting wheat yields in the dry and low fertile agro-ecologies having low N in the root zone soil strata. Moreover, majority of farmers in India and South Asia are small to marginal with meagre capacity to invest in costly nitrogen fertilizers. Therefore, there is an immense need to identify lines that use nitrogen efficiently. A set of 50 diverse wheat genotypes consisting of indigenous germplasm lines (05), cultivars released for commercial cultivation (23) and selected elite lines from CIMMYT nurseries (22) were evaluated in an alpha-lattice design with two replications, a six-rowed plot of 2.5m length for 24 agro morphological, physiological and NUE related traits during two consecutive crop seasons in an N-depleted precision field under two different N levels of 50%-N50 (T1) and 100%-N100 (T2) of recommended N, i.e., 100 kg/ha. Analysis of variance revealed significant genetic variation among genotypes for all the traits studied. About 11.36% yield reduction was observed at reduced N levels. Significant correlations among NUE traits and yield component traits were observed which indicated pivotal role of N remobilization to the grain in enhancing yield levels. Among N-insensitive genotypes identified based on their yielding ability at low N levels, UASBW13356, UASBW13358, UASBW13354, UASBW13357 and KRL1-4 showed their inherent genotypic plasticity toward N application. The genotypes with more yield and high to moderate NUtE can be used as parents for the breeding of N efficient genotypes for marginal agro-ecologies. Low N tolerant genotypes identified from the current investigation may be further utilized in the identification of genomic regions responsible for NUE and its deployment in wheat breeding programs. The comprehensive data of 24 traits under different nitrogen levels for diverse genotypes from India and global sources (mainly CIMMYT) should be useful for supporting breeding for NUE and thus will be of great help for small and marginal farmers in India and South Asia.

Genome-wide association studies identifies genetic loci related to fatty acid and branched-chain amino acid metabolism and histone modifications under varying nitrogen treatments in safflower (Carthamus tinctorius)

Effective identification and usage of genetic variation are prerequisites for developing nutrient-efficient cultivars. A collection of 94 safflower (Carthamus tinctorius ) genotypes (G) was investigated for important morphological and photosynthetic traits at four nitrogen (N) treatments. We found significant variation for all the studied traits except chlorophyll b (chl b ) among safflower genotypes, nitrogen treatments and G×N interaction. The examined traits showed a 2.82-50.00% increase in response to N application. Biological yield (BY) reflected a significantly positive correlation with fresh shoot weight (FSW), root length (RL), fresh root weight (FRW) and number of leaves (NOL), while a significantly positive correlation was also observed among carotenoids (C), chlorophyll a (chl a ), chl b and total chlorophyll content (CT) under all treatments. Superior genotypes with respect to plant height (PH), FSW, NOL, RL, FRW and BY were clustered into Group 3, while genotypes with better mean performance regarding chl a , chl b C and CT were clustered into Group 2 as observed in principal component analysis. The identified eight best-performing genotypes could be useful to develop improved nitrogen efficient cultivars. Genome-wide association analysis resulted in 32 marker-trait associations (MTAs) under four treatments. Markers namely DArT-45481731 , DArT-17812864 , DArT-15670279 and DArT-45482737 were found consistent. Protein-protein interaction networks of loci associated with MTAs were related to fatty acid and branched-chain amino acid metabolism and histone modifications.

Genetic diversity of grain yield traits and identification of a grain weight gene SiTGW6 in foxtail millet

KEY MESSAGE

Agronomic traits were evaluated in 1250 foxtail millet accessions, and a crucial gene SiTGW6 governing grain yield was identified. Elite haplotypes and dCAPS markers developed for SiTGW6 facilitate molecular breeding. A comprehensive evaluation of phenotypic characteristics and genetic diversity in germplasm resources are important for gene discovery and breeding improvements. In this study, we conducted a comprehensive evaluation of 1250 foxtail millet varieties, assessing seven grain yield-related traits and fourteen common agronomic traits over two years. Principal component analysis, correlation analysis, and cluster analysis revealed a strong positive correlation between 1000-grain weight and grain width with grain yield, emphasizing their importance in foxtail millet breeding. Additionally, we found that panicle weight positively correlated with 1000-grain weight but negatively correlated with branch and tiller numbers, indicating selection factors during domestication and breeding. Using this information, we identified 27 germplasm resources suitable for high-yield foxtail millet breeding. Furthermore, through an integration of haplotype variations and phenotype association analysis, we pinpointed a crucial gene, SiTGW6, responsible for governing grain yield in foxtail millet. SiTGW6 encodes an IAA-glucose hydrolase, primarily localized in the cytoplasm and predominantly expressed in flowering panicles. Employing RNAseq analysis, we identified 1439 differentially expressed genes across various SiTGW6 haplotypes. Functional enrichment analysis indicating that SiTGW6 regulates grain yield through the orchestration of auxin and glucan metabolism, as well as plant hormone signaling pathways. Additionally, we have identified elite haplotypes and developed dCAPS markers for SiTGW6, providing valuable technical tools to facilitate molecular breeding efforts in foxtail millet.

Genome-wide association study of agronomic traits related to nitrogen use efficiency in Henan wheat

BACKGROUND

Nitrogen use efficiency (NUE) is closely related to crop yield and nitrogen fertilizer application rate. Although NUE is susceptible to environments, quantitative trait nucleotides (QTNs) for NUE in wheat germplasm populations have been rarely reported in genome-wide associated study.

RESULTS

In this study, 244 wheat accessions were phenotyped by three NUE-related traits in three environments and genotyped by 203,224 SNPs. All the phenotypes for each trait were used to associate with all the genotypes of these SNP markers for identifying QTNs and QTN-by-environment interactions via 3VmrMLM. Among 279 QTNs and one QTN-by-environment interaction for low nitrogen tolerance, 33 were stably identified, especially, one large QTN (r2 > 10%), qPHR3A.2, was newly identified for plant height ratio in one environment and multi-environment joint analysis. Among 52 genes around qPHR3A.2, four genes (TraesCS3A01G101900, TraesCS3A01G102200, TraesCS3A01G104100, and TraesCS3A01G105400) were found to be differentially expressed in low-nitrogen-tolerant wheat genotypes, while TaCLH2 (TraesCS3A01G101900) was putatively involved in porphyrin metabolism in KEGG enrichment analyses.

CONCLUSIONS

This study identified valuable candidate gene for low-N-tolerant wheat breeding and provides new insights into the genetic basis of low N tolerance in wheat.

The Dissection of Nitrogen Response Traits Using Drone Phenotyping and Dynamic Phenotypic Analysis to Explore N Responsiveness and Associated Genetic Loci in Wheat

Inefficient nitrogen (N) utilization in agricultural production has led to many negative impacts such as excessive use of N fertilizers, redundant plant growth, greenhouse gases, long-lasting toxicity in ecosystem, and even effect on human health, indicating the importance to optimize N applications in cropping systems. Here, we present a multiseasonal study that focused on measuring phenotypic changes in wheat plants when they were responding to different N treatments under field conditions. Powered by drone-based aerial phenotyping and the AirMeasurer platform, we first quantified 6 N response-related traits as targets using plot-based morphological, spectral, and textural signals collected from 54 winter wheat varieties. Then, we developed dynamic phenotypic analysis using curve fitting to establish profile curves of the traits during the season, which enabled us to compute static phenotypes at key growth stages and dynamic phenotypes (i.e., phenotypic changes) during N response. After that, we combine 12 yield production and N-utilization indices manually measured to produce N efficiency comprehensive scores (NECS), based on which we classified the varieties into 4 N responsiveness (i.e., N-dependent yield increase) groups. The NECS ranking facilitated us to establish a tailored machine learning model for N responsiveness-related varietal classification just using N-response phenotypes with high accuracies. Finally, we employed the Wheat55K SNP Array to map single-nucleotide polymorphisms using N response-related static and dynamic phenotypes, helping us explore genetic components underlying N responsiveness in wheat. In summary, we believe that our work demonstrates valuable advances in N response-related plant research, which could have major implications for improving N sustainability in wheat breeding and production.

The Genetic Dissection of Nitrogen Use-Related Traits in Flax (Linum usitatissimum L.) at the Seedling Stage through the Integration of Multi-Locus GWAS, RNA-seq and Genomic Selection

Nitrogen (N), the most important macro-nutrient for plant growth and development, is a key factor that determines crop yield. Yet its excessive applications pollute the environment and are expensive. Hence, studying nitrogen use efficiency (NUE) in crops is fundamental for sustainable agriculture. Here, an association panel consisting of 123 flax accessions was evaluated for 21 NUE-related traits at the seedling stage under optimum N (N+) and N deficiency (N-) treatments to dissect the genetic architecture of NUE-related traits using a multi-omics approach integrating genome-wide association studies (GWAS), transcriptome analysis and genomic selection (GS). Root traits exhibited significant and positive correlations with NUE under N- conditions (r = 0.33 to 0.43, p < 0.05). A total of 359 QTLs were identified, accounting for 0.11% to 23.1% of the phenotypic variation in NUE-related traits. Transcriptomic analysis identified 1034 differentially expressed genes (DEGs) under contrasting N conditions. DEGs involved in N metabolism, root development, amino acid transport and catabolism and others, were found near the QTLs. GS models to predict NUE stress tolerance index (NUE_STI) trait were tested using a random genome-wide SNP dataset and a GWAS-derived QTLs dataset. The latter produced superior prediction accuracy (r = 0.62 to 0.79) compared to the genome-wide SNP marker dataset (r = 0.11) for NUE_STI. Our results provide insights into the QTL architecture of NUE-related traits, identify candidate genes for further studies, and propose genomic breeding tools to achieve superior NUE in flax under low N input.

Genetic regions determine tolerance to nitrogen deficiency in European elite bread wheats grown under contrasting nitrogen stress scenarios

KEY MESSAGE

Clustering 24 environments in four contrasting nitrogen stress scenarios enabled the detection of genetic regions determining tolerance to nitrogen deficiency in European elite bread wheats. Increasing the nitrogen use efficiency of wheat varieties is an important goal for breeding. However, most genetic studies of wheat grown at different nitrogen levels in the field report significant interactions with the genotype. The chromosomal regions possibly involved in these interactions are largely unknown. The objective of this study was to quantify the response of elite bread wheat cultivars to different nitrogen field stress scenarios and identify genomic regions involved in this response. For this purpose, 212 elite bread wheat varieties were grown in a multi-environment trial at different nitrogen levels. Genomic regions associated with grain yield, protein concentration and grain protein deviation responses to nitrogen deficiency were identified. Environments were clustered according to adjusted means for grain yield, yield components and grain protein concentration. Four nitrogen availability scenarios were identified: optimal condition, moderate early deficiency, severe late deficiency, and severe continuous deficiency. A large range of tolerance to nitrogen deficiency was observed among varieties, which were ranked differently in different nitrogen deficiency scenarios. The well-known negative correlation between grain yield and grain protein concentration also existed between their respective tolerance indices. Interestingly, the tolerance indices for grain yield and grain protein deviation were either null or weakly positive meaning that breeding for the two traits should be less difficult than expected. Twenty-two QTL regions were identified for the tolerance indices. By selecting associated markers, these regions may be selected separately or combined to improve the tolerance to N deficiency within a breeding programme.

A Haplotype-Based GWAS Identified Trait-Improving QTL Alleles Controlling Agronomic Traits under Contrasting Nitrogen Fertilization Treatments in the MAGIC Wheat Population WM-800

The multi-parent-advanced-generation-intercross (MAGIC) population WM-800 was developed by intercrossing eight modern winter wheat cultivars to enhance the genetic diversity present in breeding populations. We cultivated WM-800 during two seasons in seven environments under two contrasting nitrogen fertilization treatments. WM-800 lines exhibited highly significant differences between treatments, as well as high heritabilities among the seven agronomic traits studied. The highest-yielding WM-line achieved an average yield increase of 4.40 dt/ha (5.2%) compared to the best founder cultivar Tobak. The subsequent genome-wide-association-study (GWAS), which was based on haplotypes, located QTL for seven agronomic traits including grain yield. In total, 40, 51, and 46 QTL were detected under low, high, and across nitrogen treatments, respectively. For example, the effect of QYLD_3A could be associated with the haplotype allele of cultivar Julius increasing yield by an average of 4.47 dt/ha (5.2%). A novel QTL on chromosome 2B exhibited pleiotropic effects, acting simultaneously on three-grain yield components (ears-per-square-meter, grains-per-ear, and thousand-grain-weight) and plant-height. These effects may be explained by a member of the nitrate-transporter-1 (NRT1)/peptide-family, TaNPF5.34, located 1.05 Mb apart. The WM-800 lines and favorable QTL haplotypes, associated with yield improvements, are currently implemented in wheat breeding programs to develop advanced nitrogen-use efficient wheat cultivars.

Genome-wide association study of agronomic traits related to nitrogen use efficiency in wheat

GWAS identified 347 QTLs associated with eight traits related to nitrogen use efficiency in a 389-count wheat panel. Four novel candidate transcription factor genes were verified using qRT-PCR. Nitrogen is an essential nutrient for plants that determines crop yield. Improving nitrogen use efficiency (NUE) should considerably increase wheat yield and reduce the use of nitrogen fertilisers. However, knowledge on the genetic basis of NUE during wheat maturity is limited. In this study, a diversity panel incorporating 389 wheat accessions was phenotyped for eight NUE-related agronomic traits across five different environments. A total of 347 quantitative trait loci (QTLs) for low nitrogen tolerance indices (ratio of agronomic characters under low and high nitrogen conditions) were identified through a genome-wide association study utilising 397,384 single nucleotide polymorphisms (SNPs) within the MLM (Q + K) model, including 11 stable QTLs. Furthermore, 69 candidate genes were predicted for low nitrogen tolerance indices of best linear unbiased predictions values of the eight studied agronomic traits, and four novel candidate transcription factors (TraesCS5A02G237500 for qFsnR5A.2, TraesCS5B02G384500 and TraesCS5B02G384600 for qSLR5B.1, and TraesCS3B02G068800 for qTKWR3B.1) showed differing expression patterns in contrasting low-nitrogen-tolerant wheat genotypes. Moreover, the number of favourable marker alleles calculated using NUE that were significantly related to SNP in accessions decreased over the decades, indicating a decline in the NUE of the 389 wheat varieties. These findings denote promising NUE markers that could be useful in breeding high-NUE wheat varieties, and the candidate genes could further detail the NUE-related regulation network in wheat.

Rapid prediction of winter wheat yield and nitrogen use efficiency using consumer-grade unmanned aerial vehicles multispectral imagery

Rapid and accurate assessment of yield and nitrogen use efficiency (NUE) is essential for growth monitoring, efficient utilization of fertilizer and precision management. This study explored the potential of a consumer-grade DJI Phantom 4 Multispectral (P4M) camera for yield or NUE assessment in winter wheat by using the universal vegetation indices independent of growth period. Three vegetation indices having a strong correlation with yield or NUE during the entire growth season were determined through Pearson's correlational analysis, while multiple linear regression (MLR), stepwise MLR (SMLR), and partial least-squares regression (PLSR) methods based on the aforementioned vegetation indices were adopted during different growth periods. The cumulative results showed that the reciprocal ratio vegetation index (repRVI) had a high potential for yield assessment throughout the growing season, and the late grain-filling stage was deemed as the optimal single stage with R², root mean square error (RMSE), and mean absolute error (MAE) of 0.85, 793.96 kg/ha, and 656.31 kg/ha, respectively. MERIS terrestrial chlorophyll index (MTCI) performed better in the vegetative period and provided the best prediction results for the N partial factor productivity (NPFP) at the jointing stage, with R², RMSE, and MAE of 0.65, 10.53 kg yield/kg N, and 8.90 kg yield/kg N, respectively. At the same time, the modified normalized difference blue index (mNDblue) was more accurate during the reproductive period, providing the best accuracy for agronomical NUE (aNUE) assessment at the late grain-filling stage, with R², RMSE, and MAE of 0.61, 7.48 kg yield/kg N, and 6.05 kg yield/kg N, respectively. Furthermore, the findings indicated that model accuracy cannot be improved by increasing the number of input features. Overall, these results indicate that the consumer-grade P4M camera is suitable for early and efficient monitoring of important crop traits, providing a cost-effective choice for the development of the precision agricultural system.

Genetic diversity and marker trait association for phytophthora resistance in chilli

BACKGROUND

Chilli is an important commercial crop with positive returns tendency. Phytophthora root rot causes drastic damage to chilli plant. Dearth of detecting marker trait associations is a major hinderance in practicing marker assisted selection in chilli breeding.

METHODS AND RESULTS

Herein, 110 chilli accessions were assessed for 15 agronomic traits under control and disease infected conditions for two crop seasons (2018-2019). The SSR genotyping revealed high values of major allele frequency (MAF = 0.70), genetic diversity (GD = 0.39) and Polymorphic Information Content (PIC = 0.31). Principal coordinate analysis and population structure analysis showed distribution of diverse genotypes in all groups by dividing 110 genotypes in three populations and nine sub-populations. The UPGMA based Archaeopteryx tree was in concordance with population structure analysis. Linkage disequilibrium analysis evaluated that LD decays within 3-10 bp. Marker trait association (MTA) revealed the associations of 35 SSRs with 14 morphological traits. The significant MTA for marker CAeMS073 with relative leaf damage (RLD, 0.183 R²) under control and treated conditions was consistently observed in both models. The markers, CAMS173 and CAMS194 were found to be strongly associated with RLD and Disease Index (DI), respectively. The absence of MTA was detected for height of first branch.

CONCLUSION

The MTAs reported in this study can facilitate marker assisted breeding for developing chilli germplasm resistant against Phytophthora capsici.

Recent Advances in Agronomic and Physio-Molecular Approaches for Improving Nitrogen Use Efficiency in Crop Plants

The efficiency with which plants use nutrients to create biomass and/or grain is determined by the interaction of environmental and plant intrinsic factors. The major macronutrients, especially nitrogen (N), limit plant growth and development (1.5-2% of dry biomass) and have a direct impact on global food supply, fertilizer demand, and concern with environmental health. In the present time, the global consumption of N fertilizer is nearly 120 MT (million tons), and the N efficiency ranges from 25 to 50% of applied N. The dynamic range of ideal internal N concentrations is extremely large, necessitating stringent management to ensure that its requirements are met across various categories of developmental and environmental situations. Furthermore, approximately 60 percent of arable land is mineral deficient and/or mineral toxic around the world. The use of chemical fertilizers adds to the cost of production for the farmers and also increases environmental pollution. Therefore, the present study focused on the advancement in fertilizer approaches, comprising the use of biochar, zeolite, and customized nano and bio-fertilizers which had shown to be effective in improving nitrogen use efficiency (NUE) with lower soil degradation. Consequently, adopting precision farming, crop modeling, and the use of remote sensing technologies such as chlorophyll meters, leaf color charts, etc. assist in reducing the application of N fertilizer. This study also discussed the role of crucial plant attributes such as root structure architecture in improving the uptake and transport of N efficiency. The crosstalk of N with other soil nutrients plays a crucial role in nutrient homeostasis, which is also discussed thoroughly in this analysis. At the end, this review highlights the more efficient and accurate molecular strategies and techniques such as N transporters, transgenes, and omics, which are opening up intriguing possibilities for the detailed investigation of the molecular components that contribute to nitrogen utilization efficiency, thus expanding our knowledge of plant nutrition for future global food security.

Genetic analysis of novel resistance sources and genome-wide association mapping identified novel QTLs for resistance to Zymoseptoria tritici, the causal agent of septoria tritici blotch in wheat

Septoria tritici blotch (STB) caused by Zymoseptoria tritici is one of the most important foliar diseases of wheat causing significant yield losses worldwide. In this study, a panel of bread wheat genotypes comprised 185 globally diverse genotypes were tested against 10 Z. tritici isolates at the seedling stage. Genome-wide association study (GWAS) using high-throughput DArTseq markers was performed and further gene expression analysis of significant markers trait association (MTAs) associated with resistance to STB was analyzed. Disease severity level showed significant differences among wheat genotypes for resistance to different Z. tritici isolates. We found novel landrace genotypes that showed highly resistance spectra to all tested isolates. GWAS analysis resulted in 19 quantitative trait loci (QTLs) for resistance to STB that were located on 14 chromosomes. Overall, 14 QTLs were overlapped with previously known QTLs or resistance genes, as well as five potentially novel QTLs on chromosomes 1A, 4A, 5B, 5D, and 6D. Identified novel resistance sources and also novel QTLs for resistance to different Z. tritici isolates can be used for gene pyramiding and development of durable resistance cultivars in future wheat breeding programs.

Do lower nitrogen fertilization levels require breeding of different types of cultivars in triticale?

The comparably low genotype-by-nitrogen level interaction suggests that selection in early generations can be done under high-input conditions followed by selection under different nitrogen levels to identify genotypes ideally suited for the target environment. Breeding high-yielding, nitrogen-efficient crops is of utmost importance to achieve greater agricultural sustainability. The aim of this study was to evaluate nitrogen use efficiency (NUE) of triticale, investigate long-term genetic trends and the genetic architecture, and develop strategies for NUE improvement by breeding. For this, we evaluated 450 different triticale genotypes under four nitrogen fertilization levels in multi-environment field trials for grain yield, protein content, starch content and derived indices. Analysis of temporal trends revealed that modern cultivars are better in exploiting the available nitrogen. Genome-wide association mapping revealed a complex genetic architecture with many small-effect QTL and a high level of pleiotropy for NUE-related traits, in line with phenotypic correlations. Furthermore, the effect of some QTL was dependent on the nitrogen fertilization level. High correlations of each trait between N levels and the rather low genotype-by-N-level interaction variance showed that generally the same genotypes perform well over different N levels. Nevertheless, the best performing genotype was always a different one. Thus, selection in early generations can be done under high nitrogen fertilizer conditions as these provide a stronger differentiation, but the final selection in later generations should be conducted with a nitrogen fertilization as in the target environment.

Comprehensive evaluation of mapping complex traits in wheat using genome-wide association studies

Genome-wide association studies (GWAS) are effectively applied to detect the marker trait associations (MTAs) using whole genome-wide variants for complex quantitative traits in different crop species. GWAS has been applied in wheat for different quality, biotic and abiotic stresses, and agronomic and yield-related traits. Predictions for marker-trait associations are controlled with the development of better statistical models taking population structure and familial relatedness into account. In this review, we have provided a detailed overview of the importance of association mapping, population design, high-throughput genotyping and phenotyping platforms, advancements in statistical models and multiple threshold comparisons, and recent GWA studies conducted in wheat. The information about MTAs utilized for gene characterization and adopted in breeding programs is also provided. In the literature that we surveyed, as many as 86,122 wheat lines have been studied under various GWA studies reporting 46,940 loci. However, further utilization of these is largely limited. The future breakthroughs in area of genomic selection, multi-omics-based approaches, machine, and deep learning models in wheat breeding after exploring the complex genetic structure with the GWAS are also discussed. This is a most comprehensive study of a large number of reports on wheat GWAS and gives a comparison and timeline of technological developments in this area. This will be useful to new researchers or groups who wish to invest in GWAS.

Influence of new sulfur-containing fertilizers on performance of wheat yield

Wheat is the main cereal crop in Kazakhstan and fertilizers play an important role in enhancing harvest growth. In this study, the impact of new sulfur-containing fertilizers on the growth and yield of wheat was evaluated, and the resistance of varieties to Puccinia triticina Erikss was also investigated. (also known as Puccinia recondite Rob. ex Desm.) for recommendations in agriculture. The study was conducted from 2017 to 2020 in a nursery and greenhouse. The sulfur-containing fertilizer contains nutrients that allow you to extend the duration of absorption by the plant, thereby extending the period of their availability to plants, compared to conventional preparations. By encapsulating molten elemental sulfur and impregnating with a solution of calcium polysulfide, a long-acting compound based on amorphous and monocalcium phosphate was developed. The sulfur is in a water-soluble sulfate form, which, in turn, is slowly oxidized by bacteria and retained in the soil. Three different types of the developed sulfur-containing nano-particle have been used to test in greenhouses and nurseries: powdered, pasty sulfur-containing composition, and a solution of calcium polysulfide. The results showed that the use of powdered and dissolved sulfur-containing fertilizers contributed to the early ripeness and increased productivity of wheat. Wheat varieties were tested for the presence of key Lr genes that determine resistance to brown rust. The Omskaya 29 sample showed an immune response according to phytopathological assessment, and molecular screening revealed four resistance genes. The new sulfur-containing product is recommended for improving wheat productivity in agriculture, and the Omskaya 29 variety can also be used as a valuable breeding material resistant to brown rust.

Using chlorate as an analogue to nitrate to identify candidate genes for nitrogen use efficiency in barley

Nitrogen (N) is one of the most important macronutrients for crop growth and development. Large amounts of N fertilizers are applied exogenously to improve grain yield and quality, which has led to environmental pollution and high cost of production. Therefore, improvement of N use efficiency (NUE) is a very important aspect for sustainable agriculture. Here, a pilot experiment was firstly conducted with a set of barley genotypes with confirmed NUE to validate the fast NUE screening, using chlorate as an analogue to nitrate. High NUE genotypes were susceptible to chlorate-induced toxicity whereas the low NUE genotypes were tolerant. A total of 180 barley RILs derived from four parents (Compass, GrangeR, Lockyer and La Trobe) were further screened for NUE. Leaf chlorosis induced by chlorate toxicity was the key parameter observed which was later related to low-N tolerance of the RILs. There was a distinct variation in chlorate susceptibility of the RILs with leaf chlorosis in the oldest leaf ranging from 10 to 80%. A genome-wide association study (GWAS) identified 9 significant marker-trait associations (MTAs) conferring high chlorate sensitivity on chromosomes 2H (2), 3H (1), 4H (4), 5H (1) and Un (1). Genes flanking with these markers were retrieved as potential targets for genetic improvement of NUE. Genes encoding Ferredoxin 3, leucine-rich receptor-like protein kinase family protein and receptor kinase are responsive to N stress. MTA4H5468 which exhibits concordance with high NUE phenotype can further be explored under different genetic backgrounds and successfully applied in marker-assisted selection.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-021-01239-8.

Genetic Variation for Nitrogen Use Efficiency Traits in Global Diversity Panel and Parents of Mapping Populations in Pearl Millet

Nitrogen (N) is one of the primary macronutrients required for crop growth and yield. This nutrient is especially limiting in the dry and low fertility soils where pearl millet [Pennisetum glaucum (L.) R. Br] is typically grown. Globally, pearl millet is the sixth most important cereal grown by subsistence farmers in the arid and semi-arid regions of sub-Saharan Africa and the Indian subcontinent. Most of these agro-ecologies have low N in the root zone soil strata. Therefore, there is an immense need to identify lines that use nitrogen efficiently. A set of 380 diverse pearl millet lines consisting of a global diversity panel (345), parents of mapping populations (20), and standard checks (15) were evaluated in an alpha-lattice design with two replications, 25 blocks, a three-row plot for 11 nitrogen use efficiency (NUE) related traits across three growing seasons (Summer 2017, Rainy 2017, and Summer 2018) in an N-depleted precision field under three different N levels (0%-N0, 50%-N50, 100%-N100 of recommended N, i.e., 100 kg ha-1). Analysis of variance revealed significant genetic variation for NUE-related traits across treatments and seasons. Nitrogen in limited condition (N0) resulted in a 27.6 and 17.6% reduction in grain yield (GY) and dry stover yield (DSY) compared to N50. Higher reduction in GY and DSY traits by 24.6 and 23.6% were observed under N0 compared to N100. Among the assessed traits, GY exhibited significant positive correlations with nitrogen utilization efficiency (NUtE) and nitrogen harvest index (NHI). This indicated the pivotal role of N remobilization to the grain in enhancing yield levels. Top 25 N-insensitive (NIS-top grain yielders) and N-sensitive (NS-poor grain yielders) genotypes were identified under low N conditions. Out of 25 NIS lines, nine genotypes (IP 10820, IP 17720, ICMB 01222-P1, IP 10379, ICMB 89111-P2, IP 8069, ICMB 90111-P2, ICMV IS89305, and ICMV 221) were common with the top 25 lines for N100 level showing the genotype plasticity toward varying N levels. Low N tolerant genotypes identified from the current investigation may help in the identification of genomic regions responsible for NUE and its deployment in pearl millet breeding programs through marker-assisted selection (MAS).

Biochemical and Genetic Approaches Improving Nitrogen Use Efficiency in Cereal Crops: A Review

Nitrogen is an essential nutrient required in large quantities for the proper growth and development of plants. Nitrogen is the most limiting macronutrient for crop production in most of the world's agricultural areas. The dynamic nature of nitrogen and its tendency to lose soil and environment systems create a unique and challenging environment for its proper management. Exploiting genetic diversity, developing nutrient efficient novel varieties with better agronomy and crop management practices combined with improved crop genetics have been significant factors behind increased crop production. In this review, we highlight the various biochemical, genetic factors and the regulatory mechanisms controlling the plant nitrogen economy necessary for reducing fertilizer cost and improving nitrogen use efficiency while maintaining an acceptable grain yield.

Genome-Wide Association Study and Identification of Candidate Genes for Nitrogen Use Efficiency in Barley (Hordeum vulgare L.)

Nitrogen (N) fertilizer is largely responsible for barley grain yield potential and quality, yet excessive application leads to environmental pollution and high production costs. Therefore, efficient use of N is fundamental for sustainable agriculture. In the present study, we investigated the performance of 282 barley accessions through hydroponic screening using optimal and low NH4NO3 treatments. Low-N treatment led to an average shoot dry weight reduction of 50%, but there were significant genotypic differences among the accessions. Approximately 20% of the genotypes showed high (>75%) relative shoot dry weight under low-N treatment and were classified as low-N tolerant, whereas 20% were low-N sensitive (≤55%). Low-N tolerant accessions exhibited well-developed root systems with an average increase of 60% in relative root dry weight to facilitate more N absorption. A genome-wide association study (GWAS) identified 66 significant marker trait associations (MTAs) conferring high nitrogen use efficiency, four of which were stable across experiments. These four MTAs were located on chromosomes 1H(1), 3H(1), and 7H(2) and were associated with relative shoot length, relative shoot and root dry weight. Genes corresponding to the significant MTAs were retrieved as candidate genes, including members of the asparagine synthetase gene family, several transcription factor families, protein kinases, and nitrate transporters. Most importantly, the high-affinity nitrate transporter 2.7 (HvNRT2.7) was identified as a promising candidate on 7H for root and shoot dry weight. The identified candidate genes provide new insights into our understanding of the molecular mechanisms driving nitrogen use efficiency in barley and represent potential targets for genetic improvement.

How does nitrogen shape plant architecture?

Plant nitrogen (N), acquired mainly in the form of nitrate and ammonium from soil, dominates growth and development, and high-yield crop production relies heavily on N fertilization. The mechanisms of root adaptation to altered supply of N forms and concentrations have been well characterized and reviewed, while reports concerning the effects of N on the architecture of vegetative and reproductive organs are limited and are widely dispersed in the literature. In this review, we summarize the nitrate and amino acid regulation of shoot branching, flowering, and panicle development, as well as the N regulation of cell division and expansion in shaping plant architecture, mainly in cereal crops. The basic regulatory steps involving the control of plant architecture by the N supply are auxin-, cytokinin-, and strigolactone-controlled cell division in shoot apical meristem and gibberellin-controlled inverse regulation of shoot height and tillering. In addition, transport of amino acids has been shown to be involved in the control of shoot branching. The N supply may alter the timing and duration of the transition from the vegetative to the reproductive growth phase, which in turn may affect cereal crop architecture, particularly the structure of panicles for grain yield. Thus, proper manipulation of N-regulated architecture can increase crop yield and N use efficiency.

Hazards of nitrogen fertilizers and ways to reduce nitrate accumulation in crop plants

In modern agriculture, farm produce accumulates a lot of nitrates that can reach toxic levels owing to the unfair use of nitrogen fertilizers, cultural methods, farming policies in multiple areas of the world, thereby increasing concerns about the availability of hygienic food supply and environmental hazards. Over the past few decades, global interest in achieving greater output through intensive fertilization has been a growing trend. The fertilizer based on urea or ammonium mainly yields ammonium, which is then transformed to nitrate through the oxidation process that is biologically mediated. Nitrate tends to accumulate differently in distinct crop plants and distinct components of agricultural commodities based on species, crop variety, genetic history, environmental circumstances, harvest phase, post-harvest storage conditions, agronomic variables, nature, and fertilizer application rate. The current article highlights various factors that could directly or indirectly contribute to the accumulation of nitrates in different parts of crop plants and discusses strategies to minimize the accumulation of nitrates in farm produce, thus ensuring healthy food supply and protecting the environment from the accumulation of nitrates.

Identification of quantitative trait loci associated with nitrogen use efficiency in winter wheat

Maintaining winter wheat (Triticum aestivum L.) productivity with more efficient nitrogen (N) management will enable growers to increase profitability and reduce the negative environmental impacts associated with nitrogen loss. Wheat breeders would therefore benefit greatly from the identification and application of genetic markers associated with nitrogen use efficiency (NUE). To investigate the genetics underlying N response, two bi-parental mapping populations were developed and grown in four site-seasons under low and high N rates. The populations were derived from a cross between previously identified high NUE parents (VA05W-151 and VA09W-52) and a shared common low NUE parent, ‘Yorktown.’ The Yorktown × VA05W-151 population was comprised of 136 recombinant inbred lines while the Yorktown × VA09W-52 population was comprised of 138 doubled haploids. Phenotypic data was collected on parental lines and their progeny for 11 N-related traits and genotypes were sequenced using a genotyping-by-sequencing platform to detect more than 3,100 high quality single nucleotide polymorphisms in each population. A total of 130 quantitative trait loci (QTL) were detected on 20 chromosomes, six of which were associated with NUE and N-related traits in multiple testing environments. Two of the six QTL for NUE were associated with known photoperiod (Ppd-D1 on chromosome 2D) and disease resistance (FHB-4A) genes, two were reported in previous investigations, and one QTL, QNue.151-1D, was novel. The NUE QTL on 1D, 6A, 7A, and 7D had LOD scores ranging from 2.63 to 8.33 and explained up to 18.1% of the phenotypic variation. The QTL identified in this study have potential for marker-assisted breeding for NUE traits in soft red winter wheat.

In-depth genome diversity, population structure and linkage disequilibrium analysis of worldwide diverse safflower (Carthamus tinctorius L.) accessions using NGS data generated by DArTseq technology

Safflower (Carthamus tinctorius L.) is one of the most important oilseed crops for its seed oil rich in unsaturated fatty acids. Precise utilization of diverse genetic resources is fundamental in breeding programs to improve high yield genotypes with desirable traits. In this study, for the first time we report successful application of DArTseq technology; an efficient genotyping-by-sequencing (NGS); to analysis genetic diversity and population structure of 89 safflower accessions from worldwide origins. Totally, 19,639 DArTseq markers (10,130 SilicoDArTs and 9509 SNPs) generated through DArTseq genotyping. After filtering the data, 3431 polymorphic DArTseq markers (1136 SilicoDArTs and 2295 SNPs) used for genetic diversity, population structure and linkage disequilibrium analysis in safflower genotypes. All the SilicoDArT and SNP markers showed high reproducibility and call rate. Polymorphism information content (PIC) values ranged from 0.1 to 0.5, while ≥ 0.50% of SilicoDArTs and ≥ 0.64% SNPs showed PIC values more than median. Genotypes grouping using DArTseq markers resulted in three distinct clusters. Results showed weak correlation between safflower diversity pattern and origins. Analysis of molecular variance revealed that the majority of genetic variation was attributed to the differences among varieties within cluster populations and there was no significant molecular variance between origins. However, safflower of accessions belonged to Iran, Turkey, Pakistan and India indeed appear to be genetically similar and grouped close in referred cluster, while the accessions from Near East (Afghanistan, China) being distinct. Our results were in agreement with hypothesis that safflower domesticated in somewhere west of Fertile Crescent and then expanded through Africa and Europe. Present study using a panel of globally diverse safflower accessions and large number of DArTseq markers set the stage for future analysis of safflower domestication using large germplasm from proposed domestication centers. Also, studied germplasm in this study can be used as a valuable source for future genomic studies in safflower for mapping desirable traits through genome-wide association mapping studies.

Whole-genome diversity, population structure and linkage disequilibrium analysis of globally diverse wheat genotypes using genotyping-by-sequencing DArTseq platform

In this study, 129 wheat genotypes from globally diverse origins were genotyped using DArTseq (SilicoDArT and SNP) markers. After filtering markers for quality-filtering, 14,270 SilicoDArTs and 6484 SNPs were retained and used for genetic diversity, population structure and linkage disequilibrium analyses. The highest number of SilicoDArT and SNP markers mapped on genome A and B compared to genome D. In both marker types, polymorphism information content (PIC) values ranged from 0.1 to 0.5, while > 0.80% of SilicoDArTs and > 0.44% SNPs showed PIC value more than median (0.25%). Un-weighted Neighbor Joining cluster analysis and Bayesian-based model population structure grouped wheat genotypes into three and four clusters, respectively. Principal component analysis and discriminant analysis of principal component results showed highly match with cluster and population structure analysis. Linkage disequilibrium (LD) was more extensive in both marker types, while graphical display of LD decay for both marker types showed that LD declined in the region close to 15 kbp, where r 2-values corresponded to r 2 = 0.16. Overall, our genetic diversity analysis showed high level of variation in studied wheat genotypes, even though there was no relationship between wheat grouping and origins. This might be attributed to admixture level that occurred during long-term natural selection of wheat genotypes in different parts of the world. Highly diverse wheat genotypes used in this study may possess unique genes and are useful sources in breeding programs to improve grain yield and quality.

Unlocking the Genetic Diversity and Population Structure of a Wild Gene Source of Wheat, Aegilops biuncialis Vis., and Its Relationship With the Heading Time

Understanding the genetic diversity of Aegilops biuncialis, a valuable source of agronomical useful genes, may significantly facilitate the introgression breeding of wheat. The genetic diversity and population structure of 86 Ae. biuncialis genotypes were investigated by 32700 DArT markers with the simultaneous application of three statistical methods- neighbor-joining clustering, Principal Coordinate Analysis, and the Bayesian approach to classification. The collection of Ae. biuncialis accessions was divided into five groups that correlated well with their eco-geographic habitat: A (North Africa), B (mainly from Balkans), C (Kosovo and Near East), D (Turkey, Crimea, and Peloponnese), and E (Azerbaijan and the Levant region). The diversity between the Ae. biuncialis accessions for a phenological trait (heading time), which is of decisive importance in the adaptation of plants to different eco-geographical environments, was studied over 3 years. A comparison of the intraspecific variation in the heading time trait by means of analysis of variance and principal component analysis revealed four phenotypic categories showing association with the genetic structure and geographic distribution, except for minor differences. The detailed exploration of genetic and phenologic divergence provides an insight into the adaptation capacity of Ae. biuncialis, identifying promising genotypes that could be utilized for wheat improvement.

Whole Genome Diversity, Population Structure, and Linkage Disequilibrium Analysis of Chickpea (Cicer arietinum L.) Genotypes Using Genome-Wide DArTseq-Based SNP Markers

Characterization of genetic diversity, population structure, and linkage disequilibrium is a prerequisite for proper management of breeding programs and conservation of genetic resources. In this study, 186 chickpea genotypes, including advanced "Kabuli" breeding lines and Iranian landrace "Desi" chickpea genotypes, were genotyped using DArTseq-Based single nucleotide polymorphism (SNP) markers. Out of 3339 SNPs, 1152 markers with known chromosomal position were selected for genome diversity analysis. The number of mapped SNP markers varied from 52 (LG8) to 378 (LG4), with an average of 144 SNPs per linkage group. The chromosome size that was covered by SNPs varied from 16,236.36 kbp (LG8) to 67,923.99 kbp (LG5), while LG4 showed a higher number of SNPs, with an average of 6.56 SNPs per Mbp. Polymorphism information content (PIC) value of SNP markers ranged from 0.05 to 0.50, with an average of 0.32, while the markers on LG4, LG6, and LG8 showed higher mean PIC value than average. Unweighted neighbor joining cluster analysis and Bayesian-based model population structure grouped chickpea genotypes into four distinct clusters. Principal component analysis (PCoA) and discriminant analysis of principal component (DAPC) results were consistent with that of the cluster and population structure analysis. Linkage disequilibrium (LD) was extensive and LD decay in chickpea germplasm was relatively low. A few markers showed r2 ≥ 0.8, while 2961 pairs of markers showed complete LD (r2 = 1), and a huge LD block was observed on LG4. High genetic diversity and low kinship value between pairs of genotypes suggest the presence of a high genetic diversity among the studied chickpea genotypes. This study also demonstrates the efficiency of DArTseq-based SNP genotyping for large-scale genome analysis in chickpea. The genotypic markers provided in this study are useful for various association mapping studies when combined with phenotypic data of different traits, such as seed yield, abiotic, and biotic stresses, and therefore can be efficiently used in breeding programs to improve chickpea.

Exploiting genetic variation in nitrogen use efficiency for cereal crop improvement

Cereals are the most important sources of calories and nutrition for the human population, and are an essential animal feed. Food security depends on adequate production and demands are predicted to rise as the global population rises. The need for increased yields will have to be coupled to the efficient use of resources including fertilisers such as nitrogen to underpin the sustainability of food production. Although optimally performing crops with high yields require a balanced mineral nutrition, nitrogen fundamentally drives growth and yield as well as requirements for other nutrients. It is estimated that globally only 33% of applied nitrogen fertiliser is recovered in the harvested grain, indicative of a huge waste of resource and potential major pollutant and is thus a major target for crop improvement. Both agronomy and breeding will contribute to improved nitrogen use efficiency (NUE) and an important component of the latter is harnessing germplasm variation. This review will consider the key traits involved in NUE, the potential to exploit genetic variation for these specific traits, and the approaches to be utilised.

Genome-Wide Association Analyses Identify QTL Hotspots for Yield and Component Traits in Durum Wheat Grown under Yield Potential, Drought, and Heat Stress Environments

Understanding the genetic bases of economically important traits is fundamentally important in enhancing genetic gains in durum wheat. In this study, a durum panel of 208 lines (comprised of elite materials and exotics from the International Maize and Wheat Improvement Center gene bank) were subjected to genome wide association study (GWAS) using 6,211 DArTseq single nucleotide polymorphisms (SNPs). The panel was phenotyped under yield potential (YP), drought stress (DT), and heat stress (HT) conditions for 2 years. Mean yield of the panel was reduced by 72% (to 1.64 t/ha) under HT and by 60% (to 2.33 t/ha) under DT, compared to YP (5.79 t/ha). Whereas, the mean yield of the panel under HT was 30% less than under DT. GWAS identified the largest number of significant marker-trait associations on chromosomes 2A and 2B with p-values 10-06 to 10-03 and the markers from the whole study explained 7-25% variation in the traits. Common markers were identified for stress tolerance indices: stress susceptibility index, stress tolerance, and stress tolerance index estimated for the traits under DT (82 cM on 2B) and HT (68 and 83 cM on 3B; 25 cM on 7A). GWAS of irrigated (YP and HT combined), stressed (DT and HT combined), combined analysis of three environments (YP + DT + HT), and its comparison with trait per se and stress indices identified QTL hotspots on chromosomes 2A (54-70 cM) and 2B (75-82 cM). This study enhances our knowledge about the molecular markers associated with grain yield and its components under different stress conditions. It identifies several marker-trait associations for further exploration and validation for marker-assisted breeding.