Search

Key Message: Sedimentation values and falling number in the last decades have helped maintain high baking quality despite rigorous selection for grain yield in wheat. Allelic combinations of major loci sustained the bread-making quality while improving grain yield. Glu-D1, Pinb-D1, and non-gluten proteins are associated with sedimentation values and falling number in European wheat. Zeleny sedimentation values (ZSV) and Hagberg-Perten falling number (HFN) are among the most important parameters that help determine the baking quality classes of wheat and, thus, influence the monetary benefits for growers. We used a published data set of 372 European wheat varieties evaluated in replicated field trials in multiple environments. ZSV and HFN traits hold a wide and significant genotypic variation and high broad-sense heritability. The genetic correlations revealed positive and significant associations of ZSV and HFN with each other, grain protein content (GPC) and grain hardness; however, they were all significantly negatively correlated with grain yield. Besides, GPC appeared to be the major predictor for ZSV and HFN. Our genome-wide association analyses based on high-quality SSR, SNP, and candidate gene markers revealed a strong quantitative genetic nature of ZSV and HFN by explaining their total genotypic variance as 41.49% and 38.06%, respectively. The association of known Glutenin (Glu-1) and Puroindoline (Pin-1) with ZSV provided positive analytic proof of our studies. We report novel candidate loci associated with globulins and albumins-the non-gluten monomeric proteins in wheat. In addition, predictive breeding analyses for ZSV and HFN suggest using genomic selection in the early stages of breeding programs with an average prediction accuracy of 81 and 59%, respectively., (© 2023. The Author(s).)

In plant sciences, curation and availability of interoperable phenotypic and genomic data is still in its infancy and represents an obstacle to rapid scientific discoveries in this field. To that end, supplementing the efforts being made to generate open access wheat genome, pan wheat genome and other bioinformatic resources, we present the GABI-WHEAT panel of elite European cultivars comprising 358 winter and 14 summer wheat varieties released between 1975 to 2007. The panel has been genotyped with SNP arrays of increasing density to investigate several important agronomic, quality and disease resistance traits. The robustness of investigated traits and interoperability of genomic and phenotypic data was assessed in the current publication with the aim to transform this panel into a public data resource for future genetic research in wheat. Consecutively, the phenotypic data was formatted to comply with FAIR principles and linked to online databases to substantiate panel origin information and quality. Thus, we were able to make a valuable resource available for plant science in a sustainable way., (© 2022. The Author(s).)

The resistance to cereal cyst nematode (Heterodera avenae Woll.) in wheat (Triticum aestivum L.) was studied using 114 doubled haploid lines from a novel ITMI mapping population. These lines were screened for nematode infestation in a controlled environment for two years. QTL-mapping analyses were performed across two years (Y1 and Y2) as well as combining two years (CY) data. On the 114 lines that were screened, a total of 2,736 data points (genotype, batch or years, and replication combinations) were acquired. For QTL analysis, 12,093 markers (11,678 SNPs and 415 SSRs markers) were used, after filtering the genotypic data, for the QTL mapping. Composite interval mapping, using Haley-Knott regression (hk) method in R/QTL, was used for QTL analysis. In total, 19 QTLs were detected out of which 13 were novel and six were found to be colocalized or nearby to previously reported Cre genes, QTLs or MTAs for H. avenae or H. filipjevi. Nine QTLs were detected across all three groups (Y1, Y2 and CY) including a significant QTL "QCcn.ha-2D" on chromosome 2D that explains 23% of the variance. This QTL colocalized with a previously identified Cre3 locus. Novel QTL, QCcn.ha-2A, detected in the present study could be the possible unreported homeoloci to QCcn.ha-2D, QCcn.ha-2B.1 and QCcn.ha-2B.2. Six significant digenic epistatic interactions were also observed. In addition, 26 candidate genes were also identified including genes known for their involvement in PPNs (plant parasitic nematodes) resistance in different plant species. In-silico expression of putative candidate genes showed differential expression in roots during specific developmental stages. Results obtained in the present study are useful for wheat breeding to generate resistant genetic resources against H. avenae., (© 2022. The Author(s).)

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

Total spikelet number per spike (TSN) is a major component of spike architecture in wheat (Triticum aestivum L.). A major and consistent quantitative trait locus (QTL) was discovered for TSN in a doubled haploid spring wheat population grown in the field over 4 years. The QTL on chromosome 7B explained up to 20.5% of phenotypic variance. In its physical interval (7B: 6.37-21.67 Mb), the gene FLOWERING LOCUS T (FT-B1) emerged as candidate for the observed effect. In one of the parental lines, FT-B1 carried a non-synonymous substitution on position 19 of the coding sequence. This mutation modifying an aspartic acid (D) into a histidine (H) occurred in a highly conserved position. The mutation was observed with a frequency of ca. 68% in a set of 135 hexaploid wheat varieties and landraces, while it was not found in other plant species. FT-B1 only showed a minor effect on heading and flowering time (FT) which were dominated by a major QTL on chromosome 5A caused by segregation of the vernalization gene VRN-A1. Individuals carrying the FT-B1 allele with amino acid histidine had, on average, a higher number of spikelets (15.1) than individuals with the aspartic acid allele (14.3) independent of their VRN-A1 allele. We show that the effect of TSN is not mainly related to flowering time; however, the duration of pre-anthesis phases may play a major role.

Hexaploid wheat (Triticum aestivum L.) is a natural allopolyploid and provides a usable model system to better understand the genetic mechanisms that underlie allopolyploid speciation through the hybrid genome doubling. Here we aimed to identify the contribution of chromosome 1D in the development and evolution of hexaploid wheat. We identified and mapped a novel DEFECTIVE ENDOSPERM-D1 (Dee-D1) locus on 1DL that is involved in the genetic control of endosperm development. The absence of Dee-D1 leads to non-viable grains in distant crosses and alters grain shape, which negatively affects grain number and thousand-grain weight. Dee-D1 can be classified as speciation locus with a positive effect on the function of genes which are involved in endosperm development in hybrid genomes. The presence of Dee-D1 is necessary for the normal development of endosperm, and thus play an important role in the evolution and improvement of grain yield in hexaploid wheat.

Grain quality traits determine the classification of registered wheat (Triticum aestivum L.) varieties. Although environmental factors and crop management practices exert a considerable influence on wheat quality traits, a significant proportion of the variance is attributed to the genetic factors. To identify the underlying genetic factors of wheat quality parameters viz., grain protein content (GPC), grain starch content (GSC), and grain hardness (GH), we evaluated 372 diverse European wheat varieties in replicated field trials in up to eight environments. We observed that all of the investigated traits hold a wide and significant genetic variation, and a significant negative correlation exists between GPC and GSC plus grain yield. Our association analyses based on 26,694 high-quality single nucleotide polymorphic markers revealed a strong quantitative genetic nature of GPC and GSC with associations on groups 2, 3, and 6 chromosomes. The identification of known Puroindoline-b gene for GH provided a positive analytic proof for our studies. We report that a locus QGpc.ipk-6A controls both GPC and GSC with opposite allelic effects. Based on wheat's reference and pan-genome sequences, the physical characterization of two loci viz., QGpc.ipk-2B and QGpc.ipk-6A facilitated the identification of the candidate genes for GPC. Furthermore, by exploiting additive and epistatic interactions of loci, we evaluated the prospects of predictive breeding for the investigated traits that suggested its efficient use in the breeding programs.

We dissected the genetic basis of total spikelet number (TSN) along with other traits, viz. spike length (SL) and flowering time (FT) in a panel of 518 elite European winter wheat varieties. Genome-wide association studies (GWAS) based on 39,908 SNP markers revealed highly significant quantitative trait loci (QTL) for TSN on chromosomes 2D, 7A, and 7B, for SL on 5A, and FT on 2D, with 2D-QTL being the functional marker for the gene Ppd-D1. The physical region of the 7A-QTL for TSN revealed the presence of a wheat ortholog (TaAPO-A1) to APO1-a rice gene that positively controls the spikelet number on the panicles. Interspecific analyses of the TaAPO-A1 orthologs showed that it is a highly conserved gene important for floral development and present in a wide range of terrestrial plants. Intraspecific studies of the TaAPO-A1 across wheat genotypes revealed a polymorphism in the conserved F-box domain, defining two haplotypes. A KASP marker developed on the polymorphic site showed a highly significant association of TaAPO-A1 with TSN, explaining 23.2% of the total genotypic variance. Also, the TaAPO-A1 alleles showed weak but significant differences for SL and grain yield. Our results demonstrate the importance of wheat sequence resources to identify candidate genes for important traits based on genetic analyses.

blotch (STB) caused by the fungus is a devastating foliar disease of wheat ( L.) that can lead to substantial yield losses. Quantitative genetic resistance has been proposed as a durable strategy for STB control. In this study, we dissected the genetic basis of STB infection in 371 European wheat varieties based on 35k and 90k single nucleotide polymorphism marker arrays. The phenotypic data analyses suggested that large genetic variance exists for STB infection with a broad-sense heritability of 0.78. Genome-wide association studies (GWAS) propose the highly quantitative nature of STB infection with potential associations on chromosomes 1A, 1B, 2D, 4A, 5A, 6A, 6D, 7A, and 7B. Increased marker density in GWAS by combining markers from both arrays helped to detect additional markers explaining increased genotypic variance. Linkage disequilibrium analyses revealed genes with a possible role in disease resistance. The potential of genomic prediction (GP) assessed via two models accounting for additive effects and additive plus epistatic interactions among the loci suggested the possibility of genomic selection for improved STB resistance. Genomic prediction results also indicated that the higher-order epistatic interactions are not abundant and that both marker platforms are equally suitable for GP of STB infection. Our results provide further understanding of the quantitative genetic nature of STB infection, serve as a resource for marker-assisted breeding, and highlight the potential of genomic selection for improved STB resistance., (Copyright © 2019 Crop Science Society of America.)

Malnutrition of iron (Fe) affects two billion people worldwide. Therefore, enhancing grain Fe concentration (GFeC) in wheat ( Triticum aestivum L.) is an important goal for breeding. Here we study the genetic factors underlying GFeC trait by genome-wide association studies (GWAS) and the prediction abilities using genomic prediction (GP) in a panel of 369 European elite wheat varieties which was genotyped with 15,523 mapped single-nucleotide polymorphism markers (SNP) and a subpanel of 183 genotypes with 44,233 SNP markers. The resulting means of GFeC from three field experiments ranged from 24.42 to 52.42 μg·g -1 with a broad-sense heritability ( H ²) equaling 0.59 over the years. GWAS revealed 41 and 137 significant SNPs in the whole and subpanel, respectively, including significant marker-trait associations (MTAs) for best linear unbiased estimates (BLUEs) of GFeC on chromosomes 2A, 3B and 5A. Putative candidate genes such as NAC transcription factors and transmembrane proteins were present on chromosome 2A (763,689,738⁻765,710,113 bp). The GP for a GFeC trait ranged from low to moderate values. The current study reported GWAS of GFeC for the first time in hexaploid wheat varieties. These findings confirm the utility of GWAS and GP to explore the genetic architecture of GFeC for breeding programs aiming at the improvement of wheat grain quality.

One of the primary objectives of wheat breeding was to increase grain yield. Floral abortion during the stem elongation phase (SEP) leads to a loss of more than 50% of the grain number potential. In this study, we quantified 75 plant growth-associated traits at seven stages during the SEP and mapped 15 696 single nucleotide polymorphism (SNP) markers in 210 accessions of wheat (Triticum aestivum). Our genomewide association study identified trait-associated SNPs that are shared among various stages of the SEP, as well as SNPs that are shared between plant growth traits and grain yield in the field. The genomic selection analysis shows variation among the prediction abilities of various traits and stages. Furthermore, we found that the allelic variants of Ppd-D1 (chromosome 2D) and Rht-D1 (chromosome 4D) loci affect some plant growth traits (e.g. leaf area and spike length). These results have identified a narrow time window within the SEP in which plant growth traits can be manipulated to alter grain yield. This suggests that there may be multiple ways to regulate plant growth during the SEP, to ultimately influence grain number in wheat., (© 2018 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.)

In wheat (Triticum spp.), modifying inflorescence (spike) morphology can increase grain number and size and thus improve yield. Here, we demonstrated the potential for manipulating and predicting spike morphology, based on 44 traits. In 12 wheat cultivars, we observed that detillering (removal of branches), which alters photosynthate distribution, changed spike morphology. Our genome-wide association study detected close associations between carbon partitioning (e.g. tiller number, main shoot dry weight) and spike morphology (e.g. spike length, spikelet density) traits in 210 cultivars. Most carbon-partitioning traits (e.g. tiller dry weight, harvest index) demonstrated high prediction abilities (>0.5). For spike morphology, some traits (e.g. total and fertile spikelet number, spike length) displayed high prediction abilities (0.3-0.5), but others (e.g. spikelet fertility, spikelet density) exhibited low prediction abilities (<0.2). Grain size traits were closely correlated in field and greenhouse experiments. Stepwise regression analysis suggests that significantly associated traits in the greenhouse explain 35.35% of the variation in grain yield and 67.63% of the variation in thousand-kernel weight in the field. Therefore, the traits identified in this study affect spike morphology; these traits can be used to predict and improve plant architecture and thus increase yield.

Wheat ( Triticum aestivum L.) is one of the major staple food crops worldwide. Despite efforts in improving wheat quality, micronutrient levels are still below the optimal range for human nutrition. In particular, zinc (Zn) deficiency is a widespread problem in human nutrition in countries relying mainly on a cereal diet; hence improving Zn accumulation in grains is an imperative need. This study was designed to understand the genetic architecture of Zn grain concentrations in wheat grains. We performed a genome-wide association study (GWAS) for grain Zn concentrations in 369 European wheat genotypes, using field data from 3 years. The complete wheat panel was genotyped by high-density arrays of single nucleotide polymorphic (SNP) markers (90k iSELECT Infinium and 35k Affymetrix arrays) resulting in 15,523 polymorphic markers. Additionally, a subpanel of 183 genotypes was analyzed with a novel 135k Affymetrix marker array resulting in 28,710 polymorphic SNPs for high-resolution mapping of the potential genomic regions. The mean grain Zn concentration of the genotypes ranged from 25.05-52.67 μg g -1 dry weight across years with a moderate heritability value. Notably, 40 marker-trait associations (MTAs) were detected in the complete panel of varieties on chromosomes 2A, 3A, 3B, 4A, 4D, 5A, 5B, 5D, 6D, 7A, 7B, and 7D. The number of MTAs in the subpanel was increased to 161 MTAs whereas the most significant and consistent associations were located on chromosomes 3B (723,504,241-723,611,488 bp) and 5A (462,763,758-466,582,184 bp) having major effects. These genomic regions include newly identified putative candidate genes, which are related to Zn uptake and transport or represent bZIP and mitogen-activated protein kinase genes. These findings provide the basis for understanding the genetic background of Zn concentration in wheat grains that in turn may help breeders to select high Zn-containing genotypes to improve human health and grain quality.

Flowering time is an important factor affecting grain yield in wheat. In this study, we divided reproductive spike development into eight sub-phases. These sub-phases have the potential to be delicately manipulated to increase grain yield. We measured 36 traits with regard to sub-phase durations, determined three grain yield-related traits in eight field environments and mapped 15 696 single nucleotide polymorphism (SNP, based on 90k Infinium chip and 35k Affymetrix chip) markers in 210 wheat genotypes. Phenotypic and genetic associations between grain yield traits and sub-phase durations showed significant consistency (Mantel test; r = 0.5377, P < 0.001). The shared quantitative trait loci (QTLs) revealed by the genome-wide association study suggested a close association between grain yield and sub-phase duration, which may be attributed to effects on spikelet initiation/spikelet number (double ridge to terminal spikelet stage, DR-TS) and assimilate accumulation (green anther to anthesis stage, GA-AN). Moreover, we observed that the photoperiod-sensitivity allele at the Ppd-D1 locus on chromosome 2D markedly extended all sub-phase durations, which may contribute to its positive effects on grain yield traits. The dwarfing allele at the Rht-D1 (chromosome 4D) locus altered the sub-phase duration and displayed positive effects on grain yield traits. Data for 30 selected genotypes (from among the original 210 genotypes) in the field displayed a close association with that from the greenhouse. Most importantly, this study demonstrated specific connections to grain yield in narrower time windows (i.e. the eight sub-phases), rather than the entire stem elongation phase as a whole., (© 2018 The Authors. The Plant Journal published by John Wiley & Sons Ltd and Society for Experimental Biology.)

The production and cultivation of hybrid wheat is a possible strategy to close the yield gap in wheat. Efficient hybrid wheat seed production largely depends on high rates of cross-pollination which can be ensured through high anther extrusion (AE) by male parental lines. Here, we report the AE capacity and elucidate its genetics in 514 elite European winter wheat varieties via genome-wide association studies (GWAS). We observed a wide range of variation among genotypes and a high heritability (0.80) for AE. The whole panel was genotyped with the 35k Affymetrix and 90k iSELECT single nucleotide polymorphism (SNP) arrays plus Ppd-D1, Rht-B1 and Rht-D1 candidate markers. GWAS revealed 51 marker-trait associations (MTAs) on chromosomes 1A, 1B, 2A, 4D and 5B, with Rht-D1 (4D) being the most significant marker. Division of whole panel according to the Rht-D1 genotype resulted in 212 and 294 varieties harboring Rht-D1a and Rht-D1b allele, respectively. The presence of Rht-D1a compared to Rht-D1b (mutant) allele had a large phenotypic influence on AE resulting in its ~17% increase. GWAS performed on the sub-panels detected novel MTAs on chromosomes 2D, 3B and 6A with increased phenotypic variance imparted by individual markers. Our study shows that AE is a highly quantitative trait and wild type Rht-D1a allele greatly improves AE. Moreover, demarcating the quantitative trait loci regions based on intra-chromosomal linkage disequilibrium revealed AE's candidate genes/genomic regions. Understanding the genetics of AE in elite European wheat and utilizing the linked markers in breeding programs can help to enhance cross-pollination for better exploitation of heterosis.

Grain yield (GY) of bread wheat (Triticum aestivum L.) is quantitatively inherited. Correlated GY-syndrome traits such as plant height (PH), heading date (HD), thousand grain weight (TGW), test weight (TW), grains per ear (GPE), and ear weight (EW) influence GY. Most quantitative genetics studies assessed the multiple-trait (MT) complex of GY-syndrome using single-trait approaches, and little is known about its underlying pleiotropic architecture. We investigated the pleiotropic architecture of wheat GY-syndrome through MT association mapping (MT-GWAS) using 372 varieties phenotyped in up to eight environments and genotyped with 18 832 single nucleotide polymorphisms plus 24 polymorphic functional markers. MT-GWAS revealed a total of 345 significant markers spread genome wide, representing 8, 40, 11, 40, 34, and 35 effective GY-PH, GY-HD, GY-TGW, GY-TW, GY-GPE, and GY-EW associations, respectively. Among them, pleiotropic roles of Rht-B1 and TaGW2-6B loci were corroborated. Only one marker presented simultaneous associations for three traits (i.e. GY-TGW-TW). Close linkage was difficult to differentiate from pleiotropy; thus, the pleiotropic architecture of GY-syndrome was dissected more as a cause of pleiotropy rather than close linkage. Simulations showed that minor allele frequencies, along with sizes and distances between quantitative trait loci for two traits, influenced the ability to distinguish close linkage from pleiotropy., (© The Author 2017. Published by Oxford University Press on behalf of the Society for Experimental Biology.)

Increasing grain yield is still the main target of wheat breeding; yet today's wheat plants utilize less than half of their yield potential. Owing to the difficulty of determining grain yield potential in a large population, few genetic factors regulating floret fertility (i.e. the difference between grain yield potential and grain number) have been reported to date. In this study, we conducted a genome-wide association study (GWAS) by quantifying 54 traits (16 floret fertility traits and 38 traits for assimilate partitioning and spike morphology) in 210 European winter wheat accessions. The results of this GWAS experiment suggested potential associations between floret fertility, assimilate partitioning and spike morphology revealed by shared quantitative trait loci (QTLs). Several candidate genes involved in carbohydrate metabolism, phytohormones or floral development colocalized with such QTLs, thereby providing potential targets for selection. Based on our GWAS results we propose a genetic network underlying floret fertility and related traits, nominating determinants for improved yield performance., (© 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.)

Key Message: Compared with independent validation, cross-validation simultaneously sampling genotypes and environments provided similar estimates of accuracy for genomic selection, but inflated estimates for marker-assisted selection. Estimates of prediction accuracy of marker-assisted (MAS) and genomic selection (GS) require validations. The main goal of our study was to compare the prediction accuracies of MAS and GS validated in an independent sample with results obtained from fivefold cross-validation using genomic and phenotypic data for Fusarium head blight resistance in wheat. In addition, the applicability of the reliability criterion, a concept originally developed in the context of classic animal breeding and GS, was explored for MAS. We observed that prediction accuracies of MAS were overestimated by 127% using cross-validation sampling genotype and environments in contrast to independent validation. In contrast, prediction accuracies of GS determined in independent samples are similar to those estimated with cross-validation sampling genotype and environments. This can be explained by small population differentiation between the training and validation sets in our study. For European wheat breeding, which is so far characterized by a slow temporal dynamic in allele frequencies, this assumption seems to be realistic. Thus, GS models used to improve European wheat populations are expected to possess a long-lasting validity. Since quantitative trait loci information can be exploited more precisely if the predicted genotype is more related to the training population, the reliability criterion is also a valuable tool to judge the level of prediction accuracy of individual genotypes in MAS.

Key Message: Genotypes with recombination events in the Triticum ventricosum introgression on chromosome 7D allowed to fine-map resistance gene Pch1, the main source of eyespot resistance in European winter wheat cultivars. Eyespot (also called Strawbreaker) is a common and serious fungal disease of winter wheat caused by the necrotrophic fungi Oculimacula yallundae and Oculimacula acuformis (former name Pseudocercosporella herpotrichoides). A genome-wide association study (GWAS) for eyespot was performed with 732 microsatellite markers (SSR) and 7761 mapped SNP markers derived from the 90 K iSELECT wheat array using a panel of 168 European winter wheat varieties as well as three spring wheat varieties and phenotypic evaluation of eyespot in field tests in three environments. Best linear unbiased estimations (BLUEs) were calculated across all trials and ranged from 1.20 (most resistant) to 5.73 (most susceptible) with an average value of 4.24 and a heritability of H 2  = 0.91. A total of 108 SSR and 235 SNP marker-trait associations (MTAs) were identified by considering associations with a -log 10 (P value) ≥3.0. Significant MTAs for eyespot-score BLUEs were found on chromosomes 1D, 2A, 2D, 3D, 5A, 5D, 6A, 7A and 7D for the SSR markers and chromosomes 1B, 2A, 2B, 2D, 3B and 7D for the SNP markers. For 18 varieties (10.5%), a highly resistant phenotype was detected that was linked to the presence of the resistance gene Pch1 on chromosome 7D. The identification of genotypes with recombination events in the introgressed genomic segment from Triticum ventricosum harboring the Pch1 resistance gene on chromosome 7DL allowed the fine-mapping of this gene using additional SNP markers and a potential candidate gene Traes&#95;7DL&#95;973A33763 coding for a CC-NBS-LRR class protein was identified.

Key Message: The Brassica napus Illumina array provides genome-wide markers linked to the available genome sequence, a significant tool for genetic analyses of the allotetraploid B. napus and its progenitor diploid genomes. A high-density single nucleotide polymorphism (SNP) Illumina Infinium array, containing 52,157 markers, was developed for the allotetraploid Brassica napus. A stringent selection process employing the short probe sequence for each SNP assay was used to limit the majority of the selected markers to those represented a minimum number of times across the highly replicated genome. As a result approximately 60 % of the SNP assays display genome-specificity, resolving as three clearly separated clusters (AA, AB, and BB) when tested with a diverse range of B. napus material. This genome specificity was supported by the analysis of the diploid ancestors of B. napus, whereby 26,504 and 29,720 markers were scorable in B. oleracea and B. rapa, respectively. Forty-four percent of the assayed loci on the array were genetically mapped in a single doubled-haploid B. napus population allowing alignment of their physical and genetic coordinates. Although strong conservation of the two positions was shown, at least 3 % of the loci were genetically mapped to a homoeologous position compared to their presumed physical position in the respective genome, underlying the importance of genetic corroboration of locus identity. In addition, the alignments identified multiple rearrangements between the diploid and tetraploid Brassica genomes. Although mostly attributed to genome assembly errors, some are likely evidence of rearrangements that occurred since the hybridisation of the progenitor genomes in the B. napus nucleus. Based on estimates for linkage disequilibrium decay, the array is a valuable tool for genetic fine mapping and genome-wide association studies in B. napus and its progenitor genomes., Competing Interests: The authors MWG, RW, and JP have competing commercial interests as members of TraitGenetics GmbH which is a company that offers marker development and analysis (including this array) for commercial purposes. This does not alter the authors’ adherence to sharing data.

The Capsicum genus (Pepper) is a part of the Solanacae family. It has been important in many cultures worldwide for its key nutritional components and uses as spices, medicines, ornamentals and vegetables. Worldwide population growth is associated with demand for more nutritionally valuable vegetables while contending with decreasing resources and available land. These conditions require increased efficiency in pepper breeding to deal with these imminent challenges. Through resequencing of inbred lines we have completed a valuable haplotype map (HapMap) for the pepper genome based on single-nucleotide polymorphisms (SNP). The identified SNPs were annotated and classified based on their gene annotation in the pepper draft genome sequence and phenotype of the sequenced inbred lines. A selection of one marker per gene model was utilized to create the PepperSNP16K array, which simultaneously genotyped 16 405 SNPs, of which 90.7% were found to be informative. A set of 84 inbred and hybrid lines and a mapping population of 90 interspecific F2 individuals were utilized to validate the array. Diversity analysis of the inbred lines shows a distinct separation of bell versus chile/hot pepper types and separates them into five distinct germplasm groups. The interspecific population created between Tabasco (C. frutescens chile type) and P4 (C. annuum blocky type) produced a linkage map with 5546 markers separated into 1361 bins on twelve 12 linkage groups representing 1392.3 cM. This publically available genotyping platform can be used to rapidly assess a large number of markers in a reproducible high-throughput manner for pepper. As a standardized tool for genetic analyses, the PepperSNP16K can be used worldwide to share findings and analyze QTLs for important traits leading to continued improvement of pepper for consumers. Data and information on the array are available through the Solanaceae Genomics Network.

Key Message: We have developed a SNP array for sunflower containing more than 25 K markers, representing single loci mostly in or near transcribed regions of the genome. The array was successfully applied to genotype a diversity panel of lines, hybrids, and mapping populations and represented well the genetic diversity of cultivated sunflower. Results of PCoA and population substructure analysis underlined the complexity of the genetic composition of current elite breeding material. The performance of this genotyping platform for genome-based prediction of phenotypes and detection of QTL with improved resolution could be demonstrated based on the re-evaluation of a population segregating for resistance to Sclerotinia midstalk rot. Given our results, the newly developed 25 K SNP array is expected to be of great utility for the most important applications in genome-based sunflower breeding and research., Abstract: Genotyping with a large number of molecular markers is a prerequisite to conduct genome-based genetic analyses with high precision. Here, we report the design and performance of a 25 K SNP genotyping array for sunflower (Helianthus annuus L.). SNPs were discovered based on variant calling in de novo assembled, UniGene-based contigs of sunflower derived from whole genome sequencing and amplicon sequences originating from four and 48 inbred lines, respectively. After inclusion of publically available transcriptome-derived SNPs, in silico design of the Illumina(®) Infinium iSelect HD BeadChip yielded successful assays for 22,299 predominantly haplotype-specific SNPs. The array was validated in a sunflower diversity panel including inbred lines, open-pollinated varieties, introgression lines, landraces, recombinant inbred lines, and F2 populations. Validation provided 20,502 high-quality bi-allelic SNPs with stable cluster performance whereby each SNP marker represents a single locus mostly in or near transcribed regions of the sunflower genome. Analyses of population structure and quantitative resistance to Sclerotinia midstalk rot demonstrate that this array represents a significant improvement over currently available genomic tools for genetic diversity analyses, genome-wide marker-trait association studies, and genetic mapping in sunflower.

Grain weight, an essential yield component, is under strong genetic control and at the same time markedly influenced by the environment. Genetic analysis of the thousand grain weight (TGW) by genome-wide association study (GWAS) was performed with a panel of 358 European winter wheat (Triticum aestivum L.) varieties and 14 spring wheat varieties using phenotypic data of field tests in eight environments. Wide phenotypic variations were indicated for the TGW with BLUEs (best linear unbiased estimations) values ranging from 35.9 to 58.2 g with a mean value of 45.4 g and a heritability of H(2) = 0.89. A total of 12 candidate genes for plant height, photoperiodism and grain weight were genotyped on all varieties. Only three candidates, the photoperiodism gene Ppd-D1, dwarfing gene Rht-B1and the TaGW-6A gene were significant explaining up to 14.4, 2.3, and 3.4% of phenotypic variation, respectively. For a comprehensive genome-wide analysis of TGW-QTL genotyping data from 732 microsatellite markers and a set of 7769 mapped SNP-markers genotyped with the 90k iSELECT array were analyzed. In total, 342 significant (-log10 (P-value) ≥ 3.0) marker trait associations (MTAs) were detected for SSR-markers and 1195 MTAs (-log10(P-value) ≥ 3.0) for SNP-markers in all single environments plus the BLUEs. After Bonferroni correction, 28 MTAs remained significant for SSR-markers (-log10 (P-value) ≥ 4.82) and 58 MTAs for SNP-markers (-log10 (P-value) ≥ 5.89). Apart from chromosomes 4B and 6B for SSR-markers and chromosomes 4D and 5D for SNP-markers, MTAs were detected on all chromosomes. The highest number of significant SNP-markers was found on chromosomes 3B and 1B, while for the SSRs most markers were significant on chromosomes 6D and 3D. Overall, TGW was determined by many markers with small effects. Only three SNP-markers had R(2) values above 6%.

High-throughput genotyping arrays provide a standardized resource for plant breeding communities that are useful for a breadth of applications including high-density genetic mapping, genome-wide association studies (GWAS), genomic selection (GS), complex trait dissection, and studying patterns of genomic diversity among cultivars and wild accessions. We have developed the CottonSNP63K, an Illumina Infinium array containing assays for 45,104 putative intraspecific single nucleotide polymorphism (SNP) markers for use within the cultivated cotton species Gossypium hirsutum L. and 17,954 putative interspecific SNP markers for use with crosses of other cotton species with G. hirsutum. The SNPs on the array were developed from 13 different discovery sets that represent a diverse range of G. hirsutum germplasm and five other species: G. barbadense L., G. tomentosum Nuttal × Seemann, G. mustelinum Miers × Watt, G. armourianum Kearny, and G. longicalyx J.B. Hutchinson and Lee. The array was validated with 1,156 samples to generate cluster positions to facilitate automated analysis of 38,822 polymorphic markers. Two high-density genetic maps containing a total of 22,829 SNPs were generated for two F2 mapping populations, one intraspecific and one interspecific, and 3,533 SNP markers were co-occurring in both maps. The produced intraspecific genetic map is the first saturated map that associates into 26 linkage groups corresponding to the number of cotton chromosomes for a cross between two G. hirsutum lines. The linkage maps were shown to have high levels of collinearity to the JGI G. raimondii Ulbrich reference genome sequence. The CottonSNP63K array, cluster file and associated marker sequences constitute a major new resource for the global cotton research community., (Copyright © 2015 Hulse-Kemp et al.)

Genome-wide mapping approaches in diverse populations are powerful tools to unravel the genetic architecture of complex traits. The main goals of our study were to investigate the potential and limits to unravel the genetic architecture and to identify the factors determining the accuracy of prediction of the genotypic variation of Fusarium head blight (FHB) resistance in wheat (Triticum aestivum L.) based on data collected with a diverse panel of 372 European varieties. The wheat lines were phenotyped in multi-location field trials for FHB resistance and genotyped with 782 simple sequence repeat (SSR) markers, and 9k and 90k single-nucleotide polymorphism (SNP) arrays. We applied genome-wide association mapping in combination with fivefold cross-validations and observed surprisingly high accuracies of prediction for marker-assisted selection based on the detected quantitative trait loci (QTLs). Using a random sample of markers not selected for marker-trait associations revealed only a slight decrease in prediction accuracy compared with marker-based selection exploiting the QTL information. The same picture was confirmed in a simulation study, suggesting that relatedness is a main driver of the accuracy of prediction in marker-assisted selection of FHB resistance. When the accuracy of prediction of three genomic selection models was contrasted for the three marker data sets, no significant differences in accuracies among marker platforms and genomic selection models were observed. Marker density impacted the accuracy of prediction only marginally. Consequently, genomic selection of FHB resistance can be implemented most cost-efficiently based on low- to medium-density SNP arrays.

The genetic architecture of plant height was investigated in a set of 358 recent European winter wheat varieties plus 14 spring wheat varieties based on field data in eight environments. Genotyping of diagnostic markers revealed the Rht-D1b mutant allele in 58% of the investigated varieties, while the Rht-B1b mutant was only present in 7% of the varieties. Rht-D1 was significantly associated with plant height by using a mixed linear model and employing a kinship matrix to correct for population stratification. Further genotyping data included 732 microsatellite markers, resulting in 770 loci, of which 635 markers were placed on the ITMI map plus a set of 7769 mapped SNP markers genotyped with the 90 k iSELECT chip. When Bonferroni correction was applied, a total of 153 significant marker-trait associations (MTAs) were observed for plant height and the SSR markers (-log10 (P-value) ≥ 4.82) and 280 (-log10 (P-value) ≥ 5.89) for the SNPs. Linear regression between the most effective markers and the BLUEs for plant height indicated additive effects for the MTAs of different chromosomal regions. Analysis of syntenic regions in the rice genome revealed closely linked rice genes related to gibberellin acid (GA) metabolism and perception, i.e. GA20 and GA2 oxidases orthologous to wheat chromosomes 1A, 2A, 3A, 3B, 5B, 5D and 7B, ent-kaurenoic acid oxidase orthologous to wheat chromosome 7A, ent-kaurene synthase on wheat chromosome 2B, as well as GA-receptors like DELLA genes orthologous to wheat chromosomes 4B, 4D and 7A and genes of the GID family orthologous to chromosomes 2B and 5B. The data indicated that besides the widely used GA-insensitive dwarfing genes Rht-B1 and Rht-D1 there is a wide spectrum of loci available that could be used for modulating plant height in variety development.

A genome-wide association study (GWAS) for heading date (HD) was performed with a panel of 358 European winter wheat (Triticum aestivum L.) varieties and 14 spring wheat varieties through the phenotypic evaluation of HD in field tests in eight environments. Genotyping data consisted of 770 mapped microsatellite loci and 7934 mapped SNP markers derived from the 90K iSelect wheat chip. Best linear unbiased estimations (BLUEs) were calculated across all trials and ranged from 142.5 to 159.6 days after the 1st of January with an average value of 151.4 days. Considering only associations with a -log10 (P-value) ≥ 3.0, a total of 340 SSR and 2983 SNP marker-trait associations (MTAs) were detected. After Bonferroni correction for multiple testing, a total of 72 SSR and 438 SNP marker-trait associations remained significant. Highly significant MTAs were detected for the photoperiodism gene Ppd-D1, which was genotyped in all varieties. Consistent associations were found on all chromosomes with the highest number of MTAs on chromosome 5B. Linear regression showed a clear dependence of the HD score BLUEs on the number of favorable alleles (decreasing HD) and unfavorable alleles (increasing HD) per variety meaning that genotypes with a higher number of favorable or a low number of unfavorable alleles showed lower HD and therefore flowered earlier. For the vernalization gene Vrn-A2 co-locating MTAs on chromosome 5A, as well as for the photoperiodism genes Ppd-A1 and Ppd-B1 on chromosomes 2A and 2B were detected. After the construction of an integrated map of the SSR and SNP markers and by exploiting the synteny to sequenced species, such as rice and Brachypodium distachyon, we were able to demonstrate that a marker locus on wheat chromosome 5BL with homology to the rice photoperiodism gene Hd6 played a significant role in the determination of the heading date in wheat.

A total of 358 recent European winter wheat varieties plus 14 spring wheat varieties were evaluated for resistance to Fusarium head blight (FHB) caused by Fusarium graminearum and Fusarium culmorum in four separate environments. The FHB scores based on FHB incidence (Type I resistance)×FHB severity (Type II resistance) indicated a wide phenotypic variation of the varieties with BLUE (best linear unbiased estimation) values ranging from 0.07 to 33.67. Genotyping with 732 microsatellite markers resulted in 782 loci of which 620 were placed on the ITMI map. The resulting average marker distance of 6.8 cM allowed genome wide association mapping employing a mixed model. Though no clear population structure was discovered, a kinship matrix was used for stratification. A total of 794 significant (-log10(p)-value≥3.0) associations between SSR-loci and environment-specific FHB scores or BLUE values were detected, which included 323 SSR alleles. For FHB incidence and FHB severity a total of 861 and 877 individual marker-trait associations (MTA) were detected, respectively. Associations for both traits co-located with FHB score in most cases. Consistent associations detected in three or more environments were found on all chromosomes except chromosome 6B, and with the highest number of MTA on chromosome 5B. The dependence of the number of favourable and unfavourable alleles within a variety to the respective FHB scores indicated an additive effect of favourable and unfavourable alleles, i.e. genotypes with more favourable or less unfavourable alleles tended to show greater resistance to FHB. Assessment of a marker specific for the dwarfing gene Rht-D1 resulted in strong effects. The results provide a prerequisite for designing genome wide breeding strategies for FHB resistance.

Genotyping with large numbers of molecular markers is now an indispensable tool within plant genetics and breeding. Especially through the identification of large numbers of single nucleotide polymorphism (SNP) markers using the novel high-throughput sequencing technologies, it is now possible to reliably identify many thousands of SNPs at many different loci in a given plant genome. For a number of important crop plants, SNP markers are now being used to design genotyping arrays containing thousands of markers spread over the entire genome and to analyse large numbers of samples. In this article, we discuss aspects that should be considered during the design of such large genotyping arrays and the analysis of individuals. The fact that crop plants are also often autopolyploid or allopolyploid is given due consideration. Furthermore, we outline some potential applications of large genotyping arrays including high-density genetic mapping, characterization (fingerprinting) of genetic material and breeding-related aspects such as association studies and genomic selection.

The concurrent development of high-throughput genotyping platforms and next generation sequencing (NGS) has increased the number and density of genetic markers, the efficiency of constructing detailed linkage maps, and our ability to overlay recombination and physical maps of the genome. We developed an array for tomato with 8,784 Single Nucleotide Polymorphisms (SNPs) mainly discovered based on NGS-derived transcriptome sequences. Of the SNPs, 7,720 (88%) passed manufacturing quality control and could be scored in tomato germplasm. The array was used to generate high-density linkage maps for three interspecific F(2) populations: EXPEN 2000 (Solanum lycopersicum LA0925 x S. pennellii LA0716, 79 individuals), EXPEN 2012 (S. lycopersicum Moneymaker x S. pennellii LA0716, 160 individuals), and EXPIM 2012 (S. lycopersicum Moneymaker x S. pimpinellifolium LA0121, 183 individuals). The EXPEN 2000-SNP and EXPEN 2012 maps consisted of 3,503 and 3,687 markers representing 1,076 and 1,229 unique map positions (genetic bins), respectively. The EXPEN 2000-SNP map had an average marker bin interval of 1.6 cM, while the EXPEN 2012 map had an average bin interval of 0.9 cM. The EXPIM 2012 map was constructed with 4,491 markers (1,358 bins) and an average bin interval of 0.8 cM. All three linkage maps revealed an uneven distribution of markers across the genome. The dense EXPEN 2012 and EXPIM 2012 maps showed high levels of colinearity across all 12 chromosomes, and also revealed evidence of small inversions between LA0716 and LA0121. Physical positions of 7,666 SNPs were identified relative to the tomato genome sequence. The genetic and physical positions were mostly consistent. Exceptions were observed for chromosomes 3, 10 and 12. Comparing genetic positions relative to physical positions revealed that genomic regions with high recombination rates were consistent with the known distribution of euchromatin across the 12 chromosomes, while very low recombination rates were observed in the heterochromatic regions.

The effects of selection on genome variation were investigated and visualized in tomato using a high-density single nucleotide polymorphism (SNP) array. 7,720 SNPs were genotyped on a collection of 426 tomato accessions (410 inbreds and 16 hybrids) and over 97% of the markers were polymorphic in the entire collection. Principal component analysis (PCA) and pairwise estimates of F(st) supported that the inbred accessions represented seven sub-populations including processing, large-fruited fresh market, large-fruited vintage, cultivated cherry, landrace, wild cherry, and S. pimpinellifolium. Further divisions were found within both the contemporary processing and fresh market sub-populations. These sub-populations showed higher levels of genetic diversity relative to the vintage sub-population. The array provided a large number of polymorphic SNP markers across each sub-population, ranging from 3,159 in the vintage accessions to 6,234 in the cultivated cherry accessions. Visualization of minor allele frequency revealed regions of the genome that distinguished three representative sub-populations of cultivated tomato (processing, fresh market, and vintage), particularly on chromosomes 2, 4, 5, 6, and 11. The PCA loadings and F(st) outlier analysis between these three sub-populations identified a large number of candidate loci under positive selection on chromosomes 4, 5, and 11. The extent of linkage disequilibrium (LD) was examined within each chromosome for these sub-populations. LD decay varied between chromosomes and sub-populations, with large differences reflective of breeding history. For example, on chromosome 11, decay occurred over 0.8 cM for processing accessions and over 19.7 cM for fresh market accessions. The observed SNP variation and LD decay suggest that different patterns of genetic variation in cultivated tomato are due to introgression from wild species and selection for market specialization.

SNP genotyping arrays have been useful for many applications that require a large number of molecular markers such as high-density genetic mapping, genome-wide association studies (GWAS), and genomic selection. We report the establishment of a large maize SNP array and its use for diversity analysis and high density linkage mapping. The markers, taken from more than 800,000 SNPs, were selected to be preferentially located in genes and evenly distributed across the genome. The array was tested with a set of maize germplasm including North American and European inbred lines, parent/F1 combinations, and distantly related teosinte material. A total of 49,585 markers, including 33,417 within 17,520 different genes and 16,168 outside genes, were of good quality for genotyping, with an average failure rate of 4% and rates up to 8% in specific germplasm. To demonstrate this array's use in genetic mapping and for the independent validation of the B73 sequence assembly, two intermated maize recombinant inbred line populations - IBM (B73×Mo17) and LHRF (F2×F252) - were genotyped to establish two high density linkage maps with 20,913 and 14,524 markers respectively. 172 mapped markers were absent in the current B73 assembly and their placement can be used for future improvements of the B73 reference sequence. Colinearity of the genetic and physical maps was mostly conserved with some exceptions that suggest errors in the B73 assembly. Five major regions containing non-colinearities were identified on chromosomes 2, 3, 6, 7 and 9, and are supported by both independent genetic maps. Four additional non-colinear regions were found on the LHRF map only; they may be due to a lower density of IBM markers in those regions or to true structural rearrangements between lines. Given the array's high quality, it will be a valuable resource for maize genetics and many aspects of maize breeding.

Oilseed rape (Brassica napus) is an allotetraploid species consisting of two genomes, derived from B. rapa (A genome) and B. oleracea (C genome). The presence of these two genomes makes single nucleotide polymorphism (SNP) marker identification and SNP analysis more challenging than in diploid species, as for a given locus usually two versions of a DNA sequence (based on the two ancestral genomes) have to be analyzed simultaneously during SNP identification and analysis. One hundred amplicons derived from expressed sequence tag (ESTs) were analyzed to identify SNPs in a panel of oilseed rape varieties and within two sister species representing the ancestral genomes. A total of 604 SNPs were identified, averaging one SNP in every 42 bp. It was possible to clearly discriminate SNPs that are polymorphic between different plant varieties from SNPs differentiating the two ancestral genomes. To validate the identified SNPs for their use in genetic analysis, we have developed Illumina GoldenGate assays for some of the identified SNPs. Through the analysis of a number of oilseed rape varieties and mapping populations with GoldenGate assays, we were able to identify a number of different segregation patterns in allotetraploid oilseed rape. The majority of the identified SNP markers can be readily used for genetic mapping, showing that amplicon sequencing and Illumina GoldenGate assays can be used to reliably identify SNP markers in tetraploid oilseed rape and to convert them into successful SNP assays that can be used for genetic analysis.

In many plants, single nucleotide polymorphism (SNP) markers are increasingly becoming the marker system of choice. However, for many crop plants there are surprisingly low numbers of validated SNP markers available although they are needed in large numbers for studies regarding genetic variation, linkage mapping, population structure analysis, association genetics, map-based gene isolation, and plant breeding. This review summarizes the current status of SNP marker development technologies for major crop plants. It will also provide an outlook into the future regarding possible SNP identification approaches in crop plants on the basis of current development in model systems such as Arabidopsis which will become available with the full sequencing of more plant genomes, genome resequencing, and in conjunction with the next-generation sequencing technologies.

Hordeum vulgare subsp. spontaneum, the wild progenitor of barley, is a potential source of useful genetic variation for barley breeding programs. The objective of this study was to map quantitative trait loci (QTLs) in an advanced backcross population of barley. A total of 207 BC3 lines were developed using the 2-rowed German spring cultivar Hordeum vulgare subsp. vulgare 'Brenda' as a recurrent parent and the H. vulgare subsp. spontaneum accession HS584 as a donor parent. The lines were genotyped by 108 simple-sequence repeat (SSR) markers and evaluated in field tests for the measurement of grain yield and its components, such as ear length, spikelet number per spike, grain number per spike, spike number, and 1000-grain mass, as well as heading date and plant height. A total of 100 QTLs were detected. Ten QTLs with increasing effects were found for ear length, spikelet number, and grain number per spike. Three QTLs contributed by HS584 were found to significantly decrease days to heading across all years at 2 locations. In addition, 2 QTLs from HS584 on chromosomes 2H and 3H were associated with resistance to leaf rust. Based on genotypic data obtained from this population, 55 introgression lines carrying 1 or 2 donor segments were selected to develop a set of doubled-haploid lines, which will be used to reconfirm and investigate the effects of 100 QTLs for future genetic studies.

Background: The goal of our study was a systematic survey of the molecular diversity in barley genetic resources. To this end 953 cultivated barley accessions originating from all inhabited continents except Australia were genotyped with 48 SSR markers. Molecular diversity was evaluated with routine statistics (allelic richness, gene diversity, allele frequency, heterozygosity and unique alleles), Principal Coordinate Analysis (PCoA), and analysis of genome-wide linkage disequilibrium., Results: A genotyping database for 953 cultivated barley accessions profiled with 48 SSR markers was established. The PCoA revealed structuring of the barley population with regard to (i) geographical regions and (ii) agronomic traits. Geographic origin contributed most to the observed molecular diversity. Genome-wide linkage disequilibrium (LD) was estimated as squared correlation of allele frequencies (r2). The values of LD for barley were comparable to other plant species (conifers, poplar, maize). The pattern of intrachromosomal LD with distances between the genomic loci ranging from 1 to 150 cM revealed that in barley LD extended up to distances as long as 50 cM with r2 > 0.05, or up to 10 cM with r2 > 0.2. Few loci mapping to different chromosomes showed significant LD with r2 > 0.05. The number of loci in significant LD as well as the pattern of LD were clearly dependent on the population structure. The LD in the homogenous group of 207 European 2-rowed spring barleys compared to the highly structured worldwide barley population was increased in the number of loci pairs with r2 > 0.05 and had higher values of r2, although the percentage of intrachromosomal loci pairs in significant LD based on P < 0.001 was 100% in the whole set of varieties, but only 45% in the subgroup of European 2-rowed spring barleys. The value of LD also varied depending on the polymorphism of the loci selected for genotyping. The 17 most polymorphic loci (PIC > 0.80) provided higher LD values as compared to 19 low polymorphic loci (PIC < 0.73) in both structured (all accessions) and non-structured (European 2-rowed spring varieties) barley populations., Conclusion: A global population of cultivated barley accessions was highly structured. Clustering highlighted the accessions with the same geographic origin, as well as accessions possessing similar agronomic characters. LD in barley extended up to 50 cM, and was strongly dependent on the population structure. The data on LD were summarized as a genome-wide LD map for barley.

Advanced backcross (AB)-quantitative trait locus (QTL) analysis has been successfully applied for detecting and transferring QTLs from unadapted germplasm into elite breeding lines in various plant species. Here, we describe the application of a modified AB breeding scheme to spring barley. A BC3-doubled haploid (DH) population consisting of 181 lines derived from the German spring barley cultivar 'Brenda' (Hordeum vulgare subsp. vulgare) as the recurrent parent and the wild species line 'HS213' (H. vulgare subsp. spontaneum) as the donor line was evaluated for yield and its components as well as malting quality traits. A set of 60 microsatellite markers was used to genotype the population, and phenotypic data were collected at two locations in Germany in continuous years. Altogether, 25 significant QTLs were detected by single-marker regression analysis and interval mapping. Most positive QTLs originated from the recurrent parent 'Brenda'. A QTL, Qhd2.1, on chromosome 2HS from 'Brenda' explained 18.3% and 20.7% of the phenotypic variation for yield and heading date, respectively. Due to the small percentage of donor-parent genome of 6.25%, the BC3-DH lines could be directly used for the extraction of near-isogenic lines (NILs) for Qhd2.1. Consequently, it was possible to determine the precise location of the locus hd2.1 within a region of 6.5 cM, using an F2 population consisting of 234 individuals developed from a cross between an NIL containing a defined donor segment at this locus and 'Brenda'. The location of this QTL was consistent with the presence of a major photoperiod response gene, Ppd-H1, previously reported in this region, which is associated with pleiotropic effects on yield components. In summary, the analysis of a BC3-DH population in barley provides a compromise between the analysis of QTLs by means of an AB scheme and the generation of defined substitution lines. Several lines carrying defined different donor segments for only one single chromosome or trait in the genetic background of 'Brenda' could be selected for further genetic studies.

We report here the second advanced backcross quantitative trait locus (AB-QTL) analysis carried out in winter wheat. Seven agronomic traits were studied in a BC2F1 population derived from a cross between the German winter wheat variety Flair and the synthetic wheat line XX86 developed in Japan. We selected 111 BC2F1 lines and genotyped these with 197 microsatellite markers. Field data for seven agronomic traits were collected from corresponding BC2F3 families that were grown at up to six locations in Germany. QTL analyses for yield and yield components were performed using single-marker regression and interval mapping. A total of 57 putative QTLs derived from XX86 were detected, of which 24 (42.1%) were found to have a positive effect from the synthetic wheat XX86. These favourable QQTLs were mainly associated with thousand-grain weight and grain weight per ear. Many QTLs for correlated traits were mapped in similar chromosomal regions. The AB-QTL data obtained in the present study are discussed and compared with results from previous QTL analyses.

To enhance the marker density of existing genetic maps of barley ( Hordeum vulgare L.), a new set of microsatellite markers containing dinucleotide motifs was developed from genomic clones. Out of 254 primer pairs tested, a total of 167 primer pairs were classifed as functional in a panel of six barley cultivars and three H. spontaneum accessions, and of those, 127 primer pairs resulting in 133 loci were either mapped or located onto chromosomes. The polymorphism information content (PIC) ranged from 0.05 to 0.94 with an average of 0.60. The number of alleles per locus varied from 1 to 9. On average, 3.9 alleles per primer pair were observed. The RFLP frameworks of two previously published linkage maps were used to locate a total of 115 new microsatellite loci on at least one mapping population. The chromosomal assignment of 48 mapped loci was corroborated on a set of wheat-barley chromosome addition lines; 18 additional loci which were not polymorphic in the mapping populations were assigned to chromosomes by this method. The microsatellites were located on all seven linkage groups with four significant clusters in the centromeric regions of 2H, 3H, 6H and 7H. These newly developed microsatellites improve the density of existing barley microsatellite maps and can be used in genetic studies and breeding research.

Genetic analysis of the wound response pathway in tomato indicates that systemin and its precursor protein, prosystemin, are upstream components of a defensive signaling cascade that involves the synthesis and subsequent action of the octadecatrienoic acid (18:3)-derived plant hormone jasmonic acid (JA). The suppressor of prosystemin-mediated responses2 (spr2) mutation, which was isolated previously as a suppressor of (pro)systemin-mediated signaling, impairs wound-induced JA biosynthesis and the production of a long-distance signal for the expression of defensive Proteinase inhibitor genes. Using a map-based cloning approach, we demonstrate here that Spr2 encodes a chloroplast fatty acid desaturase involved in JA biosynthesis. Loss of Spr2 function reduced the 18:3 content of leaves to <10% of wild-type levels, abolished the accumulation of hexadecatrienoic acid, and caused a corresponding increase in the level of dienoic fatty acids. The effect of spr2 on the fatty acyl content of various classes of glycerolipids indicated that the Spr2 gene product catalyzes most, if not all, omega3 fatty acid desaturation within the "prokaryotic pathway" for lipid synthesis in tomato leaves. Despite the reduced levels of trienoic fatty acids, spr2 plants exhibited normal growth, development, and reproduction. However, the mutant was compromised in defense against attack by tobacco hornworm larvae. These results indicate that jasmonate synthesis from chloroplast pools of 18:3 is required for wound- and systemin-induced defense responses and support a role for systemin in the production of a transmissible signal that is derived from the octadecanoid pathway.

Advanced backcross QTL (AB-QTL) analysis was used to identify quantitative trait loci (QTLs) for yield and yield components in a BC(2)F(2) population derived from a cross between the German winter wheat variety 'Prinz' and the synthetic wheat line W-7984 developed by CIMMYT. Two hundred and ten microsatellite markers were employed to genotype 72 pre-selected BC(2)F(2) plants and phenotypic data were collected for five agronomic traits from corresponding BC(2)F(3) families that were grown at four locations in Germany. Using single-marker regression and interval mapping, a total of 40 putative QTLs derived from W-7984 were detected, of which 11 were for yield, 16 for yield components, eight for ear emergence time and five for plant height. For 24 (60.0%) of them, alleles from the synthetic wheat W-7984 were associated with a positive effect on agronomic traits, despite the fact that synthetic wheat was overall inferior with respect to agronomic appearance and performance. The present study indicated that favorable QTL alleles could be transferred from wild relatives of wheat into an elite wheat variety for improvement of quantitative trait loci like yield by the advanced backcross QTL strategy and molecular breeding. To our knowledge, the results presented here were the first report on AB-QTL analysis in wheat.

A database of 502 recent European wheat varieties, mainly of winter type, was constructed using 19 wheat microsatellites and one secalin-specific marker. All datapoints were generated in at least two laboratories using different techniques for fragment analysis. An overall level of >99.5% accuracy was achieved. The 199 alleles detected allowed discrimination between all of the varieties except duplicates, and varieties derived from identical parents. Approximately 25% of the varieties showed some heterogeneities, with the highest level of heterogeneity in south-eastern European material. The highest genetic diversity and the highest number of rare alleles were found in varieties from southern Europe. The relative allele frequencies varied for most microsatellites in different geographical regions.

The Hero gene of tomato is a broad spectrum resistance gene that confers a high level of resistance to all pathotypes of the potato cyst nematodes Globodera rostochiensis and partial resistance to G. pallida. The gene was identified by map-based cloning, sequencing and complementation analysis of two susceptible tomato lines with an array of 13 overlapping cosmids spanning a total distance of 135 kb. Hero encodes a protein with a nucleotide-binding site (NBS) and a leucine-rich-repeat (LRR) domain and is a member of a gene family of 14 highly homologous genes, which are clustered within a continuous 118-kb region. The isolated Hero gene displayed resistance to various G. rostochiensis pathotypes and partial resistance to G. pallida pathotype Pa2/3 in transgenic tomato lines. None of the Hero homologues conferred resistance to G. rostochiensis pathotypes. Hero can be distinguished from its homologues by the length of a compound hexanucleotide microsatellite, which codes for a charged and repetitive amino acid domain within the LRR. We propose that the expansion of this microsatellite may be involved in the evolution of the Hero resistance gene.

Previously isolated tomato ( Lycopersicon esculentum) microsatellite markers were mainly clustered in the centromeric heterochromatin and not located in euchromatic regions. To achieve a more-uniform distribution of microsatellite markers for genome mapping purposes, a set of tomato microsatellite markers containing dinucleotide simple sequence repeats were developed by screening genomic libraries enriched for single-copy sequences, and screening the tomato EST database. The tomato microsatellites isolated in these ways were characterized by combinations of different types of repeated motifs and they were polymorphic in a set of L. esculentum varieties detecting up to four alleles. A total of 20 markers were placed on the genetic map of tomato. Interestingly, all markers isolated from genomic libraries enriched for single-copy sequences by PstI-pre-digestion mapped into the centromeric regions. The majority of markers derived from EST sequences contained predominantly AT microsatellites and were located in euchromatic regions.

The Rh2 resistance gene of barley (Hordeum vulgare) confers resistance against the scald pathogen (Rhynchosporium secalis). A high-resolution genetic map of the Rh2 region on chromosome I (7H) was established by the use of molecular markers. Tightly linked markers from this region were used to screen existing and a newly constructed yeast artificial chromosome (YAC) library of barley cv. Franka composed of 45,000 clones representing approximately two genome equivalents. Corresponding YAC clones were identified for most markers, indicating that the combined YAC library has good representation of the barley genome. The contiguous sets of YAC clones with the most tightly linked molecular markers represent entry points for map-based cloning of this resistance gene.

The potential of Aegilops tauschii, the diploid progenitor of the D genome of wheat, as a source of microsatellite markers for hexaploid bread wheat was investigated. By screening lambda phage and plasmid libraries of Ae. tauschii genomic DNA, dinucleotide microsatellites containing GA and GT motifs were isolated and a total of 65 functional microsatellite markers were developed. All primer pairs that were functional in Ae. tauschii amplified well in hexaploid wheat. Fifty-five loci amplified by 48 primer sets were placed onto a genetic framework map of the reference population of the International Triticeae Mapping Initiative (ITMI) 'Opata 85' x 'W7984'. The majority of microsatellite markers could be assigned to the chromosomes of the D genome of wheat. The distribution of the markers along the chromosomes is random. Chromosomal location of 22 loci nonpolymorphic in the reference population was determined using nullitetrasomic lines of Triticum aestivum 'Chinese Spring'. The results of this study demonstrate the value of microsatellite markers isolated from Ae. tauschii for the study of bread wheat. The microsatellite markers developed improve the existing wheat microsatellite map and can be used in a wide range of genetic studies and breeding programs.

The uptake of iron in plants is a highly regulated process that is induced on iron starvation. In tomato, the mutant chloronerva exhibits constitutive expression of iron uptake responses and intercostal chlorosis. Biochemically, chloronerva is an auxotroph for nicotianamine, a key polyamine in plant iron uptake metabolism. The chloronerva gene has been fine-mapped onto the long arm of chromosome 1 in a large segregating tomato population and yeast artificial chromosome clones encompassing the region were isolated by using flanking markers. A cosmid contig containing the chloronerva gene was established, and complementing cosmids were identified by transformation into the mutant. The chloronerva transcript was identified by cDNA isolation using the complementing cosmids. The gene encodes a unique protein of 35 kDa. The mutant harbors a single base change compared with the wild type. Based on enzyme activity and sequence similarity to the coding DNA sequence of the purified barley enzyme the chloronerva gene encodes the enzyme nicotianamine synthase.

Microsatellites as genetic markers are used in many crop plants. Major criteria for their usability as molecular markers include that they are highly polymorphic and evenly spread throughout a genome. In tomato, it has been reported that long arrays of tetranucleotide microsatellites containing the motif GATA are highly clustered around the centromeres of all chromosomes. In this study, we have isolated tomato microsatellites containing long arrays (> 20 repeats) of the dinucleotide motifs GA, GT, AT, as well as GATA, assessed their variability within Lycopersicon esculentum varieties and mapped them onto a genetic map of tomato. The investigated microsatellite markers exhibited between 1 and 5 alleles in a diverse set of L. esculentum lines. Mapping of the microsatellites onto the genetic map of tomato demonstrates that, as previously shown, GATA microsatellites are highly clustered in the regions of the tomato centromeres. Interestingly, the same centromeric location was now found for long dinucleotide microsatellite markers. Because of this uneven distribution, genetic mapping of the entire tomato genome using long dinucleotide microsatellites will be very difficult to achieve and microsatellite markers with shorter arrays of microsatellites could be more suitable for mapping experiments albeit their lower level of polymorphism. Some microsatellite markers described in this study might provide a useful tool to study the molecular structure of tomato centromeric regions and for variety identification.

Hexaploid bread wheat (Triticum aestivum L. em. Thell) is one of the world's most important crop plants and displays a very low level of intraspecific polymorphism. We report the development of highly polymorphic microsatellite markers using procedures optimized for the large wheat genome. The isolation of microsatellite-containing clones from hypomethylated regions of the wheat genome increased the proportion of useful markers almost twofold. The majority (80%) of primer sets developed are genome-specific and detect only a single locus in one of the three genomes of bread wheat (A, B, or D). Only 20% of the markers detect more than one locus. A total of 279 loci amplified by 230 primer sets were placed onto a genetic framework map composed of RFLPs previously mapped in the reference population of the International Triticeae Mapping Initiative (ITMI) Opata 85 x W7984. Sixty-five microsatellites were mapped at a LOD >2.5, and 214 microsatellites were assigned to the most likely intervals. Ninety-three loci were mapped to the A genome, 115 to the B genome, and 71 to the D genome. The markers are randomly distributed along the linkage map, with clustering in several centromeric regions.