The statistical power of genome-wide association studies for threshold traits with different frequencies of causal variants.

This study aimed to investigate the effects of incidence rate, heritability, and polygenic variance on the statistical power of genome-wide association studies (GWAS) for threshold traits. Different incidence rates of threshold trait (1, 3, 5, 10, 25, 40, 50, 60, 75 and 90%), heritability (10 and 25%), and polygenic variance ratio (0 and 25%) were simulated separately for common (MAF ≥ 0.05), low-frequency (0.05 > MAF ≥ 0.01), and rare (MAF < 0.01) variants. Association studies were performed by logistic and linear mixed models. The highest statistical powers were observed in common and low-frequency variants with an incidence of 25-50% and 10-40%, respectively, but for rare variants, the highest statistical power was observed at low incidence. For all causal variant frequencies, the estimated heritability decline with an increase in incidence rate. We found high statistical power for traits with high heritability. In contrast, those with a high polygenic variance ratio have lower statistical power to detect common causal variants using a linear mixed model. These results demonstrate that the incidence rate of threshold traits, heritability, and polygenic variance may affect the statistical power of GWAS. Therefore, it is recommended that the effect of incidence rate, heritability, and polygenic variance be considered in designing GWAS for threshold traits.

Bayesian estimate of genetic parameters for growth traits in Lori Bakhtiari sheep.

The information of birth (10,017 records), weaning (9439 records), 6 months (7669 records), 9 months (4536 records), and yearling weights (417 records) collected from 1989 to 2016 by the Lori Bakhtiari (Sholi) sheep breeding station located in Shahrekord were used to estimate the genotypic and phenotypic parameters of growth traits of Lori Bakhtiari sheep. The components of variance and genetic parameters were estimated by the Bayesian statistical method based on the Gibbs sampling technique due to the high accuracy of this method. Factors including birth year, lamb sex, birth type, and maternal age at lambing have significant effects on all of these traits (P < 0.01) and were considered fixed effects in the statistical model for estimation of genetic parameters. Lamb weight at weaning was used as a covariate in the model. Based on the models with the lowest Akaike information criterion, direct heritability for birth, weaning, 6-month, 9-month, and yearling weights were 0.36, 0.18, 0.21, 0.27, and 0.32, respectively. The moderate heritability obtained for the studied traits pointed up the effectiveness of selection in genetic improvement, but the environmental conditions should be improved for better performance of weight traits.