A genetic framework for grain size and shape variation in wheat

The TaSnRK1-TabHLH489 module integrates brassinosteroid and sugar signalling to regulate the grain length in bread wheat

Regulation of grain size is a crucial strategy for improving the crop yield and is also a fundamental aspect of developmental biology. However, the underlying molecular mechanisms governing grain development in wheat remain largely unknown. In this study, we identified a wheat atypical basic helix-loop-helix (bHLH) transcription factor, TabHLH489, which is tightly associated with grain length through genome-wide association study and map-based cloning. Knockout of TabHLH489 and its homologous genes resulted in increased grain length and weight, whereas the overexpression led to decreased grain length and weight. TaSnRK1α1, the α-catalytic subunit of plant energy sensor SnRK1, interacted with and phosphorylated TabHLH489 to induce its degradation, thereby promoting wheat grain development. Sugar treatment induced TaSnRK1α1 protein accumulation while reducing TabHLH489 protein levels. Moreover, brassinosteroid (BR) promotes grain development by decreasing TabHLH489 expression through the transcription factor BRASSINAZOLE RESISTANT1 (BZR1). Importantly, natural variations in the promoter region of TabHLH489 affect the TaBZR1 binding ability, thereby influencing TabHLH489 expression. Taken together, our findings reveal that the TaSnRK1α1-TabHLH489 regulatory module integrates BR and sugar signalling to regulate grain length, presenting potential targets for enhancing grain size in wheat.

Natural variation in SSW1 coordinates seed growth and nitrogen use efficiency in Arabidopsis

Seed size is controlled not only by intrinsic genetic factors but also by external environmental signals. Here, we report a major quantitative trait locus (QTL) gene for seed size and weight on chromosome 1 (SSW1) in Arabidopsis, and we found SSW1 acts maternally to positively regulate seed size. Natural variation in SSW1 contains three types of alleles. The SSW1Cvi allele produces larger seeds with more amino acid and storage protein contents than the SSW1Ler allele. SSW1Cvi displays higher capacity for amino acid transport than SSW1Ler due to the differences in transport efficiency. Under low nitrogen supply, the SSW1Cvi allele exhibits increased seed yield and nitrogen use efficiency (NUE). Locations of natural variation alleles of SSW1 are associated with local soil nitrogen contents, suggesting that SSW1 might contribute to geographical adaptation in Arabidopsis. Thus, our findings reveal a mechanism that coordinates seed growth and NUE, suggesting a potential target for improving seed yield and NUE in crops.

Domestication and the evolution of crops: variable syndromes, complex genetic architectures, and ecological entanglements

Domestication can be considered a specialized mutualism in which a domesticator exerts control over the reproduction or propagation (fitness) of a domesticated species to gain resources or services. The evolution of crops by human-associated selection provides a powerful set of models to study recent evolutionary adaptations and their genetic bases. Moreover, the domestication and dispersal of crops such as rice, maize, and wheat during the Holocene transformed human social and political organization by serving as the key mechanism by which human societies fed themselves. Here we review major themes and identify emerging questions in three fundamental areas of crop domestication research: domestication phenotypes and syndromes, genetic architecture underlying crop evolution, and the ecology of domestication. Current insights on the domestication syndrome in crops largely come from research on cereal crops such as rice and maize, and recent work indicates distinct domestication phenotypes can arise from different domestication histories. While early studies on the genetics of domestication often identified single large-effect loci underlying major domestication traits, emerging evidence supports polygenic bases for many canonical traits such as shattering and plant architecture. Adaptation in human-constructed environments also influenced ecological traits in domesticates such as resource acquisition rates and interactions with other organisms such as root mycorrhizal fungi and pollinators. Understanding the ecological context of domestication will be key to developing resource-efficient crops and implementing more sustainable land management and cultivation practices.

Fine mapping of a major QTL, qKl-1BL controlling kernel length in common wheat

KEY MESSAGE

A major stable QTL, qKl-1BL, for kernel length of wheat was narrowed down to a 2.04-Mb interval on chromosome 1BL; the candidate genes were predicated and the genetic effects on yield-related traits were characterized. As a key factor influencing kernel weight, wheat kernel shape is closely related to yield formation, and in turn affects both wheat processing quality and market value. Fine mapping of the major quantitative trait loci (QTL) for kernel shape could provide genetic resources and a theoretical basis for the genetic improvement of wheat yield-related traits. In this study, a major QTL for kernel length (KL) on 1BL, named qKl-1BL, was identified from the recombinant inbred lines (RIL) in multiple environments based on the genetic map and physical map, with 4.76-21.15% of the phenotypic variation explained. To fine map qKl-1BL, the map-based cloning strategy was used. By using developed InDel markers, the near-isogenic line (NIL) pairs and eight key recombinants were identified from a segregating population containing 3621 individuals derived from residual heterozygous lines (RHLs) self-crossing. In combination with phenotype identification, qKl-1BL was finely positioned into a 2.04-Mb interval, KN1B:698.15-700.19 Mb, with eight differentially expressed genes enriched at the key period of kernel elongation. Based on transcriptome analysis and functional annotation information, two candidate genes for qKl-1BL controlling kernel elongation were identified. Additionally, genetic effect analysis showed that the superior allele of qKl-1BL from Jing411 could increase KL, thousand kernel weight (TKW), and yield per plant (YPP) significantly, as well as kernel bulk density and stability time. Taken together, this study identified a QTL interval for controlling kernel length with two possible candidate genes, which provides an important basis for qKl-1BL cloning, functional analysis, and application in molecular breeding programs.

A wheat chromosome segment substitution line series supports characterization and use of progenitor genetic variation

Genome-wide introgression and substitution lines have been developed in many plant species, enhancing mapping precision, gene discovery, and the identification and exploitation of variation from wild relatives. Created over multiple generations of crossing and/or backcrossing accompanied by marker-assisted selection, the resulting introgression lines are a fixed genetic resource. In this study we report the development of spring wheat (Triticum aestivum L.) chromosome segment substitution lines (CSSLs) generated to systematically capture genetic variation from tetraploid (T. turgidum ssp. dicoccoides) and diploid (Aegilops tauschii) progenitor species. Generated in a common genetic background over four generations of backcrossing, this is a base resource for the mapping and characterization of wheat progenitor variation. To facilitate further exploitation the final population was genetically characterized using a high-density genotyping array and a range of agronomic and grain traits assessed to demonstrate the potential use of the populations for trait localization in wheat.

Grain yield trade-offs in spike-branching wheat can be mitigated by elite alleles affecting sink capacity and post-anthesis source activity

Introducing variations in inflorescence architecture, such as the 'Miracle-Wheat' (Triticum turgidum convar. compositum (L.f.) Filat.) with a branching spike, has relevance for enhancing wheat grain yield. However, in the spike-branching genotypes, the increase in spikelet number is generally not translated into grain yield advantage because of reduced grains per spikelet and grain weight. Here, we investigated if such trade-offs might be a function of source-sink strength by using 385 recombinant inbred lines developed by intercrossing the spike-branching landrace TRI 984 and CIRNO C2008, an elite durum (T. durum L.) cultivar; they were genotyped using the 25K array. Various plant and spike architectural traits, including flag leaf, peduncle, and spike senescence rate, were phenotyped under field conditions for 2 consecutive years. On chromosome 5AL, we found a new modifier QTL for spike branching, branched headt3 (bht-A3), which was epistatic to the previously known bht-A1 locus. Besides, bht-A3 was associated with more grains per spikelet and a delay in flag leaf senescence rate. Importantly, favourable alleles, viz. bht-A3 and grain protein content (gpc-B1) that delayed senescence, are required to improve grain number and grain weight in the spike-branching genotypes. In summary, achieving a balanced source-sink relationship might minimize grain yield trade-offs in Miracle-Wheat.

Meta-QTL analysis in wheat: progress, challenges and opportunities

Wheat, an important cereal crop globally, faces major challenges due to increasing global population and changing climates. The production and productivity are challenged by several biotic and abiotic stresses. There is also a pressing demand to enhance grain yield and quality/nutrition to ensure global food and nutritional security. To address these multifaceted concerns, researchers have conducted numerous meta-QTL (MQTL) studies in wheat, resulting in the identification of candidate genes that govern these complex quantitative traits. MQTL analysis has successfully unraveled the complex genetic architecture of polygenic quantitative traits in wheat. Candidate genes associated with stress adaptation have been pinpointed for abiotic and biotic traits, facilitating targeted breeding efforts to enhance stress tolerance. Furthermore, high-confidence candidate genes (CGs) and flanking markers to MQTLs will help in marker-assisted breeding programs aimed at enhancing stress tolerance, yield, quality and nutrition. Functional analysis of these CGs can enhance our understanding of intricate trait-related genetics. The discovery of orthologous MQTLs shared between wheat and other crops sheds light on common evolutionary pathways governing these traits. Breeders can leverage the most promising MQTLs and CGs associated with multiple traits to develop superior next-generation wheat cultivars with improved trait performance. This review provides a comprehensive overview of MQTL analysis in wheat, highlighting progress, challenges, validation methods and future opportunities in wheat genetics and breeding, contributing to global food security and sustainable agriculture.

Genome wide association in Spanish bread wheat landraces identifies six key genomic regions that constitute potential targets for improving grain yield related traits

KEY MESSAGE

Association mapping conducted in 189 Spanish bread wheat landraces revealed six key genomic regions that constitute stable QTLs for yield and include 15 candidate genes. Genetically diverse landraces provide an ideal population to conduct association analysis. In this study, association mapping was conducted in a collection of 189 Spanish bread wheat landraces whose genomic diversity had been previously assessed. These genomic data were combined with characterization for yield-related traits, including grain size and shape, and phenological traits screened across five seasons. The association analysis revealed a total of 881 significant marker trait associations, involving 434 markers across the genome, that could be grouped in 366 QTLs based on linkage disequilibrium. After accounting for days to heading, we defined 33 high density QTL genomic regions associated to at least four traits. Considering the importance of detecting stable QTLs, 6 regions associated to several grain traits and thousand kernel weight in at least three environments were selected as the most promising ones to harbour targets for breeding. To dissect the genetic cause of the observed associations, we studied the function and in silico expression of the 413 genes located inside these six regions. This identified 15 candidate genes that provide a starting point for future analysis aimed at the identification and validation of wheat yield related genes.

Image facilitated assessment of intra-spike variation in grain size in wheat under high temperature and drought stress

In wheat (Triticum aestivum L.), the grain size varies according to position within the spike. Exposure to drought and high temperature stress during grain development in wheat reduces grain size, and this reduction also varies across the length of the spike. We developed the phenomics approach involving image-based tools to assess the intra-spike variation in grain size. The grains were arranged corresponding to the spikelet position and the camera of smart phone was used to acquire 333 images. The open-source software ImageJ was used to analyze features of each grain and the image-derived parameters were used to calculate intra-spike variation as standard deviation (ISVAD). The effect of genotype and environment were highly significant on the ISVAD of grain area. Sunstar and Raj 4079 contrasted in the ISVAD of grain area under late sown environment, and RNA sequencing of the spike was done at 25 days after anthesis. The genes for carbohydrate transport and stress response were upregulated in Sunstar as compared to Raj 4079, suggesting that these play a role in intra-spike assimilate distribution. The phenomics method developed may be useful for grain phenotyping and identifying germplasm with low intra-spike variation in grain size for their further validation as parental material in breeding.

Research on the evolutionary history of the morphological structure of cotton seeds: a new perspective based on high-resolution micro-CT technology

Cotton (Gossypium hirsutum L.) seed morphological structure has a significant impact on the germination, growth and quality formation. However, the wide variation of cotton seed morphology makes it difficult to achieve quantitative analysis using traditional phenotype acquisition methods. In recent years, the application of micro-CT technology has made it possible to analyze the three-dimensional morphological structure of seeds, and has shown technical advantages in accurate identification of seed phenotypes. In this study, we reconstructed the seed morphological structure based on micro-CT technology, deep neural network Unet-3D model, and threshold segmentation methods, extracted 11 basics phenotypes traits, and constructed three new phenotype traits of seed coat specific surface area, seed coat thickness ratio and seed density ratio, using 102 cotton germplasm resources with clear year characteristics. Our results show that there is a significant positive correlation (P< 0.001) between the cotton seed size and that of the seed kernel and seed coat volume, with correlation coefficients ranging from 0.51 to 0.92, while the cavity volume has a lower correlation with other phenotype indicators (r<0.37, P< 0.001). Comparison of changes in Chinese self-bred varieties showed that seed volume, seed surface area, seed coat volume, cavity volume and seed coat thickness increased by 11.39%, 10.10%, 18.67%, 115.76% and 7.95%, respectively, while seed kernel volume, seed kernel surface area and seed fullness decreased by 7.01%, 0.72% and 16.25%. Combining with the results of cluster analysis, during the hundred-year cultivation history of cotton in China, it showed that the specific surface area of seed structure decreased by 1.27%, the relative thickness of seed coat increased by 8.70%, and the compactness of seed structure increased by 50.17%. Furthermore, the new indicators developed based on micro-CT technology can fully consider the three-dimensional morphological structure and cross-sectional characteristics among the indicators and reflect technical advantages. In this study, we constructed a microscopic phenotype research system for cotton seeds, revealing the morphological changes of cotton seeds with the year in China and providing a theoretical basis for the quantitative analysis and evaluation of seed morphology.

QTL mapping for kernel-related traits in a durum wheat x T. dicoccum segregating population

Durum wheat breeding relies on grain yield improvement to meet its upcoming demand while coping with climate change. Kernel size and shape are the determinants of thousand kernel weight (TKW), which is a key component of grain yield, and the understanding of the genetic control behind these traits supports the progress in yield potential. The present study aimed to dissect the genetic network responsible for kernel size components (length, width, perimeter, and area) and kernel shape traits (width-to-length ratio and formcoefficient) as well as their relationships with kernel weight, plant height, and heading date in durum wheat. Quantitative Trait Locus (QTL) mapping was performed on a segregating population of 110 recombinant inbred lines, derived from a cross between the domesticated emmer wheat accession MG5323 and the durum wheat cv. Latino, evaluated in four different environments. A total of 24 QTLs stable across environments were found and further grouped in nine clusters on chromosomes 2A, 2B, 3A, 3B, 4B, 6B, and 7A. Among them, a QTL cluster on chromosome 4B was associated with kernel size traits and TKW, where the parental MG5323 contributed the favorable alleles, highlighting its potential to improve durum wheat germplasm. The physical positions of the clusters, defined by the projection on the T. durum reference genome, overlapped with already known genes (i.e., BIG GRAIN PROTEIN 1 on chromosome 4B). These results might provide genome-based guidance for the efficient exploitation of emmer wheat diversity in wheat breeding, possibly through yield-related molecular markers.

Reviving grain quality in wheat through non-destructive phenotyping techniques like hyperspectral imaging

A long-term goal of breeders and researchers is to develop crop varieties that can resist environmental stressors and produce high yields. However, prioritising yield often compromises improvement of other key traits, including grain quality, which is tedious and time-consuming to measure because of the frequent involvement of destructive phenotyping methods. Recently, non-destructive methods such as hyperspectral imaging (HSI) have gained attention in the food industry for studying wheat grain quality. HSI can quantify variations in individual grains, helping to differentiate high-quality grains from those of low quality. In this review, we discuss the reduction of wheat genetic diversity underlying grain quality traits due to modern breeding, key traits for grain quality, traditional methods for studying grain quality and the application of HSI to study grain quality traits in wheat and its scope in breeding. Our critical review of literature on wheat domestication, grain quality traits and innovative technology introduces approaches that could help improve grain quality in wheat.

Phenotypic evolution in durum wheat (Triticum durum Desf.) based on SNPs, morphological traits, UPOV descriptors and kernel-related traits

Durum wheat is a worldwide staple crop cultivated mainly in the Mediterranean basin. Progress in durum wheat breeding requires the exploitation of genetic variation among the gene pool enclosed in landraces, old cultivars and modern cultivars. The aim of this study was to provide a more comprehensive view of the genetic architecture evolution among 123 durum wheat accessions (41 landraces, 41 old cultivars and 41 modern cultivars), grown in replicated randomized complete block in two areas, Metaponto (Basilicata) and Foggia (Apulia), using the Illumina iSelect 15K wheat SNP array and 33 plant and kernel traits including the International Union for the Protection of new Varieties of Plants (UPOV) descriptors. Through DAPC and Bayesian population structure five groups were identified according to type of material data and reflecting the genetic basis and breeding strategies involved in their development. Phenotypic and genotypic coefficient of variation were low for kernel width (6.43%) and for grain protein content (1.03%). Highly significant differences between environments, genotypes and GEI (Genotype x Environment Interaction) were detected by mixed ANOVAs for agro-morphological-quality traits. Number of kernels per spike (h2 = 0.02) and grain protein content (h2 = 0.03) were not a heritability character and highly influenced by the environment. Nested ANOVAs revealed highly significant differences between DAPC clusters within environments for all traits except kernel roundness. Ten UPOV traits showed significant diversity for their frequencies in the two environments. By PCAmix multivariate analysis, plant height, heading time, spike length, weight of kernels per spike, thousand kernel weight, and the seed related traits had heavy weight on the differentiation of the groups, while UPOV traits discriminated moderately or to a little extent. The data collected in this study provide useful resources to facilitate management and use of wheat genetic diversity that has been lost due to selection in the last decades.

Genome wide association and haplotype analyses for the crease depth trait in bread wheat (Triticum aestivum L.)

Wheat grain has a complex structure that includes a crease on one side, and tissues within the crease region play an important role in nutrient transportation during wheat grain development. However, the genetic architecture of the crease region is still unclear. In this study, 413 global wheat accessions were resequenced and a method was developed for evaluating the phenotypic data of crease depth (CD). The CD values exhibited continuous and considerable large variation in the population, and the broad-sense heritability was 84.09%. CD was found to be positively correlated with grain-related traits and negatively with quality-related traits. Analysis of differentiation of traits between landraces and cultivars revealed that grain-related traits and CD were simultaneously improved during breeding improvement. Moreover, 2,150.8-Mb genetic segments were identified to fall within the selective sweeps between the landraces and cultivars; they contained some known functional genes for quality- and grain-related traits. Genome-wide association study (GWAS) was performed using around 10 million SNPs generated by genome resequencing and 551 significant SNPs and 18 QTLs were detected significantly associated with CD. Combined with cluster analysis of gene expression, haplotype analysis, and annotated information of candidate genes, two promising genes TraesCS3D02G197700 and TraesCS5A02G292900 were identified to potentially regulate CD. To the best of our knowledge, this is the first study to provide the genetic basis of CD, and the genetic loci identified in this study may ultimately assist in wheat breeding programs.

Fine mapping of KLW1 that conditions kernel weight mainly through regulating kernel length in wheat (Triticum aestivum L.)

KLW1 was localized to a 0.6 cM interval near the centromere of chromosome 4B and found to be dominant in conditioning longer kernels and higher kernel weight. Kernel weight is a major wheat yield component and affected by kernel dimensions, filling process and kernel density. Because of this complexity, the mechanism underlying kernel weight is still far from clear. Qtgw.nau-4B or KLW1 was a major kernel weight QTL identified in the Nanda2419 × Wangshuibai population. We showed that introduction of the Nanda2419 allele into elite cultivar Wenmai6 resulted in longer kernels as well as higher kernel weight, without affecting other traits such as spike number per plant, plant height, spike length, spikelet number per spike, and kernel number per spike. KLW1 was dominant in conditioning higher kernel weight and functioned mainly through affecting kernel length. Using F₂ plants derived from KLW1 NIL, a high-density genetic map covering the QTL was constructed. KLW1 was consequently confined to the 0.6 cM Xwgrc4219-Xwgrc4067 interval by evaluating the recombinant lines in three field trials. KLW1 is complementary to KT1, the QTL on chromosome 5A of Nanda2419 for thicker and heavier kernels, in producing larger kernels with higher commercial value, augmenting its usefulness in wheat breeding.

The endosperm microstructure, physical, thermal properties and specific milling energy of spelt (Triticum aestivum ssp. spelta) grain and flour

Previous research has shown that the endosperm microstructure and physical properties of grain have significance in grain processing and in the development of processing machines. The aim of our study was to analyze the endosperm microstructure, physical, thermal properties, and specific milling energy of organic spelt (Triticum aestivum ssp. spelta) grain and flour. Image analysis combined with fractal analysis was used to describe the microstructural differences of the endosperm of spelt grain. The endosperm morphology of spelt kernels was monofractal, isotropic, and complex. A higher proportion of Type-A starch granules resulted in an increased proportion of voids and interphase boundaries in the endosperm. Changes in the fractal dimension were correlated with kernel hardness, specific milling energy, the particle size distribution of flour, and the starch damage rate. Spelt cultivars varied in size and shape of the kernels. Kernel hardness was a property that differentiated specific milling energy, particle size distribution of flour, and starch damage rate. Fractal analysis may be considered as a useful tool for evaluating milling processes in the future.

New Growth-Related Features of Wheat Grain Pericarp Revealed by Synchrotron-Based X-ray Micro-Tomography and 3D Reconstruction

Wheat (Triticum aestivum L.) is one of the most important crops as it provides 20% of calories and proteins to the human population. To overcome the increasing demand in wheat grain production, there is a need for a higher grain yield, and this can be achieved in particular through an increase in the grain weight. Moreover, grain shape is an important trait regarding the milling performance. Both the final grain weight and shape would benefit from a comprehensive knowledge of the morphological and anatomical determinism of wheat grain growth. Synchrotron-based phase-contrast X-ray microtomography (X-ray µCT) was used to study the 3D anatomy of the growing wheat grain during the first developmental stages. Coupled with 3D reconstruction, this method revealed changes in the grain shape and new cellular features. The study focused on a particular tissue, the pericarp, which has been hypothesized to be involved in the control of grain development. We showed considerable spatio-temporal diversity in cell shape and orientations, and in tissue porosity associated with stomata detection. These results highlight the growth-related features rarely studied in cereal grains, which may contribute significantly to the final grain weight and shape.

QTL cluster analysis and marker development for kernel traits based on DArT markers in spring bread wheat (Triticum aestivum L.)

Genetic dissection of yield component traits including kernel characteristics is essential for the continuous improvement in wheat yield. In the present study, one recombinant inbred line (RIL) F₆ population derived from a cross between Avocet and Chilero was used to evaluate the phenotypes of kernel traits of thousand-kernel weight (TKW), kernel length (KL), and kernel width (KW) in four environments at three experimental stations during the 2018-2020 wheat growing seasons. The high-density genetic linkage map was constructed with the diversity arrays technology (DArT) markers and the inclusive composite interval mapping (ICIM) method to identify the quantitative trait loci (QTLs) for TKW, KL, and KW. A total of 48 QTLs for three traits were identified in the RIL population on the 21 chromosomes besides 2A, 4D, and 5B, accounting for 3.00%-33.85% of the phenotypic variances. Based on the physical positions of each QTL, nine stable QTL clusters were identified in the RILs, and among these QTL clusters, TaTKW-1A was tightly linked to the DArT marker interval 3950546-1213099, explaining 10.31%-33.85% of the phenotypic variances. A total of 347 high-confidence genes were identified in a 34.74-Mb physical interval. TraesCS1A02G045300 and TraesCS1A02G058400 were among the putative candidate genes associated with kernel traits, and they were expressed during grain development. Moreover, we also developed high-throughput kompetitive allele-specific PCR (KASP) markers of TaTKW-1A, validated in a natural population of 114 wheat varieties. The study provides a basis for cloning the functional genes underlying the QTL for kernel traits and a practical and accurate marker for molecular breeding.

Genome-wide association mapping of bread wheat genotypes using yield and grain morphology-related traits under different environments

Depleting water resources and increasing global temperature due to climate change are major challenges to agriculture and food security worldwide. Deciphering the underlying mechanisms of traits contributing to grain development and yield is essential for the development of climate-resilient cultivars. Therefore, this study assessed 105 bread wheat genotypes grown under control, drought, and heat-stress conditions for two crop seasons and performed a genome-wide association study (GWAS) using a 90k SNP array. The genotypes showed significant trait differences under all environmental conditions. Highly significant variation was observed, with moderate (50.09%) to high (76.19%) heritability in the studied germplasms. The studied traits were all also significantly positively correlated. A total of 541 significant associations (p ≤ 10^-3) between marker and trait (MTAs) were observed after crossing the FDR <0.05 threshold for all traits. Among these, 195, 179, and 167 significant MTAs were detected under control, drought, and heat-stress conditions, respectively. Under the control and drought conditions, pleiotropic loci BS00010616_51 and BS00010868_51 were observed on chromosomes 7B and 1B situated at 186.24 cM and 35.47 cM, respectively. Pleiotropic loci BS00010868_51, Kukri_c11154_1723, and Ex_c10068_1509 were identified on chromosomes 1B, 5B, and 2A, respectively, under control and heat stress conditions. A stable and consistent locus (Excalibur_c20796_395) on chromosome 7A, located at 372.34 cM, was also linked to grain morphology and yield-related attributes in control, drought, and heat-stress conditions. The results of the current study confirmed several previously reported MTAs for the traits under consideration and identified new MTAs under harsh climatic conditions. These SNPs will aid in the discovery of novel genes in wheat. SNPs showing significant associations may be used in marker-assisted selection and allow the development of drought- and heat-tolerant genotypes with high yields to address global food security concerns.

Identification of quantitative trait loci (QTL) and meta-QTL analysis for kernel size-related traits in wheat (Triticum aestivum L.)

BACKGROUND

Kernel size-related traits, including kernel length (KL), kernel width (KW), kernel diameter ratio (KDR) and kernel thickness (KT), are critical determinants for wheat kernel weight and yield and highly governed by a type of quantitative genetic basis. Genome-wide identification of major and stable quantitative trait loci (QTLs) and functional genes are urgently required for genetic improvement in wheat kernel yield. A hexaploid wheat population consisting of 120 recombinant inbred lines was developed to identify QTLs for kernel size-related traits under different water environments. The meta-analysis and transcriptome evaluation were further integrated to identify major genomic regions and putative candidate genes.

RESULTS

The analysis of variance (ANOVA) revealed more significant genotypic effects for kernel size-related traits, indicating the moderate to high heritability of 0.61-0.89. Thirty-two QTLs for kernel size-related traits were identified, explaining 3.06%-14.2% of the phenotypic variation. Eleven stable QTLs were detected in more than three water environments. The 1103 original QTLs from the 34 previous studies and the present study were employed for the MQTL analysis and refined into 58 MQTLs. The average confidence interval of the MQTLs was 3.26-fold less than that of the original QTLs. The 1864 putative candidate genes were mined within the regions of 12 core MQTLs, where 70 candidate genes were highly expressed in spikes and kernels by comprehensive analysis of wheat transcriptome data. They were involved in various metabolic pathways, such as carbon fixation in photosynthetic organisms, carbon metabolism, mRNA surveillance pathway, RNA transport and biosynthesis of secondary metabolites.

CONCLUSIONS

Major genomic regions and putative candidate genes for kernel size-related traits in wheat have been revealed by an integrative strategy with QTL linkage mapping, meta-analysis and transcriptomic assessment. The findings provide a novel insight into understanding the genetic determinants of kernel size-related traits and will be useful for the marker-assisted selection of high yield in wheat breeding.

The double round-robin population unravels the genetic architecture of grain size in barley

Grain number, size and weight primarily determine the yield of barley. Although the genes regulating grain number are well studied in barley, the genetic loci and the causal gene for sink capacity are poorly understood. Therefore, the primary objective of our work was to dissect the genetic architecture of grain size and weight in barley. We used a multi-parent population developed from a genetic cross between 23 diverse barley inbreds in a double round-robin design. Seed size-related parameters such as grain length, grain width, grain area and thousand-grain weight were evaluated in the HvDRR population comprising 45 recombinant inbred line sub-populations. We found significant genotypic variation for all seed size characteristics, and observed 84% or higher heritability across four environments. The quantitative trait locus (QTL) detection results indicate that the genetic architecture of grain size is more complex than previously reported. In addition, both cultivars and landraces contributed positive alleles at grain size QTLs. Candidate genes identified using genome-wide variant calling data for all parental inbred lines indicated overlapping and potential novel regulators of grain size in cereals. Furthermore, our results indicated that sink capacity was the primary determinant of grain weight in barley.

The Other Mechanisms by Which the Rht Genes Improve the Harvest Index of Wheat

Uncovering the mechanism that underlies the relationship between crop height and grain yield would potentially inform the strategies for improving wheat with optimal height. The aim of the research reported here was to identify the attributes able to produce wheat yield increases in Rht genotypes without further straw-shortening. Attention was given to examination in a controlled environment the question of the mechanistic foundation that determined the relationship between wheat height and yield in lines (Rht-B1b, Rht-D1b, Rht-B1c, Rht-D1c) compared to wild types in Mercia background. In addition to height reduction, this research revealed three other mechanisms by which the Rht genes may also improve the Harvest Index (HI) of wheat: (i) low Specific Leaf Area (SLA), (ii) increased Mean Residence Time (MRT) of Nitrogen (N), and (iii) increased grain number on spike.

Identification of stable QTL controlling multiple yield components in a durum × cultivated emmer wheat population under field and greenhouse conditions

Crop yield gains are needed to keep pace with a growing global population and decreasing resources to produce food. Cultivated emmer wheat is a progenitor of durum wheat and a useful source of genetic variation for trait improvement in durum. Here, we evaluated a recombinant inbred line population derived from a cross between the North Dakota durum wheat variety Divide and the cultivated emmer wheat accession PI 272527 consisting of 219 lines. The population was evaluated in 3 field environments and 2 greenhouse experiments to identify quantitative trait locus associated with 11 yield-related traits that were expressed in a consistent manner over multiple environments. We identified 27 quantitative trait locus expressed in at least 2 field environments, 17 of which were also expressed under greenhouse conditions. Seven quantitative trait locus regions on chromosomes 1B, 2A, 2B, 3A, 3B, 6A, and 7B had pleiotropic effects on multiple yield-related traits. The previously cloned genes Q and FT-B1, which are known to be associated with development and morphology, were found to consistently be associated with multiple traits across environments. PI 272527 contributed beneficial alleles for quantitative trait locus associated with multiple traits, especially for seed morphology quantitative trait locus on chromosomes 1B, 2B, and 6A. Three recombinant inbred lines with increased grain size and weight compared to Divide were identified and demonstrated the potential for improvement of durum wheat through deployment of beneficial alleles from the cultivated emmer parent. The findings from this study provide knowledge regarding stable and robust quantitative trait locus that breeders can use for improving yield in durum wheat.

Genetic identification of the pleiotropic gene Tasg-D1/2 affecting wheat grain shape by regulating brassinolide metabolism

Improving yield potential is a major goal of wheat breeding that depends on identifying key genetic loci. In this study, two residual heterozygous line RHL351- and RHL78-derived populations were employed for genetic linkage map construction and QTL detection. Two genetic populations indicated a robust grain-size QTL between Marker6 and Marker10. It covered a 95.54-99.38 Mb physical interval and was named Qpleio.nwafu.3D, containing the candidate gene Tasg (TraesCS3D02G137200). Intriguingly, RNA-seq analysis and sequencing revealed two different allelic variants in Tasg, named Tasg-D1 (G>A) and Tasg-D2 (C>G), respectively. Although the relationship between Tasg-D1 and grain size had been demonstrated previously, here we provided the first genetic evidence that C/G allelic variation in Tasg-D2 was associated with grain shape and size through a newly developed dCAPS marker. In addition, transcriptome comparison indicated that Tasg-D1/2 might primarily contribute to significant expression differences in brassinolide (BR) metabolism-related genes rather than those related to BR responses in developing grains and spikes. Our study provided new evidence and a breeder-friendly dCAPS marker for improving grain size through the selection of Tasg, as well as a basis to understand Tasg function in the future.

A comprehensive meta-QTL analysis for yield-related traits of durum wheat (Triticum turgidum L. var. durum) grown under different water regimes

Abiotic stress strongly affects yield-related traits in durum wheat, in particular drought is one of the main environmental factors that have effect on grain yield and plant architecture. In order to obtain new genotypes well adapted to stress conditions, the highest number of desirable traits needs to be combined in the same genotype. In this context, hundreds of quantitative trait loci (QTL) have been identified for yield-related traits in different genetic backgrounds and environments. Meta-QTL (MQTL) analysis is a useful approach to combine data sets and for creating consensus positions for the QTL detected in independent studies for the reliability of their location and effects. MQTL analysis is a useful method to dissect the genetic architecture of complex traits, which provide an extensive allelic coverage, a higher mapping resolution and allow the identification of putative molecular markers useful for marker-assisted selection (MAS). In the present study, a complete and comprehensive MQTL analysis was carried out to identify genomic regions associated with grain-yield related traits in durum wheat under different water regimes. A total of 724 QTL on all 14 chromosomes (genomes A and B) were collected for the 19 yield-related traits selected, of which 468 were reported under rainfed conditions, and 256 under irrigated conditions. Out of the 590 QTL projected on the consensus map, 421 were grouped into 76 MQTL associated with yield components under both irrigated and rainfed conditions, 12 genomic regions containing stable MQTL on all chromosomes except 1A, 4A, 5A, and 6B. Candidate genes associated to MQTL were identified and an in-silico expression analysis was carried out for 15 genes selected among those that were differentially expressed under drought. These results can be used to increase durum wheat grain yields under different water regimes and to obtain new genotypes adapted to climate change.

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

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

Quantitative trait loci identification and breeding value estimation of grain weight-related traits based on a new wheat 50K single nucleotide polymorphism array-derived genetic map

Mining novel and less utilized thousand grain weight (TGW) related genes are useful for improving wheat yield. In this study, a recombinant inbred line population from a cross between Zhongkemai 138 (ZKM138, high TGW) and Chuanmai 44 (CM44, low TGW) was used to construct a new Wheat 50K SNP array-derived genetic map that spanned 1,936.59 cM and contained 4, 139 markers. Based on this map, ninety-one quantitative trait loci (QTL) were detected for eight grain-related traits in six environments. Among 58 QTLs, whose superior alleles were contributed by ZKM138, QTgw.cib-6A was a noticeable major stable QTL and was also highlighted by bulked segregant analysis with RNA sequencing (BSR-Seq). It had a pyramiding effect on TGW enhancement but no significant trade-off effect on grain number per spike or tiller number, with two other QTLs (QTgw.cib-2A.2 and QTgw.cib-6D), possibly explaining the excellent grain performance of ZKM138. After comparison with known loci, QTgw.cib-6A was deduced to be a novel locus that differed from nearby TaGW2 and TaBT1. Seven simple sequence repeat (SSR) and thirty-nine kompetitive allele-specific PCR (KASP) markers were finally developed to narrow the candidate interval of QTgw.cib-6A to 4.1 Mb. Only six genes in this interval were regarded as the most likely candidate genes. QTgw.cib-6A was further validated in different genetic backgrounds and presented 88.6% transmissibility of the ZKM138-genotype and a 16.4% increase of TGW in ZKM138 derivatives. And the geographic pattern of this locus revealed that its superior allele is present in only 6.47% of 433 Chinese modern wheat varieties, indicating its potential contribution to further high-yield breeding.

QTL Analysis for Bread Wheat Seed Size, Shape and Color Characteristics Estimated by Digital Image Processing

The size, shape, and color of wheat seeds are important traits that are associated with yield and flour quality (size, shape), nutritional value, and pre-harvest sprouting (coat color). These traits are under multigenic control, and to dissect their molecular and genetic basis, quantitative trait loci (QTL) analysis is used. We evaluated 114 recombinant inbred lines (RILs) in a bi-parental RIL mapping population (the International Triticeae Mapping Initiative, ITMI/MP) grown in 2014 season. We used digital image analysis for seed phenotyping and obtained data for seven traits describing seed size and shape and 48 traits of seed coat color. We identified 212 additive and 34 pairs of epistatic QTLs on all the chromosomes of wheat genome except chromosomes 1A and 5D. Many QTLs were overlapping. We demonstrated that the overlap between QTL regions was low for seed size/shape traits and high for coat color traits. Using the literature and KEGG data, we identified sets of genes in Arabidopsis and rice from the networks controlling seed size and color. Further, we identified 29 and 14 candidate genes for seed size-related loci and for loci associated with seed coat color, respectively.

Quick mapping and characterization of a co-located kernel length and thousand-kernel weight-related QTL in wheat

A co-located KL and TKW-related QTL with no negative effect on PH and AD was rapidly identified using BSA and wheat 660 K SNP array. Its effect was validated in a panel of 218 wheat accessions. Kernel length (KL) and thousand-kernel weight (TKW) of wheat (Triticum aestivum L.) contribute significantly to kernel yield. In the present study, a recombinant inbred line (RIL) population derived from the cross between the wheat line S849-8 with larger kernels and more spikelets per spike and the line SY95-71 was developed. Further, of both the bulked segregant analysis (BSA) and the wheat 660 K single nucleotide polymorphism (SNP) array were used to rapidly identify genomic regions for kernel-related traits from this RIL population. Kompetitive Allele Specific PCR markers were further developed in the SNP-enriched region on the 2D chromosome to construct a genetic map. Both QKL.sicau-SSY-2D for KL and QTKW.sicau-SSY-2D for TKW were identified at multiple environments on chromosome arm 2DL. These two QTLs explained 9.68-23.02% and 6.73-18.32% of the phenotypic variation, respectively. The effects of this co-located QTL were successfully verified in a natural population consisting of 218 Sichuan wheat accessions. Interestingly, the major QTL was significantly and positively correlated with spike length, but did not negatively affect spikelet number per spike (SNS), plant height, or anthesis date. These results indicated that it is possible to synchronously improve kernel weight and SNS by using this QTL. Additionally, several genes associated with kernel development and filling rate were predicted and sequenced in the QTL-containing physical intervals of reference genomes of 'Chinese spring' and Aegilops tauschii. Collectively, these results provide a QTL with great breeding potential and its linked markers which should be helpful for fine mapping and molecular breeding.

Genomic regions associated with tuber traits in tetraploid potatoes and identification of superior clones for breeding purposes

In potato breeding, morphological tuber traits are important selection targets to meet the demands of the fresh and processing markets. Understanding the genetic basis of tuber traits should guide selection and improve breeding efficiencies. However, this is challenging in potato due to the complexity of the traits and the polyploid nature of the potato genome. High-throughput affordable molecular markers and new software specific for polyploid species have the potential to unlock previously unattainable levels of understanding of the genetic basis of tuber traits in tetraploid potato. In this study, we genotyped a diversity panel of 214 advanced clones with the 22 K SNP potato array and phenotyped it in three field environments in Texas. We conducted a genome-wide association study using the GWASpoly software package to identify genomic regions associated with tuber morphological traits. Some of the QTLs discovered confirmed prior studies, whereas others were discovered for the first time. The main QTL for tuber shape was detected on chromosome 10 and explained 5.8% of the phenotypic variance. GWAS analysis of eye depth detected a significant QTL on chromosome 10 and explained 3.9% of the phenotypic variance. Another QTL peak for eye depth on chromosome 5 was located near the CDF1 gene, an important regulator of maturity in potato. Our study found that multiple QTLs govern russeting in potato. A major QTL for flesh color on chromosome 3 that explained 26% of the phenotypic variance likely represents the Y locus responsible for yellow flesh in potato tubers. Several QTLs were detected for purple skin color on chromosome 11. Furthermore, genomic estimated breeding values were obtained, which will aid in the early identification of superior parental clones that should increase the chances of producing progenies with higher frequencies of the desired tuber traits. These findings will contribute to a better understanding of the genetic basis of morphological traits in potato, as well as to identifying parents with the best breeding values to improve selection efficiency in our potato breeding program.

Genetic Diversity of Transcription Factor Genes in Triticum and Mining for Promising Haplotypes for Beneficial Agronomic Traits

Transcription factor (TF) is a class of the sequence-specific DNA-binding proteins that modulate the transcription of target genes, and thus regulate their expressions. Variations in TF are the crucial determinants for phenotypic traits. Although much progress has been made in the functions of TF genes in wheat, one of the most important staple crops globally, the diversity of TF genes in wheat and its progenitors are not well understood, especially the agronomically promising haplotypes have not yet been characterized. Here, we identified a total of 6,023 TF genes from hexaploid wheat through a genome-search method and classified them into 59 gene families based on the conserved domain. The characteristics and dN/dS values of these genes showed evidently selective effects. Based on re-sequencing data, we found a strong genetic bottleneck among these TF genes on A and D subgenomes while no found in B subgenome during wheat domestication. Combined with selective signals and known QTLs on the whole genome, 21 TF genes were preliminarily found to be associated with yield-related traits. The haplotype frequency of these TF genes was further investigated in bread wheat and its progenitors and 13 major haplotypes were the casual loci related to key traits. Finally, the tissue-specific TF genes were also identified using RNA-seq analysis. This study provided insights into the diversity and evolution of TF genes and the identified TF genes and excellent haplotypes associating with traits will contribute to wheat genetic improvement.

The Triticum ispahanicum elongated glume locus P2 maps to chromosome 6A and is associated with the ectopic expression of SVP-A1

We propose the MADS-box transcription factor SVP-A1 as a promising candidate gene for the elongated glume locus P2, which maps to chromosome 6A instead of the previously proposed chromosome 7B. In rice and wheat, glume and floral organ length are positively correlated with grain size, making them an important target to increase grain size and potentially yield. The wheat subspecies Triticum ispahanicum is known to develop elongated glumes and floral organs as well as long grains. These multiple phenotypic effects are controlled by the P2 locus, which was previously mapped to wheat chromosome 7B. Using three mapping populations, we show that the long glume locus P2 does not map to chromosome 7B, but instead maps to a 1.68 Mbp interval on chromosome 6A. Within this interval, we identified SVP-A1, a MADS box transcription factor which is the direct ortholog of the maize gene underlying the 'pod corn' Tunicate locus and is a paralog to the T. polonicum elongated glume P1 gene. In T. ispahanicum, we identified a unique allele which has a 482-bp deletion in the SVP-A1 promoter and is associated with ectopic and higher expression of SVP-A1 in the elongated glumes and floral organs. We used near-isogenic lines (NILs) to show that P2 has a consistent positive effect on the length of glume, lemma, palea, spike and grain. Based on the mapping data, natural variation, biological function of SVP genes in cereals and expression analyses, we propose the MADS-box transcription factor SVP-A1 as a promising candidate for P2.

Organ-specific expression of genes involved in iron homeostasis in wheat mutant lines with increased grain iron and zinc content

Background

Iron deficiency is a well-known nutritional disorder, and the imbalance of trace-elements, specifically iron, is the most common nutrient deficiency of foods across the world, including in Kazakhstan. Wheat has significant nutritional relevance, especially in the provision of iron, however many bread wheat varieties have low iron despite the need for human nourishment. In this study, the expression profiles of wheat homologous genes related to iron homeostasis were investigated. The work resulted in the development of two new M₅ mutant lines of spring bread wheat through gamma-irradiation (200 Gy) with higher grain iron and zinc content, lower phytic acid content, and enhanced iron bioavailability compared to the parent variety. Mutant lines were also characterized by higher means of yield associated traits such as grain number per main spike, grain weight per main spike, grain weight per plant, and thousand-grain weight.

Methods

The homologous genes of bread wheat from several groups were selected for gene expression studies exploring the tight control of iron uptake, translocation rate and accumulation in leaves and roots, and comprised the following: (1) S-adenosylmethionine synthase (SAMS), nicotianamine synthase (NAS1), nicotianamine aminotransferase (NAAT), deoxymugineic acid synthetase (DMAS), involved in the synthesis and release of phytosiderophores; (2) transcription factor basic helix-loop-helix (bHLH); (3) transporters of mugineic acid (TOM), involved in long-distance iron transport; (4) yellow stripe-like (YSlA), and the vacuolar transporter (VIT2), involved in intracellular iron transport and storage; and lastly (5) natural resistance-associated macrophage protein (NRAMP) and ferritin (Fer1A).

Results

The wheat homologous genes TaSAMS, TaNAS1, and TaDMAS, were significantly up-regulated in the roots of both mutant lines by 2.1-4.7-fold compared to the parent variety. The combined over-expression of TaYSlA and TaVIT2 was also revealed in the roots of mutant lines by 1.3-2.7-fold. In one of the mutant lines, genes encoding intracellular iron transport and storage genes TaNRAMP and TaFer1A-D showed significant up-regulation in roots and leaves (by 1.4- and 3.5-fold, respectively). The highest expression was recorded in the transcription factor TabHLH, which was expressed 13.1- and 30.2-fold in the roots of mutant lines. Our research revealed that genotype-dependent and organ-specific gene expression profiles can provide new insights into iron uptake, translocation rate, storage, and regulation in wheat which aid the prioritization of gene targets for iron biofortification and bioavailability.

Genome-Wide Association Study of Kernel Traits Using a 35K SNP Array in Bread Wheat (Triticum aestivum L.)

Kernel size and weight are crucial components of grain yield in wheat. Deciphering their genetic basis is essential for improving yield potential in wheat breeding. In this study, five kernel traits, including kernel length (KL), kernel width (KW), kernel diameter ratio (KDR), kernel perimeter (KP), and thousand-kernel weight (TKW), were evaluated in a panel consisting of 198 wheat accessions under six environments. Wheat accessions were genotyped using the 35K SNP iSelect chip array, resulting in a set of 13,228 polymorphic SNP markers that were used for genome-wide association study (GWAS). A total of 146 significant marker-trait associations (MTAs) were identified for five kernel traits on 21 chromosomes [-log₁₀(P) ≥ 3], which explained 5.91-15.02% of the phenotypic variation. Of these, 12 stable MTAs were identified in multiple environments, and six superior alleles showed positive effects on KL, KP, and KDR. Four potential candidate genes underlying the associated SNP markers were predicted for encoding ML protein, F-box protein, ethylene-responsive transcription factor, and 1,4-α-glucan branching enzyme. These genes were strongly expressed in grain development at different growth stages. The results will provide new insights into the genetic basis of kernel traits in wheat. The associated SNP markers and predicted candidate genes will facilitate marker-assisted selection in wheat breeding.

Climate-Changed Wheat: The Effect of Smaller Kernels on the Nutritional Value of Wheat

Through plant breeding and improved agronomy, the average wheat kernel size increased globally by about 40% from 1940 to 2000. Millers demand larger kernels because they contain more white flour (endosperm). Climate pressures are resulting in frequently reduced kernel size and routine rejection by the commodity system. If whole-wheat flour instead of white flour is the target, these smaller kernels have unrealized value. A total of 94% of Americans do not meet the recommended fiber intake, and inadequate fiber intake plays a role in the development of multiple chronic diseases. A total of 98% of the fiber in wheat is found in the bran. Bran content was measured in “big” (x¯ = 0.042 g/kernel) and “small” (x¯ = 0.023 g/kernel) kernels in nine varieties over locations and years. On average, small kernels contained 15.9% more bran than big kernels (n = 54, p < 0.001) and, thus, had higher mineral and fiber content. In the majority of cases, baking showed no difference in whole-wheat quality among flours within the same variety, regardless of kernel size, based on bread slice height and surface area. Wheat that was rejected by commercial mills as too small produced satisfactory bread. Favoring larger kernels and white flour production has unintended health consequences. Valuing smaller kernels and whole-wheat production provides an outlet for farmers dealing with increasing climate pressures and leads to an end-use product which can improve human health by increasing dietary fiber consumption.

Identification and validation of a major QTL for kernel length in bread wheat based on two F3 biparental populations

BACKGROUND

High yield and quality are essential goals of wheat (Triticum aestivum L.) breeding. Kernel length (KL), as a main component of kernel size, can indirectly change kernel weight and then affects yield. Identification and utilization of excellent loci in wheat genetic resources is of great significance for cultivating high yield and quality wheat. Genetic identification of loci for KL has been performed mainly through genome-wide association study in natural populations or QTL mapping based on genetic linkage map in high generation populations.

RESULTS

In this study, an F₃ biparental population derived from the cross between an EMS mutant BLS1 selected from an EMS-induced wheat genotype LJ2135 (derived from the hybrid progeny of a spelt wheat (T. spelta L.) and a common wheat) mutant bank and a local breeding line 99E18 was used to rapidly identify loci controlling KL based on Bulked Segregant Analysis (BSA) and the wheat 660 K single-nucleotide polymorphism (SNP) array. The highest ratio of polymorphic SNPs was located on chromosome 4A. Linkage map analysis showed that 33 Kompetitive Allele Specific PCR markers were linked to the QTL for KL (Qkl.sicau-BLE18-4A) identified in three environments as well as the best linear unbiased prediction (BLUP) dataset. This QTL explained 10.87-19.30% of the phenotypic variation. Its effect was successfully confirmed in another F₃ population with the two flanking markers KASP-AX-111536305 and KASP-AX-110174441. Compared with previous studies and given that the of BLS1 has the genetic background of spelt wheat, the major QTL was likely a new one. A few of predicted genes related to regulation of kernel development were identified in the interval of the detected QTL.

CONCLUSION

A major, novel and stable QTL (Qkl.sicau-BLE18-4A) for KL was identified and verified in two F₃ biparental populations across three environments. Significant relationships among KL, kernel width (KW) and thousand kernel weight (TKW) were identified. Four predicted genes related to kernel growth regulation were detected in the interval of Qkl.sicau-BLE18-4A. Furthermore, this study laid foundation on subsequent fine mapping work and provided a possibility for breeding of elite wheat varieties.

Identifying Quantitative Trait Loci for Thousand Grain Weight in Eggplant by Genome Re-Sequencing Analysis

Eggplant (Solanum melongena L.; 2n = 24) is one of the most important Solanaceae vegetables and is primarily cultivated in China (approximately 42% of world production) and India (approximately 39%). Thousand-grain weight (TGW) is an important trait that affects eggplant breeding cost and variety promotion. This trait is controlled by quantitative trait loci (QTLs); however, no quantitative trait loci (QTL) has been reported for TGW in eggplant so far, and its potential genetic basis remain unclear. In this study, two eggplant lines, 17C01 (P1, wild resource, small seed) and 17C02 (P2, cultivar, large seed), were crossed to develop F1, F2 (308 lines), BC1P1 (44 lines), and BC1P2 (44 lines) populations for quantitative trait association analysis. The TGWs of P1, P2 and F1 were determined as 3.00, 3.98 and 3.77 g, respectively. The PG-ADI (polygene-controlled additive-dominance-epistasis) genetic model was identified as the optimal model for TGW and the polygene heritability value in the F2 generation was as high as 80.87%. A high-quality genetic linkage bin map was constructed with resequencing analysis. The map contained 3,918 recombination bins on 12 chromosomes, and the total length was 1,384.62 cM. A major QTL (named as TGW9.1) located on chromosome 9 was identified to be strongly associated with eggplant TGW, with a phenotypic variance explanation of 20.51%. A total of 45 annotated genes were identified in the genetic region of TGW9.1. Based on the annotation of Eggplant genome V3 and orthologous genes in Arabidopsis thaliana, one candidate gene SMEL_009g329850 (SmGTS1, encoding a putative ubiquitin ligase) contains 4 SNPs and 2 Indels consecutive intron mutations in the flank of the same exon in P1. SmGTS1 displayed significantly higher expression in P1 and was selected as a potential candidate gene controlling TGW in eggplant. The present results contribute to shed light on the genetic basis of the traits exploitable in future eggplant marker-assisted selection (MAS) breeding.

Wheat grain width: a clue for re-exploring visual indicators of grain weight

BACKGROUND

Mean grain weight (MGW) is among the most frequently measured parameters in wheat breeding and physiology. Although in the recent decades, various wheat grain analyses (e.g. counting, and determining the size, color, or shape features) have been facilitated, thanks to the automated image processing systems, MGW estimations have been limited to using few number of image-derived indices; i.e. mainly the linear or power models developed based on the projected area (Area). Following a preliminary observation which indicated the potential of grain width in improving the predictions, the present study was conducted to explore more efficient indices for increasing the precision of image-based MGW estimations. For this purpose, an image archive of the grains was processed, which were harvested from a 2-year field experiment carried out with 3 replicates under two irrigation conditions and included 15 cultivar mixture treatments (so the archive was consisted of 180 images including more than 72,000 grains).

RESULTS

It was observed that among the more than 30 evaluated indices of grain size and shape, indicators of grain width (i.e. Minor & MinFeret) along with 8 other empirical indices had a higher correlation with MGW, compared with Area. The most precise MGW predictions were obtained using the Area × Circularity, Perimeter × Circularity, and Area/Perimeter indices. Furthermore, it was found that (i) grain width and the Area/Perimeter ratio were the common factors in the structure of the superior predictive indices; and (ii) the superior indices had the highest correlation with grain width, rather than with their mathematical components. Moreover, comparative efficiency of the superior indices almost remained stable across the 4 environmental conditions. Eventually, using the selected indices, ten simple linear models were developed and validated for MGW prediction, which indicated a relatively higher precision than the current Area-based models. The considerable effect of enhancing image resolution on the precision of the models has been also evidenced.

CONCLUSIONS

It is expected that the findings of the present study, along with the simple predictive linear models developed and validated using new image-derived indices, could improve the precision of the image-based MGW estimations, and consequently facilitate wheat breeding and physiological assessments.

Genome-wide association mapping of Hagberg falling number, protein content, test weight, and grain yield in U.K. wheat

Association mapping using crop cultivars allows identification of genetic loci of direct relevance to breeding. Here, 150 U.K. wheat (Triticum aestivum L.) cultivars genotyped with 23,288 single nucleotide polymorphisms (SNPs) were used for genome-wide association studies (GWAS) using historical phenotypic data for grain protein content, Hagberg falling number (HFN), test weight, and grain yield. Power calculations indicated experimental design would enable detection of quantitative trait loci (QTL) explaining ≥20% of the variation (PVE) at a relatively high power of >80%, falling to 40% for detection of a SNP with an R2 ≥ .5 with the same QTL. Genome-wide association studies identified marker-trait associations for all four traits. For HFN (h 2 = .89), six QTL were identified, including a major locus on chromosome 7B explaining 49% PVE and reducing HFN by 44 s. For protein content (h 2 = 0.86), 10 QTL were found on chromosomes 1A, 2A, 2B, 3A, 3B, and 6B, together explaining 48.9% PVE. For test weight, five QTL were identified (one on 1B and four on 3B; 26.3% PVE). Finally, 14 loci were identified for grain yield (h 2 = 0.95) on eight chromosomes (1A, 2A, 2B, 2D, 3A, 5B, 6A, 6B; 68.1% PVE), of which five were located within 16 Mbp of genetic regions previously identified as under breeder selection in European wheat. Our study demonstrates the utility of exploiting historical crop datasets, identifying genomic targets for independent validation, and ultimately for wheat genetic improvement.

Empirical Evaluation of Inflorescences' Morphological Attributes for Yield Optimization of Medicinal Cannabis Cultivars

In recent decades with the reacknowledgment of the medicinal properties of Cannabis sativa L. (cannabis) plants, there is an increased demand for high performing cultivars that can deliver quality products for various applications. However, scientific knowledge that can facilitate the generation of advanced cannabis cultivars is scarce. In order to improve cannabis breeding and optimize cultivation techniques, the current study aimed to examine the morphological attributes of cannabis inflorescences using novel image analysis practices. The investigated plant population comprises 478 plants ascribed to 119 genotypes of high-THC or blended THC-CBD ratio that was cultivated under a controlled environment facility. Following harvest, all plants were manually processed and an image of the trimmed and refined inflorescences extracted from each plant was captured. Image analysis was then performed using in-house custom-made software which extracted 8 morphological features (such as size, shape and perimeter) for each of the 127,000 extracted inflorescences. Our findings suggest that environmental factors play an important role in the determination of inflorescences' morphology. Therefore, further studies that focus on genotype X environment interactions are required in order to generate inflorescences with desired characteristics. An examination of the intra-plant inflorescences weight distribution revealed that processing 75% of the plant's largest inflorescences will gain 90% of its overall yield weight. Therefore, for the optimization of post-harvest tasks, it is suggested to evaluate if the benefits from extracting and processing the plant's smaller inflorescences outweigh its operational costs. To advance selection efficacy for breeding purposes, a prediction equation for forecasting the plant's production biomass through width measurements of specific inflorescences, formed under the current experimental methodology, was generated. Thus, it is anticipated that findings from the current study will contribute to the field of medicinal cannabis by improving targeted breeding programs, advancing crop productivity and enhancing the efficacy of post-harvest procedures.

GWAS for main effects and epistatic interactions for grain morphology traits in wheat

In the present study in wheat, GWAS was conducted for identification of marker trait associations (MTAs) for the following six grain morphology traits: (1) grain cross-sectional area (GCSA), (2) grain perimeter (GP), (3) grain length (GL), (4) grain width (GWid), (5) grain length-width ratio (GLWR) and (6) grain form-density (GFD). The data were recorded on a subset of spring wheat reference set (SWRS) comprising 225 diverse genotypes, which were genotyped using 10,904 SNPs and phenotyped for two consecutive years (2017-2018, 2018-2019). GWAS was conducted using five different models including two single-locus models (CMLM, SUPER), one multi-locus model (FarmCPU), one multi-trait model (mvLMM) and a model for Q x Q epistatic interactions. False discovery rate (FDR) [P value -log10(p) ≥ 5] and Bonferroni correction [P value -log10(p) ≥ 6] (corrected p value < 0.05) were applied to eliminate false positives due to multiple testing. This exercise gave 88 main effect and 29 epistatic MTAs after FDR and 13 main effect and 6 epistatic MTAs after Bonferroni corrections. MTAs obtained after Bonferroni corrections were further utilized for identification of 55 candidate genes (CGs). In silico expression analysis of CGs in different tissues at different parts of the seed at different developmental stages was also carried out. MTAs and CGs identified during the present study are useful addition to available resources for MAS to supplement wheat breeding programmes after due validation and also for future strategic basic research.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12298-022-01164-w.

Meta-QTLs, ortho-meta-QTLs and candidate genes for grain yield and associated traits in wheat (Triticum aestivum L.)

In wheat, 2852 major QTLs of 8998 QTLs available for yield and related traits were used for meta-analysis; 141 meta-QTLs were identified, which included 13 breeder's MQTLs and 24 ortho-MQTLs; 1202 candidate genes and 50 homologues of genes for yield from other cereals were also identified. Meta-QTL analysis was conducted using 2852 of the 8998 known QTLs, retrieved from 230 reports published during 1999-2020 (including 19 studies on tetraploid wheat) for grain yield (GY) and the following ten component traits: (i) grain weight (GWei), (ii) grain morphology-related traits (GMRTs), (iii) grain number (GN), (iv) spikes-related traits (SRTs), (v) plant height (PH), (vi) tiller number (TN), (vii) harvest index (HI), (viii) biomass yield (BY), (ix) days to heading/flowering and maturity (DTH/F/M), and (x) grain filling duration (GFD). The study resulted in the identification of 141 meta-QTLs (MQTLs), with an average confidence interval (CI) of 1.4 cM as against a CI of > 12.1 cM (8.8 fold reduction) in the QTLs that were used. The corresponding physical length of CI ranged from 0.01 Mb to 661.9 Mb (mean, 31.5 Mb). Seventy-seven (77) of these 141 MQTLs overlapped marker-trait associations (MTAs) reported in genome-wide association studies. Also, 63 MQTLs (each based on at least 10 QTLs) were considered stable and robust, with 13 MQTLs described as breeder's MQTLs (selected based on small CI, large LOD, and high level of phenotypic variation explained). Thirty-five yield-related genes from rice, barley, and maize were also utilized to identify 50 wheat homologues in MQTLs. Further, the use of synteny and collinearity allowed the identification of 24 ortho-MQTLs which were common among the wheat, barley, rice, and maize. The results of the present study should prove useful for wheat breeding and future basic research in cereals including wheat, barley, rice, and maize.

A comparison of phenotypic variation in Triticum durum Desf. genotypes deposited in gene banks based on the shape and color descriptors of kernels in a digital image analysis

Durum wheat is the tenth most valuable crop on a global scale. The aim of this study was to compare the phenotypic variation of T. durum accessions of different origin with contemporary spring cultivars of this cereal species. One hundred and two accessions and 12 contemporary cultivars of Triticum durum Desf. as well as Kamut® wheat (T. turanicum), a Triticum species closely related to T. durum, were analyzed. The aim of this study was to describe the degree of variation in the phenotypic traits of grain and selected traits associated with technological quality. The examined genotypes were characterized by considerable phenotypic variation, and they can be a valuable source of material for genetic recombination in durum wheat breeding. The analyzed accessions were characterized by a higher average content of protein (16.48 vs. 14.56%) and wet gluten (38.04 vs. 32.07%), higher Zeleny sedimentation values (69.7 vs. 60.4ml), and higher flour strength (W index values of 404.64 vs. 353.47) than the reference cultivars. The kernels of the evaluated accessions and cultivars did not differ significantly in average crease depth, but significant differences were observed in the values of descriptors directly linked with kernel size, especially kernel image area and minimal Feret diameter. The traits responsible for the processing suitability of grain were more strongly correlated with color descriptors than shape descriptors, which suggests that color parameters can be used to select high-quality breeding material. The analyzed accessions have two major weaknesses, namely relatively low yields (22.6 dt ha^-1 on average) and undesirable grain color, indicative of low carotenoid concentration. The accessions deposited in gene banks do not meet the relevant agronomic requirements. However, both grain yield and carotenoid concentration are polygenic traits which can be improved if desirable combinations of QTLs are assembled in breeding lines and cultivars.

Improvement and Re-Evolution of Tetraploid Wheat for Global Environmental Challenge and Diversity Consumption Demand

Allotetraploid durum wheat is the second most widely cultivated wheat, following hexaploid bread wheat, and is one of the major protein and calorie sources of the human diet. However, durum wheat is encountered with a severe grain yield bottleneck due to the erosion of genetic diversity stemming from long-term domestication and especially modern breeding programs. The improvement of yield and grain quality of durum wheat is crucial when confronted with the increasing global population, changing climate environments, and the non-ignorable increasing incidence of wheat-related disorders. This review summarized the domestication and evolution process and discussed the durum wheat re-evolution attempts performed by global researchers using diploid einkorn, tetraploid emmer wheat, hexaploid wheat (particularly the D-subgenome), etc. In addition, the re-evolution of durum wheat would be promoted by the genetic enrichment process, which could diversify allelic combinations through enhancing chromosome recombination (pentaploid hybridization or pairing of homologous chromosomes gene Ph mutant line induced homoeologous recombination) and environmental adaptability via alien introgressive genes (wide cross or distant hybridization followed by embryo rescue), and modifying target genes or traits by molecular approaches, such as CRISPR/Cas9 or RNA interference (RNAi). A brief discussion of the future perspectives for exploring germplasm for the modern improvement and re-evolution of durum wheat is included.

Genetic architecture of variation in Arabidopsis thaliana rosettes

Rosette morphology across Arabidopsis accessions exhibits considerable variation. Here we report a high-throughput phenotyping approach based on automatic image analysis to quantify rosette shape and dissect the underlying genetic architecture. Shape measurements of the rosettes in a core set of Recombinant Inbred Lines from an advanced mapping population (Multiparent Advanced Generation Inter-Cross or MAGIC) derived from inter-crossing 19 natural accessions. Image acquisition and analysis was scaled to extract geometric descriptors from time stamped images of growing rosettes. Shape analyses revealed heritable morphological variation at early juvenile stages and QTL mapping resulted in over 116 chromosomal regions associated with trait variation within the population. Many QTL linked to variation in shape were located near genes related to hormonal signalling and signal transduction pathways while others are involved in shade avoidance and transition to flowering. Our results suggest rosette shape arises from modular integration of sub-organ morphologies and can be considered a functional trait subjected to selective pressures of subsequent morphological traits. On an applied aspect, QTLs found will be candidates for further research on plant architecture.

Characterization of functional genes GS3 and GW2 and their effect on the grain size of various landraces of rice (Oryza sativa)

BACKGROUND

Grain size is an essential factor of grain quality and yield in rice. The genetic studies have substantially contributed to enhancing yield and maintaining a good quality of rice. The two major genes GS3 (a negative regulator of grain length) and GW2 (a negative regulator of grain width) with functional mutation play a significant role in controlling the grain size of rice. METHODS AND RESULTS: In the study, 17 different widely grown Pakistani landraces of various genetic and geographic backgrounds were evaluated for grain phenotypic traits (1000-grain weight, length, width, and thickness) and also screened for genotypic mutation in GS3 and GW2 genes. Phenotypic data revealed the range for grain weight from 16.86 g (Lateefy) to 26.91 g (PS2), grain length ranged from 7.27 mm (JP-5) to 12.18 mm (PS2), grain width ranged from 2.01 mm (Lateefy) to 3.51 mm (JP5), and grain thickness ranged from 1.79 mm to 2.19. Correlation revealed a negative and significant correlation between grain width and length. There was no significant correlation between grain length and 1000-grain weight and grain width. LSD test displayed that the means of three variables grain length, grain width, and 1000-grain weight were statistically different from one another except grain width and grain breadth. Fifteen accessions carried the domesticated allele of GS3 while JP5 and Fakhr-e-Malakand carried the dominant allele. Similarly, fifteen accessions carried the dominant allele of GW2 while JP-5 and Fakhr-e-Malakand carried the mutant allele.

CONCLUSIONS

The study shows that the mutant alleles of both genes are of significance to pyramid them in any breeding program. However, just incorporating favorable alleles is not the sole solution for improving the grain size. Therefore, further elucidation of GS3 and GW2 genes regulatory network, their interaction, trade-off, and pathways will better coordinate their marker-assisted selection in the future breeding program. Additionally, the study concluded that the selection of grain size was not dependent on 1000-grain weight in the selected germplasm.

A Major Quantitative Trait Loci Cluster Controlling Three Components of Yield and Plant Height Identified on Chromosome 4B of Common Wheat

Wheat yield is not only affected by three components of yield, but also affected by plant height (PH). Identification and utilization of the quantitative trait loci (QTL) controlling these four traits is vitally important for breeding high-yielding wheat varieties. In this work, we conducted a QTL analysis using the recombinant inbred lines (RILs) derived from a cross between two winter wheat varieties of China, "Nongda981" (ND981) and "Nongda3097" (ND3097), exhibiting significant differences in spike number per unit area (SN), grain number per spike (GNS), thousand grain weight (TGW), and PH. A total of 11 environmentally stable QTL for these four traits were detected. Among them, four major and stable QTLs (QSn.cau-4B-1.1, QGns.cau-4B-1, QTgw.cau-4B-1.1, and QPh.cau-4B-1.2) explaining the highest phenotypic variance for SN, GNS, TGW, and PH, respectively, were mapped on the same genomic region of chromosome 4B and were considered a QTL cluster. The QTL cluster spanned a genetic distance of about 12.3 cM, corresponding to a physical distance of about 8.7 Mb. Then, the residual heterozygous line (RHL) was used for fine mapping of the QTL cluster. Finally, QSn.cau-4B-1.1, QGns.cau-4B-1, and QPh.cau-4B-1.2 were colocated to the physical interval of about 1.4 Mb containing 31 annotated high confidence genes. QTgw.cau-4B-1.1 was divided into two linked QTL with opposite effects. The elite NILs of the QTL cluster increased SN and PH by 55.71-74.82% and 14.73-23.54%, respectively, and increased GNS and TGW by 29.72-37.26% and 5.81-11.24% in two environments. Collectively, the QTL cluster for SN, GNS, TGW, and PH provides a theoretical basis for improving wheat yield, and the fine-mapping result will be beneficial for marker-assisted selection and candidate genes cloning.

Genetic dissection of quantitative trait loci for grain size and weight by high-resolution genetic mapping in bread wheat (Triticum aestivum L.)

Six major QTLs for wheat grain size and weight were identified on chromosomes 4A, 4B, 5A and 6A across multiple environments, and were validated in different genetic backgrounds. Grain size and weight are crucial components of wheat yield. Dissection of their genetic control is thus essential for the improvement of yield potential in wheat breeding. We used a doubled haploid (DH) population to detect quantitative trait loci (QTLs) for grain width (GW), grain length (GL), and thousand grain weight (TGW) in five environments. Six major QTLs, QGw.cib-4B.2, QGl.cib-4A, QGl.cib-5A.1, QGl.cib-6A, QTgw.cib-4B, and QTgw.cib-5A, were consistently identified in at least three individual environments and in best linear unbiased prediction (BLUP) datasets, and explained 5.65-34.06% of phenotypic variation. QGw.cib-4B.2, QTgw.cib-4B, QGl.cib-5A.1 and QGl.cib-6A had no effect on grain number per spike (GNS). In addition to QGl.cib-4A, the other major QTLs were further validated by using Kompetitive Allele Specific PCR (KASP) markers in different genetic backgrounds. Moreover, significant interactions between the three major GL QTLs and two major TGW QTLs were observed. Comparison analysis showed that QGl.cib-5A.1 and QGl.cib-6A are likely new loci. Notably, QGw.cib-4B.2 and QTgw.cib-4B were co-located on chromosome 4B and improved TGW by increasing only GW, unlike nearby or overlapped loci reported previously. Three genes associated with grain development within the QGw.cib-4B.2/QTgw.cib-4B interval were identified by searches on sequence similarity, spatial expression patterns, and orthologs. The major QTLs and KASP markers reported here will be useful for elucidating the genetic architecture of grain size and weight and for developing new wheat cultivars with high and stable yield.