Evaluating the estimation of genetic correlation and heritability using summary statistics

Demarcation of anxiety and fear: Evidence from behavioral genetics

Anxiety and fear are emotions often intertwined in response to aversive stimuli, complicating efforts to differentiate them and understand their distinct consequences. This study explores the common genetic and environmental factors contributing to the co-occurrence of anxiety disorders and dimensions of the revised Reinforcement Sensitivity Theory (rRST). A sample of 356 monozygotic (22.5 % males; M = 25.73, SD = 8.3) and 386 dizygotic (33.9 % males; M = 24.21, SD = 8.33) twins from the Serbian Twin Advanced Registry was analyzed. The Psychiatric Diagnostic Screening Questionnaire (PDSQ) provided scales for panic disorder, agoraphobia, social phobia, and generalized anxiety disorder (GAD), while the Reinforcement Sensitivity Questionnaire (RSQ) measured the Behavioral Inhibition System (BIS), Behavioral Activation System (BAS), and Fight/Flight/Freeze System (FFFS). Common additive genetic effects accounted for most of the variance in BIS, Fight, and panic, agoraphobia, and social phobia, while specific additive genetic effects were highest for Flight. Shared environmental effects were most pronounced for Fight across all models, with additional shared influences on BAS and BIS for panic, and BAS and Freeze for agoraphobia and social phobia. Nonshared environmental effects were the highest specific contributors across variables. Genetic overlap between anxiety disorders and rRST dimensions suggests pleiotropy, with unique environmental factors playing an important role in disorder development. While anxiety and fear may stem from distinct etiologies, their shared symptomatology complicates differentiation, highlighting the importance of considering both genetic and environmental influences in anxiety disorders.

Delineating maternal influence in regulation of variance in major economic traits of White Leghorns: Bayesian insights

Proper variance partitioning and estimation of genetic parameters at appropriate time interval is crucial for understanding the dynamics of trait variance and genetic correlations and for deciding the future breeding strategy of the population. This study was conducted on the same premise to estimate genetic parameters of major economic traits in a White Leghorn strain IWH using Bayesian approach and to identify the role of maternal effects in the regulation of trait variance. Three different models incorporating the direct additive effect (Model 1), direct additive and maternal genetic effect (Model 2) and direct additive, maternal genetic and maternal permanent environmental effects (Model 3) were tried to estimate the genetic parameters for body weight traits (birth weight, body weight at 16, 20, 40 and 52 weeks), Age at sexual maturity (ASM), egg production traits (egg production up to 24, 28, 40, 52, 64 and 72 weeks) and egg weight traits (egg weight at 28, 40 and 52 weeks). Model 2 and Model 3 with maternal effects were found to be the best having the highest accuracy for almost all the traits. The direct additive genetic heritability was moderate for ASM, moderate to high for body weight traits and egg weight traits and low to moderate for egg production traits. Though the maternal heritability (h2mat) and permanent environmental effect (c2mpe) was low (<0.1) for most of the traits, they formed an important component of trait variance. Traits like egg weight at 28 weeks (0.14±0.06) and egg production at 72 weeks (0.13±0.07) reported comparatively higher values for c2mpe and h2mat respectively. Additive genetic correlation was high and positive between body weight traits, between egg weight traits, between consecutive egg production traits and between body weight and egg weight traits. However, a negative genetic correlation existed between egg production and egg weight traits, egg production and body weight traits, ASM and early egg production traits. Overall, a moderate positive genetic correlation was estimated between ASM and body weight traits and ASM and egg weight traits. Based on our findings, we can deduce that maternal effects constitute an important source of variation for all the major economic traits in White Leghorn and should be necessarily considered in genetic evaluation programs.

Racing Performance of the Quarter Horse: Genetic Parameters, Trends and Correlation for Earnings, Best Time and Time Class

The aim of this study was to evaluate the sprint racing performance of Quarter Horses in Brazil. Estimating genetic parameters, trends and correlations were obtained by single- and two-trait analyses using Bayesian inference (earnings to 2 years of equestrian age, best time and time class at distances of 301 m and 402 m). The data comprised a period of 38 equestrian years (1978 to 2015) with 23,482 sprint race records from 5861 animals. The heritability estimates were of low to moderate magnitude, ranging from 0.10 to 0.37 (single-trait) and from 0.15 to 0.41 (two-traits), and the repeatability was 0.31 to 0.46. The additive, residual and phenotypic correlations between earnings to 2 years of equestrian age and the other traits (best time and time class in distances 301 m and 402 m) were high (-0.95, -0.96, 0.69 and 0.92), low (-0.29, -0.37, 0.26 and 0.27) and moderate (-0.41, -0.47, 0.37 and 0.47), respectively. There is a positive genetic trend for all traits considered. However, evaluation of the last 10 equestrian years (2006 to 2015) showed negative trends (genetic loss) and trends close to zero (genetic stagnation). The design of breeding programs using the earnings trait in conjunction with other racing performance traits can enhance changes in the genetic gains as a whole in speed-racing Quarter Horses. These findings suggest that the traits studied should be included in breeding selection programs for racing Quarter Horses.