Associations between prion protein genotype and type traits in East Friesian milk sheep

Linear models were used to analyse the relationships between the prion protein genotypes and the height at the withers and rump, the heart girth and the length of the trunk of 440 East Friesian milk sheep. Significant associations were found between the ARR allele and the height of the withers and rump, and heart girth. The average height at the withers of the homozygous ARR/ARR sheep was 1.9 cm less than that of ARQ/ARQ sheep and 1.6 cm less than in sheep heterozygous for ARR; the height at the rump, length of the trunk and heart girth were similarly smaller. In the ARR/ARR ewes, the average height at the withers was 2.6 cm less and the height at the rump was 1.9 cm less than in the ARQ/ARQ ewes.

Flattening Traits

Traits are fine-grained components that can be used to compose classes, while avoiding many of the problems of multiple inheritance and mixin-based approaches. Since most implementations of traits have focused on dynamically-typed languages, the question naturally arises, how can one best introduce traits to statically-typed languages, like Java and C#?

Swiss residents' speciality choices--impact of gender, personality traits, career motivation and life goals

BACKGROUND: The medical specialties chosen by doctors for their careers play an important part in the development of health-care services. This study aimed to investigate the influence of gender, personality traits, career motivation and life goal aspirations on the choice of medical specialty. METHODS: As part of a prospective cohort study of Swiss medical school graduates on career development, 522 fourth-year residents were asked in what specialty they wanted to qualify. They also assessed their career motivation and life goal aspirations. Data concerning personality traits such as sense of coherence, self-esteem, and gender role orientation were collected at the first assessment, four years earlier, in their final year of medical school. Data analyses were conducted by univariate and multivariate analyses of variance and covariance. RESULTS: In their fourth year of residency 439 (84.1%) participants had made their specialty choice. Of these, 45 (8.6%) subjects aspired to primary care, 126 (24.1%) to internal medicine, 68 (13.0%) to surgical specialties, 31 (5.9%) to gynaecology & obstetrics (G&O), 40 (7.7%) to anaesthesiology/intensive care, 44 (8.4%) to paediatrics, 25 (4.8%) to psychiatry and 60 (11.5%) to other specialties. Female residents tended to choose G&O, paediatrics, and anaesthesiology, males more often surgical specialties; the other specialties did not show gender-relevant differences of frequency distribution. Gender had the strongest significant influence on specialty choice, followed by career motivation, personality traits, and life goals. Multivariate analyses of covariance indicated that career motivation and life goals mediated the influence of personality on career choice. Personality traits were no longer significant after controlling for career motivation and life goals as covariates. The effect of gender remained significant after controlling for personality traits, career motivation and life goals. CONCLUSION: Gender had the greatest impact on specialty and career choice, but there were also two other relevant influencing factors, namely career motivation and life goals. Senior physicians mentoring junior physicians should pay special attention to these aspects. Motivational guidance throughout medical training should not only focus on the professional career but also consider the personal life goals of those being mentored.

Power and Robustness of Linkage Tests for Quantitative Traits in General Pedigrees

There are numerous statistical methods for quantitative trait linkage analysis in human studies. An ideal such method would have high power to detect genetic loci contributing to the trait, would be robust to non-normality in the phenotype distribution, would be appropriate for general pedigrees, would allow the incorporation of environmental covariates, and would be appropriate in the presence of selective sampling. We recently described a general framework for quantitative trait linkage analysis, based on generalized estimating equations, for which many current methods are special cases. This procedure is appropriate for general pedigrees and easily accommodates environmental covariates. In this paper, we use computer simulations to investigate the power robustness of a variety of linkage test statistics built upon our general framework. We also propose two novel test statistics that take account of higher moments of the phenotype distribution, in order to accommodate non-normality. These new linkage tests are shown to have high power and to be robust to non-normality. While we have not yet examined the performance of our procedures in the context of selective sampling via computer simulations, the proposed tests satisfy all of the other qualities of an ideal quantitative trait linkage analysis method.

A unifying approach for haplotype analysis of quantitative traits in family-based association studies: Testing and estimating gene-environment interactions with complex exposure variables

We propose robust and e±cient tests and estimators for gene-environment/gene-drug interactions in family-based association studies. The methodology is designed for studies in which haplotypes, quantitative pheno- types and complex exposure/treatment variables are analyzed. Using causal inference methodology, we derive family-based association tests and estimators for the genetic main effects and the interactions. The tests and estimators are robust against population admixture and strati¯cation without requiring adjustment for confounding variables. We illustrate the practical relevance of our approach by an application to a COPD study. The data analysis suggests a gene-environment interaction between a SNP in the Serpine gene and smok- ing status/pack years of smoking that reduces the FEV1 volume by about 0.02 liter per pack year of smoking. Simulation studies show that the pro- posed methodology is su±ciently powered for realistic sample sizes and that it provides valid tests and effect size estimators in the presence of admixture and stratification.

Cerebral connectivity and psychotic personality traits : A diffusion tensor imaging study

This study aims to investigate the relationship between regional connectivity in the brain white matter and the presence of psychotic personality traits, in healthy subjects with psychotic traits. Thirteen healthy controls were administered the MMPI-2, to assess psychotic traits and, according to MMPI results, a dichotomization into a group of "high-psychotic" and "low-psychotic" was performed. Diffusion tensor imaging (DTI) was used as a non-invasive measure, in order to obtain information about the fractional anisotropy (FA), an intravoxel index of local connectivity and, by means of a voxelwise approach, the between-group differences of the FA values were calculated. The "high-psychotic" group showed higher FA in the left arcuate fasciculus. Subjects with low scores for psychotic traits had significantly higher FA in the corpus callosum, right arcuate fasciculus, and fronto-parietal fibers. In line with previous brain imaging studies of schizophrenia spectrum disorders, our results suggest that psychotic personality traits are related to altered connectivity and brain asymmetry.

Heterosis for biomass-related traits in Arabidopsis investigated by quantitative trait loci analysis of the triple testcross design with recombinant inbred lines

Arabidopsis thaliana has emerged as a leading model species in plant genetics and functional genomics including research on the genetic causes of heterosis. We applied a triple testcross (TTC) design and a novel biometrical approach to identify and characterize quantitative trait loci (QTL) for heterosis of five biomass-related traits by (i) estimating the number, genomic positions, and genetic effects of heterotic QTL, (ii) characterizing their mode of gene action, and (iii) testing for presence of epistatic effects by a genomewide scan and marker x marker interactions. In total, 234 recombinant inbred lines (RILs) of Arabidopsis hybrid C24 x Col-0 were crossed to both parental lines and their F1 and analyzed with 110 single-nucleotide polymorphism (SNP) markers. QTL analyses were conducted using linear transformations Z1, Z2, and Z3 calculated from the adjusted entry means of TTC progenies. With Z1, we detected 12 QTL displaying augmented additive effects. With Z2, we mapped six QTL for augmented dominance effects. A one-dimensional genome scan with Z3 revealed two genomic regions with significantly negative dominance x additive epistatic effects. Two-way analyses of variance between marker pairs revealed nine digenic epistatic interactions: six reflecting dominance x dominance effects with variable sign and three reflecting additive x additive effects with positive sign. We conclude that heterosis for biomass-related traits in Arabidopsis has a polygenic basis with overdominance and/or epistasis being presumably the main types of gene action.