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Short heat waves (SHW), defined as periods of several consecutive days with high temperatures above the developmental optimum, will become more frequent due to climate change. The impact of SHW on yield and yield-related parameters has received considerable interest, but their effects on grain quality remain poorly understood. We employed a simulation approach to investigate the impact of SHW on durum wheat quality over a 7 day period, starting 1 week after anthesis. During the SHW treatment, carried out using portable polyethylene tents, the temperature in the treated plots increased by 10-15 °C during daily hours. The SHW treatment reduced the number of grains per spike, thousand kernel weight, and total carotenoid content in grains in stressed plants in comparison to control plants. However, no differences in the protein content or percentage of vitreous grains were observed. The behavior of individual carotenoids in response to SHW appears to differ, suggesting a differential change in the balance between ß,ε- and ß,ß-branches of the carotenoid biosynthetic pathway as a consequence of SHW-induced stress. The present study highlights the importance of developing efficient breeding strategies for reduced sensitivities to heat stress. Such strategies should not only prioritize yield but also encompass grain quality.

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BACKGROUND: Ubiquitination is an important regulatory step of selective protein degradation in the plant UPS (ubiquitin-proteasome system), which is involved in various biological processes in eukaryotes. Ubiquitin-conjugating enzymes play an intermediate role in the process of protein ubiquitination reactions and thus play an essential role in regulating plant growth and response to adverse environmental conditions. However, a genome-wide analysis of the UBC gene family in wheat (Triticum aestivum L.) has not yet been performed. RESULTS: In this study, the number, physiochemical properties, gene structure, collinearity, and phylogenetic relationships of TaUBC family members in wheat were analyzed using bioinformatics methods. The expression pattern of TaUBC genes in different tissues/organs and developmental periods, as well as the transcript levels under abiotic stress treatment, were analyzed using RNA-Seq data and qRT-PCR. Meanwhile, favorable haplotypes of TaUBC25 were investigated based on wheat resequencing data of 681 wheat cultivars from the Wheat Union Database. The analyses identified a total of 93 TaUBC family members containing a UBC domain in wheat genome. These genes were unevenly distributed across 21 chromosomes, and numerous duplication events were observed between gene members. Based on phylogenetic analysis, the TaUBC family was divided into 13 E2 groups and a separate UEV group. We investigated the expression of TaUBC family genes under different tissue/organ and stress conditions by quantitative real-time PCR (qRT-PCR) analysis. The results showed that some TaUBC genes were specifically expressed in certain tissues/organs and that most TaUBC genes responded to NaCl, PEG6000, and ABA treatment with different levels of expression. In addition, we performed association analysis for the two haplotypes based on key agronomic traits such as thousand-kernel weight (TKW), kernel length (KL), kernel weight (KW), and kernel thickness (KT), examining 122 wheat accessions at three environmental sites. The results showed that TaUBC25-Hap II had significantly higher TKW, KL, KW, and KT than TaUBC25-Hap I. The distribution analysis of haplotypes showed that TaUBC25-Hap II was preferred in the natural population of wheat. CONCLUSION: Our results identified 93 members of the TaUBC family in wheat, and several genes involved in grain development and abiotic stress response. Based on the SNPs detected in the TaUBC sequence, two haplotypes, TaUBC25-Hap I and TaUBC25-Hap II, were identified among wheat cultivars, and their potential value for wheat breeding was validated by association analysis. The above results provide a theoretical basis for elucidating the evolutionary relationships of the TaUBC gene family and lay the foundation for studying the functions of family members in the future.

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Breeding of high-yielding and stable durum wheat varieties with improved kernel characteristics is needed for dry regions around the globe. The aim of this study was to investigate the performance and stability of eight durum wheat genotypes varying in their kernel characteristics across 15 contrasting environments. The tested material included three recombinant inbred lines (NUR-072, NUR-106 and NUR-238) derived from a cross between Norsi, a Jordanian landrace with special kernel characteristics and UC1113 Yr36+Gpc-B1, an elite line from USA. Field trials were carried out for three constitutive growing seasons under rainfed conditions, except for three environments where supplementary irrigation was provided. After the harvest, grain yield (GY), total yield (TW), and harvest index (HI) were recorded. Additionally, several kernel-related traits, including thousand kernel weight (TKW), kernel area (KA), kernel width (KW), kernel length (KL), kernel circularity (KC), and kernel length-width ratio (KL:KW) were evaluated. Analysis of variance for all tested traits revealed high significant variations (p ≤ 0.01) between the genotype (except for TW) and the genotype × environment (G × E) interaction. Genotype effect contributed to substantial percentage of variation (>75%) for KA, KL, KC and KL:KW, whereas KW showed a lower percentage similar to GY. Regarding the G × E effect, explained variation was highest for the TW (67.79%), and lowest for KL (6.47%). For GY, Norsi produced significantly the lowest mean value (249.99 g.m-2) while, Bolenga produced the highest mean value (377.85 g.m-2) although no significant differences were observed with the remaining genotypes. On the other hand, Norsi, NUR-072 and NUR-106 showed best performance for TKW and kernel-related traits with NUR-106 producing the highest mean value for KL (9.07 mm). The GGE biplot and AMMI analysis of GY identified Bolenga, Um Qais and NUR-106 as good performers across several environments, while Norsi exhibited the poorest performance. For TKW, Norsi was the best performer across different environments followed by NUR-106, which showed excellent performance under irrigated and saline conditions. For stability analysis, NUR-106 emerged as the most stable genotype in this study for GY and several kernel-related traits, particularly for KL and KC. In conclusion, the results of this study offer valuable insights for durum wheat breeders seeking to develop high-yielding and stable varieties with special kernel characteristics suitable for cultivation in dry areas.

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Introduction: In wheat, kernel weight (KW) is a key determinant of grain yield (GY). However, it is often overlooked when improving wheat productivity under climate warming. Moreover, little is known about the complex effects of genetic and climatic factors on KW. Here, we explored the responses of wheat KW to diverse allelic combinations under projected climate warming conditions. Methods: To focus on KW, we selected a subset of 81 out of 209 wheat varieties with similar GY, biomass, and kernel number (KN) and focused on their thousand-kernel weight (TKW). We genotyped them at eight kompetitive allele-specific polymerase chain reaction markers closely associated with TKW. Subsequently, we calibrated and evaluated the process-based model known as Agricultural Production Systems Simulator (APSIM-Wheat) based on a unique dataset including phenotyping, genotyping, climate, soil physicochemistry, and on-farm management information. We then used the calibrated APSIM-Wheat model to estimate TKW under eight allelic combinations (81 wheat varieties), seven sowing dates, and the shared socioeconomic pathways (SSPs) designated SSP2-4.5 and SSP5-8.5, driven by climate projections from five General Circulation Models (GCMs) BCC-CSM2-MR, CanESM5, EC-Earth3-Veg, MIROC-ES2L, and UKESM1-0-LL. Results: The APSIM-Wheat model reliably simulated wheat TKW with a root mean square error (RMSE) of < 3.076 g TK-1 and R2 of > 0.575 (P < 0.001). The analysis of variance based on the simulation output showed that allelic combination, climate scenario, and sowing date extremely significantly affected TKW (P < 0.001). The impact of the interaction allelic combination × climate scenario on TKW was also significant (P < 0.05). Meanwhile, the variety parameters and their relative importance in the APSIM-Wheat model accorded with the expression of the allelic combinations. Under the projected climate scenarios, the favorable allelic combinations (TaCKX-D1b + Hap-7A-1 + Hap-T + Hap-6A-G + Hap-6B-1 + H1g + A1b for SSP2-4.5 and SSP5-8.5) mitigated the negative effects of climate change on TKW. Discussion: The present study demonstrated that optimizing favorable allelic combinations can help achieve high wheat TKW. The findings of this study clarify the responses of wheat KW to diverse allelic combinations under projected climate change conditions. Additionally, the present study provides theoretical and practical reference for marker-assisted selection of high TKW in wheat breeding.

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NAC proteins constitute one of the largest plant-specific transcription factor (TF) families and play significant roles in plant growth and development. In the present study, three TaNAC020 homoeologous genes located on chromosomes 7A, 7B, and 7D were isolated from wheat (Triticum aestivum L.). TaNAC020s were predominantly expressed in developing grains. The developed transgenic rice lines for TaNAC020-B showed higher starch density and lower amylose contents than those of the wild type (WT). Sequence polymorphism studies showed seven and eight SNPs in TaNAC020-A/B, making three and two haplotypes, respectively. No sequence polymorphism was identified in TaNAC020-D. Association analysis revealed that HAP-2 of TaNAC020-A and TaNAC020-B was the favored haplotype for higher thousand kernel weight and length. Geographic distribution and allelic frequency showed that our favored haplotype experienced strong selection in China, and likewise, diversity increased in TaNAC020s during wheat polyploidization. The results obtained in this study demonstrate that TaNAC020s positively influence starch synthesis and accumulation and are one of the key regulators of the kernel (seed) size and kernel number and have the potential for utilization in wheat breeding to improve grain yield. Molecular markers developed in this study stand instrumental in marker-assisted selection for genetic improvement and germplasm enhancement in wheat.

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Data described in this article refer to the evaluation of genetic variability for quantity (grain protein content, GPC) and composition (HMW-glutenin subunits and gliadins) of seed storage proteins, and two yield components (grain yield per spike, GYS, and thousand-kernel weight, TKW) in a durum wheat recombinant inbred line (RIL) population derived by an interspecific cross between the common wheat accession 02-5B-318 and the durum cv. Saragolla. This article provides datasets relative to GPC, GYS and TKW collected in the two parents and in 135 durum RIL progenies from plants grown in field trials conducted in Valenzano (Metropolitan City of Bari, BA, Italy) by a randomized complete block design with three replicates. Data on GPC were acquired from Near-Infrared Reflectance on whole-meal flour and are expressed as percentage of proteins on a dry weight basis. Data relative to composition of seed storage proteins refer to high molecular weight glutenin subunits (encoded by Glu-A1 and Glu-B1 loci) and gliadins (encoded by Gli-B1 locus) extracted from whole-grain samples and identified based on their electrophoretic relative mobility on SDS-PAGE. This paper also provides datasets for the detection of quantitative trait loci (QTLs) for GPC, GYS, TKW on a durum wheat genetic linkage map previously developed in the same durum population genotyped with the Illumina 90 K iSelect SNP array. The present article finally supports information for the identification of candidate genes related to wheat grain quantity, composition, and yield by providing data relative to all the SNP markers mapped in the QTL confidence intervals for each trait of interest (GPC, GYS, TKW). Data described in this paper support the published original research article titled "Genetic variation for protein content and yield-related traits in a durum population derived from an inter-specific cross between hexaploid and tetraploid wheat cultivars" (Giancaspro et al., 2019).

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Wheat is one of the most important cereal crops worldwide. A consensus map combines genetic information from multiple populations, providing an effective alternative to improve the genome coverage and marker density. In this study, we constructed a consensus map from three populations of recombinant inbred lines (RILs) of wheat using a 90K single nucleotide polymorphism (SNP) array. Phenotypic data on plant height (PH), spike length (SL), and thousand-kernel weight (TKW) was collected in six, four, and four environments in the three populations, and then used for quantitative trait locus (QTL) mapping. The mapping results obtained using the constructed consensus map were compared with previous results obtained using individual maps and previous studies on other populations. A simulation experiment was also conducted to assess the performance of QTL mapping with the consensus map. The constructed consensus map from the three populations spanned 4558.55 cM in length, with 25,667 SNPs, having high collinearity with physical map and individual maps. Based on the consensus map, 21, 27, and 19 stable QTLs were identified for PH, SL, and TKW, much more than those detected with individual maps. Four PH QTLs and six SL QTLs were likely to be novel. A putative gene called TraesCS4D02G076400 encoding gibberellin-regulated protein was identified to be the candidate gene for one major PH QTL located on 4DS, which may enrich genetic resources in wheat semi-dwarfing breeding. The simulation results indicated that the length of the confidence interval and standard errors of the QTLs detected using the consensus map were much smaller than those detected using individual maps. The consensus map constructed in this study provides the underlying genetic information for systematic mapping, comparison, and clustering of QTL, and gene discovery in wheat genetic study. The QTLs detected in this study had stable effects across environments and can be used to improve the wide adaptation of wheat cultivars through marker-assisted breeding.

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BACKGROUND: The future productivity of wheat (T. aestivum L.) as the most grown crop worldwide is of utmost importance for global food security. Thousand kernel weight (TKW) in wheat is closely associated with grain architecture-related traits, e.g. kernel length (KL), kernel width (KW), kernel area (KA), kernel diameter ratio (KDR), and factor form density (FFD). Discovering the genetic architecture of natural variation in these traits, identifying QTL and candidate genes are the main aims of this study. Therefore, grain architecture-related traits in 261 worldwide winter accessions over three field-year experiments were evaluated. RESULTS: Genome-wide association analysis using 90K SNP array in FarmCPU model revealed several interesting genomic regions including 17 significant SNPs passing false discovery rate threshold and strongly associated with the studied traits. Four of associated SNPs were physically located inside candidate genes within LD interval e.g. BobWhite_c5872_589 (602,710,399 bp) found to be inside TraesCS6A01G383800 (602,699,767-602,711,726 bp). Further analysis reveals the four novel candidate genes potentially involved in more than one grain architecture-related traits with a pleiotropic effects e.g. TraesCS6A01G383800 gene on 6A encoding oxidoreductase activity was associated with TKW and KA. The allelic variation at the associated SNPs showed significant differences betweeen the accessions carying the wild and mutated alleles e.g. accessions carying C allele of BobWhite_c5872_589, TraesCS6A01G383800 had significantly higher TKW than the accessions carying T allele. Interestingly, these genes were highly expressed in the grain-tissues, demonstrating their pivotal role in controlling the grain architecture. CONCLUSIONS: These results are valuable for identifying regions associated with kernel weight and dimensions and potentially help breeders in improving kernel weight and architecture-related traits in order to increase wheat yield potential and end-use quality.

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Tillering is a crucial agronomic trait of wheat; it determines yield and plant architecture. Strigolactones (SLs) have been reported to inhibit plant branching. D14, a receptor of SLs, has been described to affect tillering in rice, yet it has seldomly been studied in wheat. In this study, three TaD14 homoeologous genes, TaD14-4A, TaD14-4B, and TaD14-4D, were identified. TaD14-4A, TaD14-4B, and TaD14-4D were constitutively expressed, and TaD14-4D had a higher expression level in most tissues. TaD14 proteins were localized in both cytoplasm and nucleus. An SNP and a 22 bp insertion/deletion (Indel) at the exon regions of TaD14-4D were detected, forming three haplotypes, namely 4D-HapI, 4D-HapII, and 4D-HapIII. Due to the frameshift mutation in the coding region of 4D-HapII, the interaction of 4D-HapII with TaMAX2 and TaD53 was blocked, which led to the blocking of SL signal transduction. Based on the two variation sites, two molecular markers, namely dCAPS-250 and Indel-747, were developed. Association analysis suggested that haplotypes of TaD14-4D were associated with effective tillering number (ETN) and thousand kernel weight (TKW) simultaneously in four environments. The favorable haplotype 4D-HapIII underwent positive selection in global wheat breeding. This study provides insights into understanding the function of natural variations of TaD14-4D and develops two useful molecular markers for wheat breeding.

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Genetic dissection kernel weight-related traits is of great significance for improving wheat yield potential. As one of the three major yield components of wheat, thousand kernel weight (TKW) was mainly affected by grain length (GL) and grain width (GW). To uncover the key loci for these traits, we carried out a quantitative trait loci (QTL) analysis of an F6 recombinant inbred lines (RILs) population derived from a cross of Henong 5290 (small grain) and 06Dn23 (big grain) with a 50 K single nucleotide polymorphism (SNP) array. A total of 17 stable and big effect QTL, including 5 for TKW, 8 for GL and 4 for GW, were detected on the chromosomes 1B, 2A, 2B, 2D, 4B, 5A, 6A and 6D, respectively. Among these, there were two co-located loci for three traits that were mapped on the chromosome 4BS and 6AL. The QTL on 6AL was the most stable locus and explained 15.4-24.8%, 4.1-8.8% and 15.7-24.4% of TKW, GW and GL variance, respectively. In addition, two more major QTL of GL were located on chromosome arm 2BL and 2DL, accounting for 9.7-17.8% and 13.6-19.8% of phenotypic variance, respectively. In this study, we found one novel co-located QTL associated with GL and TKW in 2DL, QGl.haaf-2DL.2/QTkw.haaf-2DL.2, which could explain 13.6-19.8% and 9.8-10.7% phenotypic variance, respectively. Genetic regions and linked markers of these stable QTL will help to further refine mapping of the corresponding loci and marker-assisted selection (MAS) breeding for wheat grain yield potential improvement.

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Here, QTL mapping for thousand-kernel weight carried out within a 541 × Ot1-3 population of recombinant inbred lines using high-density DArT-based map and three methods (single-marker analysis with F parametric test, marker analysis with the Kruskal-Wallis K* nonparametric test, and the recently developed analysis named genes interaction assorting by divergent selection with χ2 test) revealed 28 QTL distributed over all seven rye chromosomes. The first two methods showed a high level of consistency in QTL detection. Each of 13 QTL revealed in the course of gene interaction assorting by divergent selection analysis coincided with those detected by the two other methods, confirming the reliability of the new approach to QTL mapping. Its unique feature of discriminating QTL classes might help in selecting positively acting QTL and alleles for marker-assisted selection. Also, interaction among seven QTL for thousand-kernel weight was analyzed using gene interaction assorting by the divergent selection method. Pairs of QTL showed a predominantly additive relationship, but epistatic and complementary types of two-loci interactions were also revealed.

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BRITTLE1 (BT1), responsible for unidirectional transmembrane transport of ADP-glucose, plays a pivotal role in starch synthesis of cereal grain. In this study, we isolated three TaBT1 homoeologous genes located on chromosomes 6A, 6B, and 6D in common wheat. TaBT1 was mainly expressed in developing grains, and knockdown of TaBT1 in common wheat produced a decrease in grain size, thousand kernel weight (TKW), and grain total starch content. High diversity was detected at the TaBT1-6B locus, with 24 polymorphic sites forming three haplotypes (Hap1, Hap2, and Hap3). Association analysis revealed that Hap1 and Hap2 were preferred haplotypes in modern breeding, for their significant correlations with higher TKW. Furthermore, ß-glucuronidase (GUS) staining and enzyme activity assays in developing grains of transgenic rice with exogenous promoters indicated that the promoters of Hap1 and Hap2 showed stronger driving activity than that of Hap3. Evolutionary analysis revealed that BT1 underwent strong selection during wheat polyploidization. In addition, the frequency distribution of TaBT1-6B haplotypes revealed that Hap1 and Hap2 were preferred in global modern wheat cultivars. Our findings suggest that TaBT1 has an important effect on starch synthesis and TKW, and provide two valuable molecular markers for marker assisted selection (MAS) in wheat high-yield breeding.

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Bread wheat is a major staple cereal provides more than 20% of dietary energy and protein supply to global population. However, with increasing population growth, the problem of nutritional deficiencies is increasingly affecting the health of resource people with predominantly cereal-based diet. Therefore, the development of wheat genotypes with micronutrient-dense grains along with high-yield potential is one of the major priorities of wheat biofortification program at CIMMYT. We conducted a QTL mapping study using a recombinant inbred line (RIL) population derived from a cross between a Chinese parental line with highGZnC and a Mexican commercial bread wheat cultivar Roelfs F2007 to identify QTLs that could potentially be integrated in mineral nutrient concentrations and agronomic-related traits breeding. We evaluated 200 RIL lines for mineral nutrient concentrations and agronomic-related traits over two years. A total of 60 QTLs were detected, of which 10 QTLs for GZnC, 9 for GFeC, 5 for GPC and 36 for agronomic-related traits. Moreover, a total of 55 promising candidate genes were identified from the list of associated markers for GFeC and GZnC using the recently annotated wheat genome sequence. We identified the promising genomic regions with high mineral nutrient concentrations and acceptable yield potential, which are good resource for further use in wheat biofortification breeding programs.

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Crop yield is determined by the acquisition and allocation of photoassimilates in sink organs. Therefore, genetic modification of sink size is essential for understanding the complex signaling network regulating sink strength and source activities. Sink size in wheat depends on the number of spikelets per spike, floret/grain number per spikelet as well as the grain weight or dry matter accumulation. Hence, increasing spikelet number and improving sink size are targets for wheat breeding. The main objective of the present work was to genetically modify the wheat spike architecture, i.e., the sink size by introgressing the 'Miracle wheat' or the bht-A1 allele into an elite durum wheat cv. Floradur. After four generations of backcrossing to the recurrent parent, Floradur (FL), we have successfully developed Near Isogenic Lines (NILs) with a modified spikelet arrangement thereby increasing spikelet and grain number per spike. Genotyping of bht-A1 NILs using the Genotyping-By-Sequencing approach revealed that the size of the introgressed donor segments carrying bht-A1 ranged from 2.3 to 38 cM. The size of the shortest donor segment introgressed into bht-A1 NILs was estimated to be 9.8 mega base pairs (Mbp). Phenotypic analysis showed that FL-bht-A1-NILs (BC3F2 and BC3F3) carry up to seven additional spikelets per spike, leading to up to 29% increase in spike dry weight at harvest (SDWh). The increased SDWh was accompanied by up to 23% more grains per spike. More interestingly, thousand kernel weight (TKW) did not show significant differences between FL-bht-A1-NILs and Floradur, suggesting that besides increasing spikelet number, bht-A1 could also be targeted for increasing grain yield in wheat. Our study suggests that the genetic modification of spikelet number in wheat can be an entry point for improving grain yield, most interestingly and also unexpectedly without the trade-off effects on TKW. Hence, FL-bht-A1-NILs are not only essential for increasing grain number, but also for understanding the molecular and genetic mechanism of the source-sink interaction for a clearer picture of the complex signaling network regulating sink strength and source activities.

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The domestication and subsequent genetic improvement of wheat led to the development of large-seeded cultivated wheat species relative to their smaller-seeded wild progenitors. While increased grain weight (GW) continues to be an important goal of many wheat breeding programs, few genes underlying this trait have been identified despite an abundance of studies reporting quantitative trait loci (QTL) for GW. Here we perform a QTL analysis for GW using a population of recombinant inbred lines (RILs) derived from the cross between wild emmer wheat accession 'Zavitan' and durum wheat variety 'Svevo'. Identified QTLs in this population were anchored to the recent Zavitan reference genome, along with previously published QTLs for GW in tetraploid wheat. This genome-based, meta-QTL analysis enabled the identification of a locus on chromosome 6A whose introgression from wild wheat positively affects GW. The locus was validated using an introgression line carrying the 6A GW QTL region from Zavitan in a Svevo background, resulting in >8% increase in GW compared to Svevo. Using the reference sequence for the 6A QTL region, we identified a wheat ortholog to OsGRF4, a rice gene previously associated with GW. The coding sequence of this gene (TtGRF4-A) contains four single nucleotide polymorphisms (SNPs) between Zavitan and Svevo, one of which reveals the Zavitan allele to be rare in a core collection of wild emmer and completely absent from the domesticated emmer genepool. Similarly, another wild emmer accession (G18-16) was found to carry a rare allele of TtGRF4-A that also positively affects GW and is characterized by a unique SNP absent from the entire core collection. These results exemplify the rich genetic diversity of wild wheat, posit TtGRF4-A as a candidate gene underlying the 6A GW QTL, and suggest that the natural Zavitan and G18-16 alleles of TtGRF4-A have potential to increase wheat yields in breeding programs.

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The aim of the this study was to identify SNP markers associated with five important wheat quality traits (grain protein content, Zeleny sedimentation, test weight, thousand-kernel weight, and falling number), and to investigate the predictive abilities of GBLUP and Bayesian Power Lasso models for genomic prediction of these traits. In total, 635 winter wheat lines from two breeding cycles in the Danish plant breeding company Nordic Seed A/S were phenotyped for the quality traits and genotyped for 10,802 SNPs. GWAS were performed using single marker regression and Bayesian Power Lasso models. SNPs with large effects on Zeleny sedimentation were found on chromosome 1B, 1D, and 5D. However, GWAS failed to identify single SNPs with significant effects on the other traits, indicating that these traits were controlled by many QTL with small effects. The predictive abilities of the models for genomic prediction were studied using different cross-validation strategies. Leave-One-Out cross-validations resulted in correlations between observed phenotypes corrected for fixed effects and genomic estimated breeding values of 0.50 for grain protein content, 0.66 for thousand-kernel weight, 0.70 for falling number, 0.71 for test weight, and 0.79 for Zeleny sedimentation. Alternative cross-validations showed that the genetic relationship between lines in training and validation sets had a bigger impact on predictive abilities than the number of lines included in the training set. Using Bayesian Power Lasso instead of GBLUP models, gave similar or slightly higher predictive abilities. Genomic prediction based on all SNPs was more effective than prediction based on few associated SNPs.

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The groundwater table has fallen sharply over the last 30years on the North China Plain, resulting in a shortage of water for winter wheat irrigation. Reducing irrigation may be an important strategy to maintain agricultural sustainability in the region; however, few studies have evaluated the transition from conventional irrigation management practices to reduced irrigation management practices in the winter wheat-summer maize rotation system. Here, we compare the yield, water consumption, and water use efficiency of winter wheat-summer maize rotation under conventional irrigation and reduced irrigation on the North China Plain from 2012 to 2015. Reducing irrigation decreased the yield but increased the water use efficiency and significantly advanced the harvest date of winter wheat. As a result, the summer maize sowing date advanced significantly, and the flowering date subsequently advanced 2-8days, thus extending the summer maize grain-filling stage. Therefore, the yield and water use efficiency of summer maize were higher under reduced irrigation than conventional irrigation, which compensated for the winter wheat yield loss under reduced irrigation. In addition, under reduced irrigation from 2012 to 2015, the yield and water use efficiency advantage of the winter wheat-summer maize rotation ranged from 0.0 to 9.7% and from 4.1 to 14.7%, respectively, and water consumption and irrigated water decreased by 20-61mm and 150mm, respectively, compared to conventional irrigation. Overall, the reduced irrigation management practice involving no irrigation after sowing winter wheat, and sowing summer maize on June 7 produced the most favorable grain yield with superb water use efficiency in the winter wheat-summer maize rotation. This study indicates that reducing irrigation could be an efficient means to cope with water resource shortages while maintaining crop production sustainability on the North China Plain.

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In previous work, we cloned TaGS5 gene and found the association of TaGS5-A1 alleles with agronomic traits. In this study, the promoter sequence of the TaGS5-A1 gene was isolated from bread wheat. Sequencing results revealed that a G insertion was found in position -1925 bp of the TaGS5-A1 gene (Reference to ATG), which occurred in the Sp1 domain of the promoter sequence. Combined with previous single nucleotide polymorphism (SNP) in the TaGS5-A1 exon sequence, four genotypes were formed at the TaGS5-A1 locus and were designated as TaGS5-A1a-a, TaGS5-A1a-b, TaGS5-A1b-a, and TaGS5-A1b-b, respectively. Analysis of the association of TaGS5-A1 alleles with agronomic traits indicated that cultivars with the TaGS5-A1a-b allele possessed significantly higher thousand-kernel weight (TKW) and lower plant height than cultivars with the TaGS5-A1a-a allele, and cultivars with the TaGS5-A1b-b allele showed higher TKW than cultivars with the TaGS5-A1b-a allele. The differences of these traits between the TaGS5-A1a-a and TaGS5-A1a-b alleles were larger than those of the TaGS5-A1b-a and TaGS5-A1b-b alleles, suggesting that the -1925G insertion plays the more important role in TaGS5-A1a genotypes than in TaGS5-A1b genotypes. qRT-PCR indicated that TaGS5-A1b-b possessed the significantly highest expression level among four TaGS5-A1 haplotypes in mature seeds and further showed a significantly higher expression level than TaGS5-A1b-a at five different developmental stages of the seeds, suggesting that high expression of TaGS5-A1 was positively associated with high TKW in bread wheat. This study could provide a relatively superior genotype in view of TKW in wheat breeding programs and could also provide important information for dissection of the regulatory mechanism of the yield-related traits.

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Genetic factors controlling thousand-kernel weight (TKW) were characterized for their association with other seed traits, including kernel width, kernel length, ratio of kernel width to kernel length (KW/KL), kernel area, and spike number per m2 (SN). For this purpose, a genetic map was established utilizing a doubled haploid population derived from a cross between German winter wheat cultivars Pamier and Format. Association studies in a diversity panel of elite cultivars supplemented genetic analysis of kernel traits. In both populations, genomic signatures of 13 candidate genes for TKW and kernel size were analyzed. Major quantitative trait loci (QTL) for TKW were identified on chromosomes 1B, 2A, 2D, and 4D, and their locations coincided with major QTL for kernel size traits, supporting the common belief that TKW is a function of other kernel traits. The QTL on chromosome 2A was associated with TKW candidate gene TaCwi-A1 and the QTL on chromosome 4D was associated with dwarfing gene Rht-D1. A minor QTL for TKW on chromosome 6B coincided with TaGW2-6B. The QTL for kernel dimensions that did not affect TKW were detected on eight chromosomes. A major QTL for KW/KL located at the distal tip of chromosome arm 5AS is being reported for the first time. TaSus1-7A and TaSAP-A1, closely linked to each other on chromosome 7A, could be related to a minor QTL for KW/KL. Genetic analysis of SN confirmed its negative correlation with TKW in this cross. In the diversity panel, TaSus1-7A was associated with TKW. Compared to the Pamier/Format bi-parental population where TaCwi-A1a was associated with higher TKW, the same allele reduced grain yield in the diversity panel, suggesting opposite effects of TaCwi-A1 on these two traits.

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MAIN CONCLUSION: A new wheat-rye 1BL•1RS translocation line, with the characteristics of superior stripe rust resistance and high thousand-kernel weight and grain number per spike, was developed and identified from progenies of wheat-rye- Psathyrostachys huashanica trigeneric hybrids. The wheat-rye 1BL•1RS translocation line from Petkus rye has contributed substantially to the world wheat production. However, due to extensive growing of cultivars with disease resistance genes from short arm of rye chromosome 1R and coevolution of pathogen virulence and host resistance, these cultivars successively lost resistance to pathogens. In this study, a new wheat-rye line K13-868, derived from the progenies of wheat-rye-Psathyrostachys huashanica trigeneric hybrids, was identified and analyzed using fluorescence in situ hybridization (FISH), genomic in situ hybridization (GISH), acid polyacrylamide gel electrophoresis (A-PAGE), and molecular markers. Cytological studies indicated that the mean chromosome configuration of K13-868 at meiosis was 2n = 42 = 0.14 I + 18.78 II (ring) + 2.15 II (rod). Sequential FISH and GISH results demonstrated that K13-868 was a compensating wheat-rye 1BL•1RS Robertsonian translocation line. Acid PAGE analysis revealed that clear specific bands of rye 1RS were expressed in K13-868. Simple sequence repeat (SSR) and rye 1RS-specific markers ω-sec-p1/ω-sec-p2 and O-SEC5'-A/O-SEC3'-R suggested that the 1BS arm of wheat had been substituted by the 1RS arm of rye. At the seedling and adult growth stage, compared with its recurrent wheat parent SM51 and six other wheat cultivars containing the 1RS arm in southwestern China, K13-868 showed high levels of resistance to stripe rust (Puccinia striiformis f. sp. tritici, Pst) pathogens prevalent in China, which are virulent to Yr10 and Yr24/Yr26. In addition, K13-868 expresses higher thousand-kernel weight and more grain number per spike than these controls in two growing seasons, suggesting that this line may carry yield-related genes of rye. This translocation line, with significant characteristics of resistance to stripe rust and high thousand-kernel weight and grain number per spike, could be utilized as a valuable germplasm for wheat improvement.

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