Genome-wide association study for oat (Avena sativa L.) beta-glucan concentration using germplasm of worldwide origin

Detection of quantitative trait loci (QTL) controlling complex traits followed by selection has become a common approach for selection in crop plants. The QTL are most often identified by linkage mapping using experimental F2, backcross, advanced inbred, or doubled haploid families. An alternative approach for QTL detection are genome-wide association studies (GWAS) that use pre-existing lines such as those found in breeding programs. We explored the implementation of GWAS in oat (Avena sativa L.) to identify QTL affecting β-glucan concentration, a soluble dietary fiber with several human health benefits when consumed as a whole grain. A total of 431 lines of worldwide origin were tested over 2 years and genotyped using Diversity Array Technology (DArT) markers. A mixed model approach was used where both population structure fixed effects and pair-wise kinship random effects were included. Various mixed models that differed with respect to population structure and kinship were tested for their ability to control for false positives. As expected, given the level of population structure previously described in oat, population structure did not play a large role in controlling for false positives. Three independent markers were significantly associated with β-glucan concentration. Significant marker sequences were compared with rice and one of the three showed sequence homology to genes localized on rice chromosome seven adjacent to the CslFgene family, known to have β-glucan synthase function. Results indicate that GWAS in oat can be a successful option for QTL detection, more so with future development of higher-density markers

Breeding for β-glucan content in elite North American oat (Avena sativa L.) using molecular markers

This dissertation explored genomewide association study (GWAS) and conducted actual breeding program in oat using different selection methods to identify molecular markers and improve beta-glucan content- a trait with positive health benefits. Results from GWAS suggested that beta-glucan content in elite oat is controlled by many QTL with small effects. Some of the important markers in our study co-localized with QTL in previous linkage studies. For the selection study, results demonstrated that after two cycles of selection the population means from marker-assisted selection and genomic selection methods were higher than BLUP phenotypic selection. The study also showed that the top performing lines came from marker-based methods indicating superiority of these methods in terms of cultivar development. The top lines in this study were also submitted to National Small Grains Collection for germplasm preservation and distribution purposes. We also found that the genetic variance for beta-glucan is mainly controlled by additive genetic component. However, the genetic variance decreased after two cycles of selection but the magnitude of decrease was different between selection methods. Particularly, the greatest reduction in genetic variance was detected for populations undergoing BLUP phenotypic selection. This could be attributed to higher chance of co-selection of sibs. On the other hand, populations under genomic selection had the lowest reduction in genetic variance which could be attributed to ability of markers to detect segregation in the estimation of breeding values. Among the three methods, only genomic selection can be conducted atleast twice a year which can result to doubling of genetic gain. Our experiments also demonstrated empirically that the accuracy of genomic selection can be increased by larger training population size, higher marker density and if selection candidates are genetically related to the training population

Post Financial Crisis Securitization: Can (EU) 2017/2402 Make any Difference? : A critical Analysis of Regulation (EU) 2017/2402

Following the devastating effect of the financial crisis, the securitization in Europe is still largely impaired and yet to get to the pre-crisis level. There are have been many regulatory interventions to revive the securitization market, with the latest being the regulation (EU) 2017/2402 that will be in force by January 2019. This thesis thus critically examines the regulation in the light of its ability to make a difference in European securitization, and possibly preventing another securitization-induced financial crisis. First, the rationale and motivations for securitization are highlighted, and possible drawbacks noted. In the same vein, the positives of having the regulation (EU) 2017/2402 are far reaching. For example, with the regulation coming to force, there is the expectation for more transparency, simplicity and standardization of securitization in Europe. The regulation (EU) 2017/2402, while replacing the laws on securitization in Europe, also creates the general framework for securitization and specific framework for simple, transparent and standardized (STS) securitization. The motivation for European securitizes to get the STS tag is that it makes them eligible for differentiated capital requirement of regulation (EU) 2017/2401. The benefits of the regulation (EU) 2017/2402, however, there are valid concerns about the overall impact on securitization in Europe. This thesis categorizes the concerns to two – sundry concerns and discrepancy concerns. The former relates to the general concerns about the regulation, while the latter expresses the concerns that show differences between what the regulation seeks (as marketed by the authorities), and what is realistically available. The thesis finally concludes on the note that the European securitization market will be greatly impacted by the regulation (EU) 2017/2402 - there will hopefully be a lot of simplicity, transparency, and standardization or comparability, going forward. In addition, parties in securitization transactions now have more clearly defined roles, e.g. investors now have the responsibility of doing their due diligence before and after holding securitization positions, as well as originators and sponsors providing material information about securitization transactions

Policy Implementation Lag in Workplace Mental Health: An Analysis of Awareness-Action Disparity

Mental health in the workplace has gained significant recognition, yet a substantial gap persists between acknowledging its importance and implementing comprehensive support systems across various industries. This manuscript aims to elucidate the factors contributing to this discrepancy and propose strategies for bridging the gap. We conducted a cross-sectional survey of professionals (n=50) across multiple sectors, including healthcare, finance, and technology, to assess workplace mental health prioritisation. Our findings reveal that while 90.9% of respondents consider workplace mental health prioritisation very important, only 39.4% report having mental health policies in their workplaces. Key barriers identified include stigma (39.4%), fear of job loss (33.3%), and privacy concerns (33.3%). Specific challenges were noted, with healthcare professionals reporting high stress levels despite good mental health knowledge. We propose a framework for transitioning from acknowledgement to action, emphasizing organizational culture change, leadership commitment, and tailored interventions. Recommendations include implementing regular mental health discussions, as 51.5% of respondents reported only occasional or rare workplace mental health promotion. This research contributes to the literature on workplace mental health and provides actionable strategies for organizations to enhance employee well-being and organizational success across diverse industries

Nanoalloying in real time: a high resolution STEM and computer simulation study

Bimetallic nanoparticles constitute a promising type of catalysts, mainly because their physical and chemical properties may be tuned by varying their chemical composition, atomic ordering, and size. Today, the design of novel nanocatalysts is possible through a combination of virtual lab simulations on massive parallel computing and modern electron microscopy with picometre resolution on one hand, and the capability of chemical analysis at the atomic scale on the other. In this work we show how the combination of theoretical calculations and characterization can solve some of the paradoxes reported about nanocatalysts: Au-Pd bimetallic nanoparticles. In particular, we demonstrate the key role played by adsorbates, such as carbon monoxide (CO), on the structure of nanoalloys. Our results imply that surface condition of nanoparticles during synthesis is a parameter of paramount importance.Fil: Mariscal, Marcelo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigaciones en Físico-química de Córdoba. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Instituto de Investigaciones en Físico-química de Córdoba; ArgentinaFil: Mayoral, Alba. Universidad de Zaragoza. Instituto de Nanociencia de Aragón; EspañaFil: Olmos Asar, Jimena Anahí. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigaciones en Físico-química de Córdoba. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Instituto de Investigaciones en Físico-química de Córdoba; ArgentinaFil: Magen, César. Universidad de Zaragoza. Instituto de Nanociencia de Aragón; EspañaFil: Mejia Rosales, Sergio Javier. Universidad Autónoma de Nuevo León; MéxicoFil: Pérez Tijerina, Eduardo. Universidad Autónoma de Nuevo León; MéxicoFil: José Yacamán, Miguel. University of Texas; Estados Unido

Accuracy and Training Population Design for Genomic Selection on Quantitative Traits in Elite North American Oats

Genomic selection (GS) is a method to estimate the breeding values of individuals by using markers throughout the genome. We evaluated the accuracies of GS using data from five traits on 446 oat (Avena sativa L.) lines genotyped with 1005 Diversity Array Technology (DArT) markers and two GS methods (ridge regression–best linear unbiased prediction [RR-BLUP] and BayesCπ) under various training designs. Our objectives were to (i) determine accuracy under increasing marker density and training population size, (ii) assess accuracies when data is divided over time, and (iii) examine accuracy in the presence of population structure. Accuracy increased as the number of markers and training size become larger. Including older lines in the training population increased or maintained accuracy, indicating that older generations retained information useful for predicting validation populations. The presence of population structure affected accuracy: when training and validation subpopulations were closely related accuracy was greater than when they were distantly related, implying that linkage disequilibrium (LD) relationships changed across subpopulations. Across many scenarios involving large training populations, the accuracy of BayesCπ and RR-BLUP did not differ. This empirical study provided evidence regarding the application of GS to hasten the delivery of cultivars through the use of inexpensive and abundant molecular markers available to the public sector

Genomic, Marker-Assisted, and Pedigree-BLUP Selection Methods for β-Glucan Concentration in Elite Oat

β-glucan, a soluble fiber found in oat (Avena sativa L.) grain, is good for human health, and selection for higher levels of this compound is regarded as an important breeding objective. Recent advances in oat DNA markers present an opportunity to investigate new selection methods for polygenic traits such as β-glucan concentration. Our objectives in this study were to compare genomic, marker-assisted, and best linear unbiased prediction (BLUP)–based phenotypic selection for short-term response to selection and ability to maintain genetic variance for β-glucan concentration. Starting with a collection of 446 elite oat lines from North America, each method was conducted for two cycles. The average β-glucan concentration increased from 4.57 g/100 g in Cycle 0 to between 6.66 and 6.88 g/100 g over the two cycles. The averages of marker-based selection methods in Cycle 2 were greater than those of phenotypic selection (P \u3c 0.08). Progenies with the highest β-glucan came from the marker-based selection methods. Marker-assisted selection (MAS) for higher β-glucan concentration resulted in a later heading date. We also found that marker-based selection methods maintained greater genetic variance than did BLUP phenotypic selection, potentially enabling greater future selection gains. Overall, the results of these experiments suggest that genomic selection is a superior method for selecting a polygenic complex trait like β-glucan concentration

Genome-wide Association Study for Beta-glucan Concentration in Elite North American Oat

Genome-wide association studies (GWAS) can be a useful approach to detect quantitative trait loci (QTL) controlling complex traits in crop plants. Oat (Avena sativa L.) β-glucan is a soluble dietary fiber and has been shown to have positive health benefits. We report a GWAS involving 446 elite oat breeding lines from North America genotyped with 1005 diversity arrays technology (DArT) markers and with phenotypic data from both historical and balanced 2-yr data. Association analyses accounting for pair-wise relationships and population structure were conducted using single-marker tests and least absolute shrinkage and selection operator (LASSO). Single-marker tests yielded six and 15 significant markers for the historical and balanced data sets, respectively. The LASSO method selected 24 and 37 markers as the most important in explaining β-glucan concentration for the historical and balanced data sets, respectively. Comparisons of genetic location showed that 15 of the markers in our study were found on the same linkage groups as QTL identified in previous studies. Four of the markers colocalized to within 4 cM of three previously detected QTL, suggesting concordance between QTL detected in our study and previous studies. Two of the significant markers were also adjacent to a β-glucan candidate gene in the rice (Oryza sativa L.) genome. Our findings suggest that GWAS can be used for QTL detection for the purpose of gene discovery and for marker-assisted selection to improve β-glucan concentration in elite oat.This article is published as Asoro, Franco G., Mark A. Newell, M. Paul Scott, William D. Beavis, and Jean-Luc Jannink. "Genome-wide association study for beta-glucan concentration in elite North American oat." Crop Science 53, no. 2 (2013): 542-553, doi: 10.2135/cropsci2012.01.0039.</p

Particle size distribution analysis of carburized HT250 gray cast iron using ImageJ

The study focused on the particle size analyses of a carburized HT250 gray cast iron using ImageJ software to understand the pattern of carbon diffusion after the carburization process. Pulverized pal kernel shell was deployed in the carburization of several samples of the grey cast iron after which the samples were characterized using scanning electron microscope (SEM) to study the microstructure of each sample. More so, ImageJ was equally deployed in the analyses of the SEM microstructures to understand the diffusion patterns of the carbon from the pulverized palm kernel shell so as to predict their structural behavior when deployed in fabrication process. Some of the important features from the ImageJ include Surface Plot, Interactive 3D surface plot and Intensity thresholding. The result showed the various diffusion patterns of carbon into the parent material. Thus, this result will help in the field of material science on the best method of material processing for adequate mechanical and structural properties