Haplotype-based genotyping-by-sequencing in oat genome research.

In a de novo genotyping-by-sequencing (GBS) analysis of short, 64-base tag-level haplotypes in 4657 accessions of cultivated oat, we discovered 164741 tag-level (TL) genetic variants containing 241224 SNPs. From this, the marker density of an oat consensus map was increased by the addition of more than 70000 loci. The mapped TL genotypes of a 635-line diversity panel were used to infer chromosome-level (CL) haplotype maps. These maps revealed differences in the number and size of haplotype blocks, as well as differences in haplotype diversity between chromosomes and subsets of the diversity panel. We then explored potential benefits of SNP vs. TL vs. CL GBS variants for mapping, high-resolution genome analysis and genomic selection in oats. A combined genome-wide association study (GWAS) of heading date from multiple locations using both TL haplotypes and individual SNP markers identified 184 significant associations. A comparative GWAS using TL haplotypes, CL haplotype blocks and their combinations demonstrated the superiority of using TL haplotype markers. Using a principal component-based genome-wide scan, genomic regions containing signatures of selection were identified. These regions may contain genes that are responsible for the local adaptation of oats to Northern American conditions. Genomic selection for heading date using TL haplotypes or SNP markers gave comparable and promising prediction accuracies of up to r = 0.74. Genomic selection carried out in an independent calibration and test population for heading date gave promising prediction accuracies that ranged between r = 0.42 and 0.67. In conclusion, TL haplotype GBS-derived markers facilitate genome analysis and genomic selection in oat.

High-density marker profiling confirms ancestral genomes of Avena species and identifies D-genome chromosomes of hexaploid oat.

KEY MESSAGE: Genome analysis of 27 oat species identifies ancestral groups, delineates the D genome, and identifies ancestral origin of 21 mapped chromosomes in hexaploid oat. We investigated genomic relationships among 27 species of the genus Avena using high-density genetic markers revealed by genotyping-by-sequencing (GBS). Two methods of GBS analysis were used: one based on tag-level haplotypes that were previously mapped in cultivated hexaploid oat (A. sativa), and one intended to sample and enumerate tag-level haplotypes originating from all species under investigation. Qualitatively, both methods gave similar predictions regarding the clustering of species and shared ancestral genomes. Furthermore, results were consistent with previous phylogenies of the genus obtained with conventional approaches, supporting the robustness of whole genome GBS analysis. Evidence is presented to justify the final and definitive classification of the tetraploids A. insularis, A. maroccana (=A. magna), and A. murphyi as containing D-plus-C genomes, and not A-plus-C genomes, as is most often specified in past literature. Through electronic painting of the 21 chromosome representations in the hexaploid oat consensus map, we show how the relative frequency of matches between mapped hexaploid-derived haplotypes and AC (DC)-genome tetraploids vs. A- and C-genome diploids can accurately reveal the genome origin of all hexaploid chromosomes, including the approximate positions of inter-genome translocations. Evidence is provided that supports the continued classification of a diverged B genome in AB tetraploids, and it is confirmed that no extant A-genome diploids, including A. canariensis, are similar enough to the D genome of tetraploid and hexaploid oat to warrant consideration as a D-genome diploid.

Including marker x environment interactions improves genomic prediction in red clover (Trifolium pratense L.).

Genomic prediction has mostly been used in single environment contexts, largely ignoring genotype x environment interaction, which greatly affects the performance of plants. However, in the last decade, prediction models including marker x environment (MxE) interaction have been developed. We evaluated the potential of genomic prediction in red clover (Trifolium pratense L.) using field trial data from five European locations, obtained in the Horizon 2020 EUCLEG project. Three models were compared: (1) single environment (SingleEnv), (2) across environment (AcrossEnv), (3) marker x environment interaction (MxE). Annual dry matter yield (DMY) gave the highest predictive ability (PA). Joint analyses of DMY from years 1 and 2 from each location varied from 0.87 in Britain and Switzerland in year 1, to 0.40 in Serbia in year 2. Overall, crude protein (CP) was predicted poorly. PAs for date of flowering (DOF), however ranged from 0.87 to 0.67 for Britain and Switzerland, respectively. Across the three traits, the MxE model performed best and the AcrossEnv worst, demonstrating that including marker x environment effects can improve genomic prediction in red clover. Leaving out accessions from specific regions or from specific breeders' material in the cross validation tended to reduce PA, but the magnitude of reduction depended on trait, region and breeders' material, indicating that population structure contributed to the high PAs observed for DMY and DOF. Testing the genomic estimated breeding values on new phenotypic data from Sweden showed that DMY training data from Britain gave high PAs in both years (0.43-0.76), while DMY training data from Switzerland gave high PAs only for year 1 (0.70-0.87). The genomic predictions we report here underline the potential benefits of incorporating MxE interaction in multi-environment trials and could have perspectives for identifying markers with effects that are stable across environments, and markers with environment-specific effects.

Genotype and Environment Affect the Grain Quality and Yield of Winter Oats (Avena sativa L.).

The extent to which the quality and yield of plant varieties are influenced by the environment is important for their successful uptake by end users particularly as climatic fluctuations are resulting in environments that are highly variable from one growing season to another. The genotype-by-environment interaction (GEI) of milling quality and yield was studied using four winter oat varieties in multi-locational trials over 4 years in the U.K. Significant differences across the 22 environments were found between physical grain quality and composition as well as grain yield, with the environment having a significant effect on all of the traits measured. Grain yield was closely related to grain number m-2 whereas milling quality traits were related to grain size attributes. Considerable genotype by environment interaction was obtained for all grain quality traits and stability analysis revealed that the variety Mascani was the least sensitive to the environment for all milling quality traits measured whereas the variety Balado was the most sensitive. Examination of environmental conditions at specific within-year stages of crop development indicated that both temperature and rainfall during grain development were correlated with grain yield and ß-glucan content and with the ease of removing the hull (hullability).

The Genetic Architecture of Milling Quality in Spring Oat Lines of the Collaborative Oat Research Enterprise.

Most oat grains destined for human consumption must possess the ability to pass through an industrial de-hulling process with minimal breakage and waste. Uniform grain size and a high groat to hull ratio are desirable traits related to milling performance. The purpose of this study was to characterize the genetic architecture of traits related to milling quality by identifying quantitative trait loci (QTL) contributing to variation among a diverse collection of elite and foundational spring oat lines important to North American oat breeding programs. A total of 501 lines from the Collaborative Oat Research Enterprise (CORE) panel were evaluated for genome-wide association with 6 key milling traits. Traits were evaluated in 13 location years. Associations for 36,315 markers were evaluated for trait means across and within location years, as well as trait variance across location years, which was used to assess trait stability. Fifty-seven QTL influencing one or more of the milling quality related traits were identified, with fourteen QTL mapped influencing mean and variance across location years. The most prominent QTL was Qkernel.CORE.4D on chromosome 4D at approximately 212 cM, which influenced the mean levels of all traits. QTL were identified that influenced trait variance but not mean, trait mean only and both.

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.

New DArT markers for oat provide enhanced map coverage and global germplasm characterization.

BACKGROUND: Genomic discovery in oat and its application to oat improvement have been hindered by a lack of genetic markers common to different genetic maps, and by the difficulty of conducting whole-genome analysis using high-throughput markers. This study was intended to develop, characterize, and apply a large set of oat genetic markers based on Diversity Array Technology (DArT). RESULTS: Approximately 19,000 genomic clones were isolated from complexity-reduced genomic representations of pooled DNA samples from 60 oat varieties of global origin. These were screened on three discovery arrays, with more than 2000 polymorphic markers being identified for use in this study, and approximately 2700 potentially polymorphic markers being identified for use in future studies. DNA sequence was obtained for 2573 clones and assembled into a non-redundant set of 1770 contigs and singletons. Of these, 705 showed highly significant (Expectation < 10E-10) BLAST similarity to gene sequences in public databases. Based on marker scores in 80 recombinant inbred lines, 1010 new DArT markers were used to saturate and improve the 'Kanota' x 'Ogle' genetic map. DArT markers provided map coverage approximately equivalent to existing markers. After binning markers from similar clones, as well as those with 99% scoring similarity, a set of 1295 non-redundant markers was used to analyze genetic diversity in 182 accessions of cultivated oat of worldwide origin. Results of this analysis confirmed that major clusters of oat diversity are related to spring vs. winter type, and to the presence of major breeding programs within geographical regions. Secondary clusters revealed groups that were often related to known pedigree structure. CONCLUSION: These markers will provide a solid basis for future efforts in genomic discovery, comparative mapping, and the generation of an oat consensus map. They will also provide new opportunities for directed breeding of superior oat varieties, and guidance in the maintenance of oat genetic diversity.

A Consensus Map in Cultivated Hexaploid Oat Reveals Conserved Grass Synteny with Substantial Subgenome Rearrangement.

Hexaploid oat ( L., 2 = 6 = 42) is a member of the Poaceae family and has a large genome (∼12.5 Gb) containing 21 chromosome pairs from three ancestral genomes. Physical rearrangements among parental genomes have hindered the development of linkage maps in this species. The objective of this work was to develop a single high-density consensus linkage map that is representative of the majority of commonly grown oat varieties. Data from a cDNA-derived single-nucleotide polymorphism (SNP) array and genotyping-by-sequencing (GBS) were collected from the progeny of 12 biparental recombinant inbred line populations derived from 19 parents representing oat germplasm cultivated primarily in North America. Linkage groups from all mapping populations were compared to identify 21 clusters of conserved collinearity. Linkage groups within each cluster were then merged into 21 consensus chromosomes, generating a framework consensus map of 7202 markers spanning 2843 cM. An additional 9678 markers were placed on this map with a lower degree of certainty. Assignment to physical chromosomes with high confidence was made for nine chromosomes. Comparison of homeologous regions among oat chromosomes and matches to orthologous regions of rice ( L.) reveal that the hexaploid oat genome has been highly rearranged relative to its ancestral diploid genomes as a result of frequent translocations among chromosomes. Heterogeneous chromosome rearrangements among populations were also evident, probably accounting for the failure of some linkage groups to match the consensus. This work contributes to a further understanding of the organization and evolution of hexaploid grass genomes.

Population Genomics Related to Adaptation in Elite Oat Germplasm.

Six hundred thirty five oat ( L.) lines and 4561 single-nucleotide polymorphism (SNP) loci were used to evaluate population structure, linkage disequilibrium (LD), and genotype-phenotype association with heading date. The first five principal components (PCs) accounted for 25.3% of genetic variation. Neither the eigenvalues of the first 25 PCs nor the cross-validation errors from = 1 to 20 model-based analyses suggested a structured population. However, the PC and = 2 model-based analyses supported clustering of lines on spring oat vs. southern United States origin, accounting for 16% of genetic variation ( < 0.0001). Single-locus -statistic () in the highest 1% of the distribution suggested linkage groups that may be differentiated between the two population subgroups. Population structure and kinship-corrected LD of = 0.10 was observed at an average pairwise distance of 0.44 cM (0.71 and 2.64 cM within spring and southern oat, respectively). On most linkage groups LD decay was slower within southern lines than within the spring lines. A notable exception was found on linkage group Mrg28, where LD decay was substantially slower in the spring subpopulation. It is speculated that this may be caused by a heterogeneous translocation event on this chromosome. Association with heading date was most consistent across location-years on linkage groups Mrg02, Mrg12, Mrg13, and Mrg24.

Genome-wide association study for crown rust (Puccinia coronata f. sp. avenae) and powdery mildew (Blumeria graminis f. sp. avenae) resistance in an oat (Avena sativa) collection of commercial varieties and landraces.

Diseases caused by crown rust (Puccinia coronata f. sp. avenae) and powdery mildew (Blumeria graminis f. sp. avenae) are among the most important constraints for the oat crop. Breeding for resistance is one of the most effective, economical, and environmentally friendly means to control these diseases. The purpose of this work was to identify elite alleles for rust and powdery mildew resistance in oat by association mapping to aid selection of resistant plants. To this aim, 177 oat accessions including white and red oat cultivars and landraces were evaluated for disease resistance and further genotyped with 31 simple sequence repeat and 15,000 Diversity Arrays Technology (DArT) markers to reveal association with disease resistance traits. After data curation, 1712 polymorphic markers were considered for association analysis. Principal component analysis and a Bayesian clustering approach were applied to infer population structure. Five different general and mixed linear models accounting for population structure and/or kinship corrections and two different statistical tests were carried out to reduce false positive. Five markers, two of them highly significant in all models tested were associated with rust resistance. No strong association between any marker and powdery mildew resistance at the seedling stage was identified. However, one DArT sequence, oPt-5014, was strongly associated with powdery mildew resistance in adult plants. Overall, the markers showing the strongest association in this study provide ideal candidates for further studies and future inclusion in strategies of marker-assisted selection.

Gene expression under temperature stress.

In this review, changes in plant gene expression in response to environmental stresses are discussed using the examples of high and low temperature treatments. While some changes may contribute to acclimatory processes which improve plant survival or performance under stress, others may be 'shock' responses indicative of sensitivity. The heat-shock response, which is almost ubiquitous among eukaryotic organisms, is characterized by repression of normal cellular protein synthesis mediated at both the transcriptional and the translational level, and induction of heat-shock protein (HSP) synthesis. There is a correlation between HSP synthesis and induced thermotolerance in plants, but the evidence for a causal relationship is not conclusive. The possible biochemical functions of some of the HSPs are now becoming apparent; they are believed to play an important role in preventing accumulation of damaged proteins in the cell during heat shock. Although no other environmental stress elicits the full heat-shock response, certain treatments do induce synthesis of subsets of the HSPs, and the reasons for this are considered. Alterations in gene expression in response to low temperatures are more diverse and usually less dramatic than the heat-shock response, with which they share little, if any, homology. Biochemical adjustments during cold treatment are discussed, with particular reference to those which contribute to acclimation. Several genes whose expression is induced by cold have been cloned and characterized, and in some cases it is possible to attribute in vivo functions to them; they include enzymes of lipid, carbohydrate and protein metabolism, structural proteins and putative cryoprotectants. The use of transgenic plants is further facilitating an investigation of the biochemical factors which are important in cold acclimation. Drought, osmotic stress and abscisic acid induce expression of many of the same genes as does cold treatment; it seems likely that some of the products of these genes contribute to increased freezing tolerance by protecting against intracellular dehydration. Contents Summary 1 I. Introduction 1 II. High temperature stress 3 III. Low temperature stress 10 IV. Concluding remarks 20 Acknowledgements 21 References 21.

Submerged batch culture of the psychrophile Monographella nivalis in a defined medium; growth, carbohydrate utilization and responses to temperature.

An asporogenous strain of the pink snow mould fungus, Monographella nivalis (Schaffnit) E. Müller, anamorph Gerlachia nivalis (Ces. ex Sac.) W. Gams & E. Müller (Syn. Fusarium nivale Ces. ex Sacc.), grew at 5 °C on a denned salts medium plus vitamins and utilized a variety of simple and polymeric carbohydrates as the sole carbon and energy source. Mycelium was grown at temperatures between 3 and 15 °C in aerated submerged fermentation culture in chemically defined medium plus sucrose. Optimum growth rates of 0·035-0·033 h-1 occurred between 9 and 12 °C. Growth in a simple medium showed that all biochemical and physiological processes necessary for growth were functional at 3 °C. The growth performance of the organism at low temperatures was no better than would be expected from extrapolation of mesophilic growth responses to temperature. The optimum growth temperature of 9-12°C showed that some biochemical or physiological process was impaired above 12 °C. Uptake and incorporation of 35 S-methionine by mycelium at different temperatures showed that general protein synthesis increased up to 25 °C, and hence was not responsible per se for the sensitivity to temperatures above 12 °C. Heat shock proteins were synthesized at the relatively low temperature of 25 °C, consistent with the low temperature optimum for growth. When grown with sucrose as the sole carbon source, the mycelium catalyzed the extracellular hydrolysis of sucrose, releasing glucose and fructose together with a small amount of fructan trisaccharides and a trace of tetra- and penta-saccharides. Fructan accumulation was transient, corresponding with maximal rates of sucrose hydrolysis. Most biomass formation occurred in the absence of fructan in the culture, hence fructan was not necessary for growth at low temperature and did not appear to function as a cryoprotectant. Invertase activity was mostly (60-70%) bound to mycelium; the remainder was free in the culture supernatant. The regulation of invertase expression appeared to be by sucrose-induction, rather than by end-product repression. Rates of sucrose hydrolysis in culture were temperature-sensitive and were markedly depressed above 12 °C, indicating inhibition of invertase formation.

SNP discovery and chromosome anchoring provide the first physically-anchored hexaploid oat map and reveal synteny with model species.

A physically anchored consensus map is foundational to modern genomics research; however, construction of such a map in oat (Avena sativa L., 2n = 6x = 42) has been hindered by the size and complexity of the genome, the scarcity of robust molecular markers, and the lack of aneuploid stocks. Resources developed in this study include a modified SNP discovery method for complex genomes, a diverse set of oat SNP markers, and a novel chromosome-deficient SNP anchoring strategy. These resources were applied to build the first complete, physically-anchored consensus map of hexaploid oat. Approximately 11,000 high-confidence in silico SNPs were discovered based on nine million inter-varietal sequence reads of genomic and cDNA origin. GoldenGate genotyping of 3,072 SNP assays yielded 1,311 robust markers, of which 985 were mapped in 390 recombinant-inbred lines from six bi-parental mapping populations ranging in size from 49 to 97 progeny. The consensus map included 985 SNPs and 68 previously-published markers, resolving 21 linkage groups with a total map distance of 1,838.8 cM. Consensus linkage groups were assigned to 21 chromosomes using SNP deletion analysis of chromosome-deficient monosomic hybrid stocks. Alignments with sequenced genomes of rice and Brachypodium provide evidence for extensive conservation of genomic regions, and renewed encouragement for orthology-based genomic discovery in this important hexaploid species. These results also provide a framework for high-resolution genetic analysis in oat, and a model for marker development and map construction in other species with complex genomes and limited resources.