Six hundred thirty five oat (Avena sativa L.) lines and 4561 single-nucleotide polymorphism (SNP) loci were used to evaluate population structure, linkage disequilibrium (LD), and genotypephenotype 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 K = 1 to 20 model-based analyses suggested a structured population. However, the PC and K = 2 model-based analyses supported clustering of lines on spring oat vs. southern United States origin, accounting for 16% of genetic variation (p < 0.0001). Single-locus F-statistic (F ST ) 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 r 2 = 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. Core Ideas• An oat association-mapping panel contributed by active breeding programs worldwide.• Characterized population structure and found subdivisions related to adaptation• Characterized genome-wide and chromosomespecific linkage disequilibrium• Performed association-mapping and post hoc modeling of heading date• Found several consistently associated QTL
Marshall, A. H., Cowan, A. A., Edwards, S., Griffiths, I. M., Howarth, C. J., Langdon, T., White, E. (2013). Crops that feed the world 9. Oats- a cereal crop for human and livestock feed with industrial applications. Food Security, 5 (1), 13-33.Oats are a low input cereal widely grown across the world as both a grain and forage crop. Significant areas of production are in Northern Europe and North America and also in China and Australia. Although a traditional crop in many countries, in the last 50 years there has been a significant shift in oat production as a consequence of changing agricultural production and competition from other cereal crops. Oats are of significant economic importance for human consumption, for livestock feed and increasingly as a source of high value compounds with industrial applications as a consequence of the many unique properties of the oat grain. Traditional use in human diets in many countries has been boosted by the recent recognition of oats as a health food. This is attributed to the presence of ?-glucan, the major endospermic cell wall polysaccharide. As a result, there has been an increase in the use of oats and a broadening of oat based products. Increasing knowledge of the composition of the oat grain and its value for the various end-users is leading to new opportunities for the crop. While the value of oats as a break crop in cereal based rotations is widely recognised, maintaining the profitability of the crop whilst meeting the needs of end users is essential for future production. Opportunities exist for plant breeders and agronomists to introduce new oat varieties with tailored agronomic approaches to address this challenge and to ensure the sustainability of oats for the future.Peer reviewe
Sponsorhip: BBSRC RONO: BB/J004405/1; BB/H009582/1; BBS/E/W/10962A01CIn this study, genetic diversity among 177 oat (Avena sativa L.) accessions including both white and red oat landraces and 36 commercial cultivars was studied for simple sequence repeat (SSR) loci. Thirty-one genomic and expressed sequence tags (EST)-derived primer pairs were selected according to high polymorphism from an initial 66 SSR batch. Markers revealed a high level of polymorphism, detecting a total of 454 alleles. The average gene diversity for the whole sample was 0.29. Genetic similarity, calculated using the Dice coefficient, was used for cluster analysis, and principal component analysis was also applied. In addition, population structure using a Bayesian clustering approach identified discrete subpopulation based on allele frequency and showed similar clustering of oat genotypes in four groups. Accessions could be classified into four main clusters that clearly separated the commercial cultivars, the red oat landraces and two clusters of white oat landraces. Cultivars showed less diversity than the landraces indicating a reduction of genetic diversity during breeding, whereas white oat landraces showed higher diversity than red ones. The average polymorphic information content of 0.80 for the SSR loci indicated the usefulness of many of the SSR for genotype identification. In particular, two markers, MAMA5 and AM04, with a total of 50 alleles and a high discrimination power (>0.90), were sufficient to discriminate among all commercial cultivars studied highlighting their potential use for variety identification.Peer reviewe
This is the author accepted manuscript. The final version is available from Elsevier via http://dx.doi.org/10.1016/j.jcs.2017.01.005Warmer temperatures and increasing interest in high provenance food and drink products are creating new opportunities for cereal growing in northern Europe. Nevertheless, cultivation of oats and barley in these areas for malting and milling remains a challenge, primarily because of the weather, and there are few reports of their nutritional content from this region. In this study, trials in Orkney compared agronomic characteristics and nutritional content of recommended UK oat and barley varieties with Scandinavian varieties over three years. For a subset of varieties, nutritional content was compared with samples cultivated in more southerly sites. For Orkney, barley was considered a more suitable crop than oats because varieties matured earlier. In both crops, Scandinavian varieties matured earlier than UK varieties and some produced comparable yields. The range of values for macronutrients and minerals in oats and barley in Orkney were similar to those reported previously for other locations, but there were some significant differences attributable to variety and year. Compared with grain samples from more southerly locations, oats in Orkney had a significantly lower ?-glucan and higher sodium content. The lower ?-glucan may have resulted from higher rainfall and lower temperatures during the months of grain filling and maturationauthorsversionPeer reviewe
Highlights The response to nitrogen of 4 winter oat varieties in three field trials was analysed. A novel high-resolution method was developed to profile metabolite changes. Conditions that enhance yield do not necessarily result in higher nutritional value. Choice of variety is of equally high importance as the nitrogen levels applied.
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 populations were developed to identify the genomic locations of the two genes and producing 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 SNP chip. Multiple interval mapping placed Pc54 on the linkage group Mrg02 (chromosome 7D) and the novel powdery mildew QTL ‘QPm.18’ on Mrg18 (chromosome 1A) both in the mapping and validating population. A total of nine and 31 significant molecular markers were identified linked with the Pc54 gene and QPm.18, respectively. Reactions to crown rust inoculations have justified separate identity of Pc54 from other genes and QTL 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 the molecular mechanism of resistance to crown rust and powdery mildew in oats. Furthermore, SNPs and SSRs 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.
Compression, shear, tensile and punch tests were used to assess the mechanical strength of a ground meat product and discriminate between effects of various treatments on this type of product. These measurements, together with chemical and moisture retention measurements, were related to sensory attributes of the cooked products. Most of the sensory textural attributes were satisfactorily (i.e., about 80% of the variance) explained or described by a combination of Warner-Brat&r shear parameters and certain compression measurements. Principal co-ordinate analysis showed that tensile measurements related better to sensory greasiness and juiciness than to mechanical strength. Methods for measuring juiciness were not adequate and indicated the need for further investigation.
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 narrowbase 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.
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