Genetic architecture of main effect QTL for heading date in European winter wheat

Genetic dissection of value-added quality traits and agronomic parameters through genome-wide association mapping in bread wheat (T. aestivum L.)

Bread wheat (T. aestivum) is one of the world's most widely consumed cereals. Since micronutrient deficiencies are becoming more common among people who primarily depend upon cereal-based diets, a need for better-quality wheat varieties has been felt. An association panel of 154 T. aestivum lines was evaluated for the following quality traits: grain appearance (GA) score, grain hardness (GH), phenol reaction (PR) score, protein percent, sodium dodecyl sulfate (SDS) sedimentation value, and test weight (TWt). In addition, the panel was also phenotyped for grain yield and related traits such as days to heading, days to maturity, plant height, and thousand kernel weight for the year 2017-18 at the Borlaug Institute for South Asia (BISA) Ludhiana and Jabalpur sites. We performed a genome-wide association analysis on this panel using 18,351 genotyping-by-sequencing (GBS) markers to find marker-trait associations for quality and grain yield-related traits. We detected 55 single nucleotide polymorphism (SNP) marker trait associations (MTAs) for quality-related traits on chromosomes 7B (10), 1A (9), 2A (8), 3B (6), 2B (5), 7A (4), and 1B (3), with 3A, 4A, and 6D, having two and the rest, 4B, 5A, 5B, and 1D, having one each. Additionally, 20 SNP MTAs were detected for yield-related traits based on a field experiment conducted in Ludhiana on 7D (4) and 4D (3) chromosomes, while 44 SNP MTAs were reported for Jabalpur on chromosomes 2D (6), 7A (5), 2A (4), and 4A (4). Utilizing these loci in marker-assisted selection will benefit from further validation studies for these loci to improve hexaploid wheat for better yield and grain quality.

Fungal Disease Tolerance with a Focus on Wheat: A Review

In this paper, an extensive review of the literature is provided examining the significance of tolerance to fungal diseases in wheat amidst the escalating global demand for wheat and threats from environmental shifts and pathogen movements. The current comprehensive reliance on agrochemicals for disease management poses risks to food safety and the environment, exacerbated by the emergence of fungicide resistance. While resistance traits in wheat can offer some protection, these traits do not guarantee the complete absence of losses during periods of vigorous or moderate disease development. Furthermore, the introduction of individual resistance genes into wheat monoculture exerts selection pressure on pathogen populations. These disadvantages can be addressed or at least mitigated with the cultivation of tolerant varieties of wheat. Research in this area has shown that certain wheat varieties, susceptible to severe infectious diseases, are still capable of achieving high yields. Through the analysis of the existing literature, this paper explores the manifestations and quantification of tolerance in wheat, discussing its implications for integrated disease management and breeding strategies. Additionally, this paper addresses the ecological and evolutionary aspects of tolerance in the pathogen-plant host system, emphasizing its potential to enhance wheat productivity and sustainability.

High-throughput field phenotyping reveals that selection in breeding has affected the phenology and temperature response of wheat in the stem elongation phase

Crop growth and phenology are driven by seasonal changes in environmental variables, with temperature as one important factor. However, knowledge about genotype-specific temperature response and its influence on phenology is limited. Such information is fundamental to improve crop models and adapt selection strategies. We measured the increase in height of 352 European winter wheat varieties in 4 years to quantify phenology, and fitted an asymptotic temperature response model. The model used hourly fluctuations in temperature to parameterize the base temperature (Tmin), the temperature optimum (rmax), and the steepness (lrc) of growth responses. Our results show that higher Tmin and lrc relate to an earlier start and end of stem elongation. A higher rmax relates to an increased final height. Both final height and rmax decreased for varieties originating from the continental east of Europe towards the maritime west. A genome-wide association study (GWAS) indicated a quantitative inheritance and a large degree of independence among loci. Nevertheless, genomic prediction accuracies (GBLUPs) for Tmin and lrc were low (r≤0.32) compared with other traits (r≥0.59). As well as known, major genes related to vernalization, photoperiod, or dwarfing, the GWAS indicated additional, as yet unknown loci that dominate the temperature response.

Deciphering spike architecture formation towards yield improvement in wheat

Wheat is the most widely grown crop globally, providing 20% of the daily consumed calories and protein content around the world. With the growing global population and frequent occurrence of extreme weather caused by climate change, ensuring adequate wheat production is essential for food security. The architecture of the inflorescence plays a crucial role in determining the grain number and size, which is a key trait for improving yield. Recent advances in wheat genomics and gene cloning techniques have improved our understanding of wheat spike development and its applications in breeding practices. Here, we summarize the genetic regulation network governing wheat spike formation, the strategies used for identifying and studying the key factors affecting spike architecture, and the progress made in breeding applications. Additionally, we highlight future directions that will aid in the regulatory mechanistic study of wheat spike determination and targeted breeding for grain yield improvement.

Genetic control and prospects of predictive breeding for European winter wheat's Zeleny sedimentation values and Hagberg-Perten falling number

KEY MESSAGE

Sedimentation values and falling number in the last decades have helped maintain high baking quality despite rigorous selection for grain yield in wheat. Allelic combinations of major loci sustained the bread-making quality while improving grain yield. Glu-D1, Pinb-D1, and non-gluten proteins are associated with sedimentation values and falling number in European wheat. Zeleny sedimentation values (ZSV) and Hagberg-Perten falling number (HFN) are among the most important parameters that help determine the baking quality classes of wheat and, thus, influence the monetary benefits for growers. We used a published data set of 372 European wheat varieties evaluated in replicated field trials in multiple environments. ZSV and HFN traits hold a wide and significant genotypic variation and high broad-sense heritability. The genetic correlations revealed positive and significant associations of ZSV and HFN with each other, grain protein content (GPC) and grain hardness; however, they were all significantly negatively correlated with grain yield. Besides, GPC appeared to be the major predictor for ZSV and HFN. Our genome-wide association analyses based on high-quality SSR, SNP, and candidate gene markers revealed a strong quantitative genetic nature of ZSV and HFN by explaining their total genotypic variance as 41.49% and 38.06%, respectively. The association of known Glutenin (Glu-1) and Puroindoline (Pin-1) with ZSV provided positive analytic proof of our studies. We report novel candidate loci associated with globulins and albumins-the non-gluten monomeric proteins in wheat. In addition, predictive breeding analyses for ZSV and HFN suggest using genomic selection in the early stages of breeding programs with an average prediction accuracy of 81 and 59%, respectively.

Genome-wide association study of lipase and esterase in wholegrain wheat flour (Triticum aestivum L.)

Lipase activity is one of the main causes of the lipid rancidity in wholegrain wheat flour, leading to its short shelf life. Genetically diverse wheat germplasm offers potential for the selection of wheat cultivars with low lipase activity for stable wholegrain end use. This study evaluated 300 European wheat cultivars harvested in 2015 and 2016 on the genetic association of lipase and esterase activities in wholegrain wheat flour. Esterase and lipase activities in wholegrain flour were measured photometrically with p-nitrophenyl butyrate and p-nitrophenyl palmitate as substrates, respectively. Both enzyme activities showed wide ranges among all cultivars within each year, with differences up to 2.5-fold. The two years showed low correlations between each other, indicating a large environmental impact on the enzyme activities. Cultivars 'Julius' and 'Bueno' were suggested to be better suited for stable wholegrain products, as they had consistently low esterase and lipase activities compared to the other cultivars. A genome-wide association study revealed associations with single nucleotide polymorphisms in genes located on the high-quality wheat genome sequence of the International Wheat Genome Sequencing Consortium. Eight and four candidate genes were tentatively proposed to be associated to esterase and lipase activity, respectively, in wholegrain flour. Our work shows esterase and lipase activities from a new perspective, that combines reverse genetics to understand the underlying causes. This study outlines the possibilities and limitations to improve lipid stability of wholegrain wheat by genomics-assisted breeding methods, thereby offering new opportunities to optimize the quality of wholegrain wheat flour and wholegrain products.

Amand P, Bai G, Baker J, Baker S, Liu S. QTL mapping of yield components and kernel traits in wheat cultivars TAM 112 and Duster

In the Southern Great Plains, wheat cultivars have been selected for a combination of outstanding yield and drought tolerance as a long-term breeding goal. To understand the underlying genetic mechanisms, this study aimed to dissect the quantitative trait loci (QTL) associated with yield components and kernel traits in two wheat cultivars `TAM 112' and `Duster' under both irrigated and dryland environments. A set of 182 recombined inbred lines (RIL) derived from the cross of TAM 112/Duster were planted in 13 diverse environments for evaluation of 18 yield and kernel related traits. High-density genetic linkage map was constructed using 5,081 single nucleotide polymorphisms (SNPs) from genotyping-by-sequencing (GBS). QTL mapping analysis detected 134 QTL regions on all 21 wheat chromosomes, including 30 pleiotropic QTL regions and 21 consistent QTL regions, with 10 QTL regions in common. Three major pleiotropic QTL on the short arms of chromosomes 2B (57.5 - 61.6 Mbps), 2D (37.1 - 38.7 Mbps), and 7D (66.0 - 69.2 Mbps) colocalized with genes Ppd-B1, Ppd-D1, and FT-D1, respectively. And four consistent QTL associated with kernel length (KLEN), thousand kernel weight (TKW), plot grain yield (YLD), and kernel spike^-1 (KPS) (Qklen.tamu.1A.325, Qtkw.tamu.2B.137, Qyld.tamu.2D.3, and Qkps.tamu.6A.113) explained more than 5% of the phenotypic variation. QTL Qklen.tamu.1A.325 is a novel QTL with consistent effects under all tested environments. Marker haplotype analysis indicated the QTL combinations significantly increased yield and kernel traits. QTL and the linked markers identified in this study will facilitate future marker-assisted selection (MAS) for pyramiding the favorable alleles and QTL map-based cloning.

Automated Quantitative Measurement of Yellow Halos Suggests Activity of Necrotrophic Effectors in Septoria tritici Blotch

Many necrotrophic plant pathogens utilize host-selective toxins or necrotrophic effectors during the infection process. We hypothesized that the chlorotic yellow halos frequently observed around necrotic lesions caused by the wheat pathogen Zymoseptoria tritici could result from the activity of necrotrophic effectors interacting with the products of toxin sensitivity genes. As an initial step toward testing this hypothesis, we developed an automated image analysis (AIA) workflow that could quantify the degree of yellow halo formation occurring in wheat leaves naturally infected by a highly diverse pathogen population under field conditions. This AIA based on statistical learning was applied to more than 10,000 naturally infected leaves collected from 335 wheat cultivars grown in a replicated field experiment. We estimated a high heritability (h² = 0.71) for the degree of yellow halo formation, suggesting that this quantitative trait has a significant genetic component. Using genome-wide association mapping, we identified six chromosome segments significantly associated with the yellow halo phenotype. Most of these segments contained candidate genes associated with targets of necrotrophic effectors in other necrotrophic pathogens. Our findings conform with the hypothesis that toxin sensitivity genes could account for a significant fraction of the observed variation in quantitative resistance to Septoria tritici blotch. [Formula: see text] Copyright © 2022 The Author(s). This is an open access article distributed under the CC BY 4.0 International license.

Gabi wheat a panel of European elite lines as central stock for wheat genetic research

In plant sciences, curation and availability of interoperable phenotypic and genomic data is still in its infancy and represents an obstacle to rapid scientific discoveries in this field. To that end, supplementing the efforts being made to generate open access wheat genome, pan wheat genome and other bioinformatic resources, we present the GABI-WHEAT panel of elite European cultivars comprising 358 winter and 14 summer wheat varieties released between 1975 to 2007. The panel has been genotyped with SNP arrays of increasing density to investigate several important agronomic, quality and disease resistance traits. The robustness of investigated traits and interoperability of genomic and phenotypic data was assessed in the current publication with the aim to transform this panel into a public data resource for future genetic research in wheat. Consecutively, the phenotypic data was formatted to comply with FAIR principles and linked to online databases to substantiate panel origin information and quality. Thus, we were able to make a valuable resource available for plant science in a sustainable way.

Measurement(s)	agronomic, quality and disease traits
Technology Type(s)	manual measurement in the field
Sample Characteristic - Organism	Triticum aestivum L.

Identification of QTLs for wheat heading time across multiple-environments

KEY MESSAGE

The genetic response to changing climatic factors selects consistent across the tested environments and location-specific thermo-sensitive and photoperiod susceptible alleles in lower and higher altitudes, respectively, for starting flowering in winter wheat. Wheat breeders select heading date to match the most favorable conditions for their target environments and this is favored by the extensive genetic variation for this trait that has the potential to be further explored. In this study, we used a germplasm with broad geographic distribution and tested it in multi-location field trials across Germany over three years. The genotypic response to the variation in the climatic parameters depending on location and year uncovered the effect of photoperiod and spring temperatures in accelerating heading date in higher and lower latitudes, respectively. Spring temperature dominates other factors in inducing heading, whereas the higher amount of solar radiation delays it. A genome-wide scan of marker-trait associations with heading date detected two QTL: an adapted allele at locus TaHd102 on chromosome 5A that has a consistent effect on HD in German cultivars in multiple environments and a non-adapted allele at locus TaHd044 on chromosome 3A that accelerates flowering by 5.6 days. TaHd102 and TaHd044 explain 13.8% and 33% of the genetic variance, respectively. The interplay of the climatic variables led to the detection of environment specific association responding to temperature in lower latitudes and photoperiod in higher ones. Another locus TaHd098 on chromosome 5A showed epistatic interactions with 15 known regulators of flowering time when non-adapted cultivars from outside Germany were included in the analysis.

Effects of Photovoltaic Solar Farms on Microclimate and Vegetation Diversity

The need for energy and the increasing importance of climate change mitigation are leading to a conversion from conventional to renewable energy sources. Solar photovoltaic (PV) power has seen the most significant increase among all renewable energy sources. However, most of these installations are land-based, significantly changing global land use (LU). The real impacts, whether positive or negative, are poorly understood. This study was undertaken to have a better understanding of the impacts of solar parks on the microclimate and vegetation dynamics. First, different solar parks were visited to take measurements of the surface temperature (Tsurf), photosynthetic active radiation (PAR), air temperature (Tair), and humidity (RH) to quantify the microclimate and perform a vegetation relevé. The measurements were taken at different positions: underneath, in between, and outside solar panels. For vegetation, the data were first converted to diversity indices, which in turn contributed to a multi-indicator land use impact assessment that evaluated effects on vegetation, biodiversity, soil and water. Solar parks had clear effects on microclimate: if the panels were high enough from the ground, they could lower the Tsurf by providing shade and enough airflow. Additionally, the multidimensional functional diversity (FD) analysis of the vegetation indicated that there was less light at a higher humidity and lower temperature underneath the panels. Interestingly, the species underneath the panels also preferred a lower pH and a higher nitrogen level. Finally, the land use impact assessment found that the total land use impact for a wheat field was higher than that of the solar park, which suggests that the conversion of conventional intensive agriculture to a solar park would be beneficial.

Genome wide association study of frost tolerance in wheat

Winter wheat growing areas in the Northern hemisphere are regularly exposed to heavy frost. Due to the negative impact on yield, the identification of genetic factors controlling frost tolerance (FroT) and development of tools for breeding is of prime importance. Here, we detected QTL associated with FroT by genome wide association studies (GWAS) using a diverse panel of 276 winter wheat genotypes that was phenotyped at five locations in Germany and Russia in three years. The panel was genotyped using the 90 K iSelect array and SNPs in FroT candidate genes. In total, 17,566 SNPs were used for GWAS resulting in the identification of 53 markers significantly associated (LOD ≥ 4) to FroT, corresponding to 23 QTL regions located on 11 chromosomes (1A, 1B, 2A, 2B, 2D, 3A, 3D, 4A, 5A, 5B and 7D). The strongest QTL effect confirmed the importance of chromosome 5A for FroT. In addition, to our best knowledge, eight FroT QTLs were discovered for the first time in this study comprising one QTL on chromosomes 3A, 3D, 4A, 7D and two on chromosomes 1B and 2D. Identification of novel FroT candidate genes will help to better understand the FroT mechanism in wheat and to develop more effective combating strategies.

Juvenile Heat Tolerance in Wheat for Attaining Higher Grain Yield by Shifting to Early Sowing in October in South Asia

Farmers in northwestern and central India have been exploring to sow their wheat much earlier (October) than normal (November) to sustain productivity by escaping terminal heat stress and to utilize the available soil moisture after the harvesting of rice crop. However, current popular varieties are poorly adapted to early sowing due to the exposure of juvenile plants to the warmer temperatures in the month of October and early November. Therefore, a study was undertaken to identify wheat genotypes suited to October sowing under warmer temperatures in India. A diverse collection of 3322 bread wheat varieties and elite lines was prepared in CIMMYT, Mexico, and planted in the 3rd week of October during the crop season 2012-2013 in six locations (Ludhiana, Karnal, New Delhi, Indore, Pune and Dharwad) spread over northwestern plains zone (NWPZ) and central and Peninsular zone (CZ and PZ; designated as CPZ) of India. Agronomic traits data from the seedling stage to maturity were recorded. Results indicated substantial diversity for yield and yield-associated traits, with some lines showing indications of higher yields under October sowing. Based on agronomic performance and disease resistance, the top 48 lines (and two local checks) were identified and planted in the next crop season (2013-2014) in a replicated trial in all six locations under October sowing (third week). High yielding lines that could tolerate higher temperature in October sowing were identified for both zones; however, performance for grain yield was more promising in the NWPZ. Hence, a new trial of 30 lines was planted only in NWPZ under October sowing. Lines showing significantly superior yield over the best check and the most popular cultivars in the zone were identified. The study suggested that agronomically superior wheat varieties with early heat tolerance can be obtained that can provide yield up to 8 t/ha by planting in the third to fourth week of October.

Alleles of the GRF3-2A Gene in Wheat and Their Agronomic Value

The Growth-regulating factors (GRF) are a family of plant-specific transcription factors that have roles in plant growth, development and stress response. In this study the diversity of the TaGRF3-2A (TraesCS2A02G435100) gene was investigated in Russian bread wheat germplasm by means of next generation sequencing and molecular markers, and the results compared with those from multiple wheat genome and exome sequencing projects. The results showed that an allele possessing c.495G>T polymorphism found in Bezostaya 1 and designated as TaGRF3-2Ab, is connected with earlier heading and better grain filling under conditions of the Krasnodar Krai. TaGRF3-2Ab is more frequent among Russian winter wheat cultivars than in other germplasms found in the world, implying that it is adaptive for the Chernozem region. A new rare mutation of the TaGRF3-2A was found in the spring wheat cultivar Novosibirskaya 67. The molecular markers developed will facilitate utilization of TaGRF3-2A mutations in future agronomic studies and wheat improvement. Albeit GRF3-2Ab may be good at maintaining high milling quality of the grain, it should be used with caution in breeding of winter wheat cultivars in the perspective of climate change.

Multiple Variant Calling Pipelines in Wheat Whole Exome Sequencing

The highly challenging hexaploid wheat (Triticum aestivum) genome is becoming ever more accessible due to the continued development of multiple reference genomes, a factor which aids in the plight to better understand variation in important traits. Although the process of variant calling is relatively straightforward, selection of the best combination of the computational tools for read alignment and variant calling stages of the analysis and efficient filtering of the false variant calls are not always easy tasks. Previous studies have analyzed the impact of methods on the quality metrics in diploid organisms. Given that variant identification in wheat largely relies on accurate mining of exome data, there is a critical need to better understand how different methods affect the analysis of whole exome sequencing (WES) data in polyploid species. This study aims to address this by performing whole exome sequencing of 48 wheat cultivars and assessing the performance of various variant calling pipelines at their suggested settings. The results show that all the pipelines require filtering to eliminate false-positive calls. The high consensus among the reference SNPs called by the best-performing pipelines suggests that filtering provides accurate and reproducible results. This study also provides detailed comparisons for high sensitivity and precision at individual and population levels for the raw and filtered SNP calls.

Identification of Main-Effect and Environmental Interaction QTL and Their Candidate Genes for Drought Tolerance in a Wheat RIL Population Between Two Elite Spring Cultivars

Understanding the genetics of drought tolerance can expedite the development of drought-tolerant cultivars in wheat. In this study, we dissected the genetics of drought tolerance in spring wheat using a recombinant inbred line (RIL) population derived from a cross between a drought-tolerant cultivar, ‘Reeder’ (PI613586), and a high-yielding but drought-susceptible cultivar, ‘Albany.’ The RIL population was evaluated for grain yield (YLD), grain volume weight (GVW), thousand kernel weight (TKW), plant height (PH), and days to heading (DH) at nine different environments. The Infinium 90 k-based high-density genetic map was generated using 10,657 polymorphic SNP markers representing 2,057 unique loci. Quantitative trait loci (QTL) analysis detected a total of 11 consistent QTL for drought tolerance-related traits. Of these, six QTL were exclusively identified in drought-prone environments, and five were constitutive QTL (identified under both drought and normal conditions). One major QTL on chromosome 7B was identified exclusively under drought environments and explained 13.6% of the phenotypic variation (PV) for YLD. Two other major QTL were detected, one each on chromosomes 7B and 2B under drought-prone environments, and explained 14.86 and 13.94% of phenotypic variation for GVW and YLD, respectively. One novel QTL for drought tolerance was identified on chromosome 2D. In silico expression analysis of candidate genes underlaying the exclusive QTLs associated with drought stress identified the enrichment of ribosomal and chloroplast photosynthesis-associated proteins showing the most expression variability, thus possibly contributing to stress response by modulating the glycosyltransferase (TraesCS6A01G116400) and hexosyltransferase (TraesCS7B01G013300) unique genes present in QTL 21 and 24, respectively. While both parents contributed favorable alleles to these QTL, unexpectedly, the high-yielding and less drought-tolerant parent contributed desirable alleles for drought tolerance at four out of six loci. Regardless of the origin, all QTL with significant drought tolerance could assist significantly in the development of drought-tolerant wheat cultivars, using genomics-assisted breeding approaches.

Identification of Resistance Sources and Genome-Wide Association Mapping of Septoria Tritici Blotch Resistance in Spring Bread Wheat Germplasm of ICARDA

Septoria tritici blotch (STB) of wheat, caused by the ascomycete Zymoseptoria tritici (formerly Mycosphaerella graminicola), is one of the most important foliar diseases of wheat. In Morocco, STB is a devastating disease in temperate wheat-growing regions, and the yield losses can exceed up to 50% under favorable conditions. The aims of this study were to identify sources of resistance to STB in Septoria Association Mapping Panel (SAMP), which is composed of 377 advanced breeding lines (ABLs) from spring bread wheat breeding program of ICARDA, and to identify loci associated with resistance to STB at seedling (SRT) as well as at the adult plant (APS) stages using genome-wide association mapping (GWAM). Seedling resistance was evaluated under controlled conditions with two virulent isolates of STB (SAT-2 and 71-R3) from Morocco, whereas adult plant resistance was assessed at two hot spot locations in Morocco (Sidi Allal Tazi, Marchouch) under artificial inoculation with a mixture of STB isolates. At seedling stage, 45 and 32 ABLs were found to be resistant to 71-R3 and SAT-2 isolates of STB, respectively. At adult plant stage, 50 ABLs were found to be resistant at hot spot locations in Morocco. Furthermore, 10 genotypes showed resistance in both locations during two cropping seasons. GWAM was conducted with 9,988 SNP markers using phenotypic data for seedling and the adult plant stage. MLM model was employed in TASSEL 5 (v 5.2.53) using principal component analysis and Kinship Matrix as covariates. The GWAM analysis indicated 14 quantitative trait loci (QTL) at the seedling stage (8 for isolate SAT-2 and 6 for isolate 71-R3), while 23 QTL were detected at the adult plant stage resistance (4 at MCH-17, 16 at SAT-17, and 3 at SAT-18). SRT QTL explained together 33.3% of the phenotypic variance for seedling resistance to STB isolate SAT-2 and 28.3% for 71-R3, respectively. QTL for adult plant stage resistance explained together 13.1, 68.6, and 11.9% of the phenotypic variance for MCH-17, SAT-17, and SAT-18, respectively. Identification of STB-resistant spring bread wheat germplasm in combination with QTL detected both at SRT and APS stage will serve as an important resource in STB resistance breeding efforts.

QTL Analysis of Five Morpho-Physiological Traits in Bread Wheat Using Two Mapping Populations Derived from Common Parents

Traits such as plant height (PH), juvenile growth habit (GH), heading date (HD), and tiller number are important for both increasing yield potential and improving crop adaptation to climate change. In the present study, these traits were investigated by using the same bi-parental population at early (F₂ and F₂-derived F₃ families) and late (F₆ and F₇, recombinant inbred lines, RILs) generations to detect quantitative trait loci (QTLs) and search for candidate genes. A total of 176 and 178 lines were genotyped by the wheat Illumina 25K Infinium SNP array. The two genetic maps spanned 2486.97 cM and 3732.84 cM in length, for the F₂ and RILs, respectively. QTLs explaining the highest phenotypic variation were found on chromosomes 2B, 2D, 5A, and 7D for HD and GH, whereas those for PH were found on chromosomes 4B and 4D. Several QTL detected in the early generations (i.e., PH and tiller number) were not detected in the late generations as they were due to dominance effects. Some of the identified QTLs co-mapped to well-known adaptive genes (i.e., Ppd-1, Vrn-1, and Rht-1). Other putative candidate genes were identified for each trait, of which PINE1 and PIF4 may be considered new for GH and TTN in wheat. The use of a large F₂ mapping population combined with NGS-based genotyping techniques could improve map resolution and allow closer QTL tagging.

O-linked N-acetylglucosamine transferase is involved in fine regulation of flowering time in winter wheat

Vernalization genes underlying dramatic differences in flowering time between spring wheat and winter wheat have been studied extensively, but little is known about genes that regulate subtler differences in flowering time among winter wheat cultivars, which account for approximately 75% of wheat grown worldwide. Here, we identify a gene encoding an O-linked N-acetylglucosamine (O-GlcNAc) transferase (OGT) that differentiates heading date between winter wheat cultivars Duster and Billings. We clone this TaOGT1 gene from a quantitative trait locus (QTL) for heading date in a mapping population derived from these two bread wheat cultivars and analyzed in various environments. Transgenic complementation analysis shows that constitutive overexpression of TaOGT1b from Billings accelerates the heading of transgenic Duster plants. TaOGT1 is able to transfer an O-GlcNAc group to wheat protein TaGRP2. Our findings establish important roles for TaOGT1 in winter wheat in adaptation to global warming in the future climate scenarios.

Genome-Wide Association Studies and Prediction of Tan Spot (Pyrenophora tritici-repentis) Infection in European Winter Wheat via Different Marker Platforms

Tan spot, caused by the fungus Pyrenophoratritici-repentis (Ptr), is a severe foliar disease of wheat (Triticumaestivum L.). Improving genetic resistance is a durable strategy to reduce Ptr-related losses. Here, we dissected Ptr-infection’s genetic basis in 372 European wheat varieties via simple sequence repeats (SSRs) plus 35k and 90k single nucleotide polymorphism (SNP) marker platforms. In our phenotypic data analyses, Ptr infection showed a significant genotypic variance and a significant negative correlation with plant height. Genome-wide association studies revealed a highly quantitative nature of Ptr infection and identified two quantitative trait loci (QTL), viz., QTs.ipk-7A and QTs.ipk-7B, which imparted 21.23 and 5.84% of the genotypic variance, respectively. Besides, the Rht-D1 gene showed a strong allelic influence on the infection scores. Due to the complex genetic nature of the Ptr infection, the potential of genome-wide prediction (GP) was assessed via three different genetic models on individual and combined marker platforms. The GP results indicated that the marker density and marker platforms do not considerably impact prediction accuracy (~40–42%) and that higher-order epistatic interactions may not be highly pervasive. Our results provide a further understanding of Ptr-infection’s genetic nature, serve as a resource for marker-assisted breeding, and highlight the potential of genome-wide selection for improved Ptr resistance.

Temperature response of wheat affects final height and the timing of stem elongation under field conditions

In wheat, temperature affects the timing and intensity of stem elongation. Genetic variation for this process is therefore important for adaptation. This study investigates the genetic response to temperature fluctuations during stem elongation and its relationship to phenology and height. Canopy height of 315 wheat genotypes (GABI wheat panel) was scanned twice weekly in the field phenotyping platform (FIP) of ETH Zurich using a LIDAR. Temperature response was modelled using linear regressions between stem elongation and mean temperature in each measurement interval. This led to a temperature-responsive (slope) and a temperature-irresponsive (intercept) component. The temperature response was highly heritable (H2=0.81) and positively related to a later start and end of stem elongation as well as final height. Genome-wide association mapping revealed three temperature-responsive and four temperature-irresponsive quantitative trait loci (QTLs). Furthermore, putative candidate genes for temperature-responsive QTLs were frequently related to the flowering pathway in Arabidopsis thaliana, whereas temperature-irresponsive QTLs corresponded to growth and reduced height genes. In combination with Rht and Ppd alleles, these loci, together with the loci for the timing of stem elongation, accounted for 71% of the variability in height. This demonstrates how high-throughput field phenotyping combined with environmental covariates can contribute to a smarter selection of climate-resilient crops.

Temperature response of wheat affects final height and the timing of stem elongation under field conditions

In wheat, temperature affects the timing and intensity of stem elongation. Genetic variation for this process is therefore important for adaptation. This study investigates the genetic response to temperature fluctuations during stem elongation and its relationship to phenology and height. Canopy height of 315 wheat genotypes (GABI wheat panel) was scanned twice weekly in the field phenotyping platform (FIP) of ETH Zurich using a LIDAR. Temperature response was modelled using linear regressions between stem elongation and mean temperature in each measurement interval. This led to a temperature-responsive (slope) and a temperature-irresponsive (intercept) component. The temperature response was highly heritable (H2=0.81) and positively related to a later start and end of stem elongation as well as final height. Genome-wide association mapping revealed three temperature-responsive and four temperature-irresponsive quantitative trait loci (QTLs). Furthermore, putative candidate genes for temperature-responsive QTLs were frequently related to the flowering pathway in Arabidopsis thaliana, whereas temperature-irresponsive QTLs corresponded to growth and reduced height genes. In combination with Rht and Ppd alleles, these loci, together with the loci for the timing of stem elongation, accounted for 71% of the variability in height. This demonstrates how high-throughput field phenotyping combined with environmental covariates can contribute to a smarter selection of climate-resilient crops.

Genetic analysis of oviposition deterrence to orange wheat blossom midge in spring wheat

A major QTL for oviposition deterrence to orange wheat blossom midge was detected on chromosome 1A in the Canadian breeding line BW278 that was inherited from the Chinese variety Sumai-3. Orange wheat blossom midge (OWBM, Sitodiplosis mosellana Géhin, Diptera: Cecidomyiidae) is an important insect pest of wheat (Triticum aestivum L.) that reduces both grain yield and quality. Oviposition deterrence results in a reduction of eggs deposited on spikes relative to that observed on a wheat line preferred by OWBM. Quantification of oviposition deterrence is labor-intensive, so wheat breeders require efficient DNA markers for the selection of this trait. The objective of this study was to identify quantitative trait loci (QTL) for oviposition deterrence in a doubled haploid (DH) population developed from the spring wheat cross Superb/BW278. The DH population and check varieties were evaluated for OWBM kernel damage from five field nurseries over three growing seasons. QTL analysis identified major effect loci on chromosomes 1A (QSm.mrc-1A) and 5A (QSm.mrc-5A). Reduced kernel damage was contributed by BW278 at QSm.mrc-1A and Superb at QSm.mrc-5A. QSm.mrc-1A mapped to the approximate location of the oviposition deterrence QTL previously found in the American variety Reeder. However, haplotype analysis revealed that BW278 inherited this oviposition deterrence allele from the Chinese spring wheat variety Sumai-3. QSm.mrc-5A mapped to the location of awn inhibitor gene B1, suggesting that awns hinder OWBM oviposition. Single-nucleotide polymorphisms (SNPs) were identified for predicting the presence or absence of QSm.mrc-1A based upon haplotype. Functional annotation of candidate genes in 1A QTL intervals revealed eleven potential candidate genes, including a gene involved in terpenoid biosynthesis. SNPs for QSm.mrc-1A and fully awned spikes provide a basis for the selection of oviposition deterrence to OWBM.

Characterizing Winter Wheat Germplasm for Fusarium Head Blight Resistance Under Accelerated Growth Conditions

Fusarium head blight (FHB) is one of the economically important diseases of wheat as it causes severe yield loss and reduces grain quality. In winter wheat, due to its vernalization requirement, it takes an exceptionally long time for plants to reach the heading stage, thereby prolonging the time it takes for characterizing germplasm for FHB resistance. Therefore, in this work, we developed a protocol to evaluate winter wheat germplasm for FHB resistance under accelerated growth conditions. The protocol reduces the time required for plants to begin heading while avoiding any visible symptoms of stress on plants. The protocol was tested on 432 genotypes obtained from a breeding program and a genebank. The mean area under disease progress curve for FHB was 225.13 in the breeding set and 195.53 in the genebank set, indicating that the germplasm from the genebank set had higher resistance to FHB. In total, 10 quantitative trait loci (QTL) for FHB severity were identified by association mapping. Of these, nine QTL were identified in the combined set comprising both genebank and breeding sets, while two QTL each were identified in the breeding set and genebank set, respectively, when analyzed separately. Some QTLs overlapped between the three datasets. The results reveal that the protocol for FHB evaluation integrating accelerated growth conditions is an efficient approach for FHB resistance breeding in winter wheat and can be even applied to spring wheat after minor modifications.

Mining the stable quantitative trait loci for agronomic traits in wheat (Triticum aestivum L.) based on an introgression line population

BACKGROUND

Human demand for wheat will continue to increase together with the continuous global population growth. Agronomic traits in wheat are susceptible to environmental conditions. Therefore, in breeding practice, priority is given to QTLs of agronomic traits that can be stably detected across multiple environments and over many years.

RESULTS

In this study, QTL analysis was conducted for eight agronomic traits using an introgression line population across eight environments (drought stressed and well-watered) for 5 years. In total, 44 additive QTLs for the above agronomic traits were detected on 15 chromosomes. Among these, qPH-6A, qHD-1A, qSL-2A, qHD-2D and qSL-6A were detected across seven, six, five, five and four environments, respectively. The means in the phenotypic variation explained by these five QTLs were 12.26, 9.51, 7.77, 7.23, and 8.49%, respectively.

CONCLUSIONS

We identified five stable QTLs, which includes qPH-6A, qHD-1A, qSL-2A, qHD-2D and qSL-6A. They play a critical role in wheat agronomic traits. One of the dwarf genes Rht14, Rht16, Rht18 and Rht25 on chromosome 6A might be the candidate gene for qPH-6A. The qHD-1A and qHD-2D were novel stable QTLs for heading date and they differed from known vernalization genes, photoperiod genes and earliness per se genes.

Suitability of Single-Nucleotide Polymorphism Arrays Versus Genotyping-By-Sequencing for Genebank Genomics in Wheat

Genebank genomics promises to unlock valuable diversity for plant breeding but first, one key question is which marker system is most suitable to fingerprint entire genebank collections. Using wheat as model species, we tested for the presence of an ascertainment bias and investigated its impact on estimates of genetic diversity and prediction ability obtained using three marker platforms: simple sequence repeat (SSR), genotyping-by-sequencing (GBS), and array-based SNP markers. We used a panel of 378 winter wheat genotypes including 190 elite lines and 188 plant genetic resources (PGR), which were phenotyped in multi-environmental trials for grain yield and plant height. We observed an ascertainment bias for the array-based SNP markers, which led to an underestimation of the molecular diversity within the population of PGR. In contrast, the marker system played only a minor role for the overall picture of the population structure and precision of genome-wide predictions. Interestingly, we found that rare markers contributed substantially to the prediction ability. This combined with the expectation that valuable novel diversity is most likely rare suggests that markers with minor allele frequency deserve careful consideration in the design of a pre-breeding program.

Genome-wide association study of agronomic traits in bread wheat reveals novel putative alleles for future breeding programs

BACKGROUND

Identification of loci for agronomic traits and characterization of their genetic architecture are crucial in marker-assisted selection (MAS). Genome-wide association studies (GWAS) have increasingly been used as potent tools in identifying marker-trait associations (MTAs). The introduction of new adaptive alleles in the diverse genetic backgrounds may help to improve grain yield of old or newly developed varieties of wheat to balance supply and demand throughout the world. Landraces collected from different climate zones can be an invaluable resource for such adaptive alleles.

RESULTS

GWAS was performed using a collection of 298 Iranian bread wheat varieties and landraces to explore the genetic basis of agronomic traits during 2016-2018 cropping seasons under normal (well-watered) and stressed (rain-fed) conditions. A high-quality genotyping by sequencing (GBS) dataset was obtained using either all original single nucleotide polymorphism (SNP, 10938 SNPs) or with additional imputation (46,862 SNPs) based on W7984 reference genome. The results confirm that the B genome carries the highest number of significant marker pairs in both varieties (49,880, 27.37%) and landraces (55,086, 28.99%). The strongest linkage disequilibrium (LD) between pairs of markers was observed on chromosome 2D (0.296). LD decay was lower in the D genome, compared to the A and B genomes. Association mapping under two tested environments yielded a total of 313 and 394 significant (-log10 P >3) MTAs for the original and imputed SNP data sets, respectively. Gene ontology results showed that 27 and 27.5% of MTAs of SNPs in the original set were located in protein-coding regions for well-watered and rain-fed conditions, respectively. While, for the imputed data set 22.6 and 16.6% of MTAs represented in protein-coding genes for the well-watered and rain-fed conditions, respectively.

CONCLUSIONS

Our finding suggests that Iranian bread wheat landraces harbor valuable alleles that are adaptive under drought stress conditions. MTAs located within coding genes can be utilized in genome-based breeding of new wheat varieties. Although imputation of missing data increased the number of MTAs, the fraction of these MTAs located in coding genes were decreased across the different sub-genomes.

Genome-wide association study of pre-harvest sprouting tolerance using a 90K SNP array in common wheat (Triticum aestivum L.)

Three major loci for pre-harvest sprouting tolerance (PHST) were mapped on chromosomes 1AL, 3BS, and 6BL, and two CAPS and one dCAPS markers were validated. Sixteen lines with favorable alleles and increased PHST were identified. Pre-harvest sprouting (PHS) significantly affects wheat grain yield and quality. In the present study, the PHS tolerance (PHST) of 192 wheat varieties (lines) was evaluated by assessment of field sprouting, seed germination index, and period of dormancy in different environments. A high-density Illumina iSelect 90K SNP array was used to genotype the panel. A genome-wide association study (GWAS) based on single- and multi-locus mixed linear models was used to detect loci for PHST. The single-locus model identified 23 loci for PHST (P < 0.0001) and explained 6.0-18.9% of the phenotypic variance. Twenty loci were consistent with known quantitative trait loci (QTLs). Three single-nucleotide polymorphism markers closely linked with three major loci (Qphs.ahau-1A, Qphs.ahau-3B, and Qphs.ahau-6B) on chromosomes 1AL, 3BS, and 6BL, respectively, were converted to two cleaved amplified polymorphic sequences (CAPS) and one derived-CAPS markers, and validated in 374 wheat varieties (lines). The CAPS marker EX06323 for Qphs.ahau-6B co-segregated with a novel major QTL underlying PHST in a recombinant inbred line population raised from the cross Jing 411 × Wanxianbaimaizi. Linear regression showed a clear dependence of PHST on the number of favorable alleles. Sixteen varieties showing an elevated degree of PHST were identified and harbored more than 16 favorable alleles. The multi-locus model detected 39 marker-trait associations for PHST (P < 0.0001), of which five may be novel. Six loci common to the two models were identified. The combination of the two GWAS methods contributes to efficient dissection of the complex genetic mechanism of PHST.

Genome wide genetic dissection of wheat quality and yield related traits and their relationship with grain shape and size traits in an elite × non-adapted bread wheat cross

The genetic gain in yield and quality are two major targets of wheat breeding programs around the world. In this study, a high density genetic map consisting of 10,172 SNP markers identified a total of 43 genomic regions associated with three quality traits, three yield traits and two agronomic traits in hard red spring wheat (HRSW). When compared with six grain shape and size traits, the quality traits showed mostly independent genetic control (~18% common loci), while the yield traits showed moderate association (~53% common loci). Association of genomic regions for grain area (GA) and thousand-grain weight (TGW), with yield suggests that targeting an increase in GA may help enhancing wheat yield through an increase in TGW. Flour extraction (FE), although has a weak positive phenotypic association with grain shape and size, they do not share any common genetic loci. A major contributor to plant height was the Rht8 locus and the reduced height allele was associated with significant increase in grains per spike (GPS) and FE, and decrease in number of spikes per square meter and test weight. Stable loci were identified for almost all the traits. However, we could not find any QTL in the region of major known genes like GPC-B1, Ha, Rht-1, and Ppd-1. Epistasis also played an important role in the genetics of majority of the traits. In addition to enhancing our knowledge about the association of wheat quality and yield with grain shape and size, this study provides novel loci, genetic information and pre-breeding material (combining positive alleles from both parents) to enhance the cultivated gene pool in wheat germplasm. These resources are valuable in facilitating molecular breeding for wheat quality and yield improvement.

A large nested association mapping population for breeding and quantitative trait locus mapping in Ethiopian durum wheat

The Ethiopian plateau hosts thousands of durum wheat (Triticum turgidum subsp. durum) farmer varieties (FV) with high adaptability and breeding potential. To harness their unique allelic diversity, we produced a large nested association mapping (NAM) population intercrossing fifty Ethiopian FVs with an international elite durum wheat variety (Asassa). The Ethiopian NAM population (EtNAM) is composed of fifty interconnected bi-parental families, totalling 6280 recombinant inbred lines (RILs) that represent both a powerful quantitative trait loci (QTL) mapping tool, and a large pre-breeding panel. Here, we discuss the molecular and phenotypic diversity of the EtNAM founder lines, then we use an array featuring 13 000 single nucleotide polymorphisms (SNPs) to characterize a subset of 1200 EtNAM RILs from 12 families. Finally, we test the usefulness of the population by mapping phenology traits and plant height using a genome wide association (GWA) approach. EtNAM RILs showed high allelic variation and a genetic makeup combining genetic diversity from Ethiopian FVs with the international durum wheat allele pool. EtNAM SNP data were projected on the fully sequenced AB genome of wild emmer wheat, and were used to estimate pairwise linkage disequilibrium (LD) measures that reported an LD decay distance of 7.4 Mb on average, and balanced founder contributions across EtNAM families. GWA analyses identified 11 genomic loci individually affecting up to 3 days in flowering time and more than 1.6 cm in height. We argue that the EtNAM is a powerful tool to support the production of new durum wheat varieties targeting local and global agriculture.

Genome-wide Association Mapping and Prediction of Adult Stage Septoria tritici Blotch Infection in European Winter Wheat via High-Density Marker Arrays

blotch (STB) caused by the fungus is a devastating foliar disease of wheat ( L.) that can lead to substantial yield losses. Quantitative genetic resistance has been proposed as a durable strategy for STB control. In this study, we dissected the genetic basis of STB infection in 371 European wheat varieties based on 35k and 90k single nucleotide polymorphism marker arrays. The phenotypic data analyses suggested that large genetic variance exists for STB infection with a broad-sense heritability of 0.78. Genome-wide association studies (GWAS) propose the highly quantitative nature of STB infection with potential associations on chromosomes 1A, 1B, 2D, 4A, 5A, 6A, 6D, 7A, and 7B. Increased marker density in GWAS by combining markers from both arrays helped to detect additional markers explaining increased genotypic variance. Linkage disequilibrium analyses revealed genes with a possible role in disease resistance. The potential of genomic prediction (GP) assessed via two models accounting for additive effects and additive plus epistatic interactions among the loci suggested the possibility of genomic selection for improved STB resistance. Genomic prediction results also indicated that the higher-order epistatic interactions are not abundant and that both marker platforms are equally suitable for GP of STB infection. Our results provide further understanding of the quantitative genetic nature of STB infection, serve as a resource for marker-assisted breeding, and highlight the potential of genomic selection for improved STB resistance.

Genome-wide association studies for yield-related traits in soft red winter wheat grown in Virginia

Grain yield is a trait of paramount importance in the breeding of all cereals. In wheat (Triticum aestivum L.), yield has steadily increased since the Green Revolution, though the current rate of increase is not forecasted to keep pace with demand due to growing world population and increasing affluence. While several genome-wide association studies (GWAS) on yield and related component traits have been performed in wheat, the previous lack of a reference genome has made comparisons between studies difficult. In this study, a GWAS for yield and yield-related traits was carried out on a population of 322 soft red winter wheat lines across a total of four rain-fed environments in the state of Virginia using single-nucleotide polymorphism (SNP) marker data generated by a genotyping-by-sequencing (GBS) protocol. Two separate mixed linear models were used to identify significant marker-trait associations (MTAs). The first was a single-locus model utilizing a leave-one-chromosome-out approach to estimating kinship. The second was a sub-setting kinship estimation multi-locus method (FarmCPU). The single-locus model identified nine significant MTAs for various yield-related traits, while the FarmCPU model identified 74 significant MTAs. The availability of the wheat reference genome allowed for the description of MTAs in terms of both genetic and physical positions, and enabled more extensive post-GWAS characterization of significant MTAs. The results indicate a number of promising candidate genes contributing to grain yield, including an ortholog of the rice aberrant panicle organization (APO1) protein and a gibberellin oxidase protein (GA2ox-A1) affecting the trait grains per square meter, an ortholog of the Arabidopsis thaliana mother of flowering time and terminal flowering 1 (MFT) gene affecting the trait seeds per square meter, and a B2 heat stress response protein affecting the trait seeds per head.

Genotype Imputation in Winter Wheat Using First-Generation Haplotype Map SNPs Improves Genome-Wide Association Mapping and Genomic Prediction of Traits

Genome-wide single nucleotide polymorphism (SNP) variation allows for the capture of haplotype structure in populations and prediction of unobserved genotypes based on inferred regions of identity-by-descent (IBD). Here we have used a first-generation wheat haplotype map created by targeted re-sequencing of low-copy genomic regions in the reference panel of 62 lines to impute marker genotypes in a diverse panel of winter wheat cultivars from the U.S. Great Plains. The IBD segments between the reference population and winter wheat cultivars were identified based on SNP genotyped using the 90K iSelect wheat array and genotyping by sequencing (GBS). A genome-wide association study and genomic prediction of resistance to stripe rust in winter wheat cultivars showed that an increase in marker density achieved by imputation improved both the power and precision of trait mapping and prediction. The majority of the most significant marker-trait associations belonged to imputed genotypes. With the vast amount of SNP variation data accumulated for wheat in recent years, the presented imputation framework will greatly improve prediction accuracy in breeding populations and increase resolution of trait mapping hence, facilitate cross-referencing of genotype datasets available across different wheat populations.

Genetic Dissection of Snow Mold Tolerance in US Pacific Northwest Winter Wheat Through Genome-Wide Association Study and Genomic Selection

Snow mold is a yield-limiting disease of wheat in the Pacific Northwest (PNW) region of the US, where there is prolonged snow cover. The objectives of this study were to identify genomic regions associated with snow mold tolerance in a diverse panel of PNW winter wheat lines in a genome-wide association study (GWAS) and to evaluate the usefulness of genomic selection (GS) for snow mold tolerance. An association mapping panel (AMP; N = 458 lines) was planted in Mansfield and Waterville, WA in 2017 and 2018 and genotyped using the Illumina^® 90K single nucleotide polymorphism (SNP) array. GWAS identified 100 significant markers across 17 chromosomes, where SNPs on chromosomes 5A and 5B coincided with major freezing tolerance and vernalization loci. Increased number of favorable alleles was related to improved snow mold tolerance. Independent predictions using the AMP as a training population (TP) to predict snow mold tolerance of breeding lines evaluated between 2015 and 2018 resulted in a mean accuracy of 0.36 across models and marker sets. Modeling nonadditive effects improved accuracy even in the absence of a close genetic relatedness between the TP and selection candidates. Selecting lines based on genomic estimated breeding values and tolerance scores resulted in a 24% increase in tolerance. The identified genomic regions associated with snow mold tolerance demonstrated the genetic complexity of this trait and the difficulty in selecting tolerant lines using markers. GS was validated and showed potential for use in PNW winter wheat for selecting on complex traits such tolerance to snow mold.

Genome-wide association analyses of plant growth traits during the stem elongation phase in wheat

One of the primary objectives of wheat breeding was to increase grain yield. Floral abortion during the stem elongation phase (SEP) leads to a loss of more than 50% of the grain number potential. In this study, we quantified 75 plant growth-associated traits at seven stages during the SEP and mapped 15 696 single nucleotide polymorphism (SNP) markers in 210 accessions of wheat (Triticum aestivum). Our genomewide association study identified trait-associated SNPs that are shared among various stages of the SEP, as well as SNPs that are shared between plant growth traits and grain yield in the field. The genomic selection analysis shows variation among the prediction abilities of various traits and stages. Furthermore, we found that the allelic variants of Ppd-D1 (chromosome 2D) and Rht-D1 (chromosome 4D) loci affect some plant growth traits (e.g. leaf area and spike length). These results have identified a narrow time window within the SEP in which plant growth traits can be manipulated to alter grain yield. This suggests that there may be multiple ways to regulate plant growth during the SEP, to ultimately influence grain number in wheat.

Genome-wide association study of heading and flowering dates and construction of its prediction equation in Chinese common wheat

Heading date is one of the most important traits in wheat breeding as it affects adaptation and yield potential. A genome-wide association study (GWAS) using the 90 K iSelect SNP genotyping assay indicated that a total of 306 loci were significantly associated with heading and flowering dates in 13 environments in Chinese common wheat from the Yellow and Huai wheat region. Of these, 105 loci were significantly correlated with both heading and flowering dates and were found in clusters on chromosomes 2, 5, 6, and 7. Based on differences in distribution of the vernalization and photoperiod genes among chromosomes, arms, or block regions, 13 novel, environmentally stable genetic loci were associated with heading and flowering dates, including RAC875_c41145_189 on 1DS, RAC875_c50422_299 on 2BL, and RAC875_c48703_148 on 2DS, that accounted for more than 20% phenotypic variance explained (PVE) of the heading/flowering date in at least four environments. GWAS and t test of a combination of SNPs and vernalization and photoperiod alleles indicated that the Vrn-B1, Vrn-D1, and Ppd-D1 genes significantly affect heading and flowering dates in Chinese common wheat. Based on the association of heading and flowering dates with the vernalization and photoperiod alleles at seven loci and three significant SNPs, optimal linear regression equations were established, which show that of the seven loci, the Ppd-D1 gene plays the most important role in modulating heading and flowering dates in Chinese wheat, followed by Vrn-B1 and Vrn-D1. Additionally, three novel genetic loci (RAC875_c41145_189, Excalibur_c60164_137, and RAC875_c50422_299) also show important effect on heading and flowering dates. Therefore, Ppd-D1, Vrn-B1, Vrn-D1, and the novel genetic loci should be further investigated in terms of improving heading and flowering dates in Chinese wheat. Further quantitative analysis of an F₁₀ recombinant inbred lines population identified a major QTL that controls heading and flowering dates within the Ppd-D1 locus with PVEs of 28.4% and 34.0%, respectively; this QTL was also significantly associated with spike length, peduncle length, fertile spikelets number, cold resistance, and tiller number.

GWAS of a soybean breeding collection from South East and South Kazakhstan for resistance to fungal diseases

Soybean (Glycine max(L.) Merr) is an essential food, feed, and technical culture. In Kazakhstan the area under soybean is increasing every year, helping to solve the problem of protein deficiency in human nutrition and animal feeding. One of the main problems of soybean production is fungal diseases causing yields losses of up to 30 %. Modern genomic studies can be applied to facilitate efficient breeding research for improvement of soybean fungal disease tolerance. Therefore, the objective of this genome-wide association study (GWAS) was analysis of a soybean collection consisting of 182 accessions in relation to fungal diseases in the conditions of South East and South Kazakh­stan. Field evaluation of the soybean collection suggested thatFusariumspp. andCercospora sojinaaffected plants in the South region (RIBSP), andSeptoria glycines– in the South East region (KRIAPP). The major objective of the study was identification of QTL associated with resistance to fusarium root rot (FUS), frogeye leaf spot (FLS), and brown spot (BS). GWAS using 4 442 SNP (single nucleotide polymorphism) markers of Illumina iSelect array allowed for identification of fifteen marker trait associations (MTA) resistant to the three diseases at two different stages of growth. Two QTL both for FUS (chromosomes 13 and 17) and BS (chromosomes 14 and 17) were genetically mapped, including one presumably novel QTL for BS (chromo­some 17). Also, five presumably novel QTL for FLS were genetically mapped on chromosomes 2, 7, and 15. The results can be used for improvement of the local breeding projects based on marker-assisted selection approach.          

A three-component system incorporating Ppd-D1, copy number variation at Ppd-B1, and numerous small-effect quantitative trait loci facilitates adaptation of heading time in winter wheat cultivars of worldwide origin

The broad adaptability of heading time has contributed to the global success of wheat in a diverse array of climatic conditions. Here, we investigated the genetic architecture underlying heading time in a large panel of 1,110 winter wheat cultivars of worldwide origin. Genome-wide association mapping, in combination with the analysis of major phenology loci, revealed a three-component system that facilitates the adaptation of heading time in winter wheat. The photoperiod sensitivity locus Ppd-D1 was found to account for almost half of the genotypic variance in this panel and can advance or delay heading by many days. In addition, copy number variation at Ppd-B1 was the second most important source of variation in heading, explaining 8.3% of the genotypic variance. Results from association mapping and genomic prediction indicated that the remaining variation is attributed to numerous small-effect quantitative trait loci that facilitate fine-tuning of heading to the local climatic conditions. Collectively, our results underpin the importance of the two Ppd-1 loci for the adaptation of heading time in winter wheat and illustrate how the three components have been exploited for wheat breeding globally.

Leveraging the Use of Historical Data Gathered During Seed Regeneration of an ex Situ Genebank Collection of Wheat

Genebanks are a rich source of genetic variation. Most of this variation is absent in breeding programs but may be useful for further crop plant improvement. However, the lack of phenotypic information forms a major obstacle for the educated choice of genebank accessions for research and breeding. A promising approach to fill this information gap is to exploit historical information gathered routinely during seed regeneration cycles. Still, this data is characterized by a high non-orthogonality hampering their analysis. By examining historical data records for flowering time, plant height, and thousand grain weight collected during 70 years of regeneration of 6,207 winter wheat (Triticum aestivum L.) accessions at the German Federal ex situ Genebank, we aimed to elaborate a strategy to analyze and validate non-orthogonal historical data in order to charge genebank information platforms with high quality ready-to-use phenotypic information. First, a three-step quality control assessment considering the plausibility of trait values and a standard as well as a weather parameter index based outlier detection was implemented, resulting in heritability estimates above 0.90 for all three traits. Then, the data was analyzed by estimating best linear unbiased estimations (BLUEs) applying a linear mixed-model approach. An in silico resampling study mimicking different missing data patterns revealed that accessions should be regenerated in a random fashion and not blocked by origin or acquisition date in order to minimize estimation biases in historical data sets. Validation data was obtained from multi-environmental orthogonal field trials considering a random subsample of 3,083 accessions. Correlations above 0.84 between BLUEs estimated for historical data and validation trials outperformed previous approaches and confirmed the robustness of our strategy as well as the high quality of the historical data. The results indicate that the IPK winter wheat collection reveals an extraordinary high phenotypic diversity compared to other collections. The quality checked ready-to-use phenotypic information resulting from this study is the first brick to extend traditional, conservation driven genebanks into bio-digital resource centers.

High-density genetic mapping of a major QTL for resistance to multiple races of loose smut in a tetraploid wheat cross

Loose smut, caused by Ustilago tritici (Pers.) Rostr., is a systemic disease of tetraploid durum wheat (Triticum turgidum L.). Loose smut can be economically controlled by growing resistant varieties, making it important to find and deploy new sources of resistance. Blackbird, a variety of T. turgidum L. subsp. carthlicum (Nevski) A. Love & D. Love, carries a high level of resistance to loose smut. Blackbird was crossed with the loose smut susceptible durum cultivar Strongfield to produce a doubled haploid (DH) mapping population. The parents and progenies were inoculated with U. tritici races T26, T32 and T33 individually and as a mixture at Swift Current, Canada in 2011 and 2012 and loose smut incidence (LSI) was assessed. Genotyping of the DH population and parents using an Infinium iSelect 90K single nucleotide polymorphism (SNP) array identified 12,952 polymorphic SNPs. The SNPs and 426 SSRs (previously genotyped in the same population) were mapped to 16 linkage groups spanning 3008.4 cM at an average inter-marker space of 0.2 cM in a high-density genetic map. Composite interval mapping analysis revealed three significant quantitative trait loci (QTL) for loose smut resistance on chromosomes 3A, 6B and 7A. The loose smut resistance QTL on 6B (QUt.spa-6B.2) and 7A (QUt.spa-7A.2) were derived from Blackbird. Strongfield contributed the minor QTL on 3A (QUt.spa-3A.2). The resistance on 6B was a stable major QTL effective against all individual races and the mixture of the three races; it explained up to 74% of the phenotypic variation. This study is the first attempt in durum wheat to identify and map loose smut resistance QTL using a high-density genetic map. The QTL QUt.spa-6B.2 would be an effective source for breeding resistance to multiple races of the loose smut pathogen because it provides near-complete broad resistance to the predominant virulence on the Canadian prairies.

GWAS for plant growth stages and yield components in spring wheat (Triticum aestivum L.) harvested in three regions of Kazakhstan

BACKGROUND

Spring wheat is the largest agricultural crop grown in Kazakhstan with an annual sowing area of 12 million hectares in 2016. Annually, the country harvests around 15 million tons of high quality grain. Despite environmental stress factors it is predicted that the use of new technologies may lead to increases in productivity from current levels of 1.5 to up to 3 tons per hectare. One way of improving wheat productivity is by the application of new genomic oriented approaches in plant breeding projects. Genome wide association studies (GWAS) are emerging as powerful tools for the understanding of the inheritance of complex traits via utilization of high throughput genotyping technologies and phenotypic assessments of plant collections. In this study, phenotyping and genotyping data on 194 spring wheat accessions from Kazakhstan, Russia, Europe, and CIMMYT were assessed for the identification of marker-trait associations (MTA) of agronomic traits by using GWAS.

RESULTS

Field trials in Northern, Central and Southern regions of Kazakhstan using 194 spring wheat accessions revealed strong correlations of yield with booting date, plant height, biomass, number of spikes per plant, and number of kernels per spike. The accessions from Europe and CIMMYT showed high breeding potential for Southern and Central regions of the country in comparison with the performance of the local varieties. The GGE biplot method, using average yield per plant, suggested a clear separation of accessions into their three breeding origins in relationship to the three environments in which they were evaluated. The genetic variation in the three groups of accessions was further studied using 3245 polymorphic SNP (single nucleotide polymorphism) markers. The application of Principal Coordinate analysis clearly grouped the 194 accessions into three clades according to their breeding origins. GWAS on data from nine field trials allowed the identification of 114 MTAs for 12 different agronomic traits.

CONCLUSIONS

Field evaluation of foreign germplasm revealed its poor yield performance in Northern Kazakhstan, which is the main wheat growing region in the country. However, it was found that EU and CIMMYT germplasm has high breeding potential to improve yield performance in Central and Southern regions. The use of Principal Coordinate analysis clearly separated the panel into three distinct groups according to their breeding origin. GWAS based on use of the TASSEL 5.0 package allowed the identification of 114 MTAs for twelve agronomic traits. The study identifies a network of key genes for improvement of yield productivity in wheat growing regions of Kazakhstan.

Genome-wide association study for agronomic and physiological traits in spring wheat evaluated in a range of heat prone environments

We identified 27 stable loci associated with agronomic traits in spring wheat using genome-wide association analysis, some of which confirmed previously reported studies. GWAS peaks identified in regions where no QTL for grain yield per se has been mapped to date, provide new opportunities for gene discovery and creation of new cultivars with desirable alleles for improving yield and yield stability in wheat. We undertook large-scale genetic analysis to determine marker-trait associations (MTAs) underlying agronomic and physiological performance in spring wheat using genome-wide association studies (GWAS). Field trials were conducted at seven sites in three countries (Sudan, Egypt, and Syria) over 2-3 years in each country. Twenty-five agronomic and physiological traits were measured on 188 wheat genotypes. After correcting for population structure and relatedness, a total of 245 MTAs distributed over 66 loci were associated with agronomic traits in individual and mean performance across environments respectively; some of which confirmed previously reported loci. Of these, 27 loci were significantly associated with days to heading, thousand kernel weight, grain yield, spike length, and leaf rolling for mean performance across environments. Despite strong QTL by environment interactions, eight of the loci on chromosomes 1A, 1D, 5A, 5D, 6B, 7A, and 7B had pleiotropic effects on days to heading and yield components (TKW, SM^-2, and SNS). The winter-type alleles at the homoeologous VRN1 loci significantly increased days to heading and grain yield in optimal environments, but decreased grain yield in heat prone environments. Top 20 high-yielding genotypes, ranked by additive main effects and multiplicative interaction (AMMI), had low kinship relationship and possessed 4-5 favorable alleles for GY MTAs except two genotypes, Shadi-4 and Qafzah-11/Bashiq-1-2. This indicated different yield stability mechanisms due to potentially favorable rare alleles that are uncharacterized. Our results will enable wheat breeders to effectively introgress several desirable alleles into locally adapted germplasm in developing wheat varieties with high yield stability and enhanced heat tolerance.

QTL mapping and comparative genome analysis of agronomic traits including grain yield in winter rye

Genetic diversity in elite rye germplasm as well as F _2:3 testcross design enables fast QTL mapping to approach genes controlling grain yield, grain weight, tiller number and heading date in rye hybrids. Winter rye (Secale cereale L.) is a multipurpose cereal crop closely related to wheat, which offers the opportunity for a sustainable production of food and feed and which continues to emerge as a renewable energy source for the production of bioethanol and biomethane. Rye contributes to increase agricultural crop species diversity particularly in Central and Eastern Europe. In contrast to other small grain cereals, knowledge on the genetic architecture of complex inherited, agronomic important traits is yet limited for the outbreeding rye. We have performed a QTL analysis based on a F_2:3 design and testcross performance of 258 experimental hybrids in multi-environmental field trials. A genetic linkage map covering 964.9 cM based on SSR, conserved-orthologous set (COS), and mixed-phase dominant DArT markers allowed to describe 22 QTL with significant effects for grain yield, heading date, tiller number, and thousand grain weight across seven environments. Using rye COS markers, orthologous segments for these traits have been identified in the rice genome, which carry cloned and functionally characterized rice genes. The initial genome scan described here together with the existing knowledge on candidate genes provides the basis for subsequent analyses of the genetic and molecular mechanisms underlying agronomic important traits in rye.

The roles of pleiotropy and close linkage as revealed by association mapping of yield and correlated traits of wheat (Triticum aestivum L.)

Grain yield (GY) of bread wheat (Triticum aestivum L.) is quantitatively inherited. Correlated GY-syndrome traits such as plant height (PH), heading date (HD), thousand grain weight (TGW), test weight (TW), grains per ear (GPE), and ear weight (EW) influence GY. Most quantitative genetics studies assessed the multiple-trait (MT) complex of GY-syndrome using single-trait approaches, and little is known about its underlying pleiotropic architecture. We investigated the pleiotropic architecture of wheat GY-syndrome through MT association mapping (MT-GWAS) using 372 varieties phenotyped in up to eight environments and genotyped with 18 832 single nucleotide polymorphisms plus 24 polymorphic functional markers. MT-GWAS revealed a total of 345 significant markers spread genome wide, representing 8, 40, 11, 40, 34, and 35 effective GY-PH, GY-HD, GY-TGW, GY-TW, GY-GPE, and GY-EW associations, respectively. Among them, pleiotropic roles of Rht-B1 and TaGW2-6B loci were corroborated. Only one marker presented simultaneous associations for three traits (i.e. GY-TGW-TW). Close linkage was difficult to differentiate from pleiotropy; thus, the pleiotropic architecture of GY-syndrome was dissected more as a cause of pleiotropy rather than close linkage. Simulations showed that minor allele frequencies, along with sizes and distances between quantitative trait loci for two traits, influenced the ability to distinguish close linkage from pleiotropy.

Genetics of mycorrhizal symbiosis in winter wheat (Triticum aestivum)

Bread wheat (Triticum aestivum) is a major staple food and therefore of prime importance for feeding the Earth's growing population. Mycorrhiza is known to improve plant growth, but although extensive knowledge concerning the interaction between mycorrhizal fungi and plants is available, genotypic differences concerning the ability of wheat to form mycorrhizal symbiosis and quantitative trait loci (QTLs) involved in mycorrhization are largely unknown. Therefore, a diverse set of 94 bread wheat genotypes was evaluated with regard to root colonization by arbuscular mycorrhizal fungi. In order to identify genomic regions involved in mycorrhization, these genotypes were analyzed using the wheat 90k iSelect chip, resulting in 17 823 polymorphic mapped markers, which were used in a genome-wide association study. Significant genotypic differences (P < 0.0001) were detected in the ability to form symbiosis and 30 significant markers associated with root colonization, representing six QTL regions, were detected on chromosomes 3A, 4A and 7A, and candidate genes located in these QTL regions were proposed. The results reported here provide key insights into the genetics of root colonization by mycorrhizal fungi in wheat.

Genomewide association study for seeding emergence and tiller number using SNP markers in an elite winter wheat population

Seeding emergence and tiller number are the most important traits for wheat (Triticum aestivum L.) yield, but the inheritance of seeding emergence and tillering is poorly understood. We conducted a genomewide association study focussing on seeding emergence and tiller number at different growth stages with a panel of 205 elite winter wheat accessions. The population was genotyped with a high-density Illumina iSelect 90K SNPs assay. A total of 31 loci were found to be associated with seeding emergence rate (SER) and tiller number in different growth stages. Loci distributed among 12 chromosomes accounted for 5.35 to 11.33% of the observed phenotypic variation. With this information, 10 stable SNPs were identified for eventual development of cleaved amplified polymorphic sequence markers for SER and tiller number in different growth stages. Additionally, a set of elite alleles were identified, such as Ra_c14761_1348-T, which may increase SER by 13.35%, and Excalibur_c11045_236-A and BobWhite_c8436_391-T, which may increase the rate of available tillering by 14.78 and 8.47%, respectively. These results should provide valuable information for marker-assisted selection and parental selection in wheat breeding programmes.

Linkage drag constrains the roots of modern wheat

Roots, the hidden half of crop plants, are essential for resource acquisition. However, knowledge about the genetic control of below-ground plant development in wheat, one of the most important small-grain crops in the world, is very limited. The molecular interactions connecting root and shoot development and growth, and thus modulating the plant's demand for water and nutrients along with its ability to access them, are largely unexplored. Here, we demonstrate that linkage drag in European bread wheat, driven by strong selection for a haplotype variant controlling heading date, has eliminated a specific combination of two flanking, highly conserved haplotype variants whose interaction confers increased root biomass. Reversing this inadvertent consequence of selection could recover root diversity that may prove essential for future food production in fluctuating environments. Highly conserved synteny to rice across this chromosome segment suggests that adaptive selection has shaped the diversity landscape of this locus across different, globally important cereal crops. By mining wheat gene expression data, we identified root-expressed genes within the region of interest that could help breeders to select positive variants adapted to specific target soil environments.

Genome-wide association mapping of resistance to eyespot disease (Pseudocercosporella herpotrichoides) in European winter wheat (Triticum aestivum L.) and fine-mapping of Pch1

Genotypes with recombination events in the Triticum ventricosum introgression on chromosome 7D allowed to fine-map resistance gene Pch1, the main source of eyespot resistance in European winter wheat cultivars. Eyespot (also called Strawbreaker) is a common and serious fungal disease of winter wheat caused by the necrotrophic fungi Oculimacula yallundae and Oculimacula acuformis (former name Pseudocercosporella herpotrichoides). A genome-wide association study (GWAS) for eyespot was performed with 732 microsatellite markers (SSR) and 7761 mapped SNP markers derived from the 90 K iSELECT wheat array using a panel of 168 European winter wheat varieties as well as three spring wheat varieties and phenotypic evaluation of eyespot in field tests in three environments. Best linear unbiased estimations (BLUEs) were calculated across all trials and ranged from 1.20 (most resistant) to 5.73 (most susceptible) with an average value of 4.24 and a heritability of H ² = 0.91. A total of 108 SSR and 235 SNP marker-trait associations (MTAs) were identified by considering associations with a -log₁₀ (P value) ≥3.0. Significant MTAs for eyespot-score BLUEs were found on chromosomes 1D, 2A, 2D, 3D, 5A, 5D, 6A, 7A and 7D for the SSR markers and chromosomes 1B, 2A, 2B, 2D, 3B and 7D for the SNP markers. For 18 varieties (10.5%), a highly resistant phenotype was detected that was linked to the presence of the resistance gene Pch1 on chromosome 7D. The identification of genotypes with recombination events in the introgressed genomic segment from Triticum ventricosum harboring the Pch1 resistance gene on chromosome 7DL allowed the fine-mapping of this gene using additional SNP markers and a potential candidate gene Traes_7DL_973A33763 coding for a CC-NBS-LRR class protein was identified.