Genomic Prediction and Genome-Wide Association Studies of Flour Yield and Alveograph Quality Traits Using Advanced Winter Wheat Breeding Material

Use of genetic markers and genomic prediction might improve genetic gain for quality traits in wheat breeding programs. Here, flour yield and Alveograph quality traits were inspected in 635 F6 winter wheat breeding lines from two breeding cycles. Genome-wide association studies revealed single nucleotide polymorphisms (SNPs) on chromosome 5D significantly associated with flour yield, Alveograph P (dough tenacity), and Alveograph W (dough strength). Additionally, SNPs on chromosome 1D were associated with Alveograph P and W, SNPs on chromosome 1B were associated with Alveograph P, and SNPs on chromosome 4A were associated with Alveograph L (dough extensibility). Predictive abilities based on genomic best linear unbiased prediction (GBLUP) models ranged from 0.50 for flour yield to 0.79 for Alveograph W based on a leave-one-out cross-validation strategy. Predictive abilities were negatively affected by smaller training set sizes, lower genetic relationship between lines in training and validation sets, and by genotype–environment (G×E) interactions. Bayesian Power Lasso models and genomic feature models resulted in similar or slightly improved predictions compared to GBLUP models. SNPs with the largest effects can be used for screening large numbers of lines in early generations in breeding programs to select lines that potentially have good quality traits. In later generations, genomic predictions might be used for a more accurate selection of high quality wheat lines

Necessity and concerns about lipid-lowering medical treatments and risk factors for non-adherence: A cross-sectional study in Palestine

Aims: Strong evidence indicates that drugs reduce blood lipids and improve cardiovascular end-points, leading to their wide usage. However, the success of these drugs can be affected by poor patient's adherence to prescribed medication. This study aimed to evaluate medication adherence in patients with dyslipidaemia in association with patient beliefs about medicines. Methods: The study was conducted from January 2019 to July 2019 at the middle governmental primary healthcare clinics in Ramallah and Bethlehem cities, and used a cross-sectional design. Adherence was determined using the 4-item Morisky medication adherence scale, while beliefs were determined using the Beliefs about Medicines Questionnaire. Results: Of 220 patients, 185 agreed to participate in the study, resulting in a response rate of 84.1%. Of the participants, 106 (57.3%) were men, and almost half (88, 46.5%) were ≥56 years. Medication non-adherence was high (47.6%), but a majority (65.5%) reported believing their treatment to be necessary for their continued good health. Accordingly, the mean necessity score (17.3, SD 3.7) significantly outweighed (P < .001) the mean concerns score (14.0, SD 3.5). Multivariate regression demonstrated four variables to be significantly correlated with non-adherence: illiterate (OR = 2.52; CI: 0.9-4.3; P = .03), polypharmacy (OR = 3.18; CI: 1.9-5.7; P = .007), having comorbidity (OR = 3.10; CI: 2.2-4.6; P = .005) and having concerns about side effects (OR = 2.89; CI: 1.1-4.6, P = .04). Conclusion: Non-adherence among patients taking lipid-lowering agents was high despite most holding positive beliefs regarding medication necessity. This may be due to concern also being high. Physicians should identify and target high-risk patients and individualise their treatment plans in order to achieve adequate control of dyslipidaemia.We thank all workers at health clinics at Ramallah and Bethlehem who helped in finishing this study and also we thank the participants who willingly accepted to share for the purpose of this study