Investigating the Performance of Frequentist and Bayesian Techniques in Genomic Evaluation.

The genomic evaluation process relies on the assumption of linkage disequilibrium between dense single-nucleotide polymorphism (SNP) markers at the genome level and quantitative trait loci (QTL). The present study was conducted with the aim of evaluating four frequentist methods including Ridge Regression, Least Absolute Shrinkage and Selection Operator (LASSO), Elastic Net, and Genomic Best Linear Unbiased Prediction (GBLUP) and five Bayesian methods including Bayes Ridge Regression (BRR), Bayes A, Bayesian LASSO, Bayes C, and Bayes B, in genomic selection using simulation data. The difference between prediction accuracy was assessed in pairs based on statistical significance (p-value) (i.e., t test and Mann-Whitney U test) and practical significance (Cohen's d effect size) For this purpose, the data were simulated based on two scenarios in different marker densities (4000 and 8000, in the whole genome). The simulated data included a genome with four chromosomes, 1 Morgan each, on which 100 randomly distributed QTL and two different densities of evenly distributed SNPs (1000 and 2000), at the heritability level of 0.4, was considered. For the frequentist methods except for GBLUP, the regularization parameter λ was calculated using a five-fold cross-validation approach. For both scenarios, among the frequentist methods, the highest prediction accuracy was observed by Ridge Regression and GBLUP. The lowest and the highest bias were shown by Ridge Regression and GBLUP, respectively. Also, among the Bayesian methods, Bayes B and BRR showed the highest and lowest prediction accuracy, respectively. The lowest bias in both scenarios was registered by Bayesian LASSO and the highest bias in the first and the second scenario were shown by BRR and Bayes B, respectively. Across all the studied methods in both scenarios, the highest and the lowest accuracy were shown by Bayes B and LASSO and Elastic Net, respectively. As expected, the greatest similarity in performance was observed between GBLUP and BRR ( d = 0.007 , in the first scenario and d = 0.003 , in the second scenario). The results obtained from parametric t and non-parametric Mann-Whitney U tests were similar. In the first and second scenario, out of 36 t test between the performance of the studied methods in each scenario, 14 ( P < . 001 ) and 2 ( P < . 05 ) comparisons were significant, respectively, which indicates that with the increase in the number of predictors, the difference in the performance of different methods decreases. This was proven based on the Cohen's d effect size, so that with the increase in the complexity of the model, the effect size was not seen as very large. The regularization parameters in frequentist methods should be optimized by cross-validation approach before using these methods in genomic evaluation.

Sex-specific genetic parameter estimates of body weight in Mazandaran indigenous chickens.

Body weight is an economically important trait in poultry that shows sexual dimorphism (SD). In the present study, variation in SD in Mazandaran native chickens was investigated in terms of the (Co) variance components and genetic parameters of body weight between males and females. Studied traits were body weights at hatch (BW1), 8 weeks (BW8) and 12 weeks of age (BW12). Also, for weight at sexual maturity (WSM) covariance components were only estimated in females. Cross-sex direct and maternal correlations were also estimated for studied traits except for WSM. For this purpose, a deep 21-generation pedigree and body weight data (57,576 BW1, 72,925 BW8, 62,727 BW12 and, 42,496 WSM) were used. Evaluation of SD of body weight was performed using six bivariate animal models with and without considering the genetic and permanent maternal environmental effects under the restricted maximum likelihood method in WOMBAT software. Model with direct additive genetic effects and maternal genetic effects without covariance between them was identified as the best model for BW1 and BW8. The Model including direct additive genetic effects and permanent maternal environmental effects was the best model for BW12 and WSM. Direct heritability (h2) estimates for BW1, BW8 and, BW12 were, respectively, 0.05 ± 0.013, 0.17 ± 0.02 and, 0.25 ± 0.03 in males and, 0.05 ± 0.012, 0.15 ± 0.01 and 0.21 ± 0.01 in females. Also, the direct heritability of WSM based on univariate analysis in females was estimated to be 0.40 ± 0.01. Maternal heritability ( h m 2 ) varied from 0.39 ± 0.01 (BW1) to 0.04 ± 0.009 (BW8) in males, and 0.36 ± 0.10 (BW1) to 0.04 ± 0.006 (BW8) in females. The correlation between direct genetic effects between males and females for BW1 was not significantly different from one. The direct genetic correlation between the two sexes for BW8 and BW12 was significantly different from 1 concluding that these traits are dimorphic in terms of direct genetic effects and therefore independent selection in both sexes is possible.

Autosomal and Z-linked genetic evaluation for body weight in Mazandaran native chicken using different models for dosage compensation on the Z chromosome.

The objectives of this study were to assess the autosomal and sex-linked genetic inheritance of growth traits and identify the effective dosage compensation on the Z chromosome in Mazandaran native chickens. The data included body weights at hatching (BW0), 8 weeks (BW8) and 12 weeks (BW12) of age, related to the first 21 generations of selection, were collected from Mazandaran native chicken breeding centre. The fixed effects included sex of birds in two classes, hatch in five classes and generation in 21 classes. The inverse of the sex-linked additive genetic relationship matrix was constructed using nadiv package in R considering different models for dosage compensation on the Z chromosome. The setup inversed matrix was then supplied externally to WOMBAT using the GIN option. Twelve univariate animal models separating participation of autosomal additive genetic, sex-linked additive genetic and maternal effects (both genetic and permanent environment effects) with considering the five different dosage compensation methods for models with sex-linked effects were analysed by WOMBAT software. BW0 was not affected by sex-linked additive genetic effects. For BW8 and BW12 the model which included autosomal, sex-linked direct additive and maternal effects with no global dosage compensation for the Z chromosome was the most appropriate model. Autosomal heritability estimates were 0.05 ± 0.02, 0.10 ± 0.01 and 0.11 ± 0.01, for BW0, BW8 and BW12, respectively. For BW8 and BW12, sex-linked heritability estimates were 0.07 and 0.27, respectively. Spearman rank correlation coefficient between autosomal and sex-linked breeding values were 0.45 and 0.12 for BW8 and BW12, respectively. Spearman rank correlation coefficient between autosomal and sex-linked breeding values were 0.45 and 0.12 for BW8 and BW12, respectively. The autosomal direct additive genetic correlations between all traits were positive. The estimate of direct sex-linked additive genetic correlation between BW8 and BW12 was high (0.88). Also, maternal genetic correlations were 0.53, 0.54 and 0.91 between BW0-BW8, BW0-BW12 and BW8-BW12, respectively. Given the importance of Z-linked genes for BW8 and BW12, it is recommended that Z-linked effects be separated from autosomal effects in order to increase the accuracy of genetic evaluation of birds for these traits.

Quantifying the effect of inbreeding on average daily gain and Kleiber ratio in Mazandaran native chickens.

The aims of this study was to evaluate inbreeding effects for growth rate (average daily gain from hatch to 8 weeks of age (ADG1-8), average daily gain from hatch to 12 weeks of age (ADG1-12), average daily gain from 8 weeks of age to 12 weeks (ADG8-12), average daily gain from hatch to sex maturity (ADG1-SM), average daily gain from 8 weeks of age to sex maturity (ADG8-SM), average daily gain from 12 weeks to sex maturity (ADG12-SM), and Kleiber ratios (KR1-8, KR1-12, KR8-12) in Mazandaran native chickens. The data set of 82,446 pedigreed individuals over 21 generations was analyzed. All individuals were grouped into three classes based on the inbreeding coefficient: First class contained non-inbred birds (F = 0) and second and third classes contained inbred individuals (0 < F ≤ 5% and F > 5%, respectively). The effects of inbreeding coefficient on the studied traits were estimated by the restricted maximum likelihood method (REML) applying the WOMBAT software and fitting individual increase in inbreeding coefficient (ΔFi) of birds as linear covariates under 6 different animal models. ADG8-SM and ADG12-SM increased non-significantly by 0.003 and 0.005 g, respectively, due to 1% increase in ΔFi, while ADG1-8, ADG1-12, ADG8-12, ADG1-SM, KR1-8, and KR1-12 decreased (P < 0.001), respectively, by 0.012 g, 0.011 g, 0.010 g, 0.014 g, 0.003 g, and 0.002 g. Also, KR8-12 non-significantly decreased by 0.001 g. Estimates of direct heritability of traits based on the most appropriate models ranged from 0.05 (KR8-12) to 0.26 (ADG12-SM). Results showed that it is important to regularly analyze inbreeding level in the herd in an attempt to prevent the reduction of performance.

Comparison of parametric, semiparametric and nonparametric methods in genomic evaluation.

Access to dense panels of molecular markers has facilitated genomic selection in animal breeding. The purpose of this study was to compare the nonparametric (random forest and support vector machine), semiparametric reproducing kernel Hilbert spaces (RKHS), and parametric methods (ridge regression and Bayes A) in prediction of genomic breeding values for traits with different genetic architecture. The predictive performance of different methods was compared in different combinations of distribution of QTL effects (normal and uniform), two levels of QTL numbers (50 and 200), three levels of heritability (0.1, 0.3 and 0.5), and two levels of training set individuals (1000 and 2000). To do this, a genome containing four chromosomes each 100-cM long was simulated on which 500, 1000 and 2000 evenly spaced single-nucleotide markers were distributed. With an increase in heritability and the number of markers, all the methods showed an increase in prediction accuracy (P<0.05). By increasing the number of QTLs from 50 to 200, we found a significant decrease in the prediction accuracy of breeding value in all methods (P<0.05). Also, with the increase in the number of training set individuals, the prediction accuracy increased significantly in all statistical methods (P<0.05). In all the various simulation scenarios, parametric methods showed higher prediction accuracy than semiparametric and nonparametric methods. This superior mean value of prediction accuracy for parametric methods was not statistically significant compared to the semiparametric method, but it was statistically significant compared to the nonparametric method. Bayes A had the highest accuracy of prediction among all the tested methods and, is therefore, recommended for genomic evaluation.

N-acetylcysteine add-on treatment in refractory obsessive-compulsive disorder: a randomized, double-blind, placebo-controlled trial.

OBJECTIVE: This study aimed to evaluate the efficacy and safety of N-acetylcysteine, a glutamate-modulating agent, in patients with treatment-refractory obsessive-compulsive disorder as an adjunct to serotonin reuptake inhibitor treatment. METHODS: Forty-eight patients (36 women; mean ± SD age, 30.93 ± 4.99) with obsessive-compulsive disorder who failed to respond to a course of serotonin reuptake inhibitor treatment were randomized to a 12-week intervention period of N-acetylcysteine (up to 2400 mg/d) or placebo. Primary outcome measures were the change in Yale-Brown Obsessive Compulsive Scale (Y-BOCS) score from baseline to end point and the rate of full response in each group at the end of trial. Full response was defined as 35% or greater reduction in Y-BOCS score from baseline. RESULTS: Changes of Y-BOCS score were different over time (P < 0.001) and between groups (P < 0.001). N-acetylcysteine-assigned patients showed significantly improved mean Y-BOCS score (P = 0.003) and Clinical Global Impression-Severity of Illness scale score (P = 0.01) but not Clinical Global Impression-Improvement scale score at study end point. Of the patients in the N-acetylcysteine group, 52.6% were full responders at the end of the study, which was significantly higher than 15% of the patients in the placebo group (P = 0.013). CONCLUSION: This trial suggests that N-acetylcysteine may be a safe and effective option to augment standard treatment in patients with refractory obsessive-compulsive disorder.