Dominance and G×E interaction effects improvegenomic prediction and genetic gain inintermediate wheatgrass (Thinopyrumintermedium)

Genomic selection (GS) based recurrent selection methods were developed to accelerate the domestication of intermediate wheatgrass [IWG, Thinopyrum intermedium (Host) Barkworth & D.R. Dewey]. A subset of the breeding population phenotyped at multiple environments is used to train GS models and then predict trait values of the breeding population. In this study, we implemented several GS models that investigated the use of additive and dominance effects and G×E interaction effects to understand how they affected trait predictions in intermediate wheatgrass. We evaluated 451 genotypes from the University of Minnesota IWG breeding program for nine agronomic and domestication traits at two Minnesota locations during 2017–2018. Genet-mean based heritabilities for these traits ranged from 0.34 to 0.77. Using fourfold cross validation, we observed the highest predictive abilities (correlation of 0.67) in models that considered G×E effects. When G×E effects were fitted in GS models, trait predictions improved by 18%, 15%, 20%, and 23% for yield, spike weight, spike length, and free threshing, respectively. Genomic selection models with dominance effects showed only modest increases of up to 3% and were trait-dependent. Crossenvironment predictions were better for high heritability traits such as spike length, shatter resistance, free threshing, grain weight, and seed length than traits with low heritability and large environmental variance such as spike weight, grain yield, and seed width. Our results confirm that GS can accelerate IWG domestication by increasing genetic gain per breeding cycle and assist in selection of genotypes with promise of better performance in diverse environments

Genotype imputation for the prediction of genomic breeding values in non-genotyped and low-density genotyped individuals

<p>Abstract</p> <p>Background</p> <p>There is wide interest in calculating genomic breeding values (GEBVs) in livestock using dense, genome-wide SNP data. The general framework for genomic selection assumes all individuals are genotyped at high-density, which may not be true in practice. Methods to add additional genotypes for individuals not genotyped at high density have the potential to increase GEBV accuracy with little or no additional cost. In this study a long haplotype library was created using a long range phasing algorithm and used in combination with segregation analysis to impute dense genotypes for non-genotyped dams in the training dataset (S1) and for non-genotyped or low-density genotyped individuals in the prediction dataset (S2), using the 14^th QTL-MAS Workshop dataset. Alternative low-density scenarios were evaluated for accuracy of imputed genotypes and prediction of GEBVs.</p> <p>Results</p> <p>In S1, females in the training population were not genotyped and prediction individuals were either not genotyped or genotyped at low-density (evenly spaced at 2, 5 or 10 Mb). The proportion of correctly imputed genotypes for training females did not change when genotypes were added for individuals in the prediction set whereas the number of correctly imputed genotypes in the prediction set increased slightly (S1). The S2 scenario assumed the complete training set was genotyped for all SNPs and the prediction set was not genotyped or genotyped at low-density. The number of correctly imputed genotypes increased with genotyping density in the prediction set. Accuracy of genomic breeding values for the prediction set in each scenario were the correlation of GEBVs with true breeding values and were used to evaluate the potential loss in accuracy with reduced genotyping. For both S1 and S2 the GEBV accuracies were similar when the prediction set was not genotyped and increased with the addition of low-density genotypes, with the increase larger for S2 than S1.</p> <p>Conclusions</p> <p>Genotype imputation using a long haplotype library and segregation analysis is promising for application in sparsely-genotyped pedigrees. The results of this study suggest that dense genotypes can be imputed for selection candidates with some loss in genomic breeding value accuracy, but with levels of accuracy higher than traditional BLUP estimated breeding values. Accurate genotype imputation would allow for a single low-density SNP panel to be used across traits.</p

A Bayesian approach to detect QTL affecting a simulated binary and quantitative trait

Background - We analyzed simulated data from the 14th QTL-MAS workshop using a Bayesian approach implemented in the program iBay. The data contained individuals genotypes for 10,031 SNPs and phenotyped for a quantitative and a binary trait. Results - For the quantitative trait we mapped 8 out of 30 additive QTL, 1 out of 3 imprinted QTL and both epistatic pairs of QTL successfully. For the binary trait we mapped 11 out of 22 additive QTL successfully. Four out of 22 pleiotropic QTL were detected as such. Conclusions - The Bayesian variable selection method showed to be a successful method for genome-wide association. This method was reasonably fast using dense marker map

An algorithm for efficient constrained mate selection

<p>Abstract</p> <p>Background</p> <p>Mate selection can be used as a framework to balance key technical, cost and logistical issues while implementing a breeding program at a tactical level. The resulting mating lists accommodate optimal contributions of parents to future generations, in conjunction with other factors such as progeny inbreeding, connection between herds, use of reproductive technologies, management of the genetic distribution of nominated traits, and management of allele/genotype frequencies for nominated QTL/markers.</p> <p>Methods</p> <p>This paper describes a mate selection algorithm that is widely used and presents an extension that makes it possible to apply constraints on certain matings, as dictated through a group mating permission matrix.</p> <p>Results</p> <p>This full algorithm leads to simpler applications, and to computing speed for the scenario tested, which is several hundred times faster than the previous strategy of penalising solutions that break constraints.</p> <p>Conclusions</p> <p>The much higher speed of the method presented here extends the use of mate selection and enables implementation in relatively large programs across breeding units.</p

Across population genomic prediction scenarios in which Bayesian variable selection outperforms GBLUP

<p>Background: The use of information across populations is an attractive approach to increase the accuracy of genomic prediction for numerically small populations. However, accuracies of across population genomic prediction, in which reference and selection individuals are from different populations, are currently disappointing. It has been shown for within population genomic prediction that Bayesian variable selection models outperform GBLUP models when the number of QTL underlying the trait is low. Therefore, our objective was to identify across population genomic prediction scenarios in which Bayesian variable selection models outperform GBLUP in terms of prediction accuracy. In this study, high density genotype information of 1033 Holstein Friesian, 105 Groningen White Headed, and 147 Meuse-Rhine-Yssel cows were used. Phenotypes were simulated using two changing variables: (1) the number of QTL underlying the trait (3000, 300, 30, 3), and (2) the correlation between allele substitution effects of QTL across populations, i.e. the genetic correlation of the simulated trait between the populations (1.0, 0.8, 0.4). Results: The accuracy obtained by the Bayesian variable selection model was depending on the number of QTL underlying the trait, with a higher accuracy when the number of QTL was lower. This trend was more pronounced for across population genomic prediction than for within population genomic prediction. It was shown that Bayesian variable selection models have an advantage over GBLUP when the number of QTL underlying the simulated trait was small. This advantage disappeared when the number of QTL underlying the simulated trait was large. The point where the accuracy of Bayesian variable selection and GBLUP became similar was approximately the point where the number of QTL was equal to the number of independent chromosome segments (M _e) across the populations. Conclusion: Bayesian variable selection models outperform GBLUP when the number of QTL underlying the trait is smaller than M _e. Across populations, M _e is considerably larger than within populations. So, it is more likely to find a number of QTL underlying a trait smaller than M _e across populations than within population. Therefore Bayesian variable selection models can help to improve the accuracy of across population genomic prediction.</p

Does a competitive voucher program for adolescents improve the quality of reproductive health care? A simulated patient study in Nicaragua

BACKGROUND: Little is known about how sexual and reproductive (SRH) health can be made accessible and appropriate to adolescents. This study evaluates the impact and sustainability of a competitive voucher program on the quality of SRH care for poor and underserved female adolescents and the usefulness of the simulated patient (SP) method for such evaluation. METHODS: 28,711 vouchers were distributed to adolescents in disadvantaged areas of Managua that gave free-of-charge access to SRH care in 4 public, 10 non-governmental and 5 private clinics. Providers received training and guidelines, treatment protocols, and financial incentives for each adolescent attended. All clinics were visited by female adolescent SPs requesting contraception. SPs were sent one week before, during (with voucher) and one month after the intervention. After each consultation they were interviewed with a standardized questionnaire. Twenty-one criteria were scored and grouped into four categories. Clinics' scores were compared using non-parametric statistical methods (paired design: before-during and before-after). Also the influence of doctors' characteristics was tested using non-parametric statistical methods. RESULTS: Some aspects of service quality improved during the voucher program. Before the program started 8 of the 16 SPs returned 'empty handed', although all were eligible contraceptive users. During the program 16/17 left with a contraceptive method (p = 0.01). Furthermore, more SPs were involved in the contraceptive method choice (13/17 vs.5/16, p = 0.02). Shared decision-making on contraceptive method as well as condom promotion had significantly increased after the program ended. Female doctors had best scores before- during and after the intervention. The improvements were more pronounced among male doctors and doctors older than 40, though these improvements did not sustain after the program ended. CONCLUSION: This study illustrates provider-related obstacles adolescents often face when requesting contraception. The care provided during the voucher program improved for some important outcomes. The improvements were more pronounced among providers with the weakest initial performance. Shared decision-making and condom promotion were improvements that sustained after the program ended. The SP method is suitable and relatively easy to apply in monitoring clinics' performance, yielding important and relevant information. Objective assessment of change through the SP method is much more complex and expensive

Adaptive Governance and Resilience Capacity of Farms: The Fit Between Farmers’ Decisions and Agricultural Policies

Greater resilience is needed for farms to deal with shocks and disturbances originating from economic, environmental, social and institutional challenges, with resilience achieved by adequate adaptive governance. This study focuses on the resilience capacity of farms in the context of multi-level adaptive governance. We define adaptive governance as adjustments in decision-making processes at farm level and policy level, through changes in management practices and policies in response to identified challenges and the delivery of desired functions (e.g. private and public goods) to be attained. The aim of the study is twofold. First, we investigate how adaptive governance processes at farm level and policy level influence the resilience capacity of farms in terms of robustness, adaptability and transformability. Second, we investigate the “fit” between the adaptive governance processes at farm level and policy level to enable resilience. We study primary egg and broiler production in Sweden taking into consideration economic, social and environmental challenges. We use semi-structured interviews with 17 farmers to explain the adaptive processes at farm level and an analysis of policy documents from the Common Agricultural Policy program 2014–2020, to explain the intervention actions taken by the Common Agricultural Policy. Results show that neither the farm level nor policy level adaptive processes on their own have the capacity to fully enable farms to be robust, adaptable and transformable. While farm level adaptive processes are mainly directed toward securing the robustness and adaptability of farms, policy level interventions are targeted at enabling adaptability. The farm- and the policy level adaptive processes do not “fit” for attaining robustness and transformability

Characteristics and outcome in cardiogenic shock according to vascular access site for percutaneous coronary intervention

Aims The optimal vascular access site for percutaneous coronary interventions (PCIs) in patients with acute myocardial infarction (AMI) complicated by cardiogenic shock (CS) remains uncertain. While observational data favour transradial access (TRA) due to lower complication rates and mortality, transfemoral access (TFA) PCI offers advantages such as shorter access and procedure times, along with quicker escalation to mechanical circulatory support (MCS). In this study, we aimed to investigate factors associated with a transfemoral approach and compare mortality rates between TRA and TFA in AMI-CS patients undergoing PCI. Methods Data from a nationwide registry of AMI-CS patients undergoing PCI (2017–2021) were analysed. We compared patient and results demographics, procedural details, and outcomes between TRA and TFA groups. Logistic regression identified access site factors and radial-to-femoral crossover predictors. Propensity score–matched (PSM) analysis examined the impact of access site on mortality. Of the 1562 patients, 45% underwent TRA PCI, with an increasing trend over time. Transfemoral access patients were more often female, had a history of coronary artery bypass grafting, lower blood pressure, higher resuscitation and intubation rates, and elevated lactate levels. After PSM, 30-day mortality was lower in TRA (33% vs. 46%, P &lt; 0.001). Predictors for crossover included left coronary artery interventions, multivessel PCI, and MCS initiation. Conclusion Significant differences exist between TRA and TFA PCI in AMI-CS. Transfemoral access was more common in patients with worse haemodynamics and was associated with higher 30-day mortality compared with TRA. This mortality difference persisted in the PSM analysis.[Figure</p

Balloon-Expandable TAVR Bioprostheses: Area or Perimeter Sizing? A Prospective Pilot Study.

OBJECTIVE: In TAVR, area sizing is used for balloon-expandable (BE) valves, whereas self-expanding valves are sized to annulus perimeter. For BE valves, this seems illogical: these frames force a circular shape even on an ellipsoid annulus. This can potentially lead to relative undersizing when area sizing is being applied. We developed a perimeter-based sizing algorithm to evaluate the safety and feasibility of perimeter sizing for the Myval BE valve. METHODS: In this prospective single-center study, 60 patients with severe aortic stenosis treated with the Myval BE valve were included. Perimeter sizing was used with limited oversizing of 3.7% ± 1.3% compared to the annulus perimeter. After TAVR, clinical outcomes were evaluated at 30 days and 1 year. An echocardiographic follow-up took place at 30 days. RESULTS: At 30 days, the need for PPI and stroke occurred in 2% and 3% of the patients, respectively. Moreover, cardiac death and moderate-severe PVL were absent. At 1-year, cardiac death and stroke were observed in 3% and 8% of the patients, respectively. In 33.3% of the patients, a larger valve size was implanted compared to the valve size calculated by area sizing. CONCLUSIONS: Perimeter sizing with the Myval BE valve leads to substantial use of larger valve sizes and favorable clinical outcomes, with low PPI and the absence of significant PVL. A randomized controlled trial is being planned to prove the superiority of this alternative sizing method