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Background: Durum wheat is one of the most important crops, especially in the Mediterranean region. Insight into the genetic diversity of germplasm can improve the breeding program management in various traits. This study was done using single nucleotide polymorphisms (SNP) markers to characterize the genetic distinctiveness and differentiation of tetraploid wheat landraces collected from nine European and Asian countries. A sum of 23,334 polymorphic SNPs was detected in 126 tetraploid wheat landraces in relation to the reference genome. Results: The number of identified SNPs was 11,613 and 11,721 in A and B genomes, respectively. The highest and lowest diversity was on 6B and 6 A chromosomes, respectively. Structure analysis classified the landraces into two distinct subpopulations (K = 2). Evaluating the principal coordinate analysis (PCoA) and weighted pair-group method using arithmetic averages (WPGMA) clustering results demonstrated that landraces (99.2%) are categorized into one of the two chief subpopulations. Therefore, the grouping pattern did not clearly show the presence of a clear pattern of relationships between genetic diversity and their geographical derivation. Part of this result could be due to the historical exchange between different germplasms. Although the result did not separate landraces based on their region of origin, the landraces collected from Iran were classified into the same group and cluster. Analysis of molecular variance (AMOVA) also confirmed the results of population structure. Finally, Durum wheat landraces in some countries, including Turkey, Russia, Ukraine, and Afghanistan, were highly diverse, while others, including Iran and China, were low-diversity. Conclusion: The recent study concluded that the 126 tetraploid wheat genotypes and their GBS-SNP markers are very appropriate for quantitative trait loci (QTLs) mapping and genome-wide association studies (GWAS). The core collection comprises two distinct subpopulations. Subpopulation II genotypes are the most diverse genotypes, and if they possess desired traits, they may be used in future breeding programs. The degree of diversity in the landraces of countries can provide the ground for the improvement of new cultivars with international cooperation. linkage disequilibrium (LD) hotspot distribution across the genome was investigated, which provides useful information about the genomic regions that contain intriguing genes. [ABSTRACT FROM AUTHOR]

Biofortification is a sustainable strategy to alleviate micronutrient deficiency in humans. It is necessary to improve grain zinc (GZnC) and iron concentrations (GFeC) in wheat based on genetic knowledge. However, the precise dissection of the genetic architecture underlying GZnC and GFeC remains challenging. In this study, high-resolution genome-wide association studies were conducted for GZnC and GFeC by three different models using 166 wheat cultivars and 373,106 polymorphic markers from the wheat 660K and 90K single nucleotide polymorphism (SNP) arrays. Totally, 25 and 16 stable loci were detected for GZnC and GFeC, respectively. Among them, 17 loci for GZnC and 8 for GFeC are likely to be new quantitative trait locus/loci (QTL). Based on gene annotations and expression profiles, 28 promising candidate genes were identified for Zn/Fe uptake (8), transport (11), storage (3), and regulations (6). Of them, 11 genes were putative wheat orthologs of known Arabidopsis and rice genes related to Zn/Fe homeostasis. A brief model, such as genes related to Zn/Fe homeostasis from root uptake, xylem transport to the final seed storage was proposed in wheat. Kompetitive allele-specific PCR (KASP) markers were successfully developed for two major QTL of GZnC on chromosome arms 3AL and 7AL, respectively, which were independent of thousand kernel weight and plant height. The 3AL QTL was further validated in a bi-parental population under multi-environments. A wheat multidrug and toxic compound extrusion (MATE) transporter TraesCS3A01G499300 , the ortholog of rice gene OsPEZ2 , was identified as a potential candidate gene. This study has advanced our knowledge of the genetic basis underlying GZnC and GFeC in wheat and provides valuable markers and candidate genes for wheat biofortification. [ABSTRACT FROM AUTHOR]

Stripe rust caused by Puccnina striiformis (Pst) is an economically important disease attacking wheat all over the world. Identifying and deploying new genes for Pst resistance is an economical and long-term strategy for controlling Pst. A genome-wide association study (GWAS) using single nucleotide polymorphisms (SNPs) and functional haplotypes were used to identify loci associated with stripe rust resistance in synthetic-derived (SYN-DER) wheats in four environments. In total, 92 quantitative trait nucleotides (QTNs) distributed over 65 different loci were associated with resistance to Pst at seedling and adult plant stages. Nine additional loci were discovered by the linkage disequilibrium-based haplotype-GWAS approach. The durable rust-resistant gene Lr34/Yr18 provided resistance in all four environments, and against all the five Pst races used in this study. The analysis identified several SYN-DER accessions that carried major genes: either Yr24/Yr26 or Yr32. New loci were also identified on chr2B, chr5B, and chr7D, and 14 QTNs and three haplotypes identified on the D-genome possibly carry new alleles of the known genes contributed by the Ae. tauschii founders. We also evaluated eleven different models for genomic prediction of Pst resistance, and a prediction accuracy up to 0.85 was achieved for an adult plant resistance, however, genomic prediction for seedling resistance remained very low. A meta-analysis based on a large number of existing GWAS would enhance the identification of new genes and loci for stripe rust resistance in wheat. The genetic framework elucidated here for stripe rust resistance in SYN-DER identified the novel loci for resistance to Pst assembled in adapted genetic backgrounds. [ABSTRACT FROM AUTHOR]

It is important to understand the genetic gain achieved through selection of key yield traits for planning future breeding strategies in developing high yielding wheat (Triticum aestivum L.) cultivars. The aim of this study was to characterize the genetic changes and genotype × environment (G×E) interaction by additive main effect and multiplicative interactions (AMMI) for morphological, physiological, and yield component traits under five environments using 24 wheat cultivars released from 1911 to 2016 in Pakistan. There was a significant increase in grain yield (9.03 kg ha−1 yr−1, 0.37%), and plant height was reduced linearly (−0.26 cm yr−1, −0.33%). The traits waxiness, leaf rolling, harvest index, spike length, and grains per spike significantly increased but the gain was only 0.16–0.2% per year. Analysis of variance revealed that genotype, environment, and G×E interaction were highly significant (P <.01) for all traits except relative chlorophyll content, biomass, days to maturity, and number of spikes. Gene‐specific markers identified the durable resistance gene Lr67/Yr46/Sr55/Pm46 in obsolete cultivars as early as 1911, whereas the photoperiod‐insensitive allele Ppd‐D1a and reduced height alleles Rht‐B1b and Rht‐D1b were present only in the post‐1965 cultivars. Diversity analysis based on a 50K single nucleotide polymorphism genotyping array clearly differentiated temporal patterns in 24 cultivars, which was correlated with the agronomic performance of the cultivars. This dataset provided detailed insight into the performance of historical wheat cultivars and could help in devising wheat breeding strategies to focus on the traits contributing to grain yield and have slower rate of genetic progress. Core Ideas: The genetic gain in morphology of Pakistani bread wheat cultivars over 105 yr areas was assessed.Leaf rolling, waxiness, and grains/spikes associated with genetic gains in grain yield were achieved by breeding.The performance and stability of yield and yield‐related traits was analyzed for the different cultivars. [ABSTRACT FROM AUTHOR]

Tajikistan is rich in genetic resources and one of a few countries where farmers still grow wheat (Triticum spp) landraces, which are important for production and breeding. This study undertook morphological description and agronomic and genomic characterization of wheat landraces collected in Tajikistan in 2013 and 2014 to develop opportunities for their use in breeding and on‐farm maintenance. In total, 60 wheat landraces were collected from 40 villages in 14 administrative districts and four regions. They were evaluated for agronomic traits in field trials in Turkey. The study identified six distinct regions where landraces are still grown. The villages growing the landraces were remote, with the distance to the nearest market being 30–100 km. The area allocated to wheat landraces varied from 0.01 to 2 ha. The main reason for maintaining the wheat landraces was their suitability for homemade bread and specific adaptation to high altitude. Overall, 68 distinct lines originating from landraces were identified using morphological and genomic descriptions. A core set of 30 lines was selected and field phenotyped under rain‐fed conditions. Several landraces (Joydori, Safedak, Surkhaki besuk, Shukhak, Surkh‐suk, and Kilaki bartang) that exceeded local check for grain yield and size were identified. Cluster analysis using single nucleotide polymorphism (SNP) array kinship matrix demonstrated relatedness between the landraces from different regions of Tajikistan and from neighboring regions of Uzbekistan. The value of this study for the international community is in conservation of rare and unique wheat landraces that could have been lost in the future. Core Ideas: Wheat landraces are cultivated in Tajikistan in mountains because of their adaptation and quality.Overall, 68 unique landraces were identified using morphological and genomic tools.Field evaluation of the core set of 30 landraces identified superior genotypes. [ABSTRACT FROM AUTHOR]

Popcorn (Zea mays L. var. Everta) is the most ancient type of cultivated maize. However, there is little known about the genetics of popping-related traits based on genotyping-by-sequencing (GBS) technology. Here, we characterized the phenotypic variation for seven popping-related traits in maize kernels among 526 CIMMYT inbred lines (CMLs). In total, 155 083 high-quality single nucleotide polymorphism (SNP) markers were identified by a GBS approach. Several trait-associated loci were detected by genome-wide association study for color, popping expansion volume, shape, pericarp, flotation index, floury/vitreous, and protein content, explaining a majority of the observed phenotypic variance, and these were validated by a diverse panel comprising 764 tropical landrace accessions. Sixty two of the identified loci were recognized to have undergone selection. On average, there was a 55.27% frequency for alleles that promote popping in CMLs. Our work not only pinpoints previously unknown loci for popping-related traits, but also reveals that many of these loci have undergone selection. Beyond establishing a new benchmark for the genetics of popcorn, our study provides a foundation for gene discovery and breeding. It also presents evidence to investigate the role of a gradual loss of popping ability as a by-product of diversification of culinary uses throughout the evolution of teosinte–to–modern maize. [ABSTRACT FROM AUTHOR]

Key message: Genetic diversity, population structure, LD decay, and selective sweeps in 687 wheat accessions were analyzed, providing relevant guidelines to facilitate the use of the germplasm in wheat breeding. Common wheat (Triticum aestivum L.) is one of the most widely grown crops in the world. Landraces were subjected to strong human-mediated selection in developing high-yielding, good quality, and widely adapted cultivars. To investigate the genome-wide patterns of allelic variation, population structure and patterns of selective sweeps during modern wheat breeding, we tested 687 wheat accessions, including landraces (148) and cultivars (539) mainly from China and Pakistan in a wheat 90 K single nucleotide polymorphism array. Population structure analysis revealed that cultivars and landraces from China and Pakistan comprised three relatively independent genetic clusters. Cultivars displayed lower nucleotide diversity and a wider average LD decay across whole genome, indicating allelic erosion and a diversity bottleneck due to the modern breeding. Analysis of genetic differentiation between landraces and cultivars from China and Pakistan identified allelic variants subjected to selection during modern breeding. In total, 477 unique genome regions showed signatures of selection, where 109 were identified in both China and Pakistan germplasm. The majority of genomic regions were located in the B genome (225), followed by the A genome (175), and only 77 regions were located in the D genome. EigenGWAS was further used to identify key selection loci in modern wheat cultivars from China and Pakistan by comparing with global winter wheat and spring wheat diversity panels, respectively. A few known functional genes or loci found within these genome regions corresponded to known phenotypes for disease resistance, vernalization, quality, adaptability and yield-related traits. This study uncovered molecular footprints of modern wheat breeding and explained the genetic basis of polygenic adaptation in wheat. The results will be useful for understanding targets of modern wheat breeding, and in devising future breeding strategies to target beneficial alleles currently not pursued. [ABSTRACT FROM AUTHOR]

Understanding the genomic basis of adaptation in maize is important for gene discovery and the improvement of breeding germplasm, but much remains a mystery in spite of significant population genetics and archaeological research. Identifying the signals underpinning adaptation are challenging as adaptation often coincided with genetic drift, and the base genomic diversity of the species in massive. In this study, tGBS technology was used to genotype 1,143 diverse maize accessions including landraces collected from 20 countries and elite breeding lines of tropical lowland, highland, subtropical/midaltitude and temperate ecological zones. Based on 355,442 high‐quality single nucleotide polymorphisms, 13 genomic regions were detected as being under selection using the bottom‐up searching strategy, EigenGWAS. Of the 13 selection regions, 10 were first reported, two were associated with environmental parameters via EnvGWAS, and 146 genes were enriched. Combining large‐scale genomic and ecological data in this diverse maize panel, our study supports a polygenic adaptation model of maize and offers a framework to enhance our understanding of both the mechanistic basis and the evolutionary consequences of maize domestication and adaptation. The regions identified here are promising candidates for further, targeted exploration to identify beneficial alleles and haplotypes for deployment in maize breeding. [ABSTRACT FROM AUTHOR]

Background: Wheat genetic resources have been used for genetic improvement since 1876, when Stephen Wilson (Transactions and Proceedings of the Botanical Society of Edinburgh 12: 286) consciously made the first wide hybrid involving wheat and rye in Scotland. Wide crossing continued with sporadic attempts in the first half of 19th century and became a sophisticated scientific discipline during the last few decades with considerable impact in farmers' fields. However, a large diversity of untapped genetic resources could contribute in meeting future wheat production challenges. Perspectives and Conclusion: Recently the complete reference genome of hexaploid (Chinese Spring) and tetraploid (Triticum turgidum ssp. dicoccoides) wheat became publicly available coupled with on-going international efforts on wheat pan-genome sequencing. We anticipate that an objective appraisal is required in the post-genomics era to prioritize genetic resources for use in the improvement of wheat production if the goal of doubling yield by 2050 is to be met. Advances in genomics have resulted in the development of high-throughput genotyping arrays, improved and efficient methods of gene discovery, genomics-assisted selection and gene editing using endonucleases. Likewise, ongoing advances in rapid generation turnover, improved phenotyping, envirotyping and analytical methods will significantly accelerate exploitation of exotic genes and increase the rate of genetic gain in breeding. We argue that the integration of these advances will significantly improve the precision and targeted identification of potentially useful variation in the wild relatives of wheat, providing new opportunities to contribute to yield and quality improvement, tolerance to abiotic stresses, resistance to emerging biotic stresses and resilience to weather extremes. [ABSTRACT FROM AUTHOR]

Background and aims: Chromium (Cr) toxicity is a rapidly increasing environmental concern and poses a major threat to plant growth as well as food chain. This study was carried out to screen spring wheat diversity panel against Cr toxicity to assess yield reduction, grain contamination extents and genomic regions associated with tolerance to Cr toxicity.Methods: The diversity panel was planted in control and Cr stress (26 mg Cr/kg soil) in paved plots, and several morphological and physiological traits were recorded. Wheat 90 K Infinium iSelect SNP array was used to identify genomic regions underpinning tolerance to Cr toxicity.Results: Some wheat cultivars (Khosar-95, Miraj-08, Millet-11, Sarsabaz and NARC-11) had Cr concentration within international edible threshold limit (1 ppm), but showed greater reduction to grain yield (63–95%) due to higher leaf Cr concentrations (2.35–8.95 ppm). Contrastingly, wheat cultivars Auqab-00 and Pakistan-13 had lower yield reduction up to 9% and 39%, respectively but had higher concentration of Cr in seeds (2.1 and 3.5 ppm, respectively). Genome-wide association studies identified 71 loci linked with yield related traits under Cr stress and 48 loci for differences between control and Cr stress treatments. Further, gene ontology of trait-associated SNPs revealed proteins with significant importance in plant development and tolerance against heavy metal stress.Conclusion: To our knowledge, this is the first study for identification of genomic regions linked to Cr stress, suggesting that this could be useful to identify complex architecture of genetic factors as well as molecular breeding opportunities for tolerance to Cr stress. [ABSTRACT FROM AUTHOR]

Identification of genes for yield components, plant height (PH), and yield-related physiological traits and tightly linked molecular markers is of great importance in marker-assisted selection (MAS) in wheat breeding. In the present study, 246 F8 RILs derived from the cross of Zhou 8425B/Chinese Spring were genotyped using the high-density Illumina iSelect 90K single nucleotide polymorphism (SNP) assay. Field trials were conducted at Zhengzhou and Zhoukou of Henan Province, during the 2012-2013 and 2013-2014 cropping season under irrigated conditions, providing data for four environments. Analysis of variance (ANOVA) of agronomic and physiological traits revealed significant differences (P < 0.01) among RILs, environments, and RILs × environments interactions. Broad-sense heritabilities of all traits including thousand kernel weight (TKW), PH, spike length (SL), kernel number per spike (KNS), spike number/m² (SN), normalized difference in vegetation index at anthesis (NDVI-A) and at 10 days post-anthesis (NDVI-10), SPAD value of chlorophyll content at anthesis (Chl-A) and at 10 days post-anthesis (Chl-10) ranged between 0.65 and 0.94. A linkage map spanning 3609.4cM was constructed using 5636 polymorphic SNP markers, with an average chromosome length of 171.9cM and marker density of 0.64 cM/marker. A total of 866 SNP markers were newly mapped to the hexaploid wheat linkage map. Eighty-six QTL for yield components, PH, and yield-related physiological traits were detected on 18 chromosomes except 1D, 5D, and 6D, explaining 2.3-33.2% of the phenotypic variance. Ten stable QTL were identified across four environments, viz. QTKW.caas-6A.1, QTKW.caas-7AL, QKNS.caas-4AL, QSN.caas-1AL.1, QPH.caas-4BS.2, QPH.caas-4DS.1, QSL.caas-4AS, QSL.caas-4AL.1, QChl-A.caas-5AL, and QChl-10.caas-5BL. Meanwhile, 10 QTL-rich regions were found on chromosome 1BS, 2AL (2), 3AL, 4AL (2), 4BS, 4DS, 5BL, and 7AL exhibiting pleiotropic effects. These QTL or QTL clusters are tightly linked to SNP markers, with genetic distances to the closest SNPs ranging from 0 to 1.5 cM, and could serve as target regions for fine mapping, candidate gene discovery, and MAS in wheat breeding. [ABSTRACT FROM AUTHOR]

Genome-wide association studies (GWAS) were undertaken to identify SNP markers associated with yield and yield-related traits in 123 Pakistani historical wheat cultivars evaluated during 2011-2014 seasons under rainfed field conditions. The population was genotyped by using high-density Illumina iSelect 90K single nucleotide polymorphism (SNP) assay, and finally 14,960 high quality SNPs were used in GWAS. Population structure examined using 1000 unlinked markers identified seven subpopulations (K = 7) that were representative of different breeding programs in Pakistan, in addition to local landraces. Forty four stable marker-trait associations (MTAs) with -log p > 4 were identified for nine yield-related traits. Nine multi-trait MTAs were found on chromosomes 1AL, 1BS, 2AL, 2BS, 2BL, 4BL, 5BL, 6AL, and 6BL, and those on 5BL and 6AL were stable across two seasons. Gene annotation and syntey identified that 14 trait-associated SNPs were linked to genes having significant importance in plant development. Favorable alleles for days to heading (DH), plant height (PH), thousand grain weight (TGW), and grain yield (GY) showed minor additive effects and their frequencies were slightly higher in cultivars released after 2000. However, no selection pressure on any favorable allele was identified. These genomic regions identified have historically contributed to achieve yield gains from 2.63 million tons in 1947 to 25.7 million tons in 2015. Future breeding strategies can be devised to initiate marker assisted breeding to accumulate these favorable alleles of SNPs associated with yield-related traits to increase grain yield. Additionally, in silico identification of 454-contigs corresponding to MTAs will facilitate fine mapping and subsequent cloning of candidate genes and functional marker development. [ABSTRACT FROM AUTHOR]

Genome-wide association studies (GWAS) were undertaken to identify SNP markers associated with yield and yield-related traits in 123 Pakistani historical wheat cultivars evaluated during 2011-2014 seasons under semi-arid field conditions. The population was genotyped in a high-density Illumina iSelect 90K single nucleotide polymorphism (SNP) assay, and finally 14,960 high quality SNPs were used in GWAS. Population structure examined using 1000 unlinked markers identified seven subpopulations (K=7) that were representative of different breeding programs in Pakistan, in addition to local landraces. Forty four stable marker-trait associations (MTAs) with -- log p >4 were identified for nine yield-related traits. Nine multi-trait MTAs were found on chromosomes 1AL, 1BS, 2AL, 2BS, 2BL, 4BL, 5BL, 6AL and 6BL, and those on 5BL and 6AL were stable across two seasons. Gene annotation and syntey identified that 14 trait-associated SNPs were linked to genes having significant importance in plant development. Favorable alleles for days to heading (DH), plant height (PH), thousand grain weight (TGW) and grain yield (GY) showed minor additive effects and their frequencies were slightly higher in cultivars released after 2000. However, no selection pressure on any favorable allele was identified. These genomic regions identified have historically contributed to achieve yield gains from 2.63 million tonnes in 1947 to 25.7 million tonnes in 2015. Future breeding strategy can be devised to initiate marker-based breeding to accumulate these favorable alleles of SNPs associated with yield-related traits to increase grain yield. Additionally, in silico identification of 454-contigs corresponding to MTAs will facilitate fine mapping and Provisional subsequent cloning of candidate genes and functional marker development. [ABSTRACT FROM AUTHOR]

Genomic selection (GS) is a strategy to predict the genetic merits of individuals using genome-wide markers. However, GS prediction accuracy is affected by many factors, including missing rate and minor allele frequency (MAF) of genotypic data, GS models, trait features, etc. In this study, we used one wheat population to investigate prediction accuracies of various GS models on yield and yield-related traits from various quality control (QC) scenarios, missing genotype imputation, and genome-wide association studies (GWAS)-derived markers. Missing rate and MAF of single nucleotide polymorphism (SNP) markers were two major factors in QC. Five missing rate levels (0%, 20%, 40%, 60%, and 80%) and three MAF levels (0%, 5%, and 10%) were considered and the five-fold cross validation was used to estimate the prediction accuracy. The results indicated that a moderate missing rate level (20% to 40%) and MAF (5%) threshold provided better prediction accuracy. Under this QC scenario, prediction accuracies were further calculated for imputed and GWAS-derived markers. It was observed that the accuracies of the six traits were related to their heritability and genetic architecture, as well as the GS prediction model. Moore–Penrose generalized inverse (GenInv), ridge regression (RidgeReg), and random forest (RForest) resulted in higher prediction accuracies than other GS models across traits. Imputation of missing genotypic data had marginal effect on prediction accuracy, while GWAS-derived markers improved the prediction accuracy in most cases. These results demonstrate that QC on missing rate and MAF had positive impact on the predictability of GS models. We failed to identify one single combination of QC scenarios that could outperform the others for all traits and GS models. However, the balance between marker number and marker quality is important for the deployment of GS in wheat breeding. GWAS is able to select markers which are mostly related to traits, and therefore can be used to improve the prediction accuracy of GS. [ABSTRACT FROM AUTHOR]

Background: Identification of loci for grain yield (GY) and related traits, and dissection of the genetic architecture are important for yield improvement through marker-assisted selection (MAS). Two genome-wide association study (GWAS) methods were used on a diverse panel of 166 elite wheat varieties from the Yellow and Huai River Valleys Wheat Zone (YHRVWD) of China to detect stable loci and analyze relationships among GY and related traits. Results: A total of 326,570 single nucleotide polymorphism (SNP) markers from the wheat 90 K and 660 K SNP arrays were chosen for GWAS of GY and related traits, generating a physical distance of 14,064.8 Mb. One hundred and twenty common loci were detected using SNP-GWAS and Haplotype-GWAS, among which two were potentially functional genes underpinning kernel weight and plant height (PH), eight were at similar locations to the quantitative trait loci (QTL) identified in recombinant inbred line (RIL) populations in a previous study, and 78 were potentially new. Twelve pleiotropic loci were detected on eight chromosomes; among these the interval 714.4–725.8 Mb on chromosome 3A was significantly associated with GY, kernel number per spike (KNS), kernel width (KW), spike dry weight (SDW), PH, uppermost internode length (UIL), and flag leaf length (FLL). GY shared five loci with thousand kernel weight (TKW) and PH, indicating significantly affected by two traits. Compared with the total number of loci for each trait in the diverse panel, the average number of alleles for increasing phenotypic values of GY, TKW, kernel length (KL), KW, and flag leaf width (FLW) were higher, whereas the numbers for PH, UIL and FLL were lower. There were significant additive effects for each trait when favorable alleles were combined. UIL and FLL can be directly used for selecting high-yielding varieties, whereas FLW can be used to select spike number per unit area (SN) and KNS. Conclusions: The loci and significant SNP markers identified in the present study can be used for pyramiding favorable alleles in developing high-yielding varieties. Our study proved that both GWAS methods and high-density genetic markers are reliable means of identifying loci for GY and related traits, and provided new insight to the genetic architecture of GY. [ABSTRACT FROM AUTHOR]