Using genotyping-by-sequencing (GBS) for genomic discovery in cultivated oat

Uncovering the genomic regions underlying grain iron and zinc content using genome-wide association mapping in finger millet

Finger millet, being rich source of essential minerals like iron and zinc, is an ideal model to identify candidate genes contributing to high grain iron content (GIC) and zinc content (GZC) in plants. Hence, finger millet diversity panel comprised of 202 genotypes was evaluated in two geographical locations and found to have a wide variation for GIC and GZC. A genome-wide association study using 2977 single nucleotide polymorphism (SNP) markers identified reliable marker-trait associations (MTAs). The use of general linear model (GLM) and mixed linear model (MLM) approaches revealed 5 and 8 common MTAs linked to GIC and GZC, respectively, for both Almora and Pantnagar locations, with a high level of significance (P < 0.01). However, 12 significant MTAs were found to be linked with GIC for Pantnagar location alone. The MTAs were associated with specific genes that produce ferritin (Fer1), iron-regulated transporter-like protein (IRT2), and yellow stripe-like 2 proteins (YSL2). These genes are likely linked to GIC variation in finger millet. Additionally, the variation in GZC in finger millet was connected to genes that encode zinc transporters, namely ZIP1 protein (ZIP1) and ZTP29-like protein (ZTP29). Compared to low GIC and GZC genotypes, high GIC and GZC genotypes exhibited greater relative expression of these genes.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-023-03889-1.

Genetic Analysis and Physical Mapping of Oat Adult Plant Resistance Loci Against Puccinia coronata f. sp. avenae

Six quantitative trait loci (QTLs) for adult plant resistance against oat crown rust (Puccinia coronata f. sp. avenae) were identified from mapping three recombinant inbred populations. Using genotyping-by-sequencing with markers called against the OT3098 v1 reference genome, the QTLs were mapped on six different chromosomes: Chr1D, Chr4D, Chr5A, Chr5D, Chr7A, and Chr7C. Composite interval mapping with marker cofactor selection showed that the phenotypic variance explained by all identified QTLs for coefficient of infection range from 12.2 to 46.9%, whereas heritability estimates ranged from 0.11 to 0.38. The significant regions were narrowed down to intervals of 3.9 to 25 cM, equivalent to physical distances of 11 to 133 Mb. At least two flanking single-nucleotide polymorphism markers were identified within 10 cM of each QTL that could be used in marker-assisted introgression, pyramiding, and selection. The additive effects of the QTLs in each population were determined using single-nucleotide polymorphism haplotype data, which showed a significantly lower coefficient of infection in lines homozygous for the resistant alleles. Analysis of pairwise linkage disequilibrium also revealed high correlation of markers and presence of linkage blocks in the significant regions. To further facilitate marker-assisted breeding, polymerase chain reaction allelic competitive extension (PACE) markers for the adult plant resistance loci were developed. Putative candidate genes were also identified in each of the significant regions, which include resistance gene analogs that encode for kinases, ligases, and predicted receptors of avirulence proteins from pathogens.

Utilizing Genomics to Characterize the Common Oat Gene Pool—The Story of More than a Century of Polish Breeding

This study was undertaken to investigate the diversity and population structure of 487 oat accessions, including breeding lines from the ongoing programs of the three largest Polish breeding companies, along with modern and historical Polish and foreign cultivars. The analysis was based on 7411 DArTseq-derived SNPs distributed among three sub-genomes (A, C, and D). The heterogeneity of the studied material was very low, as only cultivars and advanced breeding lines were examined. Principal component analysis (PCA), principal coordinate analysis (PCoA), and cluster and STRUCTURE analyses found congruent results, which show that most of the examined cultivars and materials from Polish breeding programs formed major gene pools, that only some accessions derived from Strzelce Plant Breeding, and that foreign cultivars were outside of the main group. During the 120 year oat breeding process, only 67 alleles from the old gene pool were lost and replaced by 67 new alleles. The obtained results indicate that no erosion of genetic diversity was observed within the Polish native oat gene pool. Moreover, current oat breeding programs have introduced 673 new alleles into the gene pool relative to historical cultivars. The analysis also showed that most of the changes in relation to historical cultivars occurred within the A sub-genome with emphasis on chromosome 6A. The targeted changes were the rarest in the C sub-genome. This study showed that Polish oat breeding based mainly on traditional breeding methods—although focused on improving traits typical to this crop, i.e., enhancing the grain yield and quality and improving adaptability—did not significantly narrow the oat gene pool and in fact produced cultivars that are not only competitive in the European market but are also reservoirs of new alleles that were not found in the analyzed foreign materials.

Population structure analysis and genome-wide association study of a hexaploid oat landrace and cultivar collection

INTRODUCTION

Oat (Avena sativa L.) is an important cereal crop grown worldwide for grain and forage, owing to its high adaptability to diverse environments. However, the genetic and genomics research of oat is lagging behind that of other staple cereal crops.

METHODS

In this study, a collection of 288 oat lines originating worldwide was evaluated using 2,213 single nucleotide polymorphism (SNP) markers obtained from an oat iSelect 6K-beadchip array to study its genetic diversity, population structure, and linkage disequilibrium (LD) as well as the genotype-phenotype association for hullessness and lemma color.

RESULTS

The average gene diversity and polymorphic information content (PIC) were 0.324 and 0.262, respectively. The first three principal components (PCs) accounted for 30.33% of the genetic variation, indicating that the population structure of this panel of oat lines was stronger than that reported in most previous studies. In addition, accessions could be classified into two subpopulations using a Bayesian clustering approach, and the clustering pattern of accessions was closely associated with their region of origin. Additionally, evaluation of LD decay using 2,143 mapped markers revealed that the intrachromosomal whole-genome LD decayed rapidly to a critical r² value of 0.156 for marker pairs separated by a genetic distance of 1.41 cM. Genome-wide association study (GWAS) detected six significant associations with the hullessness trait. Four of these six markers were located on the Mrg21 linkage group between 194.0 and 205.7 cM, while the other two significant markers mapped to Mrg05 and Mrg09. Three significant SNPs, showing strong association with lemma color, were located on linkage groups Mrg17, Mrg18, and Mrg20.

DISCUSSION

Our results discerned relevant patterns of genetic diversity, population structure, and LD among members of a worldwide collection of oat landraces and cultivars proposed to be 'typical' of the Qinghai-Tibetan Plateau. These results have important implications for further studies on association mapping and practical breeding in high-altitude oat.

Deciphering the genomic regions governing major agronomic traits and blast resistance using genome wide association mapping in finger millet

Finger millet (Eleusine coracana L.) is climate resilient minor millet of Asia and Africa with wide adaptation and unparallel nutritional profile. To date, genomic resources available in finger millet are scanty and genetic control of agronomic traits remains elusive. Here, a collection of eco-geographically diverse 186 genotypes was quantified for variation in 13 agronomic traits and reaction to blast to identify marker-trait associations (MTAs) using genotyping-by-sequencing (GBS) and genome-wide association study (GWAS). GBS generated 2977 high quality single nucleotide polymorphism (SNPs) markers and identified three subpopulations with varying admixture levels. General linear and mixed model approaches of GWAS to correct for population structure and genetic relatedness identified 132 common MTAs for agronomic traits across the years. The phenotypic variance explained by the makers varied from 4.8% (TP692389-flag leaf width) to 20% (TP714446-green fodder weight). Of these, 26 MTAs showed homology with candidate genes having role in plant growth, development and photosynthesis in the genomes of foxtail millet, rice, maize, wheat and barley. We also found 4 common MTAs for neck blast resistance, which explained 5.9-15.1% phenotypic variance. Three MTAs for neck blast resistance showed orthologues in related genera having putative functions in pathogen defense in plants. The results of this work lay a foundation for understanding the genetic architecture of agronomic traits and blast resistance in finger millet and provide a framework for genomics assisted breeding.

High-resolution quantitative trait locus mapping for rice grain quality traits using genotyping by sequencing

Rice is a major food crop that sustains approximately half of the world population. Recent worldwide improvements in the standard of living have increased the demand for high-quality rice. Accurate identification of quantitative trait loci (QTLs) for rice grain quality traits will facilitate rice quality breeding and improvement. In the present study, we performed high-resolution QTL mapping for rice grain quality traits using a genotyping-by-sequencing approach. An F₂ population derived from a cross between an elite japonica variety, Koshihikari, and an indica variety, Nona Bokra, was used to construct a high-density genetic map. A total of 3,830 single nucleotide polymorphism markers were mapped to 12 linkage groups spanning a total length of 2,456.4 cM, with an average genetic distance of 0.82 cM. Seven grain quality traits-the percentage of whole grain, percentage of head rice, percentage of area of head rice, transparency, percentage of chalky rice, percentage of chalkiness area, and degree of chalkiness-of the F₂ population were investigated. In total, 15 QTLs with logarithm of the odds (LOD) scores >4 were identified, which mapped to chromosomes 6, 7, and 9. These loci include four QTLs for transparency, four for percentage of chalky rice, four for percentage of chalkiness area, and three for degree of chalkiness, accounting for 0.01%-61.64% of the total phenotypic variation. Of these QTLs, only one overlapped with previously reported QTLs, and the others were novel. By comparing the major QTL regions in the rice genome, several key candidate genes reported to play crucial roles in grain quality traits were identified. These findings will expedite the fine mapping of these QTLs and QTL pyramiding, which will facilitate the genetic improvement of rice grain quality.

Chromosomal Location of Pm12-A Novel Powdery Mildew Resistance Gene from Avena sterilis

Identification of new, effective disease resistance genes is a very important aspect of plant breeding. Also important is the precise location of individual loci and tagging them with DNA markers for marker assisted selection. The aim of the present study was identification of the molecular markers linked with Pm12, a new effective resistance gene to powdery mildew, and their location in the oat genome. The analysis was performed on 167 F₂ individuals from a hybrid of Fuchs × CN67383, with the status of the locus in each individual verified by progeny test in F₃. Segregation ratios confirmed the monogenic nature of resistance. Making use of the sequence data of DNA markers and the oat OT3098 v2 genome reference assembly, Pm12 is located on chromosome 7C. A comparison was also made with the reference consensus map, to which there are more reports of mapped genes to date. The mapping results suggest that Pm12 is located in the interval 103.8-111.7 cM on this map. No powdery mildew resistance locus has been identified in this region so far, suggesting that Avena sterilis CN67383 carries a novel locus offering effective resistance in oat breeding. The information included in the oat genome annotation allowed for the identification of candidate genes in the close region of the marker cluster for Pm12. This information may provide an interesting source of further analysis of the pathways of various genes in response to the stress of powdery mildew infection.

The Use of DArTseq Technology to Identify Markers Linked to Genes Responsible for Seed Germination and Seed Vigor in Maize

Seed vigor and seed germination are very important traits, determined by several factors including genetic and physical purity, mechanical damage, and physiological condition, characterized by maintaining a high seed vigor and stable content after storage. The search for molecular markers related to improvement in seed vigor under adverse condition is an important issue in maize breeding currently. Higher sowing quality of seeds is necessary for the development of the agriculture production and better ability to resist all kinds of adversity in the seeds’ storage. Condition is a very important factor affecting the yield of plants, thanks to the construction of their vitality. Identification of molecular markers associated with seed germination and seed vigor may prove to be very important in the selection of high-yielding maize varieties. The aim of this study was to identify and select new markers for maize (SNP and SilicoDArT) linked to genes influencing the seed germination and seed vigor in inbred lines of maize (Zea mays L.). The plant material used for the research was 152 inbred maize lines. The seed germination and seed vigor were analyzed. For identification of SNP and SilicoDArT markers related to the seed germination and seed vigor, the SilicoDarT technique developed by Diversity Arrays Technology was used. The analysis of variance indicated a statistically significant differentiation between genotypes for both observed traits. Positive (r = 0.41) correlation (p < 0.001) between seed germination and seed vigor was observed. As a result of next-generation sequencing, the molecular markers SilicoDArT (53,031) and SNP (28,571) were obtained. Out of 81,602 identified SilicoDArT and SNP markers, 15,409 (1559 SilicoDArT and 13,850 SNP) were selected as a result of association mapping, which showed them to be significantly related to the analyzed traits. The 890 molecular markers were associated with seed vigor, and 1323 with seed germination. Fifty-six markers (47 SilicoDArT and nine SNP) were significant for both traits. Of these 56 markers, the 20 most significant were selected (five of these markers were significant at the level of 0.001 for seed vigor and at the level of 0.05 for seed germination, another five markers were significant at the level of 0.001 for seed germination and at the level of 0.05 for seed vigor, five markers significant at the level of 0.001 only for seed vigor and five significant at the level of 0.001 only for seed germination also selected). These markers were used for physical mapping to determine their location on the genetic map. Finally, it was found that six of these markers (five silicoDArT—2,435,784, 4,772,587, 4,776,334, 2,507,310, 25,981,291, and one SNP—2,386,217) are located inside genes, the action of which may affect both seed germination and seed vigor. These markers can be used to select genotypes with high vigor and good seed germination.

OMICS in Fodder Crops: Applications, Challenges, and Prospects

Biomass yield and quality are the primary targets in forage crop improvement programs worldwide. Low-quality fodder reduces the quality of dairy products and affects cattle's health. In multipurpose crops, such as maize, sorghum, cowpea, alfalfa, and oat, a plethora of morphological and biochemical/nutritional quality studies have been conducted. However, the overall growth in fodder quality improvement is not on par with cereals or major food crops. The use of advanced technologies, such as multi-omics, has increased crop improvement programs manyfold. Traits such as stay-green, the number of tillers per plant, total biomass, and tolerance to biotic and/or abiotic stresses can be targeted in fodder crop improvement programs. Omic technologies, namely genomics, transcriptomics, proteomics, metabolomics, and phenomics, provide an efficient way to develop better cultivars. There is an abundance of scope for fodder quality improvement by improving the forage nutrition quality, edible quality, and digestibility. The present review includes a brief description of the established omics technologies for five major fodder crops, i.e., sorghum, cowpea, maize, oats, and alfalfa. Additionally, current improvements and future perspectives have been highlighted.

A reference-anchored oat linkage map reveals quantitative trait loci conferring adult plant resistance to crown rust (Puccinia coronata f. sp. avenae)

We mapped three adult plant resistance (APR) loci on oat chromosomes 4D and 6C and developed flanking KASP/PACE markers for marker-assisted selection and gene pyramiding. Using sequence orthology search and the available oat genomic and transcriptomic data, we surveyed these genomic regions for genes that may control disease resistance. Sources of durable disease resistance are needed to minimize yield losses in cultivated oat caused by crown rust (Puccinia coronata f. sp. avenae). In this study, we developed five oat recombinant inbred line mapping populations to identify sources of adult plant resistance from crosses between five APR donors and Otana, a susceptible variety. The preliminary bulk segregant mapping based on allele frequencies showed two regions in linkage group Mrg21 (Chr4D) that are associated with the APR phenotype in all five populations. Six markers from these regions in Chr4D were converted to high-throughput allele specific PCR assays and were used to genotype all individuals in each population. Simple interval mapping showed two peaks in Chr4D, named QPc.APR-4D.1 and QPc.APR-4D.2, which were detected in the OtanaA/CI4706-2 and OtanaA/CI9416-2 and in the Otana/PI189733, OtanaD/PI260616, and OtanaA/CI8000-4 populations, respectively. These results were validated by mapping two entire populations, Otana/PI189733 and OtanaA/CI9416, genotyped using Illumina HiSeq, in which polymorphisms were called against the OT3098 oat reference genome. Composite interval mapping results confirmed the presence of the two quantitative trait loci (QTL) located on oat chromosome 4D and an additional QTL with a smaller effect located on chromosome 6C. This mapping approach also narrowed down the physical intervals to between 5 and 19 Mb, and indicated that QPc.APR-4D.1, QPc.APR-4D.2, and QPc.APR-6C explained 43.4%, 38.5%, and 21.5% of the phenotypic variation, respectively. In a survey of the gene content of each QTL, several clusters of disease resistance genes that may contribute to APR were found. The allele specific PCR markers developed for these QTL regions would be beneficial for marker-assisted breeding, gene pyramiding, and future cloning of resistance genes from oat.

G-DIRT: a web server for identification and removal of duplicate germplasms based on identity-by-state analysis using single nucleotide polymorphism genotyping data

Maintaining duplicate germplasms in genebanks hampers effective conservation and utilization of genebank resources. The redundant germplasm adds to the cost of germplasm conservation by requiring a large proportion of the genebank financial resources towards conservation rather than enriching the diversity. Besides, genome-wide-association analysis using an association panel with over-represented germplasms can be biased resulting in spurious marker-trait associations. The conventional methods of germplasm duplicate removal using passport information suffer from incomplete or missing passport information and data handling errors at various stages of germplasm enrichment. This limitation is less likely in the case of genotypic data. Therefore, we developed a web-based tool, Germplasm Duplicate Identification and Removal Tool (G-DIRT), which allows germplasm duplicate identification based on identity-by-state analysis using single-nucleotide polymorphism genotyping information along with pre-processing of genotypic data. A homozygous genotypic difference threshold of 0.1% for germplasm duplicates has been determined using tetraploid wheat genotypic data with 94.97% of accuracy. Based on the genotypic difference, the tool also builds a dendrogram that can visually depict the relationship between genotypes. To overcome the constraint of high-dimensional genotypic data, an offline version of G-DIRT in the interface of R has also been developed. The G-DIRT is expected to help genebank curators, breeders and other researchers across the world in identifying germplasm duplicates from the global genebank collections by only using the easily sharable genotypic data instead of physically exchanging the seeds or propagating materials. The web server will complement the existing methods of germplasm duplicate identification based on passport or phenotypic information being freely accessible at http://webtools.nbpgr.ernet.in/gdirt/.

SilicoDArT and SNP markers for genetic diversity and population structure analysis of Trema orientalis; a fodder species

Establishing the genetic diversity and population structure of a species can guide the selection of appropriate conservation and sustainable utilization strategies. Next-generation sequencing (NGS) approaches are increasingly being used to generate multi-locus data for genetic structure determination. This study presents the genetic structure of a fodder species -Trema orientalis based on two genome-wide high-throughput diversity array technology (DArT) markers; silicoDArT and single nucleotide polymorphisms (SNPs). Genotyping of 119 individuals generated 40,650 silicoDArT and 4767 SNP markers. Both marker types had a high average scoring reproducibility (>99%). Genetic relationships explored by principal coordinates analysis (PCoA) showed that the first principal coordinate axis explained most of the variation in both the SilicoDArT (34.2%) and SNP (89.6%) marker data. The average polymorphic information content did not highly differ between silicoDArT (0.22) and SNPs (0.17) suggesting minimal differences in informativeness in the two groups of markers. The, mean observed (H_o) and expected (H_e) heterozygosity were low and differed between the silicoDArT and SNPs respectively, estimated at H_o = 0.08 and H_e = 0.05 for silicoDArT and H_o = 0.23 and H_e = 0.19 for SNPs. The population of T. orientalis was moderately differentiated (F_ST  =  0.20–0.53) and formed 2 distinct clusters based on maximum likelihood and principal coordinates analysis. Analysis of molecular variance revealed that clusters contributed more to the variation (46.3–60.8%) than individuals (32.9–31.2%). Overall, the results suggest a high relatedness of the individuals sampled and a threatened genetic potential of T. orientalis in the wild. Therefore, genetic management activities such as ex-situ germplasm management are required for the sustainability of the species. Ex-situ conservation efforts should involve core collection of individuals from different populations to capture efficient diversity. This study demonstrates the importance of silicoDArT and SNP makers in population structure and genetic diversity analysis of Trema orientalis, useful for future genome wide studies in the species.

Genome analysis in Avena sativa reveals hidden breeding barriers and opportunities for oat improvement

Oat (Avena sativa L.) is an important and nutritious cereal crop, and there is a growing need to identify genes that contribute to improved oat varieties. Here we utilize a newly sequenced and annotated oat reference genome to locate and characterize quantitative trait loci (QTLs) affecting agronomic and grain-quality traits in five oat populations. We find strong and significant associations between the positions of candidate genes and QTL that affect heading date, as well as those that influence the concentrations of oil and β-glucan in the grain. We examine genome-wide recombination profiles to confirm the presence of a large, unbalanced translocation from chromosome 1 C to 1 A, and a possible inversion on chromosome 7D. Such chromosome rearrangements appear to be common in oat, where they cause pseudo-linkage and recombination suppression, affecting the segregation, localization, and deployment of QTLs in breeding programs.

Tinker et al. identified the position and effects of major QTLs relative to a new fully annotated reference genome in five recombinant inbred line populations representing nine diverse oat (Avena sativa) varieties. They also characterized two major chromosome rearrangements that may impact breeding targets affected by QTL that are located in these regions.

Novel GBS-Based SNP Markers for Finger Millet and Their Use in Genetic Diversity Analyses

Eleusine coracana (L.) Gaertn., commonly known as finger millet, is a multipurpose crop used for food and feed. Genomic tools are required for the characterization of crop gene pools and their genomics-led breeding. High-throughput sequencing-based characterization of finger millet germplasm representing diverse agro-ecologies was considered an effective method for determining its genetic diversity, thereby suggesting potential candidates for breeding. In this study, the genotyping-by-sequencing (GBS) method was used to simultaneously identify novel single nucleotide polymorphism (SNP) markers and genotype 288 finger millet accessions collected from Ethiopia and Zimbabwe. The accessions were characterized at individual and group levels using 5,226 bi-allelic SNPs, with a minimum allele frequency (MAF) of above 0.05, distributed across 2,500 scaffolds of the finger millet reference genome. The polymorphism information content (PIC) of the SNPs was 0.23 on average, and a quarter of them have PIC values over 0.32, making them highly informative. The grouping of the 288 accessions into seven populations based on geographic proximity and the potential for germplasm exchange revealed a narrow range of observed heterozygosity (Ho; 0.09–0.11) and expected heterozygosity (He) that ranged over twofold, from 0.11 to 0.26. Alleles unique to the different groups were also identified, which merit further investigation for their potential association with desirable traits. The analysis of molecular variance (AMOVA) revealed a highly significant genetic differentiation among groups of accessions classified based on the geographic region, country of origin, days to flowering, panicle type, and Al tolerance (p < 0.01). The high genetic differentiation between Ethiopian and Zimbabwean accessions was evident in the AMOVA, cluster, principal coordinate, and population structure analyses. The level of genetic diversity of finger millet accessions varies moderately among locations within Ethiopia, with accessions from the northern region having the lowest level. In the neighbor-joining cluster analysis, most of the improved cultivars included in this study were closely clustered, probably because they were developed using genetically less diverse germplasm and/or selected for similar traits, such as grain yield. The recombination of alleles via crossbreeding genetically distinct accessions from different regions of the two countries can potentially lead to the development of superior cultivars.

Whole-genome resequencing of Sorghum bicolor and S. bicolor × S. halepense lines provides new insights for improving plant agroecological characteristics

Sorghum (Sorghum bicolor L. (Moench)) is the world's fifth economically most important cereal and is a staple particularly in the semi-arid tropics of Africa and Asia. Genetic gains in this crop can benefit from wild relatives such as Sorghum halepense. Genome sequences including those from this wild species can boost the study of genome-wide and intraspecific variation for dissecting the genetic basis and improving important traits in sorghum. The whole-genome resequencing carried out in this work on a panel of 172 populations of S. bicolor and S. bicolor × S. halepense (SbxSh) advanced lines generated a total of 567,046,841 SNPs, 91,825,474 indels, 1,532,171 SVs, and 4,973,961 CNVs. Clearly, SbxSh accumulated more variants and mutations with powerful effects on genetic differentiation. A total of 5,548 genes private to SbxSh mapped to biological process GO enrichment terms; 34 of these genes mapped to root system development (GO: 0022622). Two of the root specific genes i.e., ROOT PRIMORDIUM DEFECTIVE 1 (RPD1; GeneID: 8054879) and RETARDED ROOT GROWTH (RRG, GeneID: 8072111), were found to exert direct effect on root growth and development. This is the first report on whole-genome resequencing of a sorghum panel that includes S. halepense genome. Mining the private variants and genes of this wild species can provide insights capable of boosting sorghum genetic improvement, particularly the perenniality trait that is compliant with agroecological practices, sustainable agriculture, and climate change resilience.

Development of high-resolution multiple-SNP arrays for genetic analyses and molecular breeding through genotyping by target sequencing and liquid chip

Genotyping platforms, as critical supports for genomics, genetics, and molecular breeding, have been well implemented at national institutions/universities in developed countries and multinational seed companies that possess high-throughput, automatic, large-scale, and shared facilities. In this study, we integrated an improved genotyping by target sequencing (GBTS) system with capture-in-solution (liquid chip) technology to develop a multiple single-nucleotide polymorphism (mSNP) approach in which mSNPs can be captured from a single amplicon. From one 40K maize mSNP panel, we developed three types of markers (40K mSNPs, 251K SNPs, and 690K haplotypes), and generated multiple panels with various marker densities (1K-40K mSNPs) by sequencing at different depths. Comparative genetic diversity analysis was performed with genic versus intergenic markers and di-allelic SNPs versus non-typical SNPs. Compared with the one-amplicon-one-SNP system, mSNPs and within-mSNP haplotypes are more powerful for genetic diversity detection, linkage disequilibrium decay analysis, and genome-wide association studies. The technologies, protocols, and application scenarios developed for maize in this study will serve as a model for the development of mSNP arrays and highly efficient GBTS systems in animals, plants, and microorganisms.

Genomic prediction and training set optimization in a structured Mediterranean oat population

The strong genetic structure observed in Mediterranean oats affects the predictive ability of genomic prediction as well as the performance of training set optimization methods. In this study, we investigated the efficiency of genomic prediction and training set optimization in a highly structured population of cultivars and landraces of cultivated oat (Avena sativa) from the Mediterranean basin, including white (subsp. sativa) and red (subsp. byzantina) oats, genotyped using genotype-by-sequencing markers and evaluated for agronomic traits in Southern Spain. For most traits, the predictive abilities were moderate to high with little differences between models, except for biomass for which Bayes-B showed a substantial gain compared to other models. The consistency between the structure of the training population and the population to be predicted was key to the predictive ability of genomic predictions. The predictive ability of inter-subspecies predictions was indeed much lower than that of intra-subspecies predictions for all traits. Regarding training set optimization, the linear mixed model optimization criteria (prediction error variance (PEVmean) and coefficient of determination (CDmean)) performed better than the heuristic approach "partitioning around medoids," even under high population structure. The superiority of CDmean and PEVmean could be explained by their ability to adapt the representation of each genetic group according to those represented in the population to be predicted. These results represent an important step towards the implementation of genomic prediction in oat breeding programs and address important issues faced by the genomic prediction community regarding population structure and training set optimization.

Robust and efficient software for reference-free genomic diversity analysis of genotyping-by-sequencing data on diploid and polyploid species

Genotyping-by-sequencing (GBS) is a widely used and cost-effective technique for obtaining large numbers of genetic markers from populations by sequencing regions adjacent to restriction cut sites. Although a standard reference-based pipeline can be followed to analyse GBS reads, a reference genome is still not available for a large number of species. Hence, reference-free approaches are required to generate the genetic variability information that can be obtained from a GBS experiment. Unfortunately, available tools to perform de novo analysis of GBS reads face issues of usability, accuracy and performance. Furthermore, few available tools are suitable for analysing data sets from polyploid species. In this manuscript, we describe a novel algorithm to perform reference-free variant detection and genotyping from GBS reads. Nonexact searches on a dynamic hash table of consensus sequences allow for efficient read clustering and sorting. This algorithm was integrated in the Next Generation Sequencing Experience Platform (NGSEP) to integrate the state-of-the-art variant detector already implemented in this tool. We performed benchmark experiments with three different empirical data sets of plants and animals with different population structures and ploidies, and sequenced with different GBS protocols at different read depths. These experiments show that NGSEP has comparable and in some cases better accuracy and always better computational efficiency compared to existing solutions. We expect that this new development will be useful for many research groups conducting population genetic studies in a wide variety of species.

Population genomics of Mediterranean oat (A. sativa) reveals high genetic diversity and three loci for heading date

Genomic analysis of Mediterranean oats reveals high genetic diversity and three loci for adaptation to this environment. This information together with phenotyping and passport data, gathered in an interactive map, will be a vital resource for oat genetic improvement. During the twentieth century, oat landraces have increasingly been replaced by modern cultivars, resulting in loss of genetic diversity. However, landraces have considerable potential to improve disease and abiotic stress tolerance and may outperform cultivars under low input systems. In this work, we assembled a panel of 669 oat landraces from Mediterranean rim and 40 cultivated oat varieties and performed the first large-scale population genetic analysis of both red and white oat types of Mediterranean origin. We created a public database associated with an interactive map to visualize information for each accession. The oat collection was genotyped with 17,288 single-nucleotide polymorphism (SNP) loci to evaluate population structure and linkage disequilibrium (LD); to perform a genome-wide association study (GWAs) for heading date, a key character closely correlated with performance in this drought-prone area. Population genetic analysis using both structure and PCA distinguished two main groups composed of the red and white oats, respectively. The white oat group was further divided into two subgroups. LD decay was slower within white lines in linkage groups Mrg01, 02, 04, 12, 13, 15, 23, 33, whereas it was slower within red lines in Mrg03, 05, 06, 11, 21, 24, and 28. Association analysis showed several significant markers associated with heading date on linkage group Mrg13 in white oats and on Mrg01 and Mrg08 in red oats.

Population genomics of Mediterranean oat (A. sativa) reveals high genetic diversity and three loci for heading date

KEY MESSAGE

Genomic analysis of Mediterranean oats reveals high genetic diversity and three loci for adaptation to this environment. This information together with phenotyping and passport data, gathered in an interactive map, will be a vital resource for oat genetic improvement. During the twentieth century, oat landraces have increasingly been replaced by modern cultivars, resulting in loss of genetic diversity. However, landraces have considerable potential to improve disease and abiotic stress tolerance and may outperform cultivars under low input systems. In this work, we assembled a panel of 669 oat landraces from Mediterranean rim and 40 cultivated oat varieties and performed the first large-scale population genetic analysis of both red and white oat types of Mediterranean origin. We created a public database associated with an interactive map to visualize information for each accession. The oat collection was genotyped with 17,288 single-nucleotide polymorphism (SNP) loci to evaluate population structure and linkage disequilibrium (LD); to perform a genome-wide association study (GWAs) for heading date, a key character closely correlated with performance in this drought-prone area. Population genetic analysis using both structure and PCA distinguished two main groups composed of the red and white oats, respectively. The white oat group was further divided into two subgroups. LD decay was slower within white lines in linkage groups Mrg01, 02, 04, 12, 13, 15, 23, 33, whereas it was slower within red lines in Mrg03, 05, 06, 11, 21, 24, and 28. Association analysis showed several significant markers associated with heading date on linkage group Mrg13 in white oats and on Mrg01 and Mrg08 in red oats.

Genetic variation and population structure in China summer maize germplasm

Maize (Zea mays L.) germplasm in China Summer maize ecological region (CSM) or central corn-belt of China is diverse but has not been systematically characterized at molecular level. In this study, genetic variation, genome diversity, linkage disequilibrium patterns, population structure, and characteristics of different heterotic groups were studied using 525,141 SNPs obtained by Genotyping-By-Sequencing (GBS) for 490 inbred lines collected from researchers at CSM region. The SNP density is lower near centromere, but higher near telomere region of maize chromosome, the degree of linkage disequilibrium (r2) vary at different chromosome regions. Majority of the inbred lines (66.05%) show pairwise relative kinship near zero, indicating a large genetic diversity in the CSM breeding germplasm. Using 4849 tagSNPs derived from 3618 haplotype blocks, the 490 inbred lines were delineated into 3 supergroups, 6 groups, and 10 subgroups using ADMIXTURE software. A procedure of assigning inbred lines into heterotic groups using genomic data and tag-SNPs was developed and validated. Genome differentiation among different subgroups measured by Fst, and the genetic diversity within each subgroup measured by GD are both large. The share of heterotic groups that have significant North American germplasm contribution: P, SS, IDT, and X, accounts about 54% of the CSM breeding germplasm collection and has increased significantly in the last two decades. Two predominant types of heterotic pattern in CSM region are: M-Reid group × TSPT group, and X subgroup × Local subgroups.

Genome-Wide Association Study Reveals the Genetic Architecture of Seed Vigor in Oats

Seed vigor is crucial for crop early establishment in the field and is particularly important for forage crop production. Oat (Avena sativa L.) is a nutritious food crop and also a valuable forage crop. However, little is known about the genetics of seed vigor in oats. To investigate seed vigor-related traits and their genetic architecture in oats, we developed an easy-to-implement image-based phenotyping pipeline and applied it to 650 elite oat lines from the Collaborative Oat Research Enterprise (CORE). Root number, root surface area, and shoot length were measured in two replicates. Variables such as growth rate were derived. Using a genome-wide association (GWA) approach, we identified 34 and 16 unique loci associated with root traits and shoot traits, respectively, which corresponded to 41 and 16 unique SNPs at a false discovery rate < 0.1. Nine root-associated loci were organized into four sets of homeologous regions, while nine shoot-associated loci were organized into three sets of homeologous regions. The context sequences of five trait-associated markers matched to the sequences of rice, Brachypodium and maize (E-value < 10-10), including three markers matched to known gene models with potential involvement in seed vigor. These were a glucuronosyltransferase, a mitochondrial carrier protein domain containing protein, and an iron-sulfur cluster protein. This study presents the first GWA study on oat seed vigor and data of this study can provide guidelines and foundation for further investigations.

Genetic diversity and genome-wide association analysis in Chinese hulless oat germplasm

Genotyping-by-sequencing (GBS)-derived molecular markers reveal the distinct genetic population structure and relatively narrow genetic diversity of Chinese hulless oat landraces. Four markers linked to the naked grain gene (N1) are identified by genome-wide association study (GWAS). Interest in hulless oat (Avena sativa ssp. nuda), a variant of common oat (A. sativa) domesticated in Western Asia, has increased in recent years due to its free-threshing attribute and its domestication history. However, the genetic diversity and population structure of hulless oat, as well as the genetic mechanism of hullessness, are poorly understood. In this study, the genetic diversity and population structure of a worldwide sample of 805 oat lines including 186 hulless oats were investigated using genotyping-by-sequencing. Population structure analyses showed a strong genetic differentiation between hulless landraces vs other oat lines, including the modern hulless cultivars. The distinct subpopulation stratification of hulless landraces and their low genetic diversity suggests that a domestication bottleneck existed in hulless landraces. Additionally, low genetic diversity within European oats and strong differentiation between the spring oats and southern origin oat lines revealed by previous studies were also observed in this study. Genomic regions contributing to these genetic differentiations suggest that genetic loci related to growth habit and stress resistance may have been under intense selection, rather than the hulless-related genomic regions. Genome-wide association analysis detected four markers that were highly associated with hullessness. Three of these were mapped on linkage group Mrg21 at a genetic position between 195.7 and 212.1 cM, providing robust evidence that the dominant N1 locus located on Mrg21 is the single major factor controlling this trait.

Quantitative Trait Loci Associated with Gray Leaf Spot Resistance in St. Augustinegrass

Gray leaf spot (GLS), caused by Magnaporthe grisea, is a major fungal disease of St. Augustinegrass (Stenotaphrum secundatum), causing widespread blighting of the foliage under warm, humid conditions. To identify quantitative trait loci (QTL) controlling GLS resistance, an F₁ mapping population consisting of 153 hybrids was developed from crosses between cultivar Raleigh (susceptible parent) and plant introduction PI 410353 (resistant parent). Single-nucleotide polymorphism (SNP) markers generated from genotyping-by-sequencing constituted nine linkage groups for each parental linkage map. The Raleigh map consisted of 2,257 SNP markers and spanned 916.63 centimorgans (cM), while the PI 410353 map comprised 511 SNP markers and covered 804.27 cM. GLS resistance was evaluated under controlled environmental conditions with measurements of final disease incidence and lesion length. Additionally, two derived traits, area under the disease progress curve and area under the lesion expansion curve, were calculated for QTL analysis. Twenty QTL were identified as being associated with these GLS resistance traits, which explained 7.6 to 37.2% of the total phenotypic variation. Three potential GLS QTL "hotspots" were identified on two linkage groups: P2 (106.26 to 110.36 cM and 113.15 to 116.67 cM) and P5 (17.74 to 19.28 cM). The two major effect QTL glsp2.3 and glsp5.2 together reduced 20.2% of disease incidence in this study. Sequence analysis showed that two candidate genes encoding β-1,3-glucanases were found in the intervals of two QTL, which might function in GLS resistance response. These QTL and linked markers can be potentially used to assist the transfer of GLS resistance genes to elite St. Augustinegrass breeding lines.

Genome-Wide SNP Discovery and Mapping QTLs for Seed Iron and Zinc Concentrations in Chickpea (Cicer arietinum L.)

Biofortification through plant breeding is a cost-effective and sustainable approach towards addressing micronutrient malnutrition prevailing across the globe. Screening cultivars for micronutrient content and identification of quantitative trait loci (QTLs)/genes and markers help in the development of biofortified varieties in chickpea (Cicer arietinum L.). With the aim of identifying the genomic regions controlling seed Fe and Zn concentrations, the F2:3 population derived from a cross between MNK-1 and Annigeri 1 was genotyped using genotyping by sequencing approach and evaluated for Fe and Zn concentration. An intraspecific genetic linkage map comprising 839 single nucleotide polymorphisms (SNPs) spanning a total distance of 1,088.04 cM with an average marker density of 1.30 cM was constructed. By integrating the linkage map data with the phenotypic data of the F2:3 population, a total of 11 QTLs were detected for seed Fe concentration on CaLG03, CaLG04, and CaLG05, with phenotypic variation explained ranging from 7.2% (CaqFe3.4) to 13.4% (CaqFe4.2). For seed Zn concentration, eight QTLs were identified on CaLG04, CaLG05, and CaLG08. The QTLs individually explained phenotypic variations ranging between 5.7% (CaqZn8.1) and 13.7% (CaqZn4.3). Three QTLs for seed Fe and Zn concentrations (CaqFe4.4, CaqFe4.5, and CaqZn4.1) were colocated in the "QTL-hotspot" region on CaLG04 that harbors several drought tolerance-related QTLs. We identified genes in the QTL regions that encode iron-sulfur metabolism and zinc-dependent alcohol dehydrogenase activity on CaLG03, iron ion binding oxidoreductase on CaLG04, and zinc-induced facilitator-like protein and ZIP zinc/iron transport family protein on CaLG05. These genomic regions and the associated markers can be used in marker-assisted selection to increase seed Fe and Zn concentrations in agronomically superior chickpea varieties.

Advancing crested wheatgrass [Agropyron cristatum (L.) Gaertn.] breeding through genotyping-by-sequencing and genomic selection

Crested wheatgrass [Agropyron cristatum (L.) Gaertn.] provides high quality, highly palatable forage for early season grazing. Genetic improvement of crested wheatgrass has been challenged by its complex genome, outcrossing nature, long breeding cycle, and lack of informative molecular markers. Genomic selection (GS) has potential for improving traits of perennial forage species, and genotyping-by-sequencing (GBS) has enabled the development of genome-wide markers in non-model polyploid plants. An attempt was made to explore the utility of GBS and GS in crested wheatgrass breeding. Sequencing and phenotyping 325 genotypes representing 10 diverse breeding lines were performed. Bioinformatics analysis identified 827, 3,616, 14,090 and 46,136 single nucleotide polymorphism markers at 20%, 30%, 40% and 50% missing marker levels, respectively. Four GS models (BayesA, BayesB, BayesCπ, and rrBLUP) were examined for the accuracy of predicting nine agro-morphological and three nutritive value traits. Moderate accuracy (0.20 to 0.32) was obtained for the prediction of heading days, leaf width, plant height, clump diameter, tillers per plant and early spring vigor for genotypes evaluated at Saskatoon, Canada. Similar accuracy (0.29 to 0.35) was obtained for predicting fall regrowth and plant height for genotypes evaluated at Swift Current, Canada. The Bayesian models displayed similar or higher accuracy than rrBLUP. These findings show the feasibility of GS application for a non-model species to advance plant breeding.

Localization of the Stem Rust Resistance Gene Pg2 to Linkage Group Mrg20 in Cultivated Oat (Avena sativa)

Stem rust is an important disease of cultivated oat (Avena sativa) caused by Puccinia graminis f. sp. avenae. In North America, host resistance is the primary strategy to control this disease and is conferred by a relatively small number of resistance genes. Pg2 is a widely deployed stem rust resistance gene that originates from cultivated oat. Oat breeders wish to develop cultivars with multiple Pg genes to slow the breakdown of single gene resistance, and often require DNA markers suited for marker-assisted selection. Our objectives were to (i) construct high density linkage maps for a major oat stem rust resistance gene using three biparental mapping populations, (ii) develop Kompetitive allele-specific PCR (KASP) assays for Pg2-linked single-nucleotide polymorphisms (SNPs), and (iii) test the prediction accuracy of those markers with a diverse panel of spring oat lines and cultivars. Genotyping-by-sequencing SNP markers linked to Pg2 were identified in an AC Morgan/CDC Morrison recombinant inbred line (RIL) population. Pg2-linked SNPs were then analyzed in an AC Morgan/RL815 F₂ population and an AC Morgan/CDC Dancer RIL population. Linkage analysis identified a common location for Pg2 in all three populations on linkage group Mrg20 of the oat consensus genetic map. The most predictive markers were identified and converted to KASP assays for use in oat breeding programs. When used in combination, the KASP assays for the SNP loci avgbs2_126549.1.46 and avgbs_cluster_23819.1.27 were highly predictive of Pg2 status in panel of 54 oat breeding lines and cultivars.

SNP Genotyping with Target Amplicon Sequencing Using a Multiplexed Primer Panel and Its Application to Genomic Prediction in Japanese Cedar, Cryptomeria japonica (L.f.) D.Don

Along with progress in sequencing technology and accumulating knowledge of genome and gene sequences, molecular breeding techniques have been developed for predicting the genetic potential of individual genotypes and for selecting superior individuals. For Japanese cedar (Cryptomeria japonica (L.f.) D.Don), which is the most common coniferous species in Japanese forestry, we constructed a custom primer panel for target amplicon sequencing in order to simultaneously determine 3034 informative single nucleotide polymorphisms (SNPs). We performed primary evaluation of the custom primer panel with actual sequencing and in silico PCR. Genotyped SNPs had a distribution over almost the entire region of the C. japonica linkage map and verified the high reproducibility of genotype calls compared to SNPs obtained by genotyping arrays. Genotyping was performed for 576 individuals of the F1 population, and genomic prediction models were constructed for growth and wood property-related traits using the genotypes. Amplicon sequencing with the custom primer panel enables efficient obtaining genotype data in order to perform genomic prediction, manage clones, and advance forest tree breeding.

Narrow genetic base shapes population structure and linkage disequilibrium in an industrial oilseed crop, Brassica carinata A. Braun

Ethiopian mustard (Brassica carinata A. Braun) is an emerging sustainable source of vegetable oil, in particular for the biofuel industry. The present study exploited genome assemblies of the Brassica diploids, Brassica nigra and Brassica oleracea, to discover over 10,000 genome-wide SNPs using genotype by sequencing of 620 B. carinata lines. The analyses revealed a SNP frequency of one every 91.7 kb, a heterozygosity level of 0.30, nucleotide diversity levels of 1.31 × 10-05, and the first five principal components captured only 13% molecular variation, indicating low levels of genetic diversity among the B. carinata collection. Genome bias was observed, with greater SNP density found on the B subgenome. The 620 lines clustered into two distinct sub-populations (SP1 and SP2) with the majority of accessions (88%) clustered in SP1 with those from Ethiopia, the presumed centre of origin. SP2 was distinguished by a collection of breeding lines, implicating targeted selection in creating population structure. Two selective sweep regions on B3 and B8 were detected, which harbour genes involved in fatty acid and aliphatic glucosinolate biosynthesis, respectively. The assessment of genetic diversity, population structure, and LD in the global B. carinata collection provides critical information to assist future crop improvement.

SNP Markers and Evaluation of Duplicate Holdings of Brassica oleracea in Two European Genebanks

Around the world, there are more than 1500 genebanks storing plant genetic resources to be used in breeding and research. Such resources are essential for future food security, but many genebanks experience backlogs in their conservation work, often combined with limited budgets. Therefore, avoiding duplicate holdings is on the agenda. A process of coordination has started, aiming at sharing the responsibility of maintaining the unique accessions while allowing access according to the international treaty for plant genetic resources. Identifying duplicate holdings based on passport data has been one component of this. In the past, and especially in vegetables, different selections within the same varieties were common and the naming practices of cultivars/selections were flexible. Here, we examined 10 accession pairs/groups of cabbage (Brassica oleracea var. capitata) with similar names maintained in the Russian and Nordic genebanks. The accessions were analyzed for 11 morphological traits and with a SNP (Single Nucleotide Polymorphism) array developed for B. napus. Both proved to be useful tools for understanding the genetic structure among the accessions and for identifying duplicates, and a subset of 500 SNP markers are suggested for future Brassica oleracea genetic characterization. Within five out of 10 pairs/groups, we detected clear genetic differences among the accessions, and three of these were confirmed by significant differences in one or several morphological traits. In one case, a white cabbage and a red cabbage had similar accession names. The study highlights the necessity to be careful when identifying duplicate accessions based solely on the name, especially in older cross-pollinated species such as cabbage.

Parallel flowering time clines in native and introduced ragweed populations are likely due to adaptation

As introduced species expand their ranges, they often encounter differences in climate which are often correlated with geography. For introduced species, encountering a geographically variable climate sometimes leads to the re-establishment of clines seen in the native range. However, clines can also be caused by neutral processes, and so it is important to gather additional evidence that population differentiation is the result of selection as opposed to nonadaptive processes. Here, we examine phenotypic and genetic differences in ragweed from the native (North America) and introduced (European) ranges. We used a common garden to assess phenotypic differentiation in size and flowering time in ragweed populations. We found significant parallel clines in flowering time in both North America and Europe. Height and branch number had significant clines in North America, and, while not statistically significant, the patterns in Europe were the same. We used SNP data to assess population structure in both ranges and to compare phenotypic differentiation to neutral genetic variation. We failed to detect significant patterns of isolation by distance, geographic patterns in population structure, or correlations between the major axes of SNP variation and phenotypes or latitude of origin. We conclude that the North American clines in size and the parallel clines seen for flowering time are most likely the result of adaptation.

Mapping of the Oat Crown Rust Resistance Gene Pc39 Relative to Single Nucleotide Polymorphism Markers

Crown rust, caused by Puccinia coronata f. sp. avenae Eriks. (Pca), is among the most important oat diseases resulting in significant yield losses in many growing regions. A gene-for-gene interaction is well established in this pathosystem and has been exploited by oat breeders to control crown rust. Pc39 is a seedling crown rust resistance gene that has been widely deployed in North American oat breeding. DNA markers are desired to accurately predict the specific Pc genes present in breeding germplasm. The objectives of the study were as follows: (i) to map Pc39 in two recombinant inbred line (RIL) populations (AC Assiniboia/MN841801 and AC Medallion/MN841801) and (ii) to identify single nucleotide polymorphism (SNP) markers for postulation of Pc39 in oat germplasm. Pc39 was mapped to a linkage group consisting of 16 SNP markers, which placed the gene on linkage group Mrg11 (chromosome 1C) of the oat consensus map. Pc39 cosegregated with SNP marker GMI_ES01_c12570_390 in the AC Assiniboia/MN841801 RIL population and was flanked by the SNP markers avgbs_126086.1.41 and GMI_ES15_c276_702, with genetic distances of 1.7 and 0.3 cM, respectively. In the AC Medallion/MN841801 RIL population, similar results were obtained but the genetic distances of the flanking markers were 0.4 and 0.4 cM, respectively. Kompetitive Allele-Specific PCR assays were successfully designed for Pc39-linked SNP loci. Two SNP loci defined a haplotype that accurately predicted Pc39 status in a diverse panel of oat germplasm and will be useful for marker-assisted selection in oat breeding.

Chromosomal location of the crown rust resistance gene Pc98 in cultivated oat (Avena sativa L.)

SNP loci linked to the crown rust resistance gene Pc98 were identified by linkage analysis and KASP assays were developed for marker-assisted selection in breeding programs. Crown rust is among the most damaging diseases of oat and is caused by Puccinia coronata var. avenae f. sp. avenae (Urban and Marková) (Pca). Host resistance is the preferred method to prevent crown rust epidemics. Pc98 is a race-specific, seedling crown rust resistance gene obtained from the wild oat Avena sterilis accession CAV 1979 that is effective at all growth stages of oat. Virulence to Pc98 has been very low in the Pca populations that have been tested. The objectives of this study were to develop SNP markers linked to Pc98 for use in marker-assisted selection and to locate Pc98 on the oat consensus map. The Pc98 gene was mapped using F_2:3 populations developed from the crosses Pc98/Bingo and Pc98/Kasztan, where Pc98 is a single-gene line carrying Pc98. Both populations were evaluated in seedling inoculation experiments. Pc98 was mapped relative to Kompetitive Allele-Specific PCR SNP markers in both populations, placing Pc98 on the Mrg20 linkage group of the consensus map. Pc98 was bracketed by two SNP markers GMI_ES22_c3052_382_kom399 and GMI_ES14_lrc18344_662_kom398 in the Pc98/Bingo mapping population with genetic distances of 0.9 cM and 0.3 cM, respectively. Pc98 co-segregated with four SNP markers in the Pc98/Kasztan population, and the closest flanking markers were GMI_DS_LB_6017_kom367 and avgbs2_153634.1.59_kom410 with genetic distances of 0.7 cM and 0.3 cM, respectively. Two SNP loci defined a haplotype that accurately predicted Pc98 status in a diverse group of oat germplasm, which will be valuable for marker-assisted selection of Pc98 in breeding of new oat cultivars.

Linkage Disequilibrium, Effective Population Size and Genomic Inbreeding Rates in American Mink Using Genotyping-by-Sequencing Data

Knowledge of linkage disequilibrium (LD) patterns is necessary to determine the minimum density of markers required for genomic studies and to infer historical changes as well as inbreeding events in the populations. In this study, we used genotyping-by-sequencing (GBS) approach to detect single nucleotide polymorphisms (SNPs) across American mink genome and further to estimate LD, effective population size (Ne), and inbreeding rates based on excess of homozygosity (F_HOM) and runs of homozygosity (ROH). A GBS assay was constructed based on the sequencing of ApeKI-digested libraries from 285 American mink using Illumina HiSeq Sequencer. Data of 13,321 SNPs located on 46 scaffolds was used to perform LD analysis. The average LD (r² ± SD) between adjacent SNPs was 0.30 ± 0.35 over all scaffolds with an average distance of 51 kb between markers. The average r² < 0.2 was observed at inter-marker distances of >40 kb, suggesting that at least 60,000 informative SNPs would be required for genomic selection in American mink. The Ne was estimated to be 116 at five generations ago. In addition, the most rapid decline of population size was observed between 100 and 200 generations ago. Our results showed that short extensions of homozygous genotypes (500 kb to 1 Mb) were abundant across the genome and accounted for 33% of all ROH identified. The average inbreeding coefficient based on ROH longer than 1 Mb was 0.132 ± 0.042. The estimations of F_HOM ranged from −0.44 to 0.34 among different samples with an average of 0.15 over all individuals. This study provided useful insights to determine the density of SNP panel providing enough statistical power and accuracy in genomic studies of American mink. Moreover, these results confirmed that GBS approach can be considered as a useful tool for genomic studies in American mink.

Implementing within-cross genomic prediction to reduce oat breeding costs

A barrier to the adoption of genomic prediction in small breeding programs is the initial cost of genotyping material. Although decreasing, marker costs are usually higher than field trial costs. In this study we demonstrate the utility of stratifying a narrow-base biparental oat population genotyped with a modest number of markers to employ genomic prediction at early and later generations. We also show that early generation genotyping data can reduce the number of lines for later phenotyping based on selections of siblings to progress. Using sets of small families selected at an early generation could enable the use of genomic prediction for adaptation to multiple target environments at an early stage in the breeding program. In addition, we demonstrate that mixed marker data can be effectively integrated to combine cheap dominant marker data (including legacy data) with more expensive but higher density codominant marker data in order to make within generation and between lineage predictions based on genotypic information. Taken together, our results indicate that small programs can test and initiate genomic predictions using sets of stratified, narrow-base populations and incorporating low density legacy genotyping data. This can then be scaled to include higher density markers and a broadened population base.

A targeted genotyping-by-sequencing tool (Rapture) for genomics-assisted breeding in oat

We adapted and tested a Rapture assay as an enhancement of genotyping-by-sequencing (GBS) in oat (Avena sativa). This assay was based on an additional bait-based capture of specific DNA fragments representing approximately 10,000 loci within the enzyme-based complexity reduction provided by GBS. By increasing the specificity of GBS to include only those fragments that provided effective polymorphic markers, it was possible to achieve deeper sequence coverage of target markers, while simultaneously sequencing a greater number of samples on a single unit of next-generation sequencing. The Rapture assay consistently out-performed the GBS assay when filtering markers at 80% completeness or greater, even though the total number of reads per sample was only 25% that of GBS. The reduced sequencing cost per sample for Rapture more than compensated for the increased cost of the capture reaction. Thus, Rapture generated a more repeatable set of marker data at a cost per sample that was approximately 40% less than GBS. Additional advantages of Rapture included accurate identification of heterozygotes, and the possibility to increase the depth or length of sequence reads with less impact on the cost per sample. We tested Rapture for genomic selection and diversity analysis and concluded that it is an effective alternative to GBS or other SNP assays. We recommend the use of Rapture in oat and the development of similar assays in other crops with large complex genomes.

Mapping of the stem rust resistance gene Pg13 in cultivated oat

The widely deployed, oat stem rust resistance gene Pg13 was mapped by linkage analysis and association mapping, and KASP markers were developed for marker-assisted selection in breeding programs. Pg13 is one of the most extensively deployed stem rust resistance genes in North American oat cultivars. Identification of markers tightly linked to this gene will be useful for routine marker-assisted selection, identification of gene pyramids, and retention of the gene in backcrosses and three-way crosses. To this end, high-density linkage maps were constructed in four bi-parental mapping populations using SNP markers identified from 6K oat Infinium iSelect and genotyping-by-sequencing platforms. Additionally, genome-wide associations were identified using two sets of association panels consisting of diverse elite oat lines in one set and landrace accessions in the other. The results showed that Pg13 was located at approximately 67.7 cM on linkage group Mrg18 of the consensus genetic map. The gene co-segregated with the 7C-17A translocation breakpoint and with crown rust resistance gene Pc91. Co-segregating markers with the best prediction accuracy were identified at 67.7-68.5 cM on Mrg18. KASP assays were developed for linked SNP loci for use in oat breeding.

Genome wide association study of 5 agronomic traits in olive (Olea europaea L.)

Olive (Olea europaea L.) is one of the most economically and historically important fruit crops worldwide. Genetic progress for valuable agronomic traits has been slow in olive despite its importance and benefits. Advances in next generation sequencing technologies provide inexpensive and highly reproducible genotyping approaches such as Genotyping by Sequencing, enabling genome wide association study (GWAS). Here we present the first comprehensive GWAS study on olive using GBS. A total of 183 accessions (FULL panel) were genotyped using GBS, 94 from the Turkish Olive GenBank Resource (TOGR panel) and 89 from the USDA-ARS National Clonal Germplasm Repository (NCGR panel) in the USA. After filtering low quality and redundant markers, GWAS was conducted using 24,977 SNPs in FULL, TOGR and NCGR panels. In total, 52 significant associations were detected for leaf length, fruit weight, stone weight and fruit flesh to pit ratio using the MLM_K. Significant GWAS hits were mapped to their positions and 19 candidate genes were identified within a 10-kb distance of the most significant SNP. Our findings provide a framework for the development of markers and identification of candidate genes that could be used in olive breeding programs.

Linkage mapping and quantitative trait loci analysis of sweetness and other fruit quality traits in papaya

BACKGROUND

The identification and characterisation of quantitative trait loci (QTL) is an important step towards identifying functional sequences underpinning important crop traits and for developing accurate markers for selective breeding strategies. In this study, a genotyping-by-sequencing (GBS) approach detected QTL conditioning desirable fruit quality traits in papaya.

RESULTS

For this, a linkage map was constructed comprising 219 single nucleotide polymorphism (SNP) loci across 10 linkage groups and covering 509 centiMorgan (cM). In total, 21 QTLs were identified for seven key fruit quality traits, including flesh sweetness, fruit weight, fruit length, fruit width skin freckle, flesh thickness and fruit firmness. Several QTL for flesh sweetness, fruit weight, length, width and firmness were stable across harvest years and individually explained up to 19.8% of the phenotypic variance of a particular trait. Where possible, candidate genes were proposed and explored further for their application to marker-assisted breeding.

CONCLUSIONS

This study has extended knowledge on the inheritance and genetic control for key papaya physiological and fruit quality traits. Candidate genes together with associated SNP markers represent a valuable resource for the future of strategic selective breeding of elite Australian papaya cultivars.

Genome-wide association study for backfat thickness at 100 kg and loin muscle thickness in domestic pigs based on genotyping by sequencing

Both backfat thickness at 100 kg (B100) and loin muscle thickness (LMT) are economically important traits in pigs. In this study, a total of 1,200 pigs (600 Landrace and 600 Yorkshire pigs) were examined with genotyping by sequencing. A total of 345,570 single nucleotide polymorphisms (SNPs) were obtained from 1,200 pigs. Then, a single marker regression test was used to conduct a genome-wide association study for B100 and LMT. A total of 8 and 90 significant SNPs were detected for LMT and B100, respectively. Interestingly, two shared significant loci [located at Sus scrofa chromosome (SSC) 6: 149876694 and SSC12: 46226580] were detected in two breeds for B100. Furthermore, three potential candidate genes were found for LMT and B100. The positional candidate gene FAM3C (SSC18: 25573656, P = 2.48 × 10^-9), which controls the survival, growth, and differentiation of tissues and cells, was found for LMT in Landrace pigs. At SSC9: 6.78-6.82 Mb in Landrace pigs, the positional candidate gene, INPPL1, which has a negative regulatory effect on diet-induced obesity and is involved in the regulation of insulin function, was found for B100. The candidate gene, RAB35, which regulates the adipocyte glucose transporter SLC2A4/GLUT4, was identified at approximately SSC14: 40.09-40.13 Mb in Yorkshire pigs. The results of this GWAS will greatly advance our understanding of the genetic architecture of the LMT and B100 traits. However, these identified loci and genes need to be further verified in more pig populations, and their functions also need to be validated by more biological experiments in pigs.

Identification of Quantitative Trait Loci Associated with Nutrient Use Efficiency Traits, Using SNP Markers in an Early Backcross Population of Rice (Oryza sativa L.)

The development of rice cultivars with nutrient use efficiency (NuUE) is highly crucial for sustaining global rice production in Asia and Africa. However, this requires a better understanding of the genetics of NuUE-related traits and their relationship to grain yield. In this study, simultaneous efforts were made to develop nutrient use efficient rice cultivars and to map quantitative trait loci (QTLs) governing NuUE-related traits in rice. A total of 230 BC₁F₅ introgression lines (ILs) were developed from a single early backcross population involving Weed Tolerant Rice 1, as the recipient parent, and Hao-an-nong, as the donor parent. The ILs were cultivated in field conditions with a different combination of fertilizer schedule under six nutrient conditions: minus nitrogen (–N), minus phosphorus (–P), (–NP), minus nitrogen phosphorus and potassium (–NPK), 75% of recommended nitrogen (75N), and NPK. Analysis of variance revealed that significant differences (p < 0.01) were noted among ILs and treatments for all traits. A high-density linkage map was constructed by using 704 high-quality single nucleotide polymorphism (SNP) markers. A total of 49 main-effect QTLs were identified on all chromosomes, except on chromosome 7, 11 and 12, which are showing 20.25% to 34.68% of phenotypic variation. With further analysis of these QTLs, we refined them to four top hotspot QTLs (QTL harbor-I to IV) located on chromosomes 3, 5, 9, and 11. However, we identified four novel putative QTLs for agronomic efficiency (AE) and 22 QTLs for partial factor productivity (PFP) under –P and 75N conditions. These interval regions of QTLs, several transporters and genes are located that were involved in nutrient uptake from soil to plant organs and tolerance to biotic and abiotic stresses. Further, the validation of these potential QTLs, genes may provide remarkable value for marker-aided selection and pyramiding of multiple QTLs, which would provide supporting evidence for the enhancement of grain yield and cloning of NuUE tolerance-responsive genes in rice.

Mapping Oat Crown Rust Resistance Gene Pc45 Confirms Association with PcKM

Molecular mapping of crown rust resistance genes is important to effectively utilize these genes and improve breeding efficiency through marker-assisted selection. Pc45 is a major race-specific crown rust resistance gene initially identified in the wild hexaploid oat Avena sterilis in the early 1970s. This gene was transferred to cultivated oat (Avena sativa) and has been used as a differential for identification of crown rust races since 1974. Previous research identified an association between virulence to Pc45 and PcKM, a crown rust resistance gene in the varieties ‘Kame’ and ‘Morton’. This study was undertaken to reveal the relationship between Pc45 and PcKM. Pc45 was studied in the crosses ‘AC Morgan’/Pc45 and ‘Kasztan’/Pc45, where Pc45 is the differential line carrying Pc45. F₂ progenies and F_2:3 families of both populations were inoculated with the crown rust isolate CR258 (race NTGG) and single gene segregation ratios were observed. SNP markers for PcKM were tested on these populations and linkage maps were generated. In addition, 17 newly developed SNP markers identified from genotyping-by-sequencing (GBS) data were mapped in these two populations, plus another three populations segregating for Pc45 or PcKM. Pc45 and PcKM mapped to the same location of Mrg08 (chromosome 12D) of the oat chromosome-anchored consensus map. These results strongly suggest that Pc45 and PcKM are the same resistance gene, but allelism (i.e., functionally different alleles of the same gene) or tight linkage (i.e., two tightly linked genes) cannot be ruled out based on the present data.

Efficient curation of genebanks using next generation sequencing reveals substantial duplication of germplasm accessions

Genebanks are valuable resources for crop improvement through the acquisition, ex-situ conservation and sharing of unique germplasm among plant breeders and geneticists. With over seven million existing accessions and increasing storage demands and costs, genebanks need efficient characterization and curation to make them more accessible and usable and to reduce operating costs, so that the crop improvement community can most effectively leverage this vast resource of untapped novel genetic diversity. However, the sharing and inconsistent documentation of germplasm often results in unintentionally duplicated collections with poor characterization and many identical accessions that can be hard or impossible to identify without passport information and unmatched accession identifiers. Here we demonstrate the use of genotypic information from these accessions using a cost-effective next generation sequencing platform to find and remove duplications. We identify and characterize over 50% duplicated accessions both within and across genebank collections of Aegilops tauschii, an important wild relative of wheat and source of genetic diversity for wheat improvement. We present a pipeline to identify and remove identical accessions within and among genebanks and curate globally unique accessions. We also show how this approach can also be applied to future collection efforts to avoid the accumulation of identical material. When coordinated across global genebanks, this approach will ultimately allow for cost effective and efficient management of germplasm and better stewarding of these valuable resources.

Efficient curation of genebanks using next generation sequencing reveals substantial duplication of germplasm accessions

Genebanks are valuable resources for crop improvement through the acquisition, ex-situ conservation and sharing of unique germplasm among plant breeders and geneticists. With over seven million existing accessions and increasing storage demands and costs, genebanks need efficient characterization and curation to make them more accessible and usable and to reduce operating costs, so that the crop improvement community can most effectively leverage this vast resource of untapped novel genetic diversity. However, the sharing and inconsistent documentation of germplasm often results in unintentionally duplicated collections with poor characterization and many identical accessions that can be hard or impossible to identify without passport information and unmatched accession identifiers. Here we demonstrate the use of genotypic information from these accessions using a cost-effective next generation sequencing platform to find and remove duplications. We identify and characterize over 50% duplicated accessions both within and across genebank collections of Aegilops tauschii, an important wild relative of wheat and source of genetic diversity for wheat improvement. We present a pipeline to identify and remove identical accessions within and among genebanks and curate globally unique accessions. We also show how this approach can also be applied to future collection efforts to avoid the accumulation of identical material. When coordinated across global genebanks, this approach will ultimately allow for cost effective and efficient management of germplasm and better stewarding of these valuable resources.

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.

Construction of a high-density linkage map and QTL detection of downy mildew resistance in Vitis aestivalis-derived 'Norton'

A major QTL for downy mildew resistance was detected on chromosome 18 (Rpv27) in Vitis aestivalis-derived 'Norton' based on a high-resolution linkage map with SNP and SSR markers as well as 2 years of field and laboratory phenotyping data. Grapevine downy mildew caused by the oomycete Plasmopara viticola is one of the most widespread and destructive diseases, particularly in humid viticultural areas where it damages green tissues and defoliates vines. Traditional Vitis vinifera wine grape cultivars are susceptible to downy mildew whereas several North American and a few Asian cultivars possess various levels of resistance to this disease. To identify genetic determinants of downy mildew resistance in V. aestivalis-derived 'Norton,' a mapping population with 182 genotypes was developed from a cross between 'Norton' and V. vinifera 'Cabernet Sauvignon' from which a consensus map was constructed via 411 simple sequence repeat (SSR) markers. Using genotyping-by-sequencing, 3825 single nucleotide polymorphism (SNP) markers were also generated. Of these, 1665 SNP and 407 SSR markers were clustered into 19 linkage groups in 159 genotypes, spanning a genetic distance of 2203.5 cM. Disease progression in response to P. viticola was studied in this population for 2 years under both laboratory and field conditions, and strong correlations were observed among data sets (Spearman correlation coefficient = 0.57-0.79). A quantitative trait loci (QTL) analysis indicated a resistance locus on chromosome 18, here named Rpv27, explaining 33.8% of the total phenotypic variation. Flanking markers closely linked with the trait can be further used for marker-assisted selection in the development of new cultivars with resistance to downy mildew.

PK-profiling method for identifying the expression of resistance-associated genes in partially resistant oats to crown rust

BACKGROUND

Protein kinases play a key role in plant cell homeostasis and the activation of defense mechanisms. Partial resistance to fungi in plants is interesting because of its durability. However, the variable number of minor loci associated with this type of resistance hampers the reliable identification of the full range of genes involved. The present work reports the technique of protein kinase (PK)-profiling for the identification of the PK genes induced in the partially resistant oats line MN841801-1 following exposure to the fungus Puccinia coronata. This is the first time this technique has been used with cDNA (complementary DNA) from a suppression subtractive hybridization library obtained after the hybridization of cDNAs from inoculated and mock-inoculated plants.

RESULTS

Six degenerate primers based on the conserved domains of protein kinases were used in a PK-profiling assay including cDNA from mock-inoculated leaves and subtracted cDNA. Of the 75.7% of sequences cloned and sequenced that showed significant similarity to resistance genes, 76% were found to code for PKs. Translation and ClustalW2 alignment of each sequence cloned with the complete sequences of the most similar B. distachyon PKs allowed those of the partially resistant oat line to be deduced and characterized. Further, a phylogenetic study carried out after alignment of these B. distachyon PK sequences with the most similar protein sequences of related species also allowed to deduce different functions for the PK cloned. RT-qPCR (Reverse Transcription-quantitative PCR) was analyzed on nine representative sequences to validate the reliability of the employed PK-profiling method as a tool for identifying the expression of resistance-associated genes.

CONCLUSIONS

PK-profiling would appear to be a useful tool for the identification of the PKs expressed in oats after challenge by P. coronata, and perhaps other pathogens. Most of the PKs studied are related to receptor-like protein kinases expressed shortly after infection. This is in agreement with previous studies indicating a close relationship between partial resistance and the first layer of defense against pathogen used by plants.

Evidence for Strong Kinship Influence on the Extent of Linkage Disequilibrium in Cultivated Common Beans

Phaseolus vulgaris is an important grain legume for human consumption. Recently, association mapping studies have been performed for the species aiming to identify loci underlying quantitative variation of traits. It is now imperative to know whether the linkage disequilibrium (LD) reflects the true association between a marker and causative loci. The aim of this study was to estimate and analyze LD on a diversity panel of common beans using ordinary r² and r2 extensions which correct bias due to population structure (rS²), kinship (rV²), and both (rVS²). A total of 10,362 single nucleotide polymorphisms (SNPs) were identified by genotyping by sequencing (GBS), and polymorphisms were found to be widely distributed along the 11 chromosomes. In terms of r2, high values of LD (over 0.8) were identified between SNPs located at opposite chromosomal ends. Estimates for rV² were lower than those for rS². Results for rV² and rVS² were similar, suggesting that kinship may also include information on population structure. Over genetic distance, LD decayed to 0.1 at a distance of 1 Mb for rVS². Inter-chromosomal LD was also evidenced. This study showed that LD estimates decay dramatically according to the population structure, and especially the degree of kinship. Importantly, the LD estimates reported herein may influence our ability to perform association mapping studies on P. vulgaris.