Genetic dissection of grain size and grain number trade-offs in CIMMYT wheat germplasm

Dissection of the Genetic Basis of Genotype by Environment Interactions for Morphological Traits and Protein Content in Winter Wheat Panel Grown in Morocco and Spain

To fulfill the growing demand for wheat consumption, it is important to focus on enhancement breeding strategies targeting key parameters such as yield, thousand kernel weight (TKW), quality characteristics including morphological traits, and protein content. These elements are key to the ongoing and future objectives of wheat breeding programs. Prioritizing these factors will effectively help meet the rising demand for wheat, especially given the challenges posed by unpredictable weather patterns. This study evaluated the morphological traits and protein content of 249 winter wheat varieties and advanced lines grown in eleven different environments in Morocco and Spain incorporating three varied sowing dates. The results showed considerable variability in morphological traits and protein content. Significant correlations were observed among various grain traits, with most grain morphological parameters exhibiting negative correlations with protein content. Differences across environments (p ≤ 0.01) in all traits, genotypes, and genotype by environment interaction were significant. A factorial regression analysis revealed significant impacts of environmental conditions on all grain morphological parameters, protein content, and TKW during the three growth stages. The study identified several high-performing and stable genotypes across diverse environments, providing valuable insights for wheat breeding programs such as genotypes 129, 234, 241, and 243. Genome-Wide Association Studies pinpointed 603 significant markers across 11 environments, spread across chromosomes. Among these, 400 markers were linked with at least two traits or observed in at least two different environments. Moreover, twelve marker-trait associations were detected that surpassed the Bonferroni correction threshold. These findings highlight the importance of targeted breeding efforts to enhance wheat quality and adaptability to different environmental conditions.

Impact of rising temperatures on historical wheat yield, phenology, and grain size in Catalonia

Introduction

Climate change poses significant challenges to agriculture, impacting crop yields and necessitating adaptive strategies in breeding programs. This study investigates the genetic yield progress of wheat varieties in Catalonia, Spain, from 2007 to 2021, and examines the relationship between genetic yield and climate-related factors, such as temperature. Understanding these dynamics is crucial for ensuring the resilience of wheat crops in the face of changing environmental conditions.

Methods

Genetic yield progress was assessed using a linear regression function, comparing the average yield changes of newly released wheat varieties to benchmark varieties. Additionally, a quadratic function was employed to model genetic yield progress in winter wheat (WW). The study also analyzed correlations between genetic yield (GY) and normalized values of hectoliter weight (HLW) and the number of grains (NG) for both spring wheat (SW) and WW. Weather data were used to confirm climate change impacts on temperature and its effects on wheat growth and development.

Results

The study found that genetic yield was stagnant for SW but increased linearly by 1.31% per year for WW. However, the quadratic function indicated a possible plateau in WW genetic yield progress in recent years. Positive correlations were observed between GY and normalized values of HLW and NG for both SW and WW. Climate change was evident in Catalonia, with temperatures increasing at a rate of 0.050 °C per year. This rise in temperature had detrimental effects on days to heading (DH) and HLW, with reductions observed in both SW and WW for each °C increase in annual minimum and average temperature.

Discussion

The findings highlighted the urgent need to address the impact of climate change on wheat cultivation. The stagnation of genetic yield in SW and the potential plateau in WW genetic yield progress call for adaptive measures. Breeding programs should prioritize phenological adjustments, particularly sowing date optimization, to align with the most favorable months of the year. Moreover, efforts should be made to enhance HLW and the number of grains per unit area in new wheat varieties to counteract the negative effects of rising temperatures. This research underscores the importance of ongoing monitoring and adaptation in agricultural practices to ensure yield resilience in the context of a changing climate.

An efficient triose phosphate synthesis and distribution in wheat provides tolerance to higher field temperatures

High temperatures in the field hinder bread wheat high-yield production, mainly because of the adverse effects of heat over photosynthesis. The Yaqui Valley, the main wheat producer region in Mexico, is a zone prone to have temperatures over 30°C. The aim of this work was to test the flag leaf photosynthetic performance in 10 bread wheat genotypes grown under high temperatures in the field. The study took place during two seasons (2019-2020 and 2020-2021). In each season, control seeds were sown in December, while heat-stressed were sown in late January to subject wheat to heat stress (HS) during the grain-filling stage. HS reduced Grain yield from 20 to 58% in the first season. HS did not reduce chlorophyll content and light-dependent reactions were unaffected in any of the tested genotypes. Rubisco, chloroplast fructose 1,6-biphosphatase (FBPase), and sucrose phosphate synthase (SPS) activities were measured spectrophotometrically. Rubisco activity did not decrease under HS in any of the genotypes. FBPase activity was reduced by HS indicating that triose phosphate flux to starch synthesis was reduced, while SPS was not affected, and thus, sucrose synthesis was maintained. HS reduced aerial biomass in the 10 chosen genotypes. Genotypes SOKWB.1, SOKWB.3, and BORLAUG100 maintained their yield under HS, pointing to a potential success in their introduction in this region for breeding heat-tolerant bread wheat.

CropQuant-Air: an AI-powered system to enable phenotypic analysis of yield- and performance-related traits using wheat canopy imagery collected by low-cost drones

As one of the most consumed stable foods around the world, wheat plays a crucial role in ensuring global food security. The ability to quantify key yield components under complex field conditions can help breeders and researchers assess wheat's yield performance effectively. Nevertheless, it is still challenging to conduct large-scale phenotyping to analyse canopy-level wheat spikes and relevant performance traits, in the field and in an automated manner. Here, we present CropQuant-Air, an AI-powered software system that combines state-of-the-art deep learning (DL) models and image processing algorithms to enable the detection of wheat spikes and phenotypic analysis using wheat canopy images acquired by low-cost drones. The system includes the YOLACT-Plot model for plot segmentation, an optimised YOLOv7 model for quantifying the spike number per m² (SNpM²) trait, and performance-related trait analysis using spectral and texture features at the canopy level. Besides using our labelled dataset for model training, we also employed the Global Wheat Head Detection dataset to incorporate varietal features into the DL models, facilitating us to perform reliable yield-based analysis from hundreds of varieties selected from main wheat production regions in China. Finally, we employed the SNpM² and performance traits to develop a yield classification model using the Extreme Gradient Boosting (XGBoost) ensemble and obtained significant positive correlations between the computational analysis results and manual scoring, indicating the reliability of CropQuant-Air. To ensure that our work could reach wider researchers, we created a graphical user interface for CropQuant-Air, so that non-expert users could readily use our work. We believe that our work represents valuable advances in yield-based field phenotyping and phenotypic analysis, providing useful and reliable toolkits to enable breeders, researchers, growers, and farmers to assess crop-yield performance in a cost-effective approach.

A 'wiring diagram' for sink strength traits impacting wheat yield potential

Identifying traits for improving sink strength is a bottleneck to increasing wheat yield. The interacting processes determining sink strength and yield potential are reviewed and visualized in a set of 'wiring diagrams', covering critical phases of development (and summarizing known underlying genetics). Using this framework, we reviewed and assembled the main traits determining sink strength and identified research gaps and potential hypotheses to be tested for achieving gains in sink strength. In pre-anthesis, grain number could be increased through: (i) enhanced spike growth associated with optimized floret development and/or a reduction in specific stem-internode lengths and (ii) improved fruiting efficiency through an accelerated rate of floret development, improved partitioning between spikes, or optimized spike cytokinin levels. In post-anthesis, grain, sink strength could be augmented through manipulation of grain size potential via ovary size and/or endosperm cell division and expansion. Prospects for improving spike vascular architecture to support all rapidly growing florets, enabling the improved flow of assimilate, are also discussed. Finally, we considered the prospects for enhancing grain weight realization in relation to genetic variation in stay-green traits as well as stem carbohydrate remobilization. The wiring diagrams provide a potential workspace for breeders and crop scientists to achieve yield gains in wheat and other field crops.

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.

TaGSNE, a WRKY transcription factor, overcomes the trade-off between grain size and grain number in common wheat and is associated with root development

Wheat is one of the world's major staple food crops, and breeding for improvement of grain yield is a priority under the scenarios of climate change and population growth. WRKY transcription factors are multifaceted regulators in plant growth, development, and responses to environmental stimuli. In this study, we identify the WRKY gene TaGSNE (Grain Size and Number Enhancer) in common wheat, and find that it has relatively high expression in leaves and roots, and is induced by multiple abiotic stresses. Eleven single-nucleotide polymorphisms were identified in TaGSNE, forming two haplotypes in multiple germplasm collections, named as TaGSNE-Hap-1 and TaGSNE-Hap-2. In a range of different environments, TaGSNE-Hap-2 was significantly associated with increases in thousand-grain weight (TGW; 3.0%) and spikelet number per spike (4.1%), as well as with deeper roots (10.1%) and increased root dry weight (8.3%) at the mid-grain-filling stage, and these were confirmed in backcross introgression populations. Furthermore, transgenic rice lines overexpressing TaGSNE had larger panicles, more grains, increased grain size, and increased grain yield relative to the wild-type control. Analysis of geographic and temporal distributions revealed that TaGSNE-Hap-2 is positively selected in China and Pakistan, and TaGSNE-Hap-1 in Europe. Our findings demonstrate that TaGSNE overcomes the trade-off between TGW/grain size and grain number, leading us to conclude that these elite haplotypes and their functional markers could be utilized in marker-assisted selection for breeding high-yielding varieties.

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.

Genes Impacting Grain Weight and Number in Wheat (Triticum aestivum L. ssp. aestivum)

The primary goal of common wheat (T. aestivum) breeding is increasing yield without negatively impacting the agronomic traits or product quality. Genetic approaches to improve the yield increasingly target genes that impact the grain weight and number. An energetic trade-off exists between the grain weight and grain number, the result of which is that most genes that increase the grain weight also decrease the grain number. QTL associated with grain weight and number have been identified throughout the hexaploid wheat genome, leading to the discovery of numerous genes that impact these traits. Genes that have been shown to impact these traits will be discussed in this review, including TaGNI, TaGW2, TaCKX6, TaGS5, TaDA1, WAPO1, and TaRht1. As more genes impacting the grain weight and number are characterized, the opportunity is increasingly available to improve common wheat agronomic yield by stacking the beneficial alleles. This review provides a synopsis of the genes that impact grain weight and number, and the most beneficial alleles of those genes with respect to increasing the yield in dryland and irrigated conditions. It also provides insight into some of the genetic mechanisms underpinning the trade-off between grain weight and number and their relationship to the source-to-sink pathway. These mechanisms include the plant size, the water soluble carbohydrate levels in plant tissue, the size and number of pericarp cells, the cytokinin and expansin levels in developing reproductive tissue, floral architecture and floral fertility.

A network modeling approach provides insights into the environment-specific yield architecture of wheat

Wheat (Triticum aestivum) yield is impacted by a diversity of developmental processes which interact with the environment during plant growth. This complex genetic architecture complicates identifying quantitative trait loci (QTL) that can be used to improve yield. Trait data collected on individual processes or components of yield have simpler genetic bases and can be used to model how QTL generate yield variation. The objectives of this experiment were to identify QTL affecting spike yield, evaluate how their effects on spike yield proceed from effects on component phenotypes, and to understand how the genetic basis of spike yield variation changes between environments. A 358 F5:6 RIL population developed from the cross of LA-95135 and SS-MPV-57 was evaluated in two replications at five locations over the 2018 and 2019 seasons. The parents were two soft red winter wheat cultivars differing in flowering, plant height, and yield component characters. Data on yield components and plant growth were used to assemble a structural equation model (SEM) to characterize the relationships between QTL, yield components and overall spike yield. The effects of major QTL on spike yield varied by environment, and their effects on total spike yield were proportionally smaller than their effects on component traits. This typically resulted from contrasting effects on component traits, where an increase in traits associated with kernel number was generally associated with a decrease in traits related to kernel size. In all, the complete set of identified QTL was sufficient to explain most of the spike yield variation observed within each environment. Still, the relative importance of individual QTL varied dramatically. Path analysis based on coefficients estimated through SEM demonstrated that these variations in effects resulted from both different effects of QTL on phenotypes and environment-by-environment differences in the effects of phenotypes on one another, providing a conceptual model for yield genotype-by-environment interactions in wheat.

Parent-of-Origin Effects on Seed Size Modify Heterosis Responses in Arabidopsis thaliana

Parent-of-origin effects arise when a phenotype depends on whether it is inherited maternally or paternally. Parent-of-origin effects can exert a strong influence on F1 seed size in flowering plants, an important agronomic and life-history trait that can contribute to biomass heterosis. Here we investigate the natural variation in the relative contributions of the maternal and paternal genomes to F1 seed size across 71 reciprocal pairs of F1 hybrid diploids and the parental effect on F1 seed size heterosis. We demonstrate that the paternally derived genome influences F1 seed size more significantly than previously appreciated. We further demonstrate (by disruption of parental genome dosage balance in F1 triploid seeds) that hybridity acts as an enhancer of genome dosage effects on F1 seed size, beyond that observed from hybridity or genome dosage effects on their own. Our findings indicate that interactions between genetic hybridity and parental genome dosage can enhance heterosis effects in plants, opening new avenues for boosting heterosis breeding in crop plants.

Green revolution to grain revolution: Florigen in the frontiers

Burgeoning human population dents, globally, the brimming buffer stock as well as gain in food grain production. However, an imminent global starvation was averted through precise scientific intervention and pragmatic policy changes in the 1960s and was eulogized as the "Green Revolution". Miracle rice and wheat obtained through morphometric changes in the ideotype of these two crops yielded bumper harvest that nucleated in Asia and translated into Latin America. The altered agronomic traits in these two crops were the result of tinkering with the phyto-hormone "Gibberellin'. Recently, another plant hormone 'Cytokinin' has gained prominence for its involvement in the grain revolution in rice and other field crops. Suo moto homeostasis of CK by the cytokinin oxidase enzyme governs the cardinal shoot apical meristem that produces new flowering primordia thereby enhancing grain number. Similarly, the flowering hormone 'Florigen' impacts sympodia formation, flowering, and fruit production in tomato. The role of heterozygosity induced heterosis by florigen in revolutionizing tomato production and cellular homeostasis of CK by CK oxidising enzyme (CKX) in enhancing rice production has been path-breaking. This review highlights role of phytohormones in grain revolution and crop specific fine-tuning of gibberellins, cytokinins and florigen to accomplish maximum yield potential in field crops.

Goyal A, Chaudhury A. Molecular and Transcriptional Regulation of Seed Development in Cereals: Present Status and Future Prospects

Cereals are a rich source of vitamins, minerals, carbohydrates, fats, oils and protein, making them the world’s most important source of nutrition. The influence of rising global population, as well as the emergence and spread of disease, has the major impact on cereal production. To meet the demand, there is a pressing need to increase cereal production. Optimal seed development is a key agronomical trait that contributes to crop yield. The seed development and maturation is a complex process that includes not only embryo and endosperm development, but also accompanied by huge physiological, biochemical, metabolic, molecular and transcriptional changes. This chapter discusses the growth of cereal seed and highlights the novel biological insights, with a focus on transgenic and new molecular breeding, as well as biotechnological intervention strategies that have improved crop yield in two major cereal crops, primarily wheat and rice, over the last 21 years (2000–2021).

Large-scale field phenotyping using backpack LiDAR and CropQuant-3D to measure structural variation in wheat

Plant phenomics bridges the gap between traits of agricultural importance and genomic information. Limitations of current field-based phenotyping solutions include mobility, affordability, throughput, accuracy, scalability, and the ability to analyze big data collected. Here, we present a large-scale phenotyping solution that combines a commercial backpack Light Detection and Ranging (LiDAR) device and our analytic software, CropQuant-3D, which have been applied jointly to phenotype wheat (Triticum aestivum) and associated 3D trait analysis. The use of LiDAR can acquire millions of 3D points to represent spatial features of crops, and CropQuant-3D can extract meaningful traits from large, complex point clouds. In a case study examining the response of wheat varieties to three different levels of nitrogen fertilization in field experiments, the combined solution differentiated significant genotype and treatment effects on crop growth and structural variation in the canopy, with strong correlations with manual measurements. Hence, we demonstrate that this system could consistently perform 3D trait analysis at a larger scale and more quickly than heretofore possible and addresses challenges in mobility, throughput, and scalability. To ensure our work could reach non-expert users, we developed an open-source graphical user interface for CropQuant-3D. We, therefore, believe that the combined system is easy-to-use and could be used as a reliable research tool in multi-location phenotyping for both crop research and breeding. Furthermore, together with the fast maturity of LiDAR technologies, the system has the potential for further development in accuracy and affordability, contributing to the resolution of the phenotyping bottleneck and exploiting available genomic resources more effectively.

Genetic mechanisms determining grain number distribution along the spike and their effect on yield components in wheat

The number of wheat grains is one of the major determinants of yield. Many quantitative trait loci (QTLs) and some causal genes such as GNI-A1 and WAPO-A1 that are associated with grain number per spike (GNS) have been identified, but the underlying mechanisms remain largely unknown. We analyzed QTLs for grain number and other related traits using 188 doubled haploid lines derived from the Japanese high-yield variety, Kitahonami, as a parent to elucidate the genetic mechanism determining grain number. The major QTLs for grain number at the apical, central, and basal parts of the spike were identified in different chromosomal regions. We considered GNI-A1 and WAPO-A1 as candidate genes controlling grain number at the central and basal parts of the spike, respectively. Kitahonami had the favorable 105Y allele of GNI-A1 and WAPO-A1b allele and unfavorable alleles of QTLs for grain number at the apical part of spikes. Pyramiding the favorable alleles of these QTLs significantly increased GNS without significantly reducing thousand-grain weight (TGW). In contrast, the accumulation of favorable alleles of QTLs for TGW significantly decreased GNS, whereas days to heading positively correlated with GNS. Late heading increased the spikelet number per spike, resulting in a higher GNS. Pyramiding of the QTLs for TGW and days to heading also altered the GNS. In conclusion, GNS is a complex trait controlled by many QTLs, and it is essential for breeding to design.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-021-01255-8.

Mitigating tradeoffs in plant breeding

Tradeoffs among plant traits help maintain relative fitness under unpredictable conditions and maximize reproductive success. However, modifying tradeoffs is a breeding challenge since many genes of minor effect are involved. The intensive crosstalk and fine-tuning between growth and defense responsive phytohormones via transcription factors optimizes growth, reproduction, and stress tolerance. There are regulating genes in grain crops that deploy diverse functions to overcome tradeoffs, e.g., miR-156-IPA1 regulates crosstalk between growth and defense to achieve high disease resistance and yield, while OsALDH2B1 loss of function causes imbalance among defense, growth, and reproduction in rice. GNI-A1 regulates seed number and weight in wheat by suppressing distal florets and altering assimilate distribution of proximal seeds in spikelets. Knocking out ABA-induced transcription repressors (AITRs) enhances abiotic stress adaptation without fitness cost in Arabidopsis. Deploying AITRs homologs in grain crops may facilitate breeding. This knowledge suggests overcoming tradeoffs through breeding may expose new ones.

Genetic dissection of grain architecture-related traits in a winter wheat population

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.

Mapping QTL for spike fertility and related traits in two doubled haploid wheat (Triticum aestivum L.) populations

BACKGROUND

In breeding programs, the selection of cultivars with the highest yield potential consisted in the selection of the yield per se, which resulted in cultivars with higher grains per spike (GN) and occasionally increased grain weight (GW) (main numerical components of the yield). In this study, quantitative trait loci (QTL) for GW, GN and spike fertility traits related to GN determination were mapped using two doubled haploid (DH) populations (Baguette Premium 11 × BioINTA 2002 and Baguette 19 × BioINTA 2002).

RESULTS

In total 305 QTL were identified for 14 traits, out of which 12 QTL were identified in more than three environments and explained more than 10% of the phenotypic variation in at least one environment. Eight hotspot regions were detected on chromosomes 1A, 2B, 3A, 5A, 5B, 7A and 7B in which at least two major and stable QTL sheared confidence intervals. QTL on two of these regions (R5A.1 and R5A.2) have previously been described, but the other six regions are novel.

CONCLUSIONS

Based on the pleiotropic analysis within a robust physiological model we conclude that two hotspot genomic regions (R5A.1 and R5A.2) together with the QGW.perg-6B are of high relevance to be used in marker assisted selection in order to improve the spike yield potential. All the QTL identified for the spike related traits are the first step to search for their candidate genes, which will allow their better manipulation in the future.

Dissecting the trade-off of grain number and size in wheat

Principal component and meta-QTL analyses identified genetic loci affecting the trade-off of wheat grain number and size, which could provide opportunities to optimize local breeding strategies for further yield improvement. Grain yield of wheat is complex, and its physiological and genetic bases remain largely unknown. Using the Forno/Oberkulmer recombinant inbred lines, this study validated the negative phenotypic relationships between thousand grain weight (TGW) and grain number components. This trade-off might be alleviated at the population level by early anthesis and at the shoot level by higher shoot biomass. Principal component (PC) analysis revealed three useful PCs, of which both PC1 and PC3 were positively associated with grain yield and grains m^-2 through increased spikes m^-2 (for PC1) or grains per spike (for PC3), while PC2 primarily reflected the trade-off of grain number and TGW. Quantitative trait locus (QTL) mapping detected eight and seven loci for PC1 and PC2, respectively, on chromosomes 1D, 2A, 3A, 3B, 4A, 4B, 5A and 7B, individually explaining 11.7‒29.3% of phenotypic variations. Using the 1203 QTLs published previously, a meta-analysis was performed to reveal 12, 21, 37 and 54 genomic regions (MQTLs) affecting grains m^-2, spikes m^-2, grains per spike and TGW, respectively. Moreover, 67 MQTLs (96%) for grain number were coincided with the TGW MQTLs, with reverse phenotypic effects, suggesting intensive genetic trade-off between grain number and size. The AGP2 gene, which encodes ADP-glucose pyrophosphorylase determining TGW, was found by haplotype analysis in the Forno/Oberkulmer population to affect grain number oppositely, indicating this trade-off at the gene level. Appropriate combinations of the QTLs/genes for local breeding targets, such as higher grain number or larger grains, therefore, would be critical to achieve future yield gains.

Improving crop yield and resilience through optimization of photosynthesis: panacea or pipe dream?

Increasing the speed of breeding to enhance crop productivity and adaptation to abiotic stresses is urgently needed. The perception that a second Green Revolution should be implemented is widely established within the scientific community and among stakeholders. In recent decades, different alternatives have been proposed for increasing crop yield through manipulation of leaf photosynthetic efficiency. However, none of these has delivered practical or relevant outputs. Indeed, the actual increases in photosynthetic rates are not expected to translate into yield increases beyond 10-15%. Furthermore, instantaneous rates of leaf photosynthesis are not necessarily the reference target for research. Yield is the result of canopy photosynthesis, understood as the contribution of laminar and non-laminar organs over time, within which concepts such as canopy architecture, stay-green, or non-laminar photosynthesis need to be taken into account. Moreover, retrospective studies show that photosynthetic improvements have been more common at the canopy level. Nevertheless, it is crucial to place canopy photosynthesis in the context of whole-plant functioning, which includes sink-source balance and transport of photoassimilates, and the availability and uptake of nutrients, such as nitrogen in particular. Overcoming this challenge will only be feasible if a multiscale crop focus combined with a multidisciplinary scientific approach is adopted.

The impact of water deficit and heat stress combination on the molecular response, physiology, and seed production of soybean

A combination of drought and heat stress, occurring at the vegetative or reproductive growth phase of many different crops can have a devastating impact on yield. In soybean (Glycine max), a considerable effort has been made to develop genotypes with enhanced yield production under conditions of drought or heat stress. However, how these genotypes perform in terms of growth, physiological responses, and most importantly seed production, under conditions of drought and heat combination is mostly unknown. Here, we studied the impact of water deficit and heat stress combination on the physiology, seed production, and yield per plant of two soybean genotypes, Magellan and Plant Introduction (PI) 548313, that differ in their reproductive responses to heat stress. Our findings reveal that although PI 548313 produced more seeds than Magellan under conditions of heat stress, under conditions of water deficit, and heat stress combination its seed production decreased. Because the number of flowers and pollen germination of PI 548313 remained high under heat or water deficit and heat combination, the reduced seed production exhibited by PI 548313 under the stress combination could be a result of processes that occur at the stigma, ovaries and/or other parts of the flower following pollen germination.

Genetic analysis of wheat (Triticum aestivum) adaptation to heat stress

Adaptation to abiotic stresses such as high-temperature conditions should be considered as its independent components of total performance and responsiveness. Understanding and identifying improved adaptation to abiotic stresses such as heat stress has been the focus of a number of studies in recent decades. However, confusing and potentially misleading terminology has made progress difficult and hard to apply within breeding programs selecting for improved adaption to heat stress conditions. This study proposes that adaption to heat stress (and other abiotic stresses) be considered as the combination of total performance and responsiveness to heat stress. In this study, 1413 doubled haploid lines from seven populations were screened through a controlled environment assay, subjecting plants to three consecutive eight hour days of an air temperature of 36 °C and a wind speed of 40 km h^-1, 10 days after the end of anthesis. QTL mapping identified a total of 96 QTL for grain yield determining traits and anthesis date with nine correlating to responsiveness, 72 for total performance and 15 for anthesis date. Responsiveness QTL were found both collocated with other performance QTL as well as independently. A sound understanding of genomic regions associated with total performance and responsiveness will be important for breeders. Genomic regions of total performance, those that show higher performance that is stable under both stressed and non-stressed conditions, potentially offer significant opportunities to breeders. We propose this as a definition and selection target that has not previously been defined for heat stress adaptation.

Dissection of Genetic Basis Underpinning Kernel Weight-Related Traits in Common Wheat

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.

Overcoming the trade-off between grain weight and number in wheat by the ectopic expression of expansin in developing seeds leads to increased yield potential

Wheat is the most widely grown crop globally, providing 20% of all human calories and protein. Achieving step changes in genetic yield potential is crucial to ensure food security, but efforts are thwarted by an apparent trade-off between grain size and number. Expansins are proteins that play important roles in plant growth by enhancing stress relaxation in the cell wall, which constrains cell expansion. Here, we describe how targeted overexpression of an α-expansin in early developing wheat seeds leads to a significant increase in grain size without a negative effect on grain number, resulting in a yield boost under field conditions. The best-performing transgenic line yielded 12.3% higher average grain weight than the control, and this translated to an increase in grain yield of 11.3% in field experiments using an agronomically appropriate plant density. This targeted transgenic approach provides an opportunity to overcome a common bottleneck to yield improvement across many crops.

Elucidating the genetics of grain yield and stress-resilience in bread wheat using a large-scale genome-wide association mapping study with 55,568 lines

Wheat grain yield (GY) improvement using genomic tools is important for achieving yield breakthroughs. To dissect the genetic architecture of wheat GY potential and stress-resilience, we have designed this large-scale genome-wide association study using 100 datasets, comprising 105,000 GY observations from 55,568 wheat lines evaluated between 2003 and 2019 by the International Maize and Wheat Improvement Center and national partners. We report 801 GY-associated genotyping-by-sequencing markers significant in more than one dataset and the highest number of them were on chromosomes 2A, 6B, 6A, 5B, 1B and 7B. We then used the linkage disequilibrium (LD) between the consistently significant markers to designate 214 GY-associated LD-blocks and observed that 84.5% of the 58 GY-associated LD-blocks in severe-drought, 100% of the 48 GY-associated LD-blocks in early-heat and 85.9% of the 71 GY-associated LD-blocks in late-heat, overlapped with the GY-associated LD-blocks in the irrigated-bed planting environment, substantiating that simultaneous improvement for GY potential and stress-resilience is feasible. Furthermore, we generated the GY-associated marker profiles and analyzed the GY favorable allele frequencies for a large panel of 73,142 wheat lines, resulting in 44.5 million datapoints. Overall, the extensive resources presented in this study provide great opportunities to accelerate breeding for high-yielding and stress-resilient wheat varieties.

The Haplotype-Based Analysis of Aegilops tauschii Introgression Into Hard Red Winter Wheat and Its Impact on Productivity Traits

The introgression from wild relatives have a great potential to broaden the availability of beneficial allelic diversity for crop improvement in breeding programs. Here, we assessed the impact of the introgression from 21 diverse accessions of Aegilops tauschii, the diploid ancestor of the wheat D genome, into 6 hard red winter wheat cultivars on yield and yield component traits. We used 5.2 million imputed D genome SNPs identified by the whole-genome sequencing of parental lines and the sequence-based genotyping of introgression population, including 351 BC₁F_3:5 lines. Phenotyping data collected from the irrigated and non-irrigated field trials revealed that up to 23% of the introgression lines (ILs) produce more grain than the parents and check cultivars. Based on 16 yield stability statistics, the yield of 12 ILs (3.4%) was stable across treatments, years, and locations; 5 of these lines were also high yielding lines, producing 9.8% more grain than the average yield of check cultivars. The most significant SNP- and haplotype-trait associations were identified on chromosome arms 2DS and 6DL for the spikelet number per spike (SNS), on chromosome arms 2DS, 3DS, 5DS, and 7DS for grain length (GL) and on chromosome arms 1DL, 2DS, 6DL, and 7DS for grain width (GW). The introgression of haplotypes from A. tauschii parents was associated with an increase in SNS, which was positively correlated with a heading date (HD), whereas the haplotypes from hexaploid wheat parents were associated with an increase in GW. We show that the haplotypes on 2DS associated with an increase in the spikelet number and HD are linked with multiple introgressed alleles of Ppd-D1 identified by the whole-genome sequencing of A. tauschii parents. Meanwhile, some introgressed haplotypes exhibited significant pleiotropic effects with the direction of effects on the yield component traits being largely consistent with the previously reported trade-offs, there were haplotype combinations associated with the positive trends in yield. The characterized repertoire of the introgressed haplotypes derived from A. tauschii accessions with the combined positive effects on yield and yield component traits in elite germplasm provides a valuable source of alleles for improving the productivity of winter wheat by optimizing the contribution of component traits to yield.

Detection of genomic regions associated with tiller number in Iranian bread wheat under different water regimes using genome-wide association study

Two of the important traits for wheat yield are tiller and fertile tiller number, both of which have been thought to increase cereal yield in favorable and unfavorable environments. A total of 6,349 single nucleotide polymorphism (SNP) markers from the 15 K wheat Infinium array were employed for genome-wide association study (GWAS) of tillering number traits, generating a physical distance of 14,041.6 Mb based on the IWGSC wheat genome sequence. GWAS analysis using Fixed and random model Circulating Probability Unification (FarmCPU) identified a total of 47 significant marker-trait associations (MTAs) for total tiller number (TTN) and fertile tiller number (FTN) in Iranian bread wheat under different water regimes. After applying a 5% false discovery rate (FDR) threshold, a total of 13 and 11 MTAs distributed on 10 chromosomes were found to be significantly associated with TTN and FTN, respectively. Linked single nucleotide polymorphisms for IWB39005 (2A) and IWB44377 (7A) were highly significantly associated (FDR < 0.01) with TTN and FTN traits. Moreover, to validate GWAS results, meta-analysis was performed and 30 meta-QTL regions were identified on 11 chromosomes. The integration of GWAS and meta-QTLs revealed that tillering trait in wheat is a complex trait which is conditioned by the combined effects of minor changes in multiple genes. The information provided by this study can enrich the currently available candidate genes and genetic resources pools, offering evidence for subsequent analysis of genetic adaptation of wheat to different climatic conditions of Iran and other countries.

Identification of regions under selection and loci controlling agronomic traits in a soft red winter wheat population

Comprehensive information of a breeding population is a necessity to design promising crosses. This study was conducted to characterize a soft red winter wheat breeding population that was subject of intensive germplasm introductions and introgression from exotic germplasm. We used genome-wide markers and phenotypic assessment to identify signatures of selection and loci controlling agronomic traits in a soft red winter wheat population. The study of linkage disequilibrium (LD) revealed that the extent of LD and its decay varied among chromosomes with chromosomes 2B and 7D showing the most extended islands of high-LD with slow rates of decay. Four sub-populations, two with North American origin and two with Australian and Chinese origins, were identified. Genome-wide scans for selection signatures using F_ST and hapFLK identified 13 genomic regions under selection, of which five loci (LT, Fr-A2, Vrn-A1, Vrn-B1, Vrn3) were associated with environmental adaptation and two loci were associated with disease resistance genes (Sr36 and Fhb1). Genome-wide association studies identified major loci controlling yield and yield related traits. For days to heading and plant height, major loci with effects sizes of 2.2 days and 5 cm were identified on chromosomes 7B and 6A respectively. For test weight, number of spikes per square meter, and number of kernels per square meter, large effect loci were identified on chromosomes 1A, 4B, and 5A, respectively. However, for yield alone, no major loci were detected. A combination of selection for large effect loci for yield components and genomic selection could be a promising approach for yield improvement.

Breeder friendly phenotyping

The word phenotyping can nowadays invoke visions of a drone or phenocart moving swiftly across research plots collecting high-resolution data sets on a wide array of traits. This has been made possible by recent advances in sensor technology and data processing. Nonetheless, more comprehensive often destructive phenotyping still has much to offer in breeding as well as research. This review considers the 'breeder friendliness' of phenotyping within three main domains: (i) the 'minimum data set', where being 'handy' or accessible and easy to collect and use is paramount, visual assessment often being preferred; (ii) the high throughput phenotyping (HTP), relatively new for most breeders, and requiring significantly greater investment with technical hurdles for implementation and a steeper learning curve than the minimum data set; (iii) detailed characterization or 'precision' phenotyping, typically customized for a set of traits associated with a target environment and requiring significant time and resources. While having been the subject of debate in the past, extra investment for phenotyping is becoming more accepted to capitalize on recent developments in crop genomics and prediction models, that can be built from the high-throughput and detailed precision phenotypes. This review considers different contexts for phenotyping, including breeding, exploration of genetic resources, parent building and translational research to deliver other new breeding resources, and how the different categories of phenotyping listed above apply to each. Some of the same tools and rules of thumb apply equally well to phenotyping for genetic analysis of complex traits and gene discovery.

QTL mapping for grain yield-related traits in bread wheat via SNP-based selective genotyping

We identified four chromosome regions harboring QTL for grain yield-related traits, and breeder-friendly KASP markers were developed and validated for marker-assisted selection. Identification of major stable quantitative trait loci (QTL) for grain yield-related traits is important for yield potential improvement in wheat breeding. In the present study, 266 recombinant inbred lines (RILs) derived from a cross between Zhongmai 871 (ZM871) and its sister line Zhongmai 895 (ZM895) were evaluated for thousand grain weight (TGW), grain length (GL), grain width (GW), and grain number per spike (GNS) in 10 environments and for grain filling rate in six environments. Sixty RILs, with 30 higher and 30 lower TGW, respectively, were genotyped using the wheat 660 K SNP array for preliminary QTL mapping. Four genetic regions on chromosomes 1AL, 2BS, 3AL, and 5B were identified to have a significant effect on TGW-related traits. A set of Kompetitive Allele Specific PCR markers were converted from the SNP markers on the above target chromosomes and used to genotype all 266 RILs. The mapping results confirmed the QTL named Qgw.caas-1AL, Qgl.caas-3AL, Qtgw.caas-5B, and Qgl.caas-5BS on the targeted chromosomes, explaining 5.0-20.6%, 5.7-15.7%, 5.5-17.3%, and 12.5-20.5% of the phenotypic variation for GW, GL, TGW, and GL, respectively. A novel major QTL for GNS on chromosome 5BS, explaining 5.2-15.2% of the phenotypic variation, was identified across eight environments. These QTL were further validated using BC₁F₄ populations derived from backcrosses ZM871/ZM895//ZM871 (121 lines) and ZM871/ZM895//ZM895 (175 lines) and 186 advanced breeding lines. Collectively, selective genotyping is a simple, economic, and effective approach for rapid QTL mapping and can be generally applied to genetic mapping studies for important agronomic traits.

QTL analysis and fine mapping of a QTL for yield-related traits in wheat grown in dry and hot environments

Genetic control of grain yield and phenology was examined in the Excalibur/Kukri doubled haploid mapping population grown in 32 field experiments across the climatic zones of southern Australia, India and north-western Mexico where the wheat crop experiences drought and heat stress. A total of 128 QTL were identified for four traits: grain yield, thousand grain weight (TGW), days to heading and grain filling duration. These QTL included 24 QTL for yield and 27 for TGW, showing significant interactions with the environment (Q * E). We also identified 14 QTL with a significant, small main effects on yield across environments. The study focussed on a region of chromosome 1B where two main effect QTL were found for yield and TGW without the confounding effect of phenology. Excalibur was the source of favourable alleles: QYld.aww-1B.2 with a peak at 149.5-150.1 cM and QTgw.aww-1B at 168.5-171.4 cM. We developed near isogenic lines (NIL) for the interval including QYld.aww-1B.2 and QTgw.aww-1B and evaluated them under semi-controlled conditions. Significant differences in four pairs of NIL were observed for grain yield but not for TGW, confirming a positive effect of the Excalibur allele for QYld.aww-1B.2. The interval containing QYld.aww-1B.2 was narrowed down to 2.9 cM which corresponded to a 2.2 Mbp genomic region on the chromosome 1B genomic reference sequence of cv. Chinese Spring and contained 39 predicted genes.

Identification of quantitative trait loci for kernel traits in a wheat cultivar Chuannong16

Background

Kernel length (KL), kernel width (KW) and thousand-kernel weight (TKW) are key agronomic traits in wheat breeding. Chuannong16 (‘CN16’) is a commercial cultivar with significantly longer kernels than the line ‘20828’. To identify and characterize potential alleles from CN16 controlling KL, the previously developed recombinant inbred line (RIL) population derived from the cross ‘20828’ × ‘CN16’ and the genetic map constructed by the Wheat55K SNP array and SSR markers were used to perform quantitative trait locus/loci (QTL) analyses for kernel traits.

Results

A total of 11 putative QTL associated with kernel traits were identified and they were located on chromosomes 1A (2 QTL), 2B (2 QTL), 2D (3 QTL), 3D, 4A, 6A, and 7A, respectively. Among them, three major QTL, QKL.sicau-2D, QKW.sicau-2D and QTKW.sicau-2D, controlling KL, KW and TKW, respectively, were detected in three different environments. Respectively, they explained 10.88–18.85%, 17.21–21.49% and 10.01–23.20% of the phenotypic variance. Further, they were genetically mapped in the same interval on chromosome 2DS. A previously developed kompetitive allele-specific PCR (KASP) marker KASP-AX-94721936 was integrated in the genetic map and QTL re-mapping finally located the three major QTL in a 1- cM region flanked by AX-111096297 and KASP-AX-94721936. Another two co-located QTL intervals for KL and TKW were also identified. A few predicted genes involved in regulation of kernel growth and development were identified in the intervals of these identified QTL. Significant relationships between kernel traits and spikelet number per spike and anthesis date were detected and discussed.

Conclusions

Three major and stably expressed QTL associated with KL, KW, and TKW were identified. A KASP marker tightly linked to these three major QTL was integrated. These findings provide information for subsequent fine mapping and cloning the three co-localized major QTL for kernel traits.

Use of near-isogenic lines to precisely map and validate a major QTL for grain weight on chromosome 4AL in bread wheat (Triticum aestivum L.)

This study precisely mapped and validated a major quantitative trait locus (QTL) on chromosome 4AL for thousand-grain weight in wheat using multiple near-isogenic lines. Thousand-grain weight (TGW) is an essential yield component. Following the previous identification of a major QTL for TGW within the interval of 15.7 cM (92.7-108.4 cM) on chromosome 4AL using the Nongda3338 (ND3338)/Jingdong6 (JD6) doubled haploid population, the aim of this study was to perform more precise mapping and validate the genetic effect of the QTL. Multiple near-isogenic lines (NILs) were developed using ND3338 as the recurrent parent through marker-assisted selection. Based on five independent BC₃F_3:4 segregating populations derived from BC₃F₃ plants with different heterozygous segments for the target QTL site and the results of genotyping analysis performed using the Wheat660 K SNP array, it was possible to delimit the QTL region to a physical interval of approximately 6.5 Mb (677.11-683.61 Mb, IWGSC Ref Seq v1.0). Field trials across multiple environments showed that NILs^JD6 had a consistent effect on increasing the TGW by 5.16-27.48% and decreasing the grain number per spike (GNS) by 3.98-32.91% compared to the corresponding NILs^ND3338, which exhibited locus-specific TGW-GNS trade-offs. Moreover, by using RNA sequencing (RNA-Seq) of whole grains at 10 days after pollination stage of multiple NILs, we found that differentially expressed genes between the NIL pairs were significantly enriched for cell cycle and the replication of chromosome-related genes, hence affecting cell division and cell proliferation. Overall, our results provide a basis for map-based cloning of the major QTL and determining the mechanisms underlying TGW-GNS trade-offs in wheat, which would help to fine-tune these two components and maximize the grain yield for breeders.

Field-grown transgenic wheat expressing the sunflower gene HaHB4 significantly outyields the wild type

HaHB4 is a sunflower transcription factor belonging to the homeodomain-leucine zipper I family whose ectopic expression in Arabidopsis triggers drought tolerance. The use of PCR to clone the HaHB4 coding sequence for wheat transformation caused unprogrammed mutations producing subtle differences in its activation ability in yeast. Transgenic wheat plants carrying a mutated version of HaHB4 were tested in 37 field experiments. A selected transgenic line yielded 6% more (P<0.001) and had 9.4% larger water use efficiency (P<0.02) than its control across the evaluated environments. Differences in grain yield between cultivars were explained by the 8% improvement in grain number per square meter (P<0.0001), and were more pronounced in stress (16% benefit) than in non-stress conditions (3% benefit), reaching a maximum of 97% in one of the driest environments. Increased grain number per square meter of transgenic plants was accompanied by positive trends in spikelet numbers per spike, tillers per plant, and fertile florets per plant. The gene transcripts associated with abiotic stress showed that HaHB4's action was not dependent on the response triggered either by RD19 or by DREB1a, traditional candidates related to water deficit responses. HaHB4 enabled wheat to show some of the benefits of a species highly adapted to water scarcity, especially in marginal regions characterized by frequent droughts.

Genetic modification of spikelet arrangement in wheat increases grain number without significantly affecting grain weight

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 bh^t-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 bh^t-A1 NILs using the Genotyping-By-Sequencing approach revealed that the size of the introgressed donor segments carrying bh^t-A1 ranged from 2.3 to 38 cM. The size of the shortest donor segment introgressed into bh^t-A1 NILs was estimated to be 9.8 mega base pairs (Mbp). Phenotypic analysis showed that FL-bh^t-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 (SDW_h). The increased SDW_h was accompanied by up to 23% more grains per spike. More interestingly, thousand kernel weight (TKW) did not show significant differences between FL-bh^t-A1-NILs and Floradur, suggesting that besides increasing spikelet number, bh^t-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-bh^t-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.

Role of Modelling in International Crop Research: Overview and Some Case Studies

Crop modelling has the potential to contribute to global food and nutrition security. This paper briefly examines the history of crop modelling by international crop research centres of the CGIAR (formerly Consultative Group on International Agricultural Research but now known simply as CGIAR), whose primary focus is on less developed countries. Basic principles of crop modelling building up to a Genotype × Environment × Management × Socioeconomic (G × E × M × S) paradigm, are explained. Modelling has contributed to better understanding of crop performance and yield gaps, better prediction of pest and insect outbreaks, and improving the efficiency of crop management including irrigation systems and optimization of planting dates. New developments include, for example, use of remote sensed data and mobile phone technology linked to crop management decision support models, data sharing in the new era of big data, and the use of genomic selection and crop simulation models linked to environmental data to help make crop breeding decisions. Socio-economic applications include foresight analysis of agricultural systems under global change scenarios, and the consequences of potential food system shocks are also described. These approaches are discussed in this paper which also calls for closer collaboration among disciplines in order to better serve the crop research and development communities by providing model based recommendations ranging from policy development at the level of governmental agencies to direct crop management support for resource poor farmers.

Final grain weight is not limited by the activity of key starch-synthesising enzymes during grain filling in wheat

Since starch is by far the major component of the mature wheat grain, it has been assumed that variation in the capacity for starch synthesis during grain filling can influence final grain weight. We investigated this assumption by studying a total of 54 wheat genotypes including elite varieties and landraces that were grown in two successive years in fields in the east of England. The weight, water content, sugars, starch, and maximum catalytic activities of two enzymes of starch biosynthesis, ADP-glucose pyrophosphorylase and soluble starch synthase, were measured during grain filling. The relationships between these variables and the weights and starch contents of mature grains were analysed. Final grain weight showed few or no significant correlations with enzyme activities, sugar levels, or starch content during grain filling, or with starch content at maturity. We conclude that neither sugar availability nor enzymatic capacity for starch synthesis during grain filling significantly influenced final grain weight in our field conditions. We suggest that final grain weight may be largely determined by developmental processes prior to grain filling. Starch accumulation then fills the grain to a physical limit set by developmental processes. This conclusion is in accord with those from previous studies in which source or sink strength has been artificially manipulated.

QTL identification and KASP marker development for productive tiller and fertile spikelet numbers in two high-yielding hard white spring wheat cultivars

Selecting high-yielding wheat cultivars with more productive tillers per unit area (PTN) combined with more fertile spikelets per spike (fSNS) is difficult. QTL mapping of these traits may aid understanding of this bottleneck and accelerate precision breeding for high yield via marker-assisted selection. PTN and fSNS were assessed in four to five trials from 2015 to 2017 in a doubled haploid population derived from two high-yielding cultivars "UI Platinum" and "SY Capstone." Two QTL for PTN (QPTN.uia-4A and QPTN.uia-6A) and four QTL for fSNS (QfSNS.uia-4A, QfSNS.uia-5A, QfSNS.uia-6A, and QfSNS.uia-7A) were identified. The effects of the QTL were primarily additive and, therefore, pyramiding of multiple QTL may increase PTN and fSNS. However, the two QTL for PTN were positioned in the flanking regions for the two QTL for fSNS on chromosomes 4A and 6A, respectively, suggesting either possible pleiotropic effect of the same QTL or tightly linked QTL and explaining the difficulty of selecting both high PTN and fSNS in phenotypic selection. Kompetitive allele-specific PCR (KASP) markers for all identified QTL were developed and validated in a recombinant inbred line (RIL) population derived from the same two cultivars. In addition, KASP markers for three of the QTL (QPTN.uia-6A, QfSNS.uia-6A, and QfSNS.uia-7A) were further validated in a diverse spring wheat panel, indicating their usefulness under different genetic backgrounds. These KASP markers could be used by wheat breeders to select high PTN and fSNS.

Prospects and Challenges of Applied Genomic Selection-A New Paradigm in Breeding for Grain Yield in Bread Wheat

Genomic selection (GS) has been promising for increasing genetic gains in several species. Therefore, we evaluated the potential integration of GS for grain yield (GY) in bread wheat ( L.) in CIMMYT's elite yield trial nurseries. We observed that the genomic prediction accuracies within nurseries (0.44 and 0.35) were substantially higher than across-nursery accuracies (0.15 and 0.05) for GY evaluated in the bed and flat planting systems, respectively. The accuracies from using only a subset of 251 genotyping-by-sequencing markers were comparable to the accuracies using all 2038 markers. We also used the item-based collaborative filtering approach for incorporating other related traits in predicting GY and observed that it outperformed genomic predictions across nurseries, but was less predictive when trait correlations with GY were low. Furthermore, we compared GS and phenotypic selections (PS) and observed that at a selection intensity of 0.5, GS could select a maximum of 70.9 and 61.5% of the top lines and discard 71.5 and 60.5% of the poor lines selected or discarded by PS within and across nurseries, respectively. Comparisons of GS and pedigree-based predictions revealed that the advantage of GS over the pedigree was moderate in populations without full-sibs. However, GS was less advantageous for within-family selections in elite families with few full-sibs and minimal Mendelian sampling variance. Overall, our results demonstrate the importance of applying GS for GY at the appropriate stage of the breeding cycle, and we speculate that gains can be maximized if it is implemented in early-generation within-family selections.

Novel Grain Weight Loci Revealed in a Cross between Cultivated and Wild Sorghum

Grain weight has increased during domestication of cereals. Together with grain number it determines yield, but the two are often negatively correlated. Understanding the genetic architecture of grain weight and its relationship with grain number is critical to enhance crop yield. Sorghum is an important food, feed, and biofuel crop well-known for its adaptation to drought and heat. This study aimed to dissect the genetic basis of thousand grain weight (TGW) in a BCF population between a domesticated sorghum accession and its wild progenitor, subsp. and investigate its relationship with grain number. Thousand grain weight, grain number, and yield were measured in field trials in two successive years. A strong negative correlation between TGW and grain number was observed in both trials. In total, 17 TGW quantitative trait loci (QTL) were identified, with 11 of them exhibiting an opposing effect on grain number, implying the correlation between TGW and grain number is due to pleiotropy. Nine grain size candidate genes were identified within 6 TGW QTL, and of these 5 showed signatures of selection during sorghum domestication. Large-effect QTL in this study that have not been identified previously in cultivated sorghum were found to contain candidate genes with domestication signal, indicating that these QTL were affected during sorghum domestication. This study sheds new light on the genetic basis of TGW, its relationship with grain number, and sorghum domestication.

Effect of Ppd-A1 and Ppd-B1 Allelic Variants on Grain Number and Thousand Kernel Weight of Durum Wheat and Their Impact on Final Grain Yield

The main yield components in durum wheat are grain number per unit area (GN) and thousand kernel weight (TKW), both of which are affected by environmental conditions. The most critical developmental stage for their determination is flowering time, which partly depends on photoperiod sensitivity genes at Ppd-1 loci. Fifteen field experiments, involving 23 spring durum wheat genotypes containing all known allelic variants at the PHOTOPERIOD RESPONSE LOCUS (Ppd-A1 and Ppd-B1) were carried out at three sites at latitudes ranging from 41° to 27° N (Spain, Mexico-north, and Mexico-south, the latter in spring planting). Allele GS100 at Ppd-A1, which causes photoperiod insensitivity and results in early-flowering genotypes, tended to increase TKW and yield, albeit not substantially. Allele Ppd-B1a, also causing photoperiod insensitivity, did not affect flowering time or grain yield. Genotypes carrying the Ppd-B1b allele conferring photoperiod sensitivity had consistently higher GN, which did not translate into higher yield due to under-compensation in TKW. This increased GN was due to a greater number of grains spike-1 as a result of a higher number of spikelets spike-1. Daylength from double ridge to terminal spikelet stage was strongly and positively associated with the number of spikelets spike-1 in Spain. This association was not found in the Mexico sites, thereby indicating that Ppd-B1b had an intrinsic effect on spikelets spike-1 independently of environmental cues. Our results suggest that, in environments where yield is limited by the incapacity to produce a high GN, selecting for Ppd-B1b may be advisable.

Genetic analysis of multi-environmental spring wheat trials identifies genomic regions for locus-specific trade-offs for grain weight and grain number

GWAS on multi-environment data identified genomic regions associated with trade-offs for grain weight and grain number. Grain yield (GY) can be dissected into its components thousand grain weight (TGW) and grain number (GN), but little has been achieved in assessing the trade-off between them in spring wheat. In the present study, the Wheat Association Mapping Initiative (WAMI) panel of 287 elite spring bread wheat lines was phenotyped for GY, GN, and TGW in ten environments across different wheat growing regions in Mexico, South Asia, and North Africa. The panel genotyped with the 90 K Illumina Infinitum SNP array resulted in 26,814 SNPs for genome-wide association study (GWAS). Statistical analysis of the multi-environmental data for GY, GN, and TGW observed repeatability estimates of 0.76, 0.62, and 0.95, respectively. GWAS on BLUPs of combined environment analysis identified 38 loci associated with the traits. Among them four loci-6A (85 cM), 5A (98 cM), 3B (99 cM), and 2B (96 cM)-were associated with multiple traits. The study identified two loci that showed positive association between GY and TGW, with allelic substitution effects of 4% (GY) and 1.7% (TGW) for 6A locus and 0.2% (GY) and 7.2% (TGW) for 2B locus. The locus in chromosome 6A (79-85 cM) harbored a gene TaGW2-6A. We also identified that a combination of markers associated with GY, TGW, and GN together explained higher variation for GY (32%), than the markers associated with GY alone (27%). The marker-trait associations from the present study can be used for marker-assisted selection (MAS) and to discover the underlying genes for these traits in spring wheat.

Identification and validation of a major chromosome region for high grain number per spike under meiotic stage water stress in wheat (Triticum aestivum L.)

Grain number is a major trait for wheat yield under dryland farming. An International Triticeae Mapping Initiative (ITMI) mapping population comprising 105 recombinant inbred lines (RIL) developed from a cross between a Synthetic hexaploid wheat (Triticum aestivum) ‘W7984’ and a spring wheat variety ‘Opata M85’ was used to identify quantitative trait loci (QTL) associated with grain number per spike under two treatment conditions, normal watering and water stress during meiosis. Two major QTL for grain number per spike on the main stem Q.Gnu.uwa-5A-1 and Q.Gnu.uwa-5A-2 with phenotypic variations of 25.71% and 24.93%, respectively, were detected on the long arm of chromosome 5A when plants were exposed to water stress during meiosis. One QTL (Q.Gnu.uwa-2A) with a LOD score of 2.8 was detected on the long arm of chromosome 2A under normal watering condition. The alleles associated with higher grain number per spike under different treatment conditions came from the Synthetic W7984 parent. Two populations developed from crosses Synthetic W7984 × Lang and Synthetic W7984 × Westonia were used to validate the identified QTL under water stress during meiosis. SSR markers Xbarc230 and Xbarc319 linked with the identified QTL on chromosome 5AL were validated in the two F_2:4 segregating populations. These closely linked SSR markers could potentially be utilized in marker-assisted selection to reduce yield loss in regions where water stress during meiosis occurs frequently. The identified QTL can be incorporated into elite lines / cultivars to improve wheat grain yield.

A novel allele of TaGW2-A1 is located in a finely mapped QTL that increases grain weight but decreases grain number in wheat (Triticum aestivum L.)

A novel TaGW2-A1 allele was identified from a stable, robust QTL region, which is pleiotropic for thousand grain weight, grain number per spike, and grain morphometric parameters in wheat. Thousand grain weight (TGW) and grain number per spike (GNS) are two crucial determinants of wheat spike yield, and genetic dissection of their relationships can help to fine-tune these two components and maximize grain yield. By evaluating 191 recombinant inbred lines in 11 field trials, we identified five genomic regions on chromosomes 1B, 3A, 3B, 5B, or 7A that solely influenced either TGW or GNS, and a further region on chromosome 6A that concurrently affected TGW and GNS. The QTL of interest on chromosome 6A, which was flanked by wsnp_BE490604A_Ta_2_1 and wsnp_RFL_Contig1340_448996 and designated as QTgw/Gns.cau-6A, was finely mapped to a genetic interval shorter than 0.538 cM using near isogenic lines (NILs). The elite NILs of QTgw/Gns.cau-6A increased TGW by 8.33%, but decreased GNS by 3.05% in six field trials. Grain Weight 2 (TaGW2-A1), a well-characterized gene that negatively regulates TGW and grain width in wheat, was located within the finely mapped interval of QTgw/Gns.cau-6A. A novel and rare TaGW2-A1 allele with a 114-bp deletion in the 5' flanking region was identified in the parent with higher TGW, and it reduced TaGW2-A1 promoter activity and expression. In conclusion, these results expand our knowledge of the genetic and molecular basis of TGW-GNS trade-offs in wheat. The QTLs and the novel TaGW2-A1 allele are likely useful for the development of cultivars with higher TGW and/or higher GNS.

QTL identification and KASP marker development for productive tiller and fertile spikelet numbers in two high-yielding hard white spring wheat cultivars

Selecting high-yielding wheat cultivars with more productive tillers per unit area (PTN) combined with more fertile spikelets per spike (fSNS) is difficult. QTL mapping of these traits may aid understanding of this bottleneck and accelerate precision breeding for high yield via marker-assisted selection. PTN and fSNS were assessed in four to five trials from 2015 to 2017 in a doubled haploid population derived from two high-yielding cultivars "UI Platinum" and "SY Capstone." Two QTL for PTN (QPTN.uia-4A and QPTN.uia-6A) and four QTL for fSNS (QfSNS.uia-4A, QfSNS.uia-5A, QfSNS.uia-6A, and QfSNS.uia-7A) were identified. The effects of the QTL were primarily additive and, therefore, pyramiding of multiple QTL may increase PTN and fSNS. However, the two QTL for PTN were positioned in the flanking regions for the two QTL for fSNS on chromosomes 4A and 6A, respectively, suggesting either possible pleiotropic effect of the same QTL or tightly linked QTL and explaining the difficulty of selecting both high PTN and fSNS in phenotypic selection. Kompetitive allele-specific PCR (KASP) markers for all identified QTL were developed and validated in a recombinant inbred line (RIL) population derived from the same two cultivars. In addition, KASP markers for three of the QTL (QPTN.uia-6A, QfSNS.uia-6A, and QfSNS.uia-7A) were further validated in a diverse spring wheat panel, indicating their usefulness under different genetic backgrounds. These KASP markers could be used by wheat breeders to select high PTN and fSNS.

Correction to: Strategic crossing of biomass and harvest index-source and sink-achieves genetic gains in wheat

[This corrects the article DOI: 10.1007/s10681-017-2040-z.].

Translational genomics of grain size regulation in wheat

Identifying and mapping grain size candidate genes in the wheat genome greatly empowers reverse genetics approaches to improve grain yield potential of wheat. Grain size (GS) or grain weight is believed to be a major driving force for further improvement of wheat yield. Although the large, polyploid genome of wheat poses an obstacle to identifying GS determinants using map-based cloning, a translational genomics approach using GS regulators identified in the model plants rice and Arabidopsis as candidate genes appears to be effective and supports a hypothesis that a conserved genetic network regulates GS in rice and wheat. In this review, we summarize the progress in the studies on GS in the model plants and wheat and identify 45 GS candidate loci in the wheat genome. In silico mapping of these GS loci in the diploid wheat and barley genomes showed (1) several gene families amplified in the wheat lineage, (2) a significant number of the GS genes located in the proximal regions surrounding the centromeres, and (3) more than half of candidate genes to be negative regulators, or their expression negatively related by microRNAs. Identifying and mapping the wheat GS gene homologs will not only facilitate candidate gene analysis, but also open the door to improving wheat yield using reverse genetics approaches by mining desired alleles in landraces and wild ancestors and to developing novel germplasm by TILLING and genome editing technologies.

Predictable 'meta-mechanisms' emerge from feedbacks between transpiration and plant growth and cannot be simply deduced from short-term mechanisms

Growth under water deficit is controlled by short-term mechanisms but, because of numerous feedbacks, the combination of these mechanisms over time often results in outputs that cannot be deduced from the simple inspection of individual mechanisms. It can be analysed with dynamic models in which causal relationships between variables are considered at each time-step, allowing calculation of outputs that are routed back to inputs for the next time-step and that can change the system itself. We first review physiological mechanisms involved in seven feedbacks of transpiration on plant growth, involving changes in tissue hydraulic conductance, stomatal conductance, plant architecture and underlying factors such as hormones or aquaporins. The combination of these mechanisms over time can result in non-straightforward conclusions as shown by examples of simulation outputs: 'over production of abscisic acid (ABA) can cause a lower concentration of ABA in the xylem sap ', 'decreasing root hydraulic conductance when evaporative demand is maximum can improve plant performance' and 'rapid root growth can decrease yield'. Systems of equations simulating feedbacks over numerous time-steps result in logical and reproducible emergent properties that can be viewed as 'meta-mechanisms' at plant level, which have similar roles as mechanisms at cell level.

Identifying seedling root architectural traits associated with yield and yield components in wheat

Background and Aims

Plant roots growing underground are critical for soil resource acquisition, anchorage and plant-environment interactions. In wheat ( Triticum aestivum ), however, the target root traits to improve yield potential still remain largely unknown. This study aimed to identify traits of seedling root system architecture (RSA) associated with yield and yield components in 226 recombinant inbred lines (RILs) derived from a cross between the bread wheat Triticum aestivum 'Forno' (small, wide root system) and spelt Triticum spelta 'Oberkulmer' (large, narrow root system).

Methods

A 'pouch and wick' high-throughput phenotyping pipeline was used to determine the RSA traits of 13-day-old RIL seedlings. Two field experiments and one glasshouse experiment were carried out to investigate the yield, yield components and phenology, followed by identification of quantitative trait loci (QTLs).

Key Results

There was substantial variation in RSA traits between genotypes. Seminal root number and total root length were both positively associated with grains m -2 , grains per spike, above-ground biomass m -2 and grain yield. More seminal roots and longer total root length were also associated with delayed maturity and extended grain filling, likely to be a consequence of more grains being defined before anthesis. Additionally, the maximum width of the root system displayed positive relationships with spikes m -2 , grains m -2 and grain yield. Ten RILs selected for the longest total roots exhibited the same effects on yield and phenology as described above, compared with the ten lines with the shortest total roots. Genetic analysis revealed 38 QTLs for the RSA, and QTL coincidence between the root and yield traits was frequently observed, indicating tightly linked genes or pleiotropy, which concurs with the results of phenotypic correlation analysis.

Conclusions

Based on the results from the Forno × Oberkulmer population, it is proposed that vigorous early root growth, particularly more seminal roots and longer total root length, is important to improve yield potential, and should be incorporated into wheat ideotypes in breeding.