TSABL: Trait Specific Annotation Based Locus Predictor

The majority of GWAS loci fall in the non-coding genome, making causal variants difficult to identify and study. We hypothesized that the regulatory features underlying causal variants are biologically specific, identifiable from data, and that the regulatory architecture that influences one trait is distinct compared to biologically unrelated traits. To better characterize and identify these variants, we used publicly available GWAS loci and genomic annotations to build 17 Trait Specific Annotation Based Locus (TSABL) predictors to identify differences between GWAS loci associated with different phenotypic trait groups. We used a penalized binomial logistic regression model to select trait relevant annotations and tested all models on a holdout set of loci not used for training in any trait. We were able to successfully build models for autoimmune, electrocardiogram, lipid, platelet, red blood cell, and white blood cell trait groups. We used these models both to prioritize variants in existing loci and to identify new genomic regions of interest. We found that TSABL models identified biologically relevant regulatory features, and anticipate their future use to enhance the design and interpretation of genetic studies.

Vulnerable Dispositional Traits and Chronic Pain: Predisposing but not Predetermining

Introduction Dispositional traits can be protective or contribute to increased vulnerability in individuals with chronic pain. This study aims to evaluate the predictive utility of two dispositional trait measures, affect balance style and multi-domain trait groups specific to clinical pain, psychosocial functioning, experimental pain, and health outcomes at two years in individuals with chronic knee pain. MethodsThe study is a prospective analysis of 168 community dwelling individuals aged 45-85 years old with knee pain with or at risk for knee osteoarthritis. Affect balance style and multi-domain trait groups were developed and tested using regression analysis and machine learning (Support Vector Machine). ResultsAt baseline, affect balance style and multi-domain trait groups were predictive of psychosocial and clinical pain measures with the multi-domain trait groups showing a greater range of association with clinical measures. At the two-year time point, both the affect balance style groups and the multi-domain trait groups were predictive of physical and psychosocial functioning while the multi-domain trait groups were also predictive of all clinical pain measures. ConclusionThe multi-domain trait classification is a stronger predictor than the previously investigated affect balance style specific to clinical pain and pain-related functioning at two-years. Interestingly, in contrast to expectations, individuals in the vulnerable trait groups showed more variability in dispositional trait status at the two-year time point compared to those in the more protective trait groups. Findings reiterate that a vulnerable trait may be predisposing but is not predetermining regarding pain-related experiences.

Principal component analysis of conformation traits in Hungarian Simmental cows

The aim of the current research was to analyze the linear type traits of Hungarian Simmental dual-purpose cows scored in the first lactation using principal component analysis and cluster analysis. Data collected by the Association of Hungarian Simmental Breeders were studied during the work. The filtered database contained the results of 8 868 cows, born after 1997. From the evaluation of main conformation traits, the highest correlations (r = 0.35, P < 0.05) were found between mammary system and feet and legs traits. Within linear type traits, the highest correlation was observed between rump length and rump width (r = 0.81, P < 0.05). Using the principal component analysis, main conformation traits were combined into groups. There were three factors having 84.5 as total variance ratio after varimax rotation. Cluster analysis verified the results of the principal component analysis as most of the trait groups were similar. The strongest relationship was observed between feet and legs and mammary system (main conformation traits) and between rump length and rump width (linear type traits).

Canonical correlations among grapevine agronomic and processing characteristics

Canonical correlation analysis allows conclusions to be drawn about the occurrence and magnitude of associations between two groups of characteristics. This study estimated the magnitude of association and interdependence between two trait groups of clones of two varieties of Vitis vinifera grapes. The study was based on the mean data of eight characteristics from two experiments to test the performance of these clones: the first experiment provided data from seven clones of Cabernet Sauvignon, which evaluated in the northern San Joaquin Valley, California, United States, and the second data set was from six clones of the Chardonnay variety, which were evaluated in the Napa Valley, California, United States. The canonical correlations among the two varieties were significant, indicating that the two groups of characteristics were related or not independent. The quality and quantity of the raw material required for fine-wine production were inversely proportional and specific to each variety. For Cabernet Sauvignon, the high number of berries per bunch and high number of bunches per plant resulted in fruits with a high °Brix level and increased pH. For Chardonnay, the increase in the bunch weight and number of berries decreased the fruit pH.

Are They Learning or Playing? Students’ Perception Traits and Their Learning Self-Efficacy in a Game-Based Learning Environment

As game-based learning continues to draw attention, students’ perceptions toward classroom activities are vital in influencing the quality of learning. This study used the social cognitive theory to show the perception traits of learning and playing in game-based environments and for students to identify their self-efficacy toward game-based learning by different trait groups. The game Formosa Hope was used in an experiment with 362 fifth- and sixth-grade students at ages 11 to 12 years as participants. Three perception traits were identified through a two-step cluster analysis: I—strong perceptions of learning and playing, II—moderate perceptions of learning and playing, and III—strong perception of playing but weak perception of learning. This study showed that regardless of trait type, students demonstrated positive self-efficacy, with those with Trait I having significantly higher self-efficacy than those with Traits II and III, indicating that students’ positive perceptions of learning and playing are essential in prompting self-efficacy in game-based learning.