Application of Population Sequencing (POPSEQ) for Ordering and Imputing Genotyping-by-Sequencing Markers in Hexaploid Wheat

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

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

Genotyping-by-Sequencing Based Molecular Genetic Diversity of Pakistani Bread Wheat (Triticum aestivum L.) Accessions

Spring wheat (Triticum aestivum L.) is one of the most imperative staple food crops, with an annual production of 765 million tons globally to feed ∼40% world population. Genetic diversity in available germplasm is crucial for sustainable wheat improvement to ensure global food security. A diversity panel of 184 Pakistani wheat accessions was genotyped using 123,596 high-quality single nucleotide polymorphism (SNP) markers generated by genotyping-by-sequencing with 42% of the SNPs mapped on B, 36% on A, and 22% on D sub-genomes of wheat. Chromosome 2B contains the most SNPs (9,126), whereas 4D has the least (2,660) markers. The mean polymorphic information content, genetic diversity, and major allele frequency of the population were 0.157, 0.1844, and 0.87, respectively. Analysis of molecular variance revealed a higher genetic diversity (80%) within the sub-population than among the sub-populations (20%). The genome-wide linkage disequilibrium was 0.34 Mbp for the whole wheat genome. Among the three subgenomes, A has the highest LD decay value (0.29 Mbp), followed by B (0.2 Mbp) and D (0.07 Mbp) genomes, respectively. The results of population structure, principal coordinate analysis, phylogenetic tree, and kinship analysis also divided the whole population into three clusters comprising 31, 33, and 120 accessions in group 1, group 2, and group 3, respectively. All groups were dominated by the local wheat accessions. Estimation of genetic diversity will be a baseline for the selection of breeding parents for mutations and the genome-wide association and marker-assisted selection studies.

Drought-Tolerance QTLs Associated with Grain Yield and Related Traits in Spring Bread Wheat

The present research aims to identify the efficient combination of drought-tolerance selection criteria and associated quantitative trait loci. A panel of 197 bread wheat genotypes was evaluated for yield- and drought-tolerance-related traits in two environments (favorable and semiarid) for 2 years (2015-2016). Grain number, biomass, number of fertile spikes per plant and ground cover exhibited a significant correlation with grain yield and constitute potential secondary selection criteria for yield under drought conditions. About 73 significant marker-trait associations were detected along various chromosomal positions. The markers "wsnp_Ex_Rep_c67786_66472676" and "ExcalibuR_c24593_1217" exhibited important genetic gains associated with yield increase under drought (11 and 7%, respectively). The markers "KukRi_c94792_127" and "wsnp_Ex_c298_580660" showed a significant correlation with grain yield, biomass and grain number and were associated with a significant increase in yield performance at the semiarid site (+6 and +7%, respectively). The ground cover was found associated with grain yield and biomass through the markers "wsnp_Ex_Rep_c67786_66472676" (+11%) and "KukRi_c49927_151" (+10%). One marker "TduRuM_contig25432_1377" on chromosome 5B at 20 cM was consistently correlated with the number of fertile spikes across both environments. Further research should be considered to validate the efficiency of these markers to undertake selection for drought tolerance under various environments and genetic backgrounds.

Identification of Quantitative Trait Loci for Leaf Rust and Stem Rust Seedling Resistance in Bread Wheat Using a Genome-Wide Association Study

In recent years, leaf rust (LR) and stem rust (SR) have become a serious threat to bread wheat production in Kazakhstan. Most local cultivars are susceptible to these rusts, which has affected their yield and quality. The development of new cultivars with high productivity and LR and SR disease resistance, including using marker-assisted selection, is becoming an important priority in local breeding projects. Therefore, the search for key genetic factors controlling resistance in all plant stages, including the seedling stage, is of great significance. In this work, we applied a genome-wide association study (GWAS) approach using 212 local bread wheat accessions that were phenotyped for resistance to specific races of Puccinia triticina Eriks. (Pt) and Puccinia graminis f. sp. tritici (Pgt) at the seedling stages. The collection was genotyped using a 20 K Illumina iSelect SNP assay, and 11,150 polymorphic SNP markers were selected for the association mapping. Using a mixed linear model, we identified 11 quantitative trait loci (QTLs) for five out of six specific races of Pt and Pgt. The comparison of the results from this GWAS with those from previously published work showed that nine out of eleven QTLs for LR and SR resistance had been previously reported in a GWAS study at the adult plant stages of wheat growth. Therefore, it was assumed that these nine common identified QTLs were effective for all-stage resistance to LR and SR, and the two other QTLs appear to be novel QTLs. In addition, five out of these nine QTLs that had been identified earlier were found to be associated with yield components, suggesting that they may directly influence the field performance of bread wheat. The identified QTLs, including novel QTLs found in this study, may play an essential role in the breeding process for improving wheat resistance to LR and SR.

Genome-Wide Association Study Reveals Novel Genetic Loci for Quantitative Resistance to Septoria Tritici Blotch in Wheat (Triticum aestivum L.)

Septoria tritici blotch, caused by the fungus Zymoseptoria titici, poses serious and persistent challenges to wheat cultivation in Ethiopia and worldwide. Deploying resistant cultivars is a major component of controlling septoria tritici blotch (STB). Thus, the objective of this study was to elucidate the genomic architecture of STB resistance in an association panel of 178 bread wheat genotypes. The association panel was phenotyped for STB resistance, phenology, yield, and yield-related traits in three locations for 2 years. The panel was also genotyped for single nucleotide polymorphism (SNP) markers using the genotyping-by-sequencing (GBS) method, and a total of 7,776 polymorphic SNPs were used in the subsequent analyses. Marker-trait associations were also computed using a genome association and prediction integrated tool (GAPIT). The study then found that the broad-sense heritability for STB resistance ranged from 0.58 to 0.97 and 0.72 to 0.81 at the individual and across-environment levels, respectively, indicating the presence of STB resistance alleles in the association panel. Population structure and principal component analyses detected two sub-groups with greater degrees of admixture. A linkage disequilibrium (LD) analysis in 338,125 marker pairs also detected the existence of significant (p ≤ 0.01) linkage in 27.6% of the marker pairs. Specifically, in all chromosomes, the LD between SNPs declined within 2.26-105.62 Mbp, with an overall mean of 31.44 Mbp. Furthermore, the association analysis identified 53 loci that were significantly (false discovery rate, FDR, <0.05) associated with STB resistance, further pointing to 33 putative quantitative trait loci (QTLs). Most of these shared similar chromosomes with already published Septoria resistance genes, which were distributed across chromosomes 1B, 1D, 2A, 2B, 2D, 3A,3 B, 3D, 4A, 5A, 5B, 6A, 7A, 7B, and 7D. However, five of the putative QTLs identified on chromosomes 1A, 5D, and 6B appeared to be novel. Dissecting the detected loci on IWGSC RefSeq Annotation v2.1 revealed the existence of disease resistance-associated genes in the identified QTL regions that are involved in plant defense responses. These putative QTLs explained 2.7-13.2% of the total phenotypic variation. Seven of the QTLs (R ² = 2.7-10.8%) for STB resistance also co-localized with marker-trait associations (MTAs) for agronomic traits. Overall, this analysis reported on putative QTLs for adult plant resistance to STB and some important agronomic traits. The reported and novel QTLs have been identified previously, indicating the potential to improve STB resistance by pyramiding QTLs by marker-assisted selection.

Dissection of the genetic basis of genotype-by-environment interactions for grain yield and main agronomic traits in Iranian bread wheat landraces and cultivars

Understanding the genetic basis of performance stability is essential to maintain productivity, especially under severe conditions. In the present study, 268 Iranian bread wheat landraces and cultivars were evaluated in four well-watered and two rain-fed conditions for different traits. According to breeding programs, cultivars were in a group with a high mean and stability in terms of GY, GN, and SW traits, while in terms of PH, they had a low mean and high stability. The stability of cultivars and landraces was related to dynamic and static stability, respectively. The highest number of marker pairs and lowest LD decay distance in both cultivars and landraces was observed on the B genome. Population structure differentiated indigenous cultivars and landraces, and the GWAS results for each were almost different despite the commonalities. Chromosomes 1B, 3B, 7B, 2A, and 4A had markers with pleiotropic effects on the stability of different traits. Due to two rain-fed environments, the Gene Ontology (GO) confirmed the accuracy of the results. The identified markers in this study can be helpful in breeding high-performance and stable genotypes and future breeding programs such as fine mapping and cloning.

Elucidating SNP-based genetic diversity and population structure of advanced breeding lines of bread wheat (Triticum aestivum L.)

Genetic diversity and population structure information are crucial for enhancing traits of interest and the development of superlative varieties for commercialization. The present study elucidated the population structure and genetic diversity of 141 advanced wheat breeding lines using single nucleotide polymorphism markers. A total of 14,563 high-quality identified genotyping-by-sequencing (GBS) markers were distributed covering 13.9 GB wheat genome, with a minimum of 1,026 SNPs on the homoeologous group four and a maximum of 2,838 SNPs on group seven. The average minor allele frequency was found 0.233, although the average polymorphism information content (PIC) and heterozygosity were 0.201 and 0.015, respectively. Principal component analyses (PCA) and population structure identified two major groups (sub-populations) based on SNPs information. The results indicated a substantial gene flow/exchange with many migrants (Nm = 86.428) and a considerable genetic diversity (number of different alleles, Na = 1.977; the number of effective alleles, Ne = 1.519; and Shannon's information index, I = 0.477) within the population, illustrating a good source for wheat improvement. The average PIC of 0.201 demonstrates moderate genetic diversity of the present evaluated advanced breeding panel. Analysis of molecular variance (AMOVA) detected 1% and 99% variance between and within subgroups. It is indicative of excessive gene traffic (less genetic differentiation) among the populations. These conclusions deliver important information with the potential to contribute new beneficial alleles using genome-wide association studies (GWAS) and marker-assisted selection to enhance genetic gain in South Asian wheat breeding programs.

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

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

Genetic Diversity and Population Structure of Asian and European Common Wheat Accessions Based on Genotyping-By-Sequencing

Obtaining information on the genetic diversity and population structure of germplasm facilitates its use in wheat breeding programs. Recently, with the development of next-generation sequencing technology, genotyping-by-sequencing (GBS) has been used as a high-throughput and cost-effective molecular tool for examination of the genetic diversity of wheat breeding lines. In this study, GBS was used to characterize a population of 180 accessions of common wheat originating from Asia and Europe between the latitudes 30° and 45°N. In total, 24,767 high-quality single-nucleotide polymorphism (SNP) markers were used for analysis of genetic diversity and population structure. The B genome contained the highest number of SNPs, followed by the A and D genomes. The polymorphism information content was in the range of 0.1 to 0.4, with a mean of 0.26. The distribution of SNPs markers on the 21 chromosomes ranged from 243 on chromosome 4D to 2,337 on chromosome 3B. Structure and cluster analyses divided the panel of accessions into two subgroups (G1 and G2). G1 principally consisted of European and partial Asian accessions, and G2 comprised mainly accessions from the Middle East and partial Asia. Molecular analysis of variance showed that the genetic variation was greater within groups (99%) than between groups (1%). Comparison of the two subgroups indicated that G1 and G2 contained a high level of genetic diversity. The genetic diversity of G2 was slightly higher as indicated by the observed heterozygosity (H o) = 0.23, and unbiased diversity index (uh) = 0.34. The present results will not only help breeders to understand the genetic diversity of wheat germplasm on the Eurasian continent between the latitudes of 30° and 45°N, but also provide valuable information for wheat genetic improvement through introgression of novel genetic variation in this region.

Genome-wide association mapping for resistance to leaf, stem, and yellow rusts of common wheat under field conditions of South Kazakhstan

Common or bread wheat (Triticum aestivum L.) is the most important cereal crop in the world, including Kazakhstan, where it is a major agricultural commodity. Fungal pathogens producing leaf, stem, and yellow (stripe) rusts of wheat may cause yield losses of up to 50-60%. One of the most effective methods for preventing these losses is to develop resistant cultivars with high yield potential. This goal can be achieved using complex breeding studies, including the identification of key genetic factors controlling rust disease resistance. In this study, a panel consisting of 215 common wheat cultivars and breeding lines from Kazakhstan, Russia, Europe, USA, Canada, Mexico, and Australia, with a wide range of resistance to leaf rust (LR), stem rust (SR), and yellow rust (YR) diseases, was analyzed under field conditions in Southern Kazakhstan. The collection was genotyped using the 20K Illumina iSelect DNA array, where 11,510 informative single-nucleotide polymorphism markers were selected for further genome-wide association study (GWAS). Evaluation of the phenotypic diversity over 2 years showed a mostly mixed reaction to LR, mixed reaction/moderate susceptibility to SR, and moderate resistance to YR among wheat accessions from Kazakhstan. GWAS revealed 45 marker-trait associations (MTAs), including 23 for LR, 14 for SR, and eight for YR resistances. Three MTAs for LR resistance and one for SR resistance appeared to be novel. The MTAs identified in this work can be used for marker-assisted selection of common wheat in Kazakhstan in breeding new cultivars resistant to LR, SR, and YR diseases. These findings can be helpful for pyramiding genes with favorable alleles in promising cultivars and lines.

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

BACKGROUND

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

RESULTS

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

CONCLUSIONS

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

Population-dependent reproducible deviation from natural bread wheat genome in synthetic hexaploid wheat

Sequence elimination is one of the main mechanisms that increases the divergence among homoeologous chromosomes after allopolyploidization to enhance the stability of recently established lineages, but it can cause a loss of some economically important genes. Synthetic hexaploid wheat (SHW) is an important source of genetic variation to the natural hexaploid wheat (NHW) genepool that has low genetic diversity. Here, we investigated the change between SHW and NHW genomes by utilizing a large germplasm set of primary synthetics and synthetic derivatives. Reproducible segment elimination (RSE) was declared if a large chromosomal chunk (>5 cM) produced no aligned reads in more than five SHWs. RSE in five genomic regions was the major source of variation between SHW and NHW. One RSE eliminated almost the complete short arm of chromosome 1B, which contains major genes for flour quality, disease resistance and different enzymes. The occurrence of RSE was highly dependent on the choice of diploid and tetraploid parental lines, their ancestral subpopulation and admixture, e.g. SHWs derived from Triticum dicoccon or from one of two Aegilops tauschii subpopulations were almost free of RSE, while highly admixed parents had higher RSE rates. The rate of RSE in synthetic derivatives was almost double that in primary synthetics. Genome-wide association analysis detected four loci with minor effects on the occurrence of RSE, indicating that both parental lines and genetic factors were affecting the occurrence of RSE. Therefore, pre-pre-breeding strategies should be applied before introducing SHW into pre-breeding programs to ensure genomic stability and avoid undesirable gene loss.

Dense genotyping-by-sequencing linkage maps of two Synthetic W7984×Opata reference populations provide insights into wheat structural diversity

Wheat (Triticum aestivum) genetic maps are a key enabling tool for genetic studies. We used genotyping-by-sequencing-(GBS) derived markers to map recombinant inbred line (RIL) and doubled haploid (DH) populations from crosses of W7984 by Opata, and used the maps to explore features of recombination control. The RIL and DH populations, SynOpRIL and SynOpDH, were composed of 906 and 92 individuals, respectively. Two high-density genetic linkage framework maps were constructed of 2,842 and 2,961 cM, harboring 3,634 and 6,580 markers, respectively. Using imputation, we added 43,013 and 86,042 markers to the SynOpRIL and SynOpDH maps. We observed preferential recombination in telomeric regions and reduced recombination in pericentromeric regions. Recombination rates varied between subgenomes, with the D genomes of the two populations exhibiting the highest recombination rates of 0.26-0.27 cM/Mb. QTL mapping identified two additive and three epistatic loci associated with crossover number. Additionally, we used published POPSEQ data from SynOpDH to explore the structural variation in W7984 and Opata. We found that chromosome 5AS is missing from W7984. We also found 2,332 variations larger than 100 kb. Structural variants were more abundant in distal regions, and overlapped 9,196 genes. The two maps provide a resource for trait mapping and genomic-assisted breeding.

Genome-Wide Association Mapping of Grain Micronutrients Concentration in Aegilops tauschii

Bread wheat is an important and the most consumed cereal worldwide. However, people with predominantly cereal-based diets are increasingly affected by micronutrient deficiencies, suggesting the need for biofortified wheat varieties. The limited genetic diversity in hexaploid wheat warrants exploring the wider variation present in wheat wild relatives, among these Aegilops tauschii, the wild progenitor of the bread wheat D genome. In this study, a panel of 167 Ae. tauschii accessions was phenotyped for grain Fe, Zn, Cu, and Mn concentrations for 3 years and was found to have wide variation for these micronutrients. Comparisons between the two genetic subpopulations of Ae. tauschii revealed that lineage 2 had higher mean values for Fe and Cu concentration than lineage 1. To identify potentially new genetic sources for improving grain micronutrient concentration, we performed a genome-wide association study (GWAS) on 114 non-redundant Ae. tauschii accessions using 5,249 genotyping-by-sequencing (GBS) markers. Best linear unbiased predictor (BLUP) values were calculated for all traits across the three growing seasons. A total of 19 SNP marker trait associations (MTAs) were detected for all traits after applying Bonferroni corrected threshold of -log10(P-value) ≥ 4.68. These MTAs were found on all seven chromosomes. For grain Fe, Zn, Cu, and Mn concentrations, five, four, three, and seven significant associations were detected, respectively. The associations were linked to the genes encoding transcription factor regulators, transporters, and phytosiderophore synthesis. The results demonstrate the utility of GWAS for understanding the genetic architecture of micronutrient accumulation in Ae. tauschii, and further efforts to validate these loci will aid in using them to diversify the D-genome of hexaploid wheat.

Imputation accuracy of wheat genotyping-by-sequencing (GBS) data using barley and wheat genome references

Genotyping-by-sequencing (GBS) provides high SNP coverage and has recently emerged as a popular technology for genetic and breeding applications in bread wheat (Triticum aestivum L.) and many other plant species. Although GBS can discover millions of SNPs, a high rate of missing data is a major concern for many applications. Accurate imputation of those missing data can significantly improve the utility of GBS data. This study compared imputation accuracies among four genome references including three wheat references (Chinese Spring survey sequence, W7984, and IWGSC RefSeq v1.0) and one barley reference genome by comparing imputed data derived from low-depth sequencing to actual data from high-depth sequencing. After imputation, the average number of imputed data points was the highest in the B genome (~48.99%). The D genome had the lowest imputed data points (~15.02%) but the highest imputation accuracy. Among the four reference genomes, IWGSC RefSeq v1.0 reference provided the most imputed data points, but the lowest imputation accuracy for the SNPs with < 10% minor allele frequency (MAF). The W7984 reference, however, provided the highest imputation accuracy for the SNPs with < 10% MAF.

Tools for Genetic Studies in Experimental Populations of Polyploids

Polyploid organisms carry more than two copies of each chromosome, a condition rarely tolerated in animals but which occurs relatively frequently in the plant kingdom. One of the principal challenges faced by polyploid organisms is to evolve stable meiotic mechanisms to faithfully transmit genetic information to the next generation upon which the study of inheritance is based. In this review we look at the tools available to the research community to better understand polyploid inheritance, many of which have only recently been developed. Most of these tools are intended for experimental populations (rather than natural populations), facilitating genomics-assisted crop improvement and plant breeding. This is hardly surprising given that a large proportion of domesticated plant species are polyploid. We focus on three main areas: (1) polyploid genotyping; (2) genetic and physical mapping; and (3) quantitative trait analysis and genomic selection. We also briefly review some miscellaneous topics such as the mode of inheritance and the availability of polyploid simulation software. The current polyploid analytic toolbox includes software for assigning marker genotypes (and in particular, estimating the dosage of marker alleles in the heterozygous condition), establishing chromosome-scale linkage phase among marker alleles, constructing (short-range) haplotypes, generating linkage maps, performing genome-wide association studies (GWAS) and quantitative trait locus (QTL) analyses, and simulating polyploid populations. These tools can also help elucidate the mode of inheritance (disomic, polysomic or a mixture of both as in segmental allopolyploids) or reveal whether double reduction and multivalent chromosomal pairing occur. An increasing number of polyploids (or associated diploids) are being sequenced, leading to publicly available reference genome assemblies. Much work remains in order to keep pace with developments in genomic technologies. However, such technologies also offer the promise of understanding polyploid genomes at a level which hitherto has remained elusive.

Conversion of array-based single nucleotide polymorphic markers for use in targeted genotyping by sequencing in hexaploid wheat (Triticum aestivum)

Wheat breeders and academics alike use single nucleotide polymorphisms (SNPs) as molecular markers to characterize regions of interest within the hexaploid wheat genome. A number of SNP-based genotyping platforms are available, and their utility depends upon factors such as the available technologies, number of data points required, budgets and the technical expertise required. Unfortunately, markers can rarely be exchanged between existing and newly developed platforms, meaning that previously generated data cannot be compared, or combined, with more recently generated data sets. We predict that genotyping by sequencing will become the predominant genotyping technology within the next 5-10 years. With this in mind, to ensure that data generated from current genotyping platforms continues to be of use, we have designed and utilized SNP-based capture probes from several thousand existing and publicly available probes from Axiom® and KASP™ genotyping platforms. We have validated our capture probes in a targeted genotyping by sequencing protocol using 31 previously genotyped UK elite hexaploid wheat accessions. Data comparisons between targeted genotyping by sequencing, Axiom® array genotyping and KASP™ genotyping assays, identified a set of 3256 probes which reliably bring together targeted genotyping by sequencing data with the previously available marker data set. As such, these probes are likely to be of considerable value to the wheat community. The probe details, full probe sequences and a custom built analysis pipeline may be freely downloaded from the CerealsDB website (http://www.cerealsdb.uk.net/cerealgenomics/CerealsDB/sequence_capture.php).

Mapping of Quantitative Trait Loci for Leaf Rust Resistance in the Wheat Population Ning7840 × Clark

Leaf rust, caused by Puccinia triticina, is an important fungal disease of wheat (Triticum aestivum L.) and causes significant yield losses worldwide. To determine quantitative trait loci (QTLs) responsible for leaf rust resistance, a recombinant inbred line (RIL) population developed from a cross of Ning7840 × Clark was evaluated for leaf rust severity, and was genotyped for single nucleotide polymorphisms (SNPs) using 9K Illumina chips, and with simple sequence repeat (SSR) markers. Two major QTLs on chromosome arms 7DS and 3BS, and two minor QTLs on chromosomes 5AS and 6AS showed a significant effect on leaf rust severity. The 7DS QTL from Ning7840 and the 3BS QTL from Clark explained, respectively, about 35% and 18% of the phenotypic variation for leaf rust resistance. The QTL on 7DS was confirmed to be Lr34. The QTL on 3BS, QLr.hwwg-3B.1, was associated with adult plant resistance and was provisionally identified as Lr74. QLr.hwwg-5AS and QLr.hwwg-6AS from Ning7840 and Clark, respectively, may correspond to previously described QTLs. Lr34, QLr.hwwg-3BS.1, and QLr.hwwg-6AS had an additive effect on leaf rust severity. RILs with all three favorable alleles showed the highest resistance to leaf rust and the RILs with none of them showed the lowest resistance.

Genotyping-by-Sequencing Derived High-Density Linkage Map and its Application to QTL Mapping of Flag Leaf Traits in Bread Wheat

Winter wheat parents ‘Harry’ (drought tolerant) and ‘Wesley’ (drought susceptible) were used to develop a recombinant inbred population with future goals of identifying genomic regions associated with drought tolerance. To precisely map genomic regions, high-density linkage maps are a prerequisite. In this study genotyping-by- sequencing (GBS) was used to construct the high-density linkage map. The map contained 3,641 markers distributed on 21 chromosomes and spanned 1,959 cM with an average distance of 1.8 cM between markers. The constructed linkage map revealed strong collinearity in marker order across 21 chromosomes with POPSEQ-v2.0, which was based on a high-density linkage map. The reliability of the linkage map for QTL mapping was demonstrated by co-localizing the genes to previously mapped genomic regions for two highly heritable traits, chaff color, and leaf cuticular wax. Applicability of linkage map for QTL mapping of three quantitative traits, flag leaf length, width, and area, identified 21 QTLs in four environments, and QTL expression varied across the environments. Two major stable QTLs, one each for flag leaf length (Qfll.hww-7A) and flag leaf width (Qflw.hww-5A) were identified. The map constructed will facilitate QTL and fine mapping of quantitative traits, map-based cloning, comparative mapping, and in marker-assisted wheat breeding endeavors.

Quantitative Trait Loci for Slow-Rusting Resistance to Leaf Rust in Doubled-Haploid Wheat Population CI13227 × Lakin

CI13227 is a U.S. winter wheat line with adult-plant slow-rusting resistance that has been the subject of several studies on the characteristics and components of slow rusting. Previous genetic studies used different populations and approaches and came to different conclusions about the genetic basis of resistance in CI13227. To clarify the situation, a new doubled-haploid (DH) population of CI13227 × Lakin was produced and a linkage map was constructed using 5,570 single-nucleotide polymorphism (SNP) markers derived from wheat 90K SNP assays and 84 simple sequence repeat markers. Three quantitative trait loci (QTL) were identified for three slow-rusting traits on chromosome arms 2DS, 7AL, and 7BL from CI13227. A fourth QTL mapped on chromosome 3BS was from Lakin. The QTL on 2DS, designated QLr.hwwg-2DS, explained 11.2 to 25.6% of the phenotypic variation. It was found in the same position as a slow-rusting QTL in the CI13227 × Suwon 92 population in a previous study and, thus, verified the 2DS QTL. The QTL on chromosome 7BL explained 8.1 and 19.3% of the phenotypic variation and is likely to be Lr68. The other two QTL showed a minor effect on some of the traits evaluated in a single experiment. Flanking SNP closely linked to all QTL were converted to Kompetitive allele-specific polymerase chain reaction markers that can be used in marker-assisted selection to transfer these QTL into adapted wheat cultivars.

Genotyping-by-Sequencing (GBS) Revealed Molecular Genetic Diversity of Iranian Wheat Landraces and Cultivars

Background: Genetic diversity is an essential resource for breeders to improve new cultivars with desirable characteristics. Recently, genotyping-by-sequencing (GBS), a next-generation sequencing (NGS) technology that can simplify complex genomes, has now be used as a high-throughput and cost-effective molecular tool for routine breeding and screening in many crop species, including the species with a large genome. Results: We genotyped a diversity panel of 369 Iranian hexaploid wheat accessions including 270 landraces collected between 1931 and 1968 in different climate zones and 99 cultivars released between 1942 to 2014 using 16,506 GBS-based single nucleotide polymorphism (GBS-SNP) markers. The B genome had the highest number of mapped SNPs while the D genome had the lowest on both the Chinese Spring and W7984 references. Structure and cluster analyses divided the panel into three groups with two landrace groups and one cultivar group, suggesting a high differentiation between landraces and cultivars and between landraces. The cultivar group can be further divided into four subgroups with one subgroup was mostly derived from Iranian ancestor(s). Similarly, landrace groups can be further divided based on years of collection and climate zones where the accessions were collected. Molecular analysis of variance indicated that the genetic variation was larger between groups than within group. Conclusion: Obvious genetic diversity in Iranian wheat was revealed by analysis of GBS-SNPs and thus breeders can select genetically distant parents for crossing in breeding. The diverse Iranian landraces provide rich genetic sources of tolerance to biotic and abiotic stresses, and they can be useful resources for the improvement of wheat production in Iran and other countries.

Genome-Wide Single Nucleotide Polymorphism Discovery and the Construction of a High-Density Genetic Map for Melon (Cucumis melo L.) Using Genotyping-by-Sequencing

Although genotyping-by-sequencing (GBS) enables the efficient and low-cost generation of large numbers of markers, the utility of resultant genotypes are limited, because they are enormously error-prone and contain high proportions of missing data. In this study, we generated single nucleotide polymorphism (SNP) markers for 109 recombinant inbred lines of melon (Cucumis melo L.) using the GBS approach and ordered them according to their physical position on the draft double haploid line DHL92 genome. Next, by investigating associations between these SNPs, we discovered that some segments on the physical map conflict with linkage relationships. Therefore, to filter out error-prone loci, 4,110 SNPs in which we have a high degree of confidence were selected as anchors to test independence with respect to unselected markers, and the resultant dataset was then analyzed using the Full-Sib Family Haplotype (FSFHap) algorithm in the software TASSEL 5.2. On the basis of this analysis, 22,933 loci that have an average rate of missing data of 0.281% were used to construct a genetic map, which spans 1,088.3 cM across 12 chromosomes and has a maximum spacing of 6.0 cM. Use of this high-quality linkage map enabled the identification of several quantitative trait loci (QTL) known to control traits in fruit and validated our approach. This study highlights the utility of GBS markers for the identification of trait-associated QTLs in melon and facilitates further investigation of genome structure.

Genome-Wide Association Study of Grain Architecture in Wild Wheat Aegilops tauschii

Aegilops tauschii, the D-genome progenitor of Triticum aestivum, encompasses huge diversity for various traits of potential economic importance such as yield, biotic and abiotic stress tolerance, quality and nutrition. In the present study, variation for grain size in Ae. tauschii germplasm was studied and its genetic basis dissected using genome-wide association study (GWAS). Grain length, width, and weight evaluated in 177 Ae. tauschii accessions over 3 years showed near normal distribution with 1.74-, 1.75-, and 2.82-fold variation, respectively. These lines were genetically characterized using genotyping-by-sequencing (GBS) protocol that produced 11,489 single nucleotide polymorphic (SNP) markers. Genetic diversity analysis revealed the presence of two distinct subgroups (designated as lineage 1 and 2) in Ae. tauschii. Based on GBS markers, the genetic similarity was calculated between the accessions and GWAS was conducted using 114 non-redundant accessions and 5,249 SNP markers. A total of 17 SNPs associated with grain size traits distributed over all the seven chromosomes were revealed with 6D, 5D, and 2D harboring most significant marker-trait associations. Some of the chromosomal regions such as 6D_66.4-71.1 cM, 1D_143.5-156.7 cM, and 2D_89.9-92.5 cM had associations with multiple traits. Candidate genes associated with cell division and differentiation were identified for some of the associated SNP markers. Further efforts to validate these loci will help to understand their role in determining grain size and allelic diversity in current germplasm and its effect on grain size upon transfer to bread wheat background.

Genotype-by-sequencing facilitates genetic mapping of a stem rust resistance locus in Aegilops umbellulata, a wild relative of cultivated wheat

BACKGROUND

Wild relatives of wheat play a significant role in wheat improvement as a source of genetic diversity. Stem rust disease of wheat causes significant yield losses at the global level and stem rust pathogen race TTKSK (Ug99) is virulent to most previously deployed resistance genes. Therefore, the objective of this study was to identify loci conferring resistance to stem rust pathogen races including Ug99 in an Aegilops umbelluata bi-parental mapping population using genotype-by-sequencing (GBS) SNP markers.

RESULTS

A bi-parental F2:3 population derived from a cross made between stem rust resistant accession PI 298905 and stem rust susceptible accession PI 542369 was used for this study. F2 individuals were evaluated with stem rust race TTTTF followed by testing F2:3 families with races TTTTF and TTKSK. The segregation pattern of resistance to both stem rust races suggested the presence of one resistance gene. A genetic linkage map, comprised 1,933 SNP markers, was created for all seven chromosomes of Ae. umbellulata using GBS. A major stem rust resistance QTL that explained 80% and 52% of the phenotypic variations for TTTTF and TTKSK, respectively, was detected on chromosome 2U of Ae. umbellulata.

CONCLUSION

The novel resistance gene for stem rust identified in this study can be transferred to commercial wheat varieties assisted by the tightly linked markers identified here. These markers identified through our mapping approach can be a useful strategy to identify and track the resistance gene in marker-assisted breeding in wheat.