Mapping of Crown Rust (Puccinia coronata f. sp. avenae) Resistance Gene Pc54 and a Novel Quantitative Trait Locus Effective Against Powdery Mildew (Blumeria graminis f. sp. avenae) in the Oat (Avena sativa) Line Pc54.

The Pc54 oat line carries the crown rust resistance gene Pc54 and an unknown gene effective against powdery mildew. In this study, two recombinant inbred line (RIL) populations were developed to identify the genomic locations of the two genes and produce lists of molecular markers with a potential for marker-assisted selection. The RILs and parents were phenotyped for crown rust and powdery mildew in a controlled environment. They were also genotyped using the 6K Illumina Infinium iSelect oat single nucleotide polymorphism (SNP) chip. Multiple interval mapping placed Pc54 on the linkage group Mrg02 (chromosome 7D) and the novel powdery mildew quantitative trait locus (QTL) QPm.18 on Mrg18 (chromosome 1A) both in mapping and in the validating populations. A total of 9 and 31 significant molecular markers were identified linked with the Pc54 gene and QPm.18, respectively. Reactions to crown rust inoculations have justified separate identities of Pc54 from other genes and QTLs that have previously been reported on Mrg02 except for qPCRFd. Pm3 is the only powdery mildew resistance gene previously mapped on Mrg18. However, the pm3 differential line, Mostyn, was susceptible to the powdery mildew race used in this study, suggesting that Pm3 and QPm.18 are different genes. Determining the chromosomal locations of Pc54 and QPm.18 is helpful for better understanding of the molecular mechanism of resistance to crown rust and powdery mildew in oats. Furthermore, SNPs and single sequence repeats that are closely linked with the genes could be valuable for developing PCR-based molecular markers and facilitating the utilization of these genes in oat breeding programs.[Formula: see text] Copyright © 2022 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

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).

Assessing the impact of nitrogen supplementation in oats across multiple growth locations and years with targeted phenotyping and high-resolution metabolite profiling approaches.

Oats (Avena sativa L.) are a healthy food, being high in dietary fibre (e.g. ß-glucans), antioxidants, minerals, and vitamins. Understanding the effect of variety and crop management on nutritional quality is important. The response of four oat varieties to increased nitrogen levels was investigated across multiple locations and years with respect to yield, grain quality and metabolites (assessed via GC- and LC- MS). A novel high-resolution UHPLC-PDA-MS/MS method was developed, providing improved metabolite enrichment, resolution, and identification. The combined phenotyping approach revealed that, amino acid levels were increased by nitrogen supplementation, as were total protein and nitrogen containing lipid levels, whereas health-beneficial avenanthramides were decreased. Although nitrogen addition significantly increased grain yield and ß-glucan content, supporting increasing the total nitrogen levels recommended within agricultural guidelines, oat varietal choice as well as negative impacts upon health beneficial secondary metabolites and the environmental burdens associated with nitrogen fertilisation, require further consideration.

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.

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.

Ward-based blood gas analysis.

Blood gas analysis is a time-consuming procedure, taking up to 30 minutes from obtaining a blood sample from the patient to receiving the results. The process can involve as many as three health care professionals: the doctor, nurse and a member of the pathology department. The result is that it is difficult to provide continual monitoring of blood gas levels on patients with acute respiratory problems.