Characterization of polyploid wheat genomic diversity using a high‐density 90 000 single nucleotide polymorphism array

Evaluation of Durum and Hard Red Spring Wheat Panels for Sensitivity to Necrotrophic Effectors Produced by Parastagonospora nodorum

Septoria nodorum blotch (SNB) is an important disease of both durum and hard red spring wheat (HRSW) worldwide. The disease is caused by the necrotrophic fungal pathogen Parastagonospora nodorum when compatible gene-for-gene interactions occur between pathogen-produced necrotrophic effectors (NEs) and corresponding host sensitivity genes. To date, nine sensitivity gene-NE interactions have been identified, but there is little information available regarding their overall frequency in durum and HRSW. Here, we infiltrated a global HRSW panel (HRSWP) and the Global Durum Panel (GDP) with P. nodorum NEs SnToxA, SnTox1, SnTox267, SnTox3, and SnTox5. Frequencies of sensitivity to SnTox1 and SnTox5 were higher in durum compared with HRSW and vice versa for SnTox267 and SnTox3. Strong associations for the known sensitivity loci Tsn1, Snn1, Snn2, Snn3, Snn5, and Snn7 along with potentially novel sensitivity loci on chromosome arms 7DS and 3BL, associated with SnToxA and SnTox267, respectively, were identified in the HRSWP. In the GDP, Snn1, Snn3, and Snn5 were identified along with novel loci associated with sensitivity to SnTox267 on chromosome arms 2AS, 2AL, and 6AS and with SnTox5 sensitivity on 2BS and 7BL. These results reveal additional NE sensitivity loci beyond those previously described, demonstrating a higher level of genetic complexity of the wheat-P. nodorum system than was previously thought. Knowledge regarding the prevalence and genomic locations of SNB susceptibility genes in HRSW and durum will prove useful for developing efficient breeding strategies and improving varieties for SNB resistance.

Recombination and structural variation in a large 8-founder wheat MAGIC population

Identifying the genetic architecture of complex traits requires access to populations with sufficient genetic diversity and recombination. Multiparent Advanced Generation InterCross (MAGIC) populations are a powerful resource due to their balanced population structure, allelic diversity, and enhanced recombination. However, implementing a MAGIC population in complex polyploids such as wheat is challenging, as wheat harbors many introgressions, inversions, and other genetic factors that interfere with linkage mapping. By utilizing a comprehensive crossing strategy, additional rounds of mixing, and novel genotype calling approaches, we developed a bread wheat 8-parent MAGIC population of over 3,000 genotyped recombinant inbred lines derived from 2,151 distinct crosses. This effort resulted in a dense genetic map covering the complete genome. Further rounds of intercrossing led to increased recombination in inbred lines, as expected. We identified structural variation highlighted by segregation distortion, along with epistatic allelic interactions between specific founders. We report on a novel and effective resource for genomic and trait exploration in hexaploid wheat, capable of detecting small genetic effects and epistatic interactions due to the high level of recombination and large number of lines. The interactions and genetic effects identified provide a basis for ongoing research to understand the basis of allelic frequencies across the genome, particularly where economically important loci are involved.

Genetic dissection of total protein content, phenolic content and seed quality traits in pigeonpea (Cajanus cajan) using 62K pigeonpea genic SNP chip

Pigeonpea (Cajanus cajan L. Millsp.), South Asia's second most significant pulse crop and source of dietary protein, is facing production issues due to a lack of improved varieties with high nutritional and seed quality compositions, as well as environmental stress. Identification of genes/alleles governing the nutritional and seed quality traits is key for marker-assisted breeding for quality traits in pigeonpea. Hence, the present study was undertaken to unravel the complex genetic architecture of nutritional and seed quality traits in pigeonpea. We conducted a genome-wide association study (GWAS) to identify SNP markers associated with nutritional traits, namely total protein content (TPC), phenolics content, and seed quality traits, such as seed coat colour, length, width, size, shape, and weight using a 62K SNP genotyping chip array. We estimated TPC of a panel of 287 diverse pigeonpea genotypes using Kjeldahl method to identify 5 significant SNPs associated with TPC on chromosomes 6 and 11 (AX-165344137), encoding a putative disease resistance protein, and Chromosome 11 (AX-165358192), encoding a CBL-interacting serine/threonine-protein kinase. We identified five markers associated with the seed coat colour on Chromosomes 5 (AX-165369586), 2 (AX-165370277), and 8 (AX-165400346). Additionally, we identified 4, 6, 2, 3, 6, and 5 SNPs associated with phenolics content, seed length, seed shape, seed width, seed size, and seed weight, respectively. The study's findings are projected to bring considerable benefits to pigeonpea producers in marker-assisted breeding for the production of varieties with improved protein content and seed quality traits corresponded to consumer preferences, as well as promote improved health and nutrition. Therefore, GWAS provides strong support for exploring the genetic mechanisms underlying important pigeonpea qualities and improving breeding strategies.

Stable pleotropic loci controlling the accumulation of multiple nutritional elements in wheat

Understanding the genetic basis of nutrient accumulation in wheat is crucial for improving its nutritional content and addressing global food security challenges. Here, we identified stable pleiotropic loci controlling the accumulation of 13 nutritional elements in wheat across diverse environments using a large wheat population of 1470 individuals. Our analysis revealed significant variability in SNP-based heritability values across 13 essential elements. Genetic correlations among elements uncovered complex relations, with positive correlations observed within two distinct groups, where calcium (Ca), cobalt (Co), potassium (K), and sodium (Na) formed one group, and copper (Cu), iron (Fe), magnesium (Mg), manganese (Mn), molybdenum (Mo), nickel (Ni), phosphorus (P), and zinc (Zn) formed the other. Negative correlations were observed among elements across both groups. Through MetaGWAS analysis, we identified stable QTL associated with individual elements and elements with high positive correlations. We identified 67 stable QTL across environments that are independent from grain yield, of which 56 were detected using the MetaGWAS analysis indicating their pleiotropic effect on multiple elements. A major QTL on chromosome 7D that can shift the phenotype up to one standard deviation compared to the mean phenotype in the population exhibited differential effects on multiple elements belonging to both groups. Our findings offer novel insights into the genetic architecture of nutrient accumulation in wheat and have practical implications for breeding programmes aimed at enhancing multiple nutrients simultaneously. By targeting stable QTL, breeders can develop wheat varieties with improved nutritional profiles, contributing to global food security and human health.

Ancient diversity of Triticum aestivum subspecies as source of novel loci for bread wheat improvement

Ancient subspecies of hexaploid wheat, not yet subjected to intensive selection, harbor potentially valuable alternative genetic variability for the genetic improvement of modern cultivated bread wheat. To investigate these hitherto unexplored resources, we established a panel, currently unique, consisting of 190 accessions of Triticum aestivum belonging to five different neglected subspecies, compactum, sphaerococcum, macha, spelta, and vavilovii, with few aestivum references. The panel was genotyped through the iSelect Illumina arrays (20K and 25K) and phenotyped for 25 traits related to phenology, morphology, yield, and physiology for 4 years under field conditions. We found wide variability for all traits analyzed, both within and among subspecies, demonstrating the richness contained therein. Through a genome-wide association study (GWAS), we identified a total of 126 marker-trait associations (MTAs), including 4 for years, 58 for morphological traits, 39 related to yield, and 25 for physiological traits, some of them confirming loci previously published and others being novel. Fourteen MTAs were associated with multiple traits. Among them, one on chromosome 2D at 360.2 Mb was associated with spike density, length, and shape, and thus is of particular interest because it may underlie the compactum (C) gene, until now considered difficult to clone because of its centromeric position. The physical distance defined by this MTA is considerably smaller (1.7 Mb) than what is reported so far in the literature, paving the way toward physical mapping of the C gene. A potential candidate gene has been identified for the trait grain number per spike. This is TraesCS6A03G0476500, coding for a monosaccharide-sensing protein 2, located on chromosome 6A at 233 Mb and identified through an MTA that segregates exclusively in compactum accessions. The results obtained confirm the remarkable potential present in the panel of wheat subspecies analyzed in this study, which, being characterized by a very short linkage disequilibrium (LD) decay, allowed the definition of rather narrow ranges around key traits, such as those related to yield, providing new perspectives on transferring genes across subspecies for wheat improvement.

A Genome-Wide Association Study Identifies Markers and Candidate Genes Affecting Tolerance to the Wheat Pathogen Zymoseptoria tritici

Plants defend themselves against pathogens using either resistance, measured as the host's ability to limit pathogen multiplication, or tolerance, measured as the host's ability to reduce the negative effects of infection. Tolerance is a promising trait for crop breeding, but its genetic basis has rarely been studied and remains poorly understood. Here, we reveal the genetic basis of leaf tolerance to the fungal pathogen Zymoseptoria tritici that causes the globally important septoria tritici blotch (STB) disease on wheat. Leaf tolerance to Z. tritici is a quantitative trait that was recently discovered in wheat by using automated image analyses that quantified the symptomatic leaf area and counted the number of pycnidia found on the same leaf. A genome-wide association study identified four chromosome intervals associated with tolerance and a separate chromosome interval associated with resistance. Within these intervals, we identified candidate genes, including wall-associated kinases similar to Stb6, the first cloned STB resistance gene. Our analysis revealed a strong negative genetic correlation between tolerance and resistance to STB, indicative of a trade-off. Such a trade-off between tolerance and resistance would hinder breeding simultaneously for both traits, but our findings suggest a way forward using marker-assisted breeding. We expect that the methods described here can be used to characterize tolerance to other fungal diseases that produce visible fruiting bodies, such as speckled leaf blotch on barley, potentially unveiling conserved tolerance mechanisms shared among plant species. [Formula: see text] Copyright © 2025 The Author(s). This is an open access article distributed under the CC BY 4.0 International license.

Twisted Sister1: an agravitropic mutant of bread wheat (Triticum aestivum) with altered root and shoot architectures

We identified a mutant of hexaploid wheat (Triticum aestivum) with impaired responses to gravity. The mutant, named Twisted Sister1 (TS1), had agravitropic roots that were often twisted along with altered shoot phenotypes. Roots of TS1 were insensitive to externally applied auxin, with the genetics and physiology suggestive of a mutated AUX/IAA transcription factor gene. Hexaploid wheat possesses over 80 AUX/IAA genes, and sequence information did not identify an obvious candidate. Bulked segregant analysis of an F2 population mapped the mutation to chromosome 5A, and subsequent mapping located the mutation to a 41 Mbp region. RNA-seq identified the TraesCS5A03G0149800 gene encoding a TaAUX/IAA protein to be mutated in the highly conserved domain II motif. We confirmed TraesCS5A03G0149800 as underlying the mutant phenotype by generating transgenic Arabidopsis thaliana. Analysis of RNA-seq data suggested broad similarities between Arabidopsis and wheat for the role of AUX/IAA genes in gravity responses, although there were marked differences. Here we show that the sequenced wheat genome, along with previous knowledge of the physiology of gravity responses from other plant species, gene mapping, RNA-seq, and expression in Arabidopsis have enabled the cloning of a key wheat gene that defines plant architecture.

Genetic dissection of leaf rust resistance in a diversity panel of tetraploid wheat (Triticum turgidum)

BACKGROUND

Leaf rust, caused by Puccinia triticina Eriks (Pt) is a major threat to wheat cultivation worldwide. The rapid evolution of this pathogen has led to the emergence of new virulent strains that can overcome the resistance of commonly cultivated wheat varieties. To address this threat, continuous monitoring of leaf rust pathotypes is conducted in wheat-growing regions across the world. This approach helps prioritize the development and deployment of resistant cultivars, as well as the implementation of other effective control measures against the prevailing races. The key wheat leaf rust pathotypes in India include 77-5 (121R63-1), 77-6 (121R55-1), 77-9 (121R60-1), 12-5 (29R45), and 104 (17R23). Among these pathotypes, 77-5 (121R63-1) and 77-9 (121R60-1) are the most prevalent since 2016. As virulent pathotypes continue to evolve and adapt, there is an urgent need to continually explore the vast germplasm repositories of wheat and its related species to identify novel genetic resources and genes that confer resistance to these evolving leaf rust pathotypes. Therefore, the present study aims to identify genes and genomic regions responsible for leaf rust resistance against prevalent pathotypes in India, focusing on a subset of the Global Durum Wheat Panel, which includes genotypes from various tetraploid wheat species.

RESULTS

This study revealed wide variation in seedling-stage resistance among 189 tetraploid wheat accessions against five prevalent leaf rust pathotypes in India namely, 77-5 (121R63-1), 77-6 (121R55-1), 77-9 (121R60-1), 12-5 (29R45) and 104 (17R23). Approximately 45% of the population exhibited immune/highly resistant to moderately resistant responses to pathotypes 77-5, 77-6 and 104, while around 23-27% showed similar levels of resistance to pathotypes 77-9 and 12-5. A genome-wide association study using six multi-locus models identified 88 significantly associated quantitative trait nucleotides (QTNs) across the five leaf rust pathotypes. Among these, 22 QTNs were considered reliable, including four for pathotype 77-5, six for 12-5, three for 77-9, seven for 104, and two for 77-6. Among the 22 reliable QTNs, 10 coincided with the rust resistance regions reported in previous studies, whereas 12 appeared to be novel. Further investigations of the regions flanking all 88 QTNs revealed 300 genes, including 62 associated with disease resistance or defense responses. In silico expression analysis of these defense-related genes revealed two nucleotide-binding site-leucine-rich repeat genes: one on chromosome 6B (TRITD6Bv1G224600) near QTN RAC875_c35430_373, and another on chromosome 6A (TRITD6Av1G225060) in the vicinity of QTN Excalibur_c77841_224 with significantly higher levels of expression in the leaf-resistant genotype during the early hours of Pt infection. Therefore, these two genes could be potential candidates for resistance to leaf rust in tetraploid wheat germplasm.

CONCLUSIONS

Our study provides a comprehensive understanding of the genetic basis underlying leaf rust resistance in a diverse tetraploid wheat germplasm panel. It has also revealed novel candidate genomic regions for leaf rust resistance. These genomic regions represent important targets for inclusion in marker-assisted breeding initiatives, aimed at fostering durable resistance against leaf rust disease.

MSTmap Online: enhanced usability, visualization, and accessibility

Genetic linkage maps are an essential tool in population genetics and plant breeding research, yet user-friendly online tools for constructing and visualizing them remain scarce. MSTmap Online addresses this gap by providing a modern, accessible platform for generating high-quality genetic linkage maps from genotypic data. The web server quickly computes linkage groups using the MSTmap algorithm and generates detailed output files, including publication-ready PDF visualizations of linkage groups. The server supports bookmarking and asynchronous processing, allowing users to revisit their results at a later time. A companion Python library for MSTmap Online enables seamless integration into custom analysis pipelines. MSTmap Online is free and open to all users with no login requirement at https://mstmap.org. The companion Python library is available at https://pypi.org/project/mstmap/.

Genetic Dissection of Triple Rust Resistance (Leaf, Yellow, and Stem Rust) in Kenyan Wheat Cultivar, "Kasuku"

Climate change is driving the spread of transboundary wheat diseases, necessitating the development of resilient wheat varieties for sustainable agriculture. Wheat rusts, including leaf rust (LR), yellow rust (YR), and stem rust (SR), remain among the most economically significant diseases, causing substantial yield losses worldwide. Enhancing genetic diversity by identifying and deploying rust resistance genes is crucial for durable resistance in wheat breeding programs. This study aimed to identify quantitative trait loci (QTL) associated with rust resistance in the CIMMYT wheat line Kasuku, released in Kenya in 2018. A recombinant inbred line (RIL) population (181 lines) derived from Kasuku (triple rust-resistant) and Apav#1 (triple rust-susceptible) was evaluated under artificial LR and YR epidemics in Mexico and YR and SR in Kenya. QTL mapping using genotyping-by-sequencing (DArTSeq) and phenotypic data identified four major loci: QLrYrSr.cim-1BL (Lr46/Yr29/Sr58) on 1BL, conferring resistance to LR, YR, and SR; QLrYr.cim-2AS (Yr17/Lr37) on 2AS, providing LR and YR resistance; QLrYr.cim-3AL on 3AL; and QLrYrSr.cim-6AL on 6AL, representing novel loci associated with multiple rust resistances. Additionally, minor QTL were also identified: for LR (QLr.cim-2DS on 2DS, QLr.cim-6DS on 6DS), for YR (QYrKen.cim-3DS on 3DS, QYrKen.cim-6BS on 6BS), and for SR (QSr.cim-2BS on 2BS, QSr.cim-5AL on 5AL, QSr.cim-6AS on 6AS). RILs carrying these QTL combinations exhibited significant reductions in rust severity. Flanking markers for these loci are being used to develop Kompetitive Allele-Specific PCR (KASP) markers for fine mapping and marker-assisted selection (MAS). These findings contribute to the strategic deployment of rust resistance genes in wheat breeding programs, facilitating durable resistance to multiple rust pathogens.

Optimization of commercial SNP arrays and the generation of a high-efficiency GenoBaits Peanut 10K panel

To create a more comprehensive genetic analysis panel for peanuts, three high-density SNP panels were exploited. The refined SNP panel, PHR0301_Ah10K, comprises 10,000 SNP sites and demonstrated outstanding performance in sequence data analysis. It recorded the highest proportions of 99.53%, 96.48%, and 59.72% for the SNPs with minor allele frequency thresholds of MAF > 5%, MAF > 10%, and MAF > 20%, respectively. Moderate polymorphic information content (PIC) values were observed, with an average of 0.26, suggesting that the optimized SNP panel is informative. However, the PIC value for the four panels were skewed due to the small population size and limited genetic diversity (GD), as evidenced by the Kinship, PCA, and LD decay analyses. However, PHR0301_Ah10K demonstrated superior performance compared to the others in terms of variance explained in the PCA analysis while the outcomes of the genetic analyses confirmed its genotyping ability in peanut. The putative SNP sites associated with increased oleic acid levels have been integrated into this panel and validated, thus significantly enhancing its breeding potential. Moreover, the cost of genotyping by target sequencing (GBTS) using this panel is less than $9 per sample, making it more affordable. Due to its exceptional informativeness, cost-effectiveness, and breeding potential, we recommend this SNP panel for GBTS in peanut.

Genome-wide association mapping for the identification of stripe rust resistance loci in US hard winter wheat

KEY MESSAGE

The GWAS and testing with Yr gene linked markers identified 109 loci including 40 novel loci for all-stage and adult plant stage resistance to stripe rust in 459 US contemporary hard winter wheat genotypes. Stripe rust is a destructive wheat disease, caused by Puccinia striiformis f. sp. tritici (Pst). To identify sources of stripe rust resistance in US contemporary hard winter wheat, a panel of 459 Great Plains wheat genotypes was evaluated at the seedling stage against five US Pst races and at the adult plant stage in field environments in Oklahoma, Kansas, and Washington. The results showed that 7-14% of the genotypes were resistant to Pst races at the seedling stage, whereas 32-78% of genotypes were resistant at the adult plant stage across field environments, indicating the presence of adult plant resistance. Sixteen genotypes displayed a broad spectrum of resistance to all five Pst races and across all field environments. The panel was further genotyped using 9858 single-nucleotide polymorphisms (SNPs) generated from multiplex restriction amplicon sequencing (MRASeq) and the functional DNA markers linked to the known stripe rust resistance (Yr) genes Yr5, Yr15, Yr17, Yr18, Yr29, Yr36, Yr40, Yr46, and QYr.tamu-2B. A genome-wide association study (GWAS) was performed using genotypic and phenotypic data, which identified 110 SNPs and the functional markers linked to Yr15 and Yr17 to be significantly associated with stripe rust response. In addition, Yr5, Yr15, Yr17, Yr18, Yr29, and QYr.tamu-2B were detected by their functional DNA markers in the panel. This study identified 40 novel loci associated with stripe rust resistance in genomic regions not previously characterized by known Yr genes. These findings offer significant opportunities to diversify and enhance stripe rust resistance in hard winter wheat.

GEFormer: A genotype-environment interaction-based genomic prediction method that integrates the gating multilayer perceptron and linear attention mechanisms

The integration of genotypic and environmental data can enhance genomic prediction accuracy for crop field traits. Existing genomic prediction methods fail to consider environmental factors and the real growth environments of crops, resulting in low genomic prediction accuracy. In this work, we developed GEFormer, a genotype-environment interaction genomic prediction method that integrates gating multilayer perceptron (gMLP) and linear attention mechanisms. First, GEFormer uses gMLP to extract local and global features among SNPs. Then, Omni-dimensional Dynamic Convolution is used to extract the dynamic and comprehensive features of multiple environmental factors within each day, taking into consideration the real growth pattern of crops. A linear attention mechanism is used to capture the temporal features of environmental changes. Finally, GEFormer uses a gating mechanism to effectively fuse the genomic and environmental features. We examined the accuracy of GEFormer for predicting important agronomic traits of maize, rice, and wheat under three experimental scenarios: untested genotypes in tested environments, tested genotypes in untested environments, and untested genotypes in untested environments. The results showed that GEFormer outperforms six cutting-edge statistical learning methods and four machine learning methods, especially with great advantages under the scenario of untested genotypes in untested environments. In addition, we used GEFormer for three real-world breeding applications: phenotype prediction in unknown environments, hybrid phenotype prediction using an inbred population, and cross-population phenotype prediction. The results showed that GEFormer had better prediction performance in actual breeding scenarios and could be used to assist in crop breeding.

Unraveling the genetic basis of heat tolerance and yield in bread wheat: QTN discovery and Its KASP-assisted validation

BACKGROUND

Wheat (Triticum aestivum L.), a globally significant cereal crop and staple food, faces major production challenges due to abiotic stresses such as heat stress (HS), which pose a threat to global food security. To address this, a diverse panel of 126 wheat genotypes, primarily landraces, was evaluated across twelve environments in India, comprising of three locations, two years and two growing conditions. The study aimed to identify genetic markers associated with key agronomic traits in bread wheat, including germination percentage (GERM_PCT), ground cover (GC), days to booting (DTB), days to heading (DTHD), days to flowering (DTFL), days to maturity (DTMT), plant height (PH), grain yield (GYLD), thousand grain weight (TGW), and the normalized difference vegetation index (NDVI) under both timely and late-sown conditions using 35 K SNP genotyping assays. Multi-locus GWAS (ML-GWAS) was employed to detect significant marker-trait associations, and the identified markers were further validated using Kompetitive Allele Specific PCR (KASP).

RESULTS

Six ML-GWAS models were employed for this purpose, leading to the identification of 42 highly significant and consistent quantitative trait nucleotides (QTNs) under both timely and late sown conditions, controlled by 20 SNPs, explaining 3-58% of the total phenotypic variation. Among these, noteworthy QTNs were a major grain yield QTN (qtn_nbpgr_GYLD_3B) on chromosome 3B, a pleiotropic SNP AX-95018072 on chromosome 7A influencing phenology and NDVI, and robust TGW QTNs on chromosomes 2B (qtn_nbpgr_TGW_2B), 1A (qtn_nbpgr_TGW_1A), and 4B (qtn_nbpgr_TGW_4B). Furthermore, annotation revealed that candidate genes near these QTNs encoded stress-responsive proteins, such as chaperonins, glycosyl hydrolases, and signaling molecules. Additionally, three major SNPs AX-95018072 (7A), AX-94946941 (6B), and AX-95232570 (1B) were successfully validated using KASP assay.

CONCLUSION

Our study effectively uncovered novel QTNs and candidate genes linked to heat tolerance and yield-related traits in wheat through an extensive genetic approaches. These QTNs not only corresponded with previously identified QTLs and genes associated with yield traits but also highlighted several new loci, broadening the existing genetic understanding. These findings provide valuable insights into the genetic basis of heat tolerance in wheat and offer genomic resources, including validated markers that could accelerate marker-assisted breeding and the development of next-generation heat-resilient cultivars.

Genome-wide association study identifies QTL and candidate genes for grain size and weight in a Triticum turgidum collection

Wheat breeders are constantly looking for genes and alleles that increase grain yield. One key strategy is finding new genetic resources in the wild and domesticated gene pools of related species with genes affecting grain size. This study explored a natural population of Triticum turgidum (L.) phenotyped for grain weight and size-related traits in three field trials and genotyped with single nucleotide polymorphism markers spread across the entire genome. The genome-wide association study analysis identified 39 quantitative trait loci (QTL) for 1000-kernel weight, grain length, grain width, grain area, and grain aspect consistent in at least two and across environments. Interestingly, 23 QTL for grain-related traits were grouped in nine QTL clusters located on chromosomes 1A, 1B, 2B, 3B, 4B, 5A, and 6B, respectively. Moreover, most of these QTL support findings from previous QTL analyses and are further strengthened by the known functions of the genes (such as BG2, GS5, and SRS3) and their similarity to genes in other cereal species. QTL clusters harbored genes that participate in various metabolic processes potentially involved in seed development, phytohormone signaling, sugar transport, mitogen-activated protein kinases signaling, and transcriptional factors (such as MADS-box and WRKY). Identifying loci controlling grain-related traits will provide information on the genetic resources available to breeders to improve grain yield, as well as the opportunity to develop close gene markers to be used in marker-assisted selection programs.

A linkage map of Aegilops biuncialis reveals significant genomic rearrangements compared to bread wheat

Goatgrasses with U- and M-genomes are important sources of new alleles for wheat breeding to maintain yield and quality under extreme conditions. However, the introgression of beneficial traits from wild Aegilops species into wheat has been limited by poor knowledge of their genomes and scarcity of molecular tools. Here, we present the first linkage map of allotetraploid Aegilops biuncialis Vis., developed using 224 F2 individuals derived from a cross between MvGB382 and MvGB642 accessions. The map comprises 5663 DArTseq markers assigned to 15 linkage groups corresponding to 13 chromosomes. Chromosome 1Mb could not be constructed due to a lack of recombination caused by rearrangements in the MvGB382 accession. The genetic map spans 2518 cM with an average marker density of 2.79 cM. The skeleton map contains 920 segregating markers, divided between the Mb sub-genome (425 markers) and the Ub sub-genome (495 markers). Chromosomes of the Mb sub-genome, originating from Aegilops comosa Sm. in Sibth. et Sm., show well-preserved collinearity with Triticum aestivum L. chromosomes. In contrast, chromosomes of the Ub sub-genome, originating from Aegilops umbellulata Zhuk., exhibit a varying degree of collinearity, with 1Ub, 3Ub, and 5Ub retaining a substantial level of collinearity with Triticum aestivum, while 2Ub, 4Ub, 6Ub, and 7Ub show significant rearrangements. A quantitative trait locus affecting fertility was identified near the centromere on the long arm of chromosome 3Mb, explaining 23.5% of the variance. The genome structure of Aegilops biuncialis, highlighted by the genetic map, provides insights into the speciation within the species and will support alien gene transfer into wheat.

Identification of robust yield quantitative trait loci derived from cultivated emmer for durum wheat improvement

Durum wheat (Triticum turgidum ssp. durum L.) is an important world food crop used to make pasta products. Compared to bread wheat (Triticum aestivum L.), fewer studies have been conducted to identify genetic loci governing yield-component traits in durum wheat. A potential source of diversity for durum is its immediate progenitor, cultivated emmer (T. turgidum ssp. dicoccum). We evaluated two biparental populations of recombinant inbred lines (RILs) derived from crosses between the durum lines Ben and Rusty and the cultivated emmer wheat accessions PI 41025 and PI 193883, referred to as the Ben × PI 41025 (BP025) and Rusty × PI 193883 (RP883) RIL populations, respectively. Both populations were evaluated under field conditions in three seasons with an aim to identify quantitative trait loci (QTLs) associated with yield components and seed morphology that were expressed in multiple environments. A total of 44 and 34 multi-environment QTLs were identified in the BP025 and RP883 populations, respectively. As expected, genetic loci known to govern domestication and development were associated with some of the QTLs, but novel QTLs derived from the cultivated emmer parents and associated with yield components including spikelet number, grain weight, and grain size were identified. These QTLs offer new target loci for durum wheat improvement, and toward that goal, we identified five RILs with increased grain weight and size compared to the durum parents. These materials along with the knowledge of stable QTLs and associated markers can help to expedite the development of superior durum varieties.

Association mapping and genomic prediction for processing and end-use quality traits in wheat (Triticum aestivum L.)

End-use and processing traits in wheat (Triticum aestivum L.) are crucial for varietal development but are often evaluated only in the advanced stages of the breeding program due to the amount of grain needed and the labor-intensive phenotyping assays. Advances in genomic resources have provided new tools to address the selection for these complex traits earlier in the breeding process. We used association mapping to identify key variants underlying various end-use quality traits and evaluate the usefulness of genomic prediction for these traits in hard red spring wheat from the Northern United States. A panel of 383 advanced breeding lines and cultivars representing the diversity of the University of Minnesota wheat breeding program was genotyped using the Illumina 90K single nucleotide polymorphism array and evaluated in multilocation trials using standard assessments of end-use quality. Sixty-three associations for grain or flour characteristics, mixograph, farinograph, and baking traits were identified. The majority of these associations were mapped in the vicinity of glutenin/gliadin or other known loci. In addition, a putative novel multi-trait association was identified on chromosome 6AL, and candidate gene analysis revealed eight genes of interest. Further, genomic prediction had a high predictive ability (PA) for mixograph and farinograph traits, with PA up to 0.62 and 0.50 in cross-validation and forward prediction, respectively. The deployment of 46 markers from GWAS to predict dough-rheology traits yielded low to moderate PA for various traits. The results of this study suggest that genomic prediction for end-use traits in early generations can be effective for mixograph and farinograph assays but not baking assays.

Genetic diversity analysis and core germplasm construction of tea plants in Lu'an

BACKGROUND

Lu'an, as one of the two major tea-producing areas in Anhui Province, has a long history of tea planting and rich tea germplasm resources. However, the genetic diversity and population structure of local tea plants are still unclear. In order to better protect and utilize tea germplasm resources in Lu'an, 217 tea accessions from six geographical origins were used to assess genetic diversity of Lu'an tea plant germplasm through double digest restriction-site associated DNA sequencing (ddRAD-seq) technology.

RESULTS

A total of 306,320 high quality single nucleotide polymorphism (SNP) markers were obtained. Population structure, phylogenetic relationships and principal component analysis (PCA) divided the entire population into three groups. The genetic diversity and population differentiation analysis showed that the mean observed heterozygosity (Ho) was 0.06 ∼ 0.17, average nucleotide diversity (Pi) was 0.13 ∼ 0.26, and pairwise fixation index (Fst) was 0.01 ∼ 0.15. In addition, a core tea germplasm set composed of 50 tea germplasm sets was established.

CONCLUSION

Our study demonstrated that the germplasm resources of the Lu'an tea plants exhibit significant genetic diversity. A core germplasm sets for the Lu'an tea plants has been established, which effectively represents the genetic diversity of the entire tea germplasm collection. This study provided the basis for genetic research, germplasm protection and breeding of tea plants in Lu'an.

Plant Productivity and Leaf Starch During Grain Fill Is Linked to QTL Containing Flowering Locus T1 (FT1) in Wheat (Triticum aestivum L.)

Shifts in the environment due to climate change necessitate breeding efforts aimed at adapting wheat to longer, warmer growing seasons. In this study, 21 modern wheat (Triticum aestivum L.) cultivars and 29 landraces were screened for flag leaf starch levels, with the goal of identifying a genetic marker for targeted breeding. The landrace PI 61693 was identified as having exceptionally high flag leaf starch values. Yield trials were carried out in a Berkut × PI 61693 recombinant inbred line (RIL) population and a negative correlation was observed between leaf starch, flowering time, and yield. Genetic mapping identified a Quantitative Trait Loci (QTL) explaining 22-34% variation for leaf starch, flowering time, biomass, and seed yield. The starch synthase TraesCS7D02G117800 (wSsI-1) is located in this region, which possibly accounts for leaf starch variation in this population; also within this QTL is TraesCS7D02G111600 (FT-D1). Sequencing of FT-D1 identified a single base pair deletion in the 3rd exon of the Berkut allele. This indel has recently been shown to significantly impact flowering time and productivity, and likely led to significant variation in flowering date and yield in this population. Here, we illustrate how allelic selection of FT-D1 within breeding programs may aid in adapting wheat to changing environments.

Genome-wide association study reveals major loci for resistance to septoria tritici blotch in a Tunisian durum wheat collection

Septoria tritici blotch (STB) is a devastating fungal disease affecting durum and bread wheat worldwide. Tunisian durum wheat landraces are reported to be valuable genetic resources for resistance to STB and should prominently be deployed in breeding programs to develop new varieties resistant to STB disease. In this study, a collection of 367 old durum and 6 modern wheat genotypes previously assessed using single Tunisian Zymoseptoria tritici isolate TUN06 during 2016 and 2017 and TM220 isolate during 2017 were phenotyped for resistance to a mixture of isolates (BULK) under field conditions. Significant correlations for disease traits using the three different inoculums were observed. Using 7638 SNP markers, fifty-one marker-trait associations (MTAs) for STB resistance were identified by genome-wide association study (GWAS) at Bonferroni correction threshold of -log10(P) > 5.184 with phenotypic variance explained (PVE) reaching up to 58%. A total of eleven QTL were identified using TUN06 isolate mean disease scoring (TUNMeanD and TUNMeanA) including threeQTL controlling resistance to both isolates TUN06 and TM220. A major QTL was identified on each of chromosomes 1B, 4B, 5A, and 7B, respectively. The QTL on 7B chromosome colocalized with Stb8 identified in bread wheat. Four QTL including the major QTL identified on chromosome 1B were considered as novel. SNP linked to the significant QTL have the potential to be used in marker-assisted selection for breeding for resistance to STB.

Genome-wide association mapping for stay-green and stem reserve mobilization traits in wheat (Triticum aestivum L.) under combined heat and drought stress

Stay-green (SG) and stem reserve mobilization (SRM) are two significant mutually exclusive traits, which contributes to grain-filling during drought and heat stress in wheat. The current research was conducted in a genome-wide association study (GWAS) panel consisting of 278 wheat genotypes of advanced breeding lines to find the markers linked with SG and SRM traits and also to screen the superior genotypes. SG and SRM traits, viz. soil plant analysis development (SPAD) value, canopy temperature (CT), normalized difference vegetation index (NDVI), leaf senescence rate (LSR) and stem reserve mobilization efficiency (SRE) were recorded. The trial was conducted in α-lattice design, under control and combined heat and drought stress (HD). Analysis of variance and descriptive statistics showed a significant difference across the evaluated traits. The highest mean of SRE (31.7%) and SRM (0.42 g/stem) was reported in HD, while highest SRE in HD and lowest in control was 52.56% and 15.7%, respectively. Genotyping was carried out using the 35 K Axiom R Wheat Breeder's Array, 14,625 SNPs were kept after filtering. Through GWAS, 36 significant marker trait associations (MTAs) were identified on 16 distinct chromosomes; out of this, 22 MTAs were found under control and 14 MTAs under HD. Candidate genes that code for UDP-glycosyltransferase 73C4-like and protein detoxification 40-like was linked to SPAD and CT respectively. One MTAs was detected for SRM on chromosome 6B that code for wall associated receptor kinase 4 like. These SNPs can be utilized to generate cultivars that adapt to climate change by a marker-assisted gene transfer.

Identification and validation of two quantitative trait loci for dwarf bunt in the resistant cultivar 'UI Silver'

KEY MESSAGE

Two dwarf bunt resistance QTLs were mapped to chromosome 6D, and KASP markers associated with the loci were developed and validated in a panel of regionally adapted winter wheats. UI Silver is an invaluable adapted resistant cultivar possessing the two identified QTL potentially associated with genes Bt9 and Bt10 and will be useful in future cultivar development to improve dwarf bunt resistance. Dwarf bunt, caused by Tilletia controversa, is a fungal disease of wheat that can cause complete loss of grain yield and quality during epidemics. Traditional breeding for dwarf bunt resistance requires many years of field screening under stringent conditions with disease assessment possible only near or after plant maturity. Molecular marker-assisted selection (MAS) offers a more efficient alternative. This study identified quantitative trait loci (QTL) and associated molecular markers for dwarf bunt resistance in wheat. A doubled haploid (DH) mapping population of 135 lines, derived from bunt-resistant cultivar 'UI Silver' and susceptible line 'Shaan89150', was evaluated in field nursery in Logan, Utah in 2017, 2018, and 2023. The population was genotyped using Illumina 90 K SNP iSelect marker platform. Using inclusive composite interval mapping (ICIM), the major QTL Qdb.ssdhui-6DL was consistently identified on chromosome arm 6DL across all environments, explaining phenotypic variations ranging from 15.29% to 35.40%. Another QTL, Qdb.ssdhui-6DS, was detected on chromosome arm 6DS, explaining approximately 11% of the phenotypic variation. These two QTLs exhibit additive-by-additive effects for increased resistance within the DH population. Kompetitive allele-specific PCR (KASP) markers were developed within QTL intervals and used in a validation panel of regionally adapted winter wheat lines to confirm the association between the two QTL and dwarf bunt resistance. Thus, 'UI Silver' and additional resistant cultivars with these two QTLs are valuable parental lines for improving dwarf bunt resistance through marker-assisted selection. These genetic resources are essential for understanding gene function via map-based gene cloning.

Identification of 39 stripe rust resistance loci in a panel of 465 winter wheat entries presumed to have high-temperature adult-plant resistance through genome-wide association mapping and marker-assisted detection

Stripe rust of wheat is a serious disease caused by Puccinia striiformis f. sp. tritici (Pst). Growing resistant cultivars is the most preferred approach to control the disease. To identify wheat genotypes with quantitative trait loci (QTL) for durable resistance to stripe rust, 465 winter wheat entries that were presumed to have high-temperature adult-plant (HTAP) resistance were used in this study. In the greenhouse seedling tests with seven Pst races, 16 entries were resistant to all the tested races. The 465 entries were also phenotyped for stripe rust responses at the adult-plant stage under natural infection of Pst in multiple field locations from 2018 to 2021 in the Washington state, and 345 entries were found to have stable resistance. The contrast of the susceptibility in the greenhouse seedling tests and the resistance in the field adult-plant stage for most of the entries indicated predominantly HTAP resistance in this panel. The durability of the resistance was demonstrated by a subset of 175 entries that were tested in multiple locations from 2007 to 2021. The 465 entries were genotyped through genotyping by multiplexed sequencing of single-nucleotide polymorphism (SNP) markers. Combining the stripe rust response and SNP marker data, a genome-wide association study (GWAS) was conducted, resulting in 143 marker-trait associations, from which 28 QTL that were detected at least with two races or in two field environments were identified, including seven for all-stage resistance and 21 for HTAP resistance. These QTL each explained 6.0% to 40.0% of the phenotypic variation. Compared with previously reported Yr genes and QTL based on their genomic positions, five QTL including two for HTAP resistance were identified as new. A total of 10 user-friendly Kompetitive allele specific PCR (KASP) markers were developed for eight of the HTAP resistance loci. In addition, molecular markers were used to detect 13 previously reported HTAP resistance genes/QTL, including two also identified in the GWAS analyses, and their frequencies ranged from 0.86% to 88.17% in the panel. The durable resistant genotypes, the genes/QTL identified, and the KASP markers developed in this study should be useful to develop wheat cultivars with long-lasting resistance to stripe rust.

Reconciliation of wheat 660K and 90K SNP arrays and their utilization in dough rheological properties of bread wheat

INTRODUCTION

High-density Wheat 660K and 90K SNP arrays are powerful tools for understanding the genetic basis of wheat traits. However, their inconsistantly physical positions that were caused by different versions of Chinese Spring genome during developing arrays are confused and inconvenient for further application.

OBJECTIVE

With the repid development of wheat geonome sequencing, we aim to reconciliate Wheat 660K and 90K SNP arrays in modern cultivar and reveal the genetic basis of dough rheological properties in bread wheat.

METHODS

We refined physical positions of Wheat 660K and 90K SNP arrays in the currently popular wheat cultivar AK58 genome that was released more recently. We next performed genome-wide association studies (GWAS) and linkage analysis to identify important genetic loci related to quality traits using updated and un-updated arrays, respectively.

RESULTS

Refining results showed that 92.3% and 83% of SNPs in the Wheat 660K and 90K SNP arrays were precisely mapped to the AK58 genome, respective. GWAS results by the updated 660K and 90K arrays indicated that 26 intervals composed of 1032 significant SNPs were associated with 9 quality traits in multiple environments. The significant interval for stability time on 1D was narrowed into an 8.4-Mb region using the updated arrays, whereas the interval is 405 Mb using the un-updated arrays. Linkage analysis revealed an important QTL QST.henau-1D.2 for stability time with 1.64 Mb. Integration of GWAS and QTL results narrowed the significant interval into 6.46 Mb containing 35 annotation genes by collinearity analysis. After T-test, gene expression analysis, seven of them are potential candidate genes and thus favorable haplotypes are identified to benefit marker-assisted selection.

CONCLUSION

A reconciliation of Wheat 660K and 90K arrays promote their efficient applications. Important genetic loci and favorable haplotypes identified in this study provided valuable information for wheat quality breeding.

Developing Breeder-Friendly KASP Markers for Rust R Genes

The marker-assisted breeding (MAB) approach has become more convenient and time efficient with the advancement of allele-specific, cost-effective, and breeder-friendly single nucleotide polymorphism (SNP)-based kompetitive allele-specific (KASP) polymerase chain reaction (PCR) markers. Here, we describe a detailed protocol to develop KASP assays for rust resistance breeding in wheat.

Identification and Genetic Analysis of Rust Resistance Genes in Wheat for Marker-Assisted Selection

Wheat rusts cause severe reductions in wheat yield around the globe. Due to economic losses caused by rust pathogens, they are priority-one diseases for breeding in Canada and other countries. Given the importance of breeding for rust resistance in wheat, various wheat variety registration processes around the world require a minimum resistance threshold to rust pathogens. Considering the coevolution of rust pathogens and their host, these fungi can evolve quickly and overcome resistance in cultivated wheat varieties. Thus, identification, characterization, and breeding using novel resistance sources can result in optimal yields to ensure food security. Various sources of rust resistance actively used in wheat breeding include landraces and wild accessions in addition to international modern wheats. A typical rust resistance evaluation process involves the identification of resistant germplasm through phenotypic analysis, followed by the development of mapping populations, and finally, introgression into breeding material using phenotypic and marker-assisted selection. In this chapter, we outline greenhouse phenotyping and linkage analysis methodologies to identify loci underlying rust resistance and use of linked molecular markers for wheat breeding.

Pseudo-linkage or real-linkage of rust resistance genes in a wheat-Thinopyrum intermedium translocation line

KEY MESSAGE

We analysed the chromosomal structures of two wheat-Thinopyrum intermedium addition lines Z4 and Z5 and resolved the linkage relationship between the leaf rust and stripe rust resistance genes in Z4. Wheat addition lines Z4 and Z5 carrying rust resistance genes from Thinopyrum intermedium (JJJsJsStSt, 2n = 6x = 42) together with three wheat lines involved in the production of these addition lines were analysed by rust response, 90K SNP genotyping, and molecular cytogenetic analysis. Seedling leaf rust (LR) responses to five diverse pathotypes indicated that the LR resistance gene(s) was located in translocation chromosome T3DS-3AS.3AL-7StS common to Z4 and Z5. The stripe rust (YR) resistance gene(s) was located in translocation chromosome T3AL-7StS.7StL, which is unique to Z4, based on the seedling YR responses to four diverse pathotypes. Backcross and selfed populations involving the addition lines and various wheat cultivars were studied to understand the inheritance of the alien resistance genes. Although inheritance studies indicated genetic linkage, the alien genes for resistance to leaf rust (LR) and stripe rust (YR) in Z4 were present in different wheat-Th. intermedium translocation chromosomes. We found that LR and YR were in pseudo-linkage, rather than true linkage.

Meta-QTL mapping for wheat thousand kernel weight

Wheat domestication and subsequent genetic improvement have yielded cultivated species with larger seeds compared to wild ancestors. Increasing thousand kernel weight (TKW) remains a crucial goal in many wheat breeding programs. To identify genomic regions influencing TKW across diverse genetic populations, we performed a comprehensive meta-analysis of quantitative trait loci (MQTL), integrating 993 initial QTL from 120 independent mapping studies over recent decades. We refined 242 loci into 66 MQTL, with an average confidence interval (CI) 3.06 times smaller than that of the original QTL. In these 66 MQTL regions, a total of 4,913 candidate genes related to TKW were identified, involved in ubiquitination, phytohormones, G-proteins, photosynthesis, and microRNAs. Expression analysis of the candidate genes showed that 95 were specific to grain and might potentially affect TKW at different seed development stages. These findings enhance our understanding of the genetic factors associated with TKW in wheat, providing reliable MQTL and potential candidate genes for genetic improvement of this trait.

Genome-Wide Association Mapping of Macronutrient Mineral Accumulation in Wheat (Triticum aestivum L.) Grain

The focus on increasing wheat (Triticum aestivum L.) grain yield at the expense of grain quality and nutrient accumulation can lead to shortages in macronutrient minerals, which are dangerous for human health. This is important, especially in nations where bread wheat is used in most daily dietary regimens. One efficient way to guarantee nutritional security is through biofortification. A genome-wide association mapping approach was used to investigate the genetic basis of the differences in macronutrient mineral accumulation in wheat grains. N, P, K, Na, Ca, and Mg concentrations were measured after a panel of 200 spring wheat advanced lines from the Wheat Association Mapping Initiative were cultivated in the field. The population exhibited a wide range of natural variations in macronutrient minerals. The minerals were found to have strong positive correlations except for magnesium, which had negative correlation patterns with N, P, and K. Furthermore, there were negative correlations between N and each of Ca and Na. Remarkably, genotypes with large yields contained moderate levels of critical metals. Of the 148 significant SNPs above -log10(P) = 3, 29 had -log10(P) values greater than 4. Four, one, and nineteen significant SNPs with a -log10(P) between 4 and 5.8 were associated with N and mapped on chromosomes 1A, 1B, and 1D, respectively. Three significant SNPs on chromosome A3 were associated with K. Two significant SNPs were associated with Ca and Na and mapped on chromosomes B3 and A4, respectively. Our findings offer crucial information about the genetic underpinnings of nutritional mineral concentration augmentation, which can guide future breeding research to enhance human nutrition.

Genome-wide analysis for root and leaf architecture traits associated with drought tolerance at the seedling stage in a highly ecologically diverse wheat population

Drought stress occurred at early growth stages in wheat affecting the following growth stages. Therefore, selecting promising drought-tolerant genotypes with highly adapted traits at the seedling stage is an important task for wheat breeders and geneticists. Few research efforts were conducted on the genetic control for drought-adaptive traits at the seedling stage in wheat. In this study, a set of 146 highly diverse spring wheat core collections representing 28 different countries was evaluated under drought stress at the seedling stage. All genotypes were exposed to drought stress for 13 days by water withholding. Leaf traits including seedling length, leaf wilting, days to wilting, leaf area, and leaf rolling were scored. Moreover, root traits such as root length, maximum width, emergence angle, tip angle, and number of roots were scored. Considerable significant genetic variation was found among all genotypes tested in these experiments. The heritability estimates ranged from 0.74 (leaf witling) to 0.99 (root tip angle). A set of nine genotypes were selected and considered drought-tolerant genotypes. Among all leaf traits, shoot length had significant correlations with all root traits under drought stress. The 146 genotypes were genotyped using the Infinium Wheat 15 K single nucleotide polymorphism (SNP) array and diversity arrays technology (DArT) marker platform. The result of genotyping revealed 12,999 SNPs and 2150 DArT markers which were used to run a genome-wide association study (GWAS). The results of GWAS revealed 169 markers associated with leaf and root traits under drought stress. Out of the 169 markers, 82 were considered major quantitative trait loci (QTL). The GWAS revealed 95 candidate genes were identified with 53 genes showing evidence for drought tolerance in wheat, while the remaining candidate genes were considered novel. No shared markers were found between leaf and root traits. The results of the study provided mapping novel markers associated with new root traits at the seedling stage. Also, the selected genotypes from different countries could be employed in future wheat breeding programs not only for improving adaptive drought-tolerant traits but also for expanding genetic diversity.

Candidate selective sweeps in US wheat populations

Exploration of novel alleles from ex situ collection is still limited in modern plant breeding as these alleles exist in genetic backgrounds of landraces that are not adapted to modern production environments. The practice of backcross breeding results in preservation of the adapted background of elite parents but leaves little room for novel alleles from landraces to be incorporated. Selection of adaptation-associated linkage blocks instead of the entire adapted background may allow breeders to incorporate more of the landrace's genetic background and to observe and evaluate novel alleles. Important adaptation-associated linkage blocks would have been selected over multiple cycles of breeding and hence are likely to exhibit signatures of positive selection or selective sweeps. We conducted genome-wide scan for candidate selective sweeps (CSS) using Fst, Rsb, and xpEHH in state, regional, spring, winter, and market-class population pairs and reported 446 CSS in 19 population pairs over time and 1033 CSS in 44 population pairs across geography and class. Further validation of these CSS in specific breeding programs may lead to identification of sets of loci that can be selected to restore population-specific adaptation in pre-breeding germplasms.

Identification and validation of novel plant compactness QTL in common wheat

BACKGROUND

Plant compactness (PC) is a crucial agronomic trait that affects plant density in wheat, which in turn influences biomass and grain yield potential. The canopy of high-yielding wheat varieties should exhibit appropriate aboveground plant architecture. In this study, three recombinant inbred line (RIL) populations were generated to identify and validate quantitative trait loci (QTL) related to plant compactness. The erect and compact tillering genotype SN05525 was used as a common parent. A total of 193 F8 RILs from the cross SN05525/SN22 were genotyped using the high-density Illumina iSelect 90 K single nucleotide polymorphism (SNP) assay.

RESULTS

A linkage map with 7180 SNP loci was constructed, revealing six QTL on chromosomes 3B (Qpc.sdau-3B.1, Qpc.sdau-3B.2),5B (Qpc.sdau-5B), 5D (Qpc.sdau-5D), 2 A (Qpc.sdau-2 A), and 7 A (Qpc.sdau-7 A) that control compact tillers. Qpc.sdau-3B.1, Qpc.sdau-5D, and Qpc.sdau-5B accounted for up to 16.70%, 16.89%, and 14.56% of the phenotypic variance, respectively. Kompetitive allele-specific PCR (KASP) markers were developed for these QTL, and their effects were validated in two additional RIL populations, SN05525/Luyuan 502 and SN05525/Xinong 511. Significant effects of Qpc.sdau-3B.1 and Qpc.sdau-5D on compactness were observed in the validation populations.

CONCLUSION

Three major QTL loci closely related to plant compactness in wheat were successfully identified, and their effects were validated in two additional RIL populations across multi environments. Plant architecture plays a crucial role in enhancing yield and economic value in wheat. In the process of molecular marker-assisted selection breeding, the closely linked KASP markers could potentially be utilized in molecular marker-assisted selection for adjusting plant compactness and for further characterization of the underlying gene(s).

An eight-founder wheat MAGIC population allows fine-mapping of flowering time loci and provides novel insights into the genetic control of flowering time

Flowering time synchronizes reproductive development with favorable environmental conditions to optimize yield. Improved understanding of the genetic control of flowering will help optimize varietal adaptation to future agricultural systems under climate change. Here, we investigate the genetic basis of flowering time in winter wheat (Triticum aestivum L.) using an eight-founder multi-parent advanced generation intercross (MAGIC) population. Flowering time data was collected from field trials across six growing seasons in the United Kingdom, followed by genetic analysis using a combination of linear modelling, simple interval mapping and composite interval mapping, using either single markers or founder haplotype probabilities. We detected 57 quantitative trait loci (QTL) across three growth stages linked to flowering time, of which 17 QTL were identified only when the major photoperiod response locus Ppd-D1 was included as a covariate. Of the 57 loci, ten were identified using all genetic mapping approaches and classified as 'major' QTL, including homoeologous loci on chromosomes 1B and 1D, and 4A and 4B. Additional Earliness per se flowering time QTL were identified, along with growth stage- and year-specific effects. Furthermore, six of the main-effect QTL were found to interact epistatically with Ppd-D1. Finally, we exploited residual heterozygosity in the MAGIC recombinant inbred lines to Mendelize the Earliness per se QTL QFt.niab-5A.03, which was confirmed to modulate flowering time by at least four days. This work provides detailed understanding of the genetic control of phenological variation within varieties relevant to the north-western European wheat genepool, aiding informed manipulation of flowering time in wheat breeding.

Genetic mapping of QTLs for resistance to bacterial leaf streak in hexaploid wheat

KEY MESSAGE

Robust QTLs conferring resistance to bacterial leaf streak in wheat were mapped on chromosomes 3B and 5A from the variety Boost and on chromosome 7D from the synthetic wheat line W-7984. Bacterial leaf streak (BLS), caused by Xanthomonas translucens pv. undulosa poses a significant threat to global wheat production. High levels of BLS resistance are rare in hexaploid wheat. Here, we screened 101 diverse wheat genotypes under greenhouse conditions to identify new sources of BLS resistance. Five lines showed good levels of resistance including the wheat variety Boost and the synthetic hexaploid wheat line W-7984. Recombinant inbred populations derived from the cross of Boost × ND830 (BoostND population) and W-7984 × Opata 85 (ITMI population) were subsequently evaluated in greenhouse and field experiments to investigate the genetic basis of resistance. QTLs on chromosomes 3B, 5A, and 5B were identified in the BoostND population. The 3B and 5A QTLs were significant in all environments, but the 3B QTL was the strongest under greenhouse conditions explaining 38% of the phenotypic variation, and the 5A QTL was the most significant in the field explaining up to 29% of the variation. In the ITMI population, a QTL on chromosome 7D explained as much as 46% of the phenotypic variation in the greenhouse and 18% in the field. BLS severity in both populations was negatively correlated with days to heading, and some QTLs for these traits overlapped, which explained the tendency of later maturing lines to have relatively higher levels of BLS resistance. Markers associated with the QTLs were converted to KASP markers, which will aid in the deployment of the QTLs into elite lines for the development of BLS-resistant wheat varieties.

Mapping Seedling and Adult Plant Leaf Rust Resistance Genes in the Durum Wheat Cultivar Strongfield and Other Triticum turgidum Lines

Durum wheat (Triticum turgidum) is threatened by the appearance of new virulent races of leaf rust, caused by Puccinia triticina, in recent years. This study was conducted to determine the leaf rust resistance in a modern Canadian durum cultivar, Strongfield. Six populations derived from crosses of Strongfield with six tetraploid wheat lines, respectively, were tested at the seedling plant stage with different P. triticina races. Two of the populations were evaluated for adult plant leaf rust infection in Canada and Mexico. A stepwise regression joint linkage quantitative trait locus (QTL) mapping and analysis by MapQTL were performed. Strongfield contributed the majority of QTLs detected, contributing seven QTLs detected in field tests and eight QTLs conditioning seedling resistance. A 1B QTL, QLr-Spa-1B.1, from Strongfield had a significant effect in both Canadian and Mexican field tests and corresponded with Lr46/Yr29. The remaining field QTLs were found in only the Canadian or the Mexican environment, not both. The QTL from Strongfield on 3A, QLr-Spa-3A, conferred seedling resistance to all races tested and had a significant effect in the field in Canada. This is the first report of QLr-Spa-3A and Lr46/Yr29 as key components of genetic resistance in Canadian durum wheat. KASP markers were developed to detect QLr-Spa-3A for use in marker-assisted leaf rust resistance breeding. The susceptible parental lines contributed QTLs on 1A, 2B, and 5B that were effective in Mexican field tests and may be good targets to integrate into modern durum varieties to improve resistance to new durum virulent races.

Natural alleles of LEAFY and WAPO1 interact to regulate spikelet number per spike in wheat

KEY MESSAGE

Specific combinations of LFY and WAPO1 natural alleles maximize spikelet number per spike in wheat. Spikelet number per spike (SNS) is an important yield component in wheat that determines the maximum number of grains that can be formed in a wheat spike. In wheat, loss-of-function mutations in LEAFY (LFY) or its interacting protein WHEAT ORTHOLOG OF APO1 (WAPO1) significantly reduce SNS by reducing the rate of formation of spikelet meristems. In previous studies, we identified a natural amino acid change in WAPO1 (C47F) that significantly increases SNS in hexaploid wheat. In this study, we searched for natural variants in LFY that were associated with differences in SNS and detected significant effects in the LFY-B region in a nested association mapping population. We generated a large mapping population and confirmed that the LFY-B polymorphism R80S is linked with the differences in SNS, suggesting that LFY-B is the likely causal gene. A haplotype analysis revealed two amino acid changes P34L and R80S, which were both enriched during wheat domestication and breeding suggesting positive selection. We also explored the interactions between the LFY and WAPO1 natural variants for SNS using biparental populations and identified significant interaction, in which the positive effect of the 80S and 34L alleles from LFY-B was only detected in the WAPO-A1 47F background but not in the 47C background. Based on these results, we propose that the allele combination WAPO-A1-47F/LFY-B 34L 80S can be used in wheat breeding programs to maximize SNS and increase grain yield potential in wheat.

Comparing performances of different statistical models and multiple threshold methods in a nested association mapping population of wheat

Nested association mapping (NAM) populations emerged as a multi-parental strategy that combines the high statistical power of biparental linkage mapping with greater allelic richness of association mapping. Several statistical models have been developed for marker-trait associations (MTAs) in genome-wide association studies (GWAS), which ranges from simple to increasingly complex models. These statistical models vary in their performance for detecting real association with the avoidance of false positives and false negatives. Furthermore, significant threshold methods play an equally important role for controlling spurious associations. In this study, we compared the performance of seven different statistical models ranging from single to multi-locus models on eight different simulated traits with varied genetic architecture for a NAM population of spring wheat (Triticum aestivum L.). The best identified model was further used to identify MTAs for 11 different agronomic and spectral reflectance traits, which were collected on the NAM population between 2014 and 2016. The "Bayesian information and linkage disequilibrium iteratively nested keyway (BLINK)" model performed better than all other models observed based on QQ plots and detection of real association in a simulated data set. The results from model comparison suggest that BLINK controls both false positives and false negatives under the different genetic architecture of simulated traits. Comparison of multiple significant threshold methods suggests that Bonferroni correction performed superior for controlling false positives and false negatives and complements the performance of GWAS models. BLINK identified 45 MTAs using Bonferroni correction of 0.05 for 11 different phenotypic traits in the NAM population. This study helps identify the best statistical model and significant threshold method for performing association analysis in subsequent NAM population studies.

Identification of Genomic Regions Conferring Enhanced Zn and Fe Concentration in Wheat Varieties and Introgression Lines Derived from Wild Relatives

Wild and cultivated relatives of wheat are an important source of genetic factors for improving the mineral composition of wheat. In this work, a wheat panel consisting of modern bread wheat varieties, landraces, and introgression lines with genetic material of the wheat species Triticum timopheevii, T. durum, T. dicoccum, and T. dicoccoides and the synthetic line T. kiharae was used to identify loci associated with the grain zinc (GZnC) and iron (GFeC) content. Using a BLINK model, we identified 31 and 73 marker-trait associations (MTAs) for GZnC and GFeC, respectively, of which 19 were novel. Twelve MTAs distributed on chromosomes 1B, 2A, 2B, 5A, and 5B were significantly associated with GZnC, five MTAs on 2A, 2B, and 5D chromosomes were significantly associated with GFeC, and two SNPs located on 2A and 2B were related to the grain concentration of both trace elements. Meanwhile, most of these MTAs were inherited from At and G genomes of T. timopheevii and T. kiharae and positively affected GZnC and GFeC. Eight genes related to iron or zinc transporters, representing diverse gene families, were proposed as the best candidates. Our findings provide an understanding of the genetic basis of grain Zn and Fe accumulation in species of the Timopheevi group and could help in selecting new genotypes containing valuable loci.

Identification and fine mapping of a QTL-rich region for yield- and quality-related traits on chromosome 4BS in common wheat (Triticum aestivum L.)

Yield and quality are important for plant breeding. To better understand the genetic basis underlying yield- and quality-related traits in wheat (Triticum aestivum L.), we conducted the quantitative trait locus (QTL) analysis using recombinant inbred lines (RILs) and a high-density genetic linkage map with a 90 K array. In this study, a total of 117 QTLs were detected for spike number per area (SNPA), thousand grain weight (TGW), grain number per spike (GNS), plant height (PH), spike length (SL), total spikelet number (TSN), spikelet density (SD), grain protein content (GPC), and grain starch content (GSC). Among these QTLs, 30 environmentally stable QTLs for yield- and quality-related traits were detected. Notably, five QTL-rich regions (Qrr) for yield- and/or quality-related traits were identified, including the QTL-rich region on chromosome 4BS (QQrr.cau-4B) for eight traits (SNPA, GNS, PH, SL, TSN, SD, GPC, and GSC). The stable QTL-rich region QQrr.cau-4B was delimited into a physical interval of approximately 2.47 Mb. Based on the annotation information of the Chinese spring wheat genome v1.0 and parental re-sequencing results, the interval included twelve genes with sequence variations. Taken together, these results contribute to further understanding of the genetic basis of SNPA, GNS, PH, SL, TSN, SD, GPC, and GSC, and fine mapping of QQrr.cau-4B will be beneficial for gene cloning and marker-assisted selection in the genetic improvement of wheat varieties.

Bacterial N-Acyl Homoserine Lactone Priming Enhances Leaf-Rust Resistance in Winter Wheat and Some Genomic Regions Are Associated with Priming Efficiency

Leaf rust (Puccinia triticina) is a common disease that causes significant yield losses in wheat. The most frequently used methods to control leaf rust are the application of fungicides and the cultivation of resistant genotypes. However, high genetic diversity and associated adaptability of pathogen populations hamper achieving durable resistance in wheat. Emerging alternatives, such as microbial priming, may represent an effective measure to stimulate plant defense mechanisms and could serve as a means of controlling a broad range of pathogens. In this study, 175 wheat genotypes were inoculated with two bacterial strains: Ensifer meliloti strain expR+ch (producing N-acyl homoserine lactone (AHL)) or transformed E. meliloti carrying the lactonase gene attM (control). In total, 21 genotypes indicated higher resistance upon bacterial AHL priming. Subsequently, the phenotypic data of 175 genotypes combined with 9917 single-nucleotide polymorphisms (SNPs) in a genome-wide association study to identify quantitative trait loci (QTLs) and associated markers for relative infection under attM and expR+ch conditions and priming efficiency using the Genome Association and Prediction Integrated Tool (GAPIT). In total, 15 QTLs for relative infection under both conditions and priming efficiency were identified on chromosomes 1A, 1B, 2A, 3A, 3B, 3D, 6A, and 6B, which may represent targets for wheat breeding for priming and leaf-rust resistance.

Wheat improvement through advances in single nucleotide polymorphism (SNP) detection and genotyping with a special emphasis on rust resistance

KEY MESSAGE

Single nucleotide polymorphism (SNP) markers in wheat and their prospects in breeding with special reference to rust resistance. Single nucleotide polymorphism (SNP)-based markers are increasingly gaining momentum for screening and utilizing vital agronomic traits in wheat. To date, more than 260 million SNPs have been detected in modern cultivars and landraces of wheat. This rapid SNP discovery was made possible through the release of near-complete reference and pan-genome assemblies of wheat and its wild relatives, coupled with whole genome sequencing (WGS) of thousands of wheat accessions. Further, genotyping customized SNP sites were facilitated by a series of arrays (9 to 820Ks), a cost effective substitute WGS. Lately, germplasm-specific SNP arrays have been introduced to characterize novel traits and detect closely linked SNPs for marker-assisted breeding. Subsequently, the kompetitive allele-specific PCR (KASP) assay was introduced for rapid and large-scale screening of specific SNP markers. Moreover, with the advances and reduction in sequencing costs, ample opportunities arise for generating SNPs artificially through mutations and in combination with next-generation sequencing and comparative genomic analyses. In this review, we provide historical developments and prospects of SNP markers in wheat breeding with special reference to rust resistance where over 50 genetic loci have been characterized through SNP markers. Rust resistance is one of the most essential traits for wheat breeding as new strains of the Puccinia fungus, responsible for rust diseases, evolve frequently and globally.

QTL analysis of native Fusarium head blight and deoxynivalenol resistance in 'D8006W'/'Superior', soft white winter wheat population

BACKGROUND

Fusarium head blight (FHB), caused by Fusarium graminearum, is a major disease of wheat in North America. FHB infection causes fusarium damaged kernels (FDKs), accumulation of deoxynivalenol (DON) in the grain, and a reduction in quality and grain yield. Inheritance of FHB resistance is complex and involves multiple genes. The objective of this research was to identify QTL associated with native FHB and DON resistance in a 'D8006W'/'Superior', soft white winter wheat population.

RESULTS

Phenotyping was conducted in replicated FHB field disease nurseries across multiple environments and included assessments of morphological and FHB related traits. Parental lines had moderate FHB resistance, however, the population showed transgressive segregation. A 1913.2 cM linkage map for the population was developed with SNP markers from the wheat 90 K Infinium iSelect SNP array. QTL analysis detected major FHB resistance QTL on chromosomes 2D, 4B, 5A, and 7A across multiple environments, with resistance from both parents. Trait specific unique QTL were detected on chromosomes 1A (visual traits), 5D (FDK), 6B (FDK and DON), and 7D (DON). The plant height and days to anthesis QTL on chromosome 2D coincided with Ppd-D1 and were linked with FHB traits. The plant height QTL on chromosome 4B was also linked with FHB traits; however, the Rht-B1 locus did not segregate in the population.

CONCLUSIONS

This study identified several QTL, including on chromosome 2D linked with Ppd-D1, for FHB resistance in a native winter wheat germplasm.

Dissecting the genetic basis of resistance to Soil-borne cereal mosaic virus (SBCMV) in durum wheat by bi-parental mapping and GWAS

Soil-borne cereal mosaic virus (SBCMV), the causative agent of wheat mosaic, is a Furovirus challenging wheat production all over Europe. Differently from bread wheat, durum wheat shows greater susceptibility and stronger yield penalties, so identification and genetic characterization of resistance sources are major targets for durum genetics and breeding. The Sbm1 locus providing high level of resistance to SBCMV was mapped in bread wheat to the 5DL chromosome arm (Bass in Genome 49:1140-1148, 2006). This excluded the direct use of Sbm1 for durum wheat improvement. Only one major QTL has been mapped in durum wheat, namely QSbm.ubo-2B, on the 2BS chromosome region coincident with Sbm2, already known in bread wheat as reported (Bayles in HGCA Project Report, 2007). Therefore, QSbm.ubo-2B = Sbm2 is considered a pillar for growing durum in SBCMV-affected areas. Herein, we report the fine mapping of Sbm2 based on bi-parental mapping and GWAS, using the Infinium 90 K SNP array and high-throughput KASP®. Fine mapping pointed out a critical haploblock of 3.2 Mb defined by concatenated SNPs successfully converted to high-throughput KASP® markers coded as KUBO. The combination of KUBO-27, wPt-2106-ASO/HRM, KUBO-29, and KUBO-1 allows unequivocal tracing of the Sbm2-resistant haplotype. The interval harbors 52 high- and 41 low-confidence genes, encoding 17 cytochrome p450, three receptor kinases, two defensins, and three NBS-LRR genes. These results pave the way for Sbm2 positional cloning. Importantly, the development of Sbm2 haplotype tagging KASP® provides a valuable case study for improving efficacy of the European variety testing system and, ultimately, the decision-making process related to varietal characterization and choice.

Origin and evolution of the bread wheat D genome

Bread wheat (Triticum aestivum) is a globally dominant crop and major source of calories and proteins for the human diet. Compared with its wild ancestors, modern bread wheat shows lower genetic diversity, caused by polyploidisation, domestication and breeding bottlenecks1,2. Wild wheat relatives represent genetic reservoirs, and harbour diversity and beneficial alleles that have not been incorporated into bread wheat. Here we establish and analyse extensive genome resources for Tausch's goatgrass (Aegilops tauschii), the donor of the bread wheat D genome. Our analysis of 46 Ae. tauschii genomes enabled us to clone a disease resistance gene and perform haplotype analysis across a complex disease resistance locus, allowing us to discern alleles from paralogous gene copies. We also reveal the complex genetic composition and history of the bread wheat D genome, which involves contributions from genetically and geographically discrete Ae. tauschii subpopulations. Together, our results reveal the complex history of the bread wheat D genome and demonstrate the potential of wild relatives in crop improvement.

Fine mapping of stem rust resistance derived from soft red winter wheat cultivar AGS2000 to an NLR gene cluster on chromosome 6D

The Puccinia graminis f. sp. tritici (Pgt) Ug99-emerging virulent races present a major challenge to global wheat production. To meet present and future needs, new sources of resistance must be found. Identification of markers that allow tracking of resistance genes is needed for deployment strategies to combat highly virulent pathogen races. Field evaluation of a DH population located a QTL for stem rust (Sr) resistance, QSr.nc-6D from the breeding line MD01W28-08-11 to the distal region of chromosome arm 6DS where Sr resistance genes Sr42, SrCad, and SrTmp have been identified. A locus for seedling resistance to Pgt race TTKSK was identified in a DH population and an RIL population derived from the cross AGS2000 × LA95135. The resistant cultivar AGS2000 is in the pedigree of MD01W28-08-11 and our results suggest that it is the source of Sr resistance in this breeding line. We exploited published markers and exome capture data to enrich marker density in a 10 Mb region flanking QSr.nc-6D. Our fine mapping in heterozygous inbred families identified three markers co-segregating with resistance and delimited QSr.nc-6D to a 1.3 Mb region. We further exploited information from other genome assemblies and identified collinear regions of 6DS harboring clusters of NLR genes. Evaluation of KASP assays corresponding to our co-segregating SNP suggests that they can be used to track this Sr resistance in breeding programs. However, our results also underscore the challenges posed in identifying genes underlying resistance in such complex regions in the absence of genome sequence from the resistant genotypes.

Development of a next generation SNP genotyping array for wheat

High-throughput genotyping arrays have provided a cost-effective, reliable and interoperable system for genotyping hexaploid wheat and its relatives. Existing, highly cited arrays including our 35K Wheat Breeder's array and the Illumina 90K array were designed based on a limited amount of varietal sequence diversity and with imperfect knowledge of SNP positions. Recent progress in wheat sequencing has given us access to a vast pool of SNP diversity, whilst technological improvements have allowed us to fit significantly more probes onto a 384-well format Axiom array than previously possible. Here we describe a novel Axiom genotyping array, the 'Triticum aestivum Next Generation' array (TaNG), largely derived from whole genome skim sequencing of 204 elite wheat lines and 111 wheat landraces taken from the Watkins 'Core Collection'. We used a novel haplotype optimization approach to select SNPs with the highest combined varietal discrimination and a design iteration step to test and replace SNPs which failed to convert to reliable markers. The final design with 43 372 SNPs contains a combination of haplotype-optimized novel SNPs and legacy cross-platform markers. We show that this design has an improved distribution of SNPs compared to previous arrays and can be used to generate genetic maps with a significantly higher number of distinct bins than our previous array. We also demonstrate the improved performance of TaNGv1.1 for Genome-wide association studies (GWAS) and its utility for Copy Number Variation (CNV) analysis. The array is commercially available with supporting marker annotations and initial genotyping results freely available.

Genome-wide association study identifies loci and candidate genes for RVA parameters in wheat (Triticum aestivum L.)

The gelatinization and retrogradation characteristics of wheat starch affect the eating quality of Chinese-style food. Rapid Visco Analyzer (RVA) parameters have been widely used as important indicators to evaluate and improve the quality of wheat starch. However, the genetic basis of RVA parameters remains to be further explored. In the present study, a natural population was genotyped using 90K single nucleotide polymorphism (SNP) arrays, and the RVA parameters of this population grown in five environments were evaluated. The results showed that 22,068 high-quality SNP markers were identified and distributed unequally on the chromosomes. According to the genetic distance, 214 wheat materials were divided into four groups. Except for the pasting temperature (PTT), six parameters followed a normal distribution. Based on the general linear model, 969 significant association SNPs were detected by genome-wide association studies (GWAS), and chromosomes 7A and 2B had the most associated SNPs. Breakdown viscosity (BV) was associated with the most SNPs (n = 238), followed by PTT (n = 186), peak viscosity (PV; n = 156), trough viscosity (TV; n = 127), and final viscosity (FV; n = 126). According to the average linkage disequilibrium (LD), 33 stable quantitative trait loci (QTLs) were identified for single parameters in multiple environments, of which 12 were associated with BV, followed by peak time (PT; n = 8) and PTT (n = 7). On the other hand, 67 pleiotropic QTLs were identified for multiple parameters. Three candidate genes-TasbeIIa, TasbeI, and TassIIa-were screened for phenotyping analysis. The grain width and the weight of the TasbeIIa and TaSSIIa knockout (KO) lines were significantly lower than those of the TasbeI KO lines and the control (CK). The KO lines had smaller endosperm cells, smaller A-type starch granules, and higher amylose content. The TasbeI KO lines showed normal RVA curves, while the TasbeIIa KO lines showed flat curves. However, the TaSSIIa lines failed to paste under the RVA temperatures. Conclusively, the SNPs/QTLs significantly associated with the RVA parameters and genetic resources with novel haplotypes could be used to improve the quality of wheat starch.

Screening of CIMMYT and South Asian Bread Wheat Germplasm Reveals Marker-Trait Associations for Seedling Resistance to Septoria Nodorum Blotch

Wheat (Triticum aestivum L.) production is adversely impacted by Septoria nodorum blotch (SNB), a fungal disease caused by Parastagonospora nodorum. Wheat breeders are constantly up against this biotic challenge as they try to create resistant cultivars. The genome-wide association study (GWAS) has become an efficient tool for identifying molecular markers linked with SNB resistance. This technique is used to acquire an understanding of the genetic basis of resistance and to facilitate marker-assisted selection. In the current study, a total of 174 bread wheat accessions from South Asia and CIMMYT were assessed for SNB reactions at the seedling stage in three greenhouse experiments at CIMMYT, Mexico. The results indicated that 129 genotypes were resistant to SNB, 39 were moderately resistant, and only 6 were moderately susceptible. The Genotyping Illumina Infinium 15K Bead Chip was used, and 11,184 SNP markers were utilized to identify marker-trait associations (MTAs) after filtering. Multiple tests confirmed the existence of significant MTAs on chromosomes 5B, 5A, and 3D, and the ones at Tsn1 on 5B were the most stable and conferred the highest phenotypic variation. The resistant genotypes identified in this study could be cultivated in South Asian countries as a preventative measure against the spread of SNB. This work also identified molecular markers of SNB resistance that could be used in future wheat breeding projects.

GWAS elucidated grain yield genetics in Indian spring wheat under diverse water conditions

KEY MESSAGE

Underpinned natural variations and key genes associated with yield under different water regimes, and identified genomic signatures of genetic gain in the Indian wheat breeding program. A novel KASP marker for TKW under water stress was developed and validated. A comprehensive genome-wide association study was conducted on 300 spring wheat genotypes to elucidate the natural variations associated with grain yield and its eleven contributing traits under fully irrigated, restricted water, and simulated no water conditions. Utilizing the 35K Wheat Breeders' Array, we identified 1155 quantitative trait nucleotides (QTNs), with 207 QTNs exhibiting stability across diverse conditions. These QTNs were further delimited into 539 genomic regions using a genome-wide LD value of 3.0 Mbp, revealing pleiotropic control across traits and conditions. Sub-genome A was significantly associated with traits under irrigated conditions, while sub-genome B showed more QTNs under water stressed conditions. Favourable alleles with significantly associated QTNs were delineated, with a notable pyramiding effect for enhancing trait performance. Additionally, allele of only 921 QTNs significantly affected the population mean. Allele profiling highlighted C-306 as a most potential source of drought tolerance. Moreover, 762 genes overlapping significant QTNs were identified, narrowing down to 27 putative candidate genes overlapping 29 novel and functional SNPs expressing (≥ 0.5 tpm) relevance across various growth conditions. A new KASP assay was developed, targeting a gene TraesCS2A03G1123700 regulating thousand kernel weight under severe drought condition. Genomic selection models (GBLUP, BayesB, MxE, and R-Norm) demonstrated an average prediction accuracy of 0.06-0.58 across environments, indicating potential for trait selection. Retrospective analysis of the Indian wheat breeding program supported a genetic gain in GY at the rate of ca. 0.56% per breeding cycle, since 1960, supporting the identification of genomic signatures driving trait selection and genetic gain. These findings offer insight into improving the rate of genetic gain in wheat breeding programs globally.