scholarly journals GIBBSTHUR: Software for Estimating Variance Components and Predicting Breeding Values for Ranking Traits Based on a Thurstonian Model

Animals ◽  
2020 ◽  
Vol 10 (6) ◽  
pp. 1001
Author(s):  
Luis Varona ◽  
Andrés Legarra
Keyword(s):  
Markov Chain ◽  
Variance Components ◽  
Data Augmentation ◽  
Genetic Effect ◽  
Additive Genetic Effect ◽  
Public Repository ◽  
Breeding Values ◽  
Average Performance ◽  
Covariance Components ◽  
Variance And Covariance Components

(1) Background: Ranking traits are used commonly for breeding purposes in several equine populations; however, implementation is complex, because the position of a horse in a competition event is discontinuous and is influenced by the performance of its competitors. One approach to overcoming these limitations is to assume an underlying Gaussian liability that represents a horse’s performance and dictates the observed classification in a competition event. That approach can be implemented using Montecarlo Markov Chain (McMC) techniques with a procedure known as the Thurstonian model. (2) Methods: We have developed software (GIBBSTHUR) that analyses ranking traits along with other continuous or threshold traits. The software implements a Gibbs Sampler scheme with a data-augmentation step for the liability of the ranking traits and provides estimates of the variance and covariance components and predictions of the breeding values and the average performance of the competitors in competition events. (3) Results: The results of a simple example are presented, in which it is shown that the procedure can recover the simulated variance and covariance components. In addition, the correlation between the simulated and predicted breeding values and between the estimates of the event effects and the average additive genetic effect of the competitors demonstrates the ability of the software to produce useful predictions for breeding purposes. (4) Conclusions: the GIBBSTHUR software provides a useful tool for the breeding evaluation of ranking traits in horses and is freely available in a public repository (https://github.com/lvaronaunizar/Gibbsthur).

scholarly journals Maternal effect on sports performance traits in horses

2019 ◽  
Vol 64 (No. 8) ◽  
pp. 361-365
Author(s):  
Tomasz Próchniak ◽  
Iwona Rozempolska-Rucińska ◽  
Grzegorz Zięba
Keyword(s):  
Maternal Effect ◽  
Sampling Method ◽  
Genetic Effect ◽  
Additive Genetic Effect ◽  
Sports Performance ◽  
High Effect ◽  
Performance Traits ◽  
Covariance Components ◽  
Variance And Covariance Components ◽  
Young Horses

The aim of the study was to estimate the direct additive genetic effect and the additive maternal effect on the level of traits estimated during the Polish Jumping Championships for Young Horses. The investigations involved 541 stallions and 353 mares, which in total started in the Championships 1232 times. Variance and covariance components were estimated using the Gibbs sampling method. Heritability (h<sup>2</sup>) and repeatability (r<sup>2</sup>) coefficients as well as maternal effects (m<sup>2</sup>) were calculated for 7 sports performance traits. There was an additive maternal effect, ranging from 0.11 to 0.39, on the level of traits assessed based on achieved scores. The effect was particularly high in the case of traits the level of which was determined by the animal organism performance and stress resistance. It was also noted that the value of the maternal effect in some traits was similar or higher than the coefficient of heritability, which may indicate a high effect of the mare’s specific environment in determining sport predispositions in the offspring. There is a need to analyse the cause of trait variability in other equestrian disciplines.

scholarly journals Genomic Breeding Values for Claw Diseases/Disorders in Czech Holstein Cows

2019 ◽  
Vol 67 (5) ◽  
pp. 1245-1251
Author(s):  
Ludmila Zavadilová ◽  
Eva Kašná ◽  
Zuzana Krupová
Keyword(s):  
Infectious Diseases ◽  
Fixed Effects ◽  
Genetic Correlations ◽  
Genetic Effect ◽  
Holstein Cows ◽  
Additive Genetic Effect ◽  
Genomic Information ◽  
White Line ◽  
Genomic Breeding ◽  
Breeding Values

Genomic breeding values (GEBV) were predicted for claw diseases/disorders in Holstein cows. The data sets included 6,498, 6,641 and 16,208 cows for the three groups of analysed disorders. The analysed traits were infectious diseases (ID), including digital and interdigital dermatitis and interdigital phlegmon, and non-infectious diseases (NID), including ulcers, white line disease, horn fissures, and double sole and overall claw disease (OCD), comprising all recorded disorders. Claw diseases/disorders were defined as 0/1 occurrence per lactation. Linear animal models were employed for prediction of conventional breeding values (BV) and genomic breeding values (GEBV), including the random additive genetic effect of animal and the permanent environmental effect of cow and fixed effects of parity, herd, year and month of calving. Both high and intermediate weights (80% and 50%, respectively) of genomic information were employed for GEBV50 and GEBV80 prediction. The estimated heritability for ID was 3.47%, whereas that for NID 4.61% and for OCD was 2.29%. Approximate genetic correlations among claw diseases/disorders traits ranged from 19% (ID x NID) to 81% (NID x OCD). The correlations between predicted BV and GEBV50 (84–99%) were higher than those between BV and GEBV80 (70–98%). Reliability of breeding values was low for each claw disease/disorder (on average, 3.7 to 14.8%) and increased with the weight of genomic information employed.

Potential biases of incomplete linear models in heritability estimation and breeding value prediction

1999 ◽  
Vol 29 (6) ◽  
pp. 724-736 ◽  
Author(s):  
P X Lu ◽  
D A Huber ◽  
T L White
Keyword(s):  
Genetic Variance ◽  
Linear Models ◽  
Additive Genetic Variance ◽  
Genetic Effect ◽  
Breeding Value ◽  
Additive Genetic Effect ◽  
Unbalanced Data ◽  
Breeding Values ◽  
Incomplete Model ◽  
Heritability Estimation

Potential biases associated with incomplete linear models in the estimation of heritability and the prediction of breeding values have been investigated. Results indicate that estimates of additive genetic variance and heritability as well as predicted parental breeding values from incomplete models will inevitably be biased as long as the true variance components of ignored effects are not zero. While models ignoring the interaction effect of males and females (SCA) × environment (E) interaction downwardly biased the estimates of additive genetic variance and heritability, models ignoring SCA and (or) the additive genetic effect (GCA) × E interaction yielded upward biases. The magnitudes of biases are functions of population genetic architecture, mating design, and field experimental design and can be precisely assessed with formulae derived for balanced data. Numerical simulations using unbalanced data of different mating and field experimental designs suggest that the formulae from balanced data can be used to approximate the minimum biases associated with unbalanced data. Because of the magnitudes of biases for some typical forest genetic scenarios, it is suggested that models ignoring SCA and (or) GCA × E should be avoided when the numbers of test sites and crosses per parent are small. However, incomplete model ignoring SCA × E interaction may be used to reduce computational demand with only negligible consequences.

Evaluation genetic parameters for weight at different ages in Baluchi breed of sheep

2003 ◽  
Vol 2003 ◽  
pp. 145-145
Author(s):  
M. Hosseinpour Mashhadi ◽  
F. Eftekhari Shahroudi ◽  
R. Valizadeh
Keyword(s):  
Birth Weight ◽  
Genetic Parameters ◽  
Genetic Effect ◽  
Additive Genetic Effect ◽  
Maternal Environment ◽  
Breeding Programs ◽  
Breeding Values ◽  
Genetic Potential ◽  
Different Ages ◽  
Maternal Genetic Effect

Improving breeding values and breeding programs should be done based on genetic potential. The range of additive direct heritability and maternal environment heritability for birth weight is about 0.07 to 0.22 and 0.1 to 0.33 respectively the range of these values for the following weights are 0.09- 0.58 and 0.01- 0.17. the objective of this study was to predict the direct additive genetic effect, maternal genetic effect and heritabilities of lamb weight traits in baluchi breed of sheep.

scholarly journals Estimates of (co)variance components and genetic parameters for growth traits in Suffolk lambs

2013 ◽  
Vol 43 (12) ◽  
pp. 2215-2220 ◽  
Author(s):  
Priscilla Regina Tamioso ◽  
Jaime Luiz Alberti Filho ◽  
Laila Talarico Dias ◽  
Rodrigo de Almeida Teixeira
Keyword(s):  
Maternal Effects ◽  
Variance Components ◽  
Genetic Parameters ◽  
Growth Traits ◽  
Genetic Effect ◽  
Additive Genetic Effect ◽  
Ratio Test ◽  
Effect Model ◽  
Estimate Heritability ◽  
Heritability Estimates

The study aimed to estimate the components of (co)variance and heritability for weights at birth (BW), weaning (WW) and 180 days of age (W180), as well as the average daily gains from birth to weaning (ADG1), birth to 180 days of age (ADG2) and weaning to 180 days of age (ADG3) in Suffolk sheep. Thus, three different single-trait animal models were fitted, considering the direct additive genetic effect (Model 1), the direct additive genetic and maternal permanent environmental effects (Model 2), and in Model 3, in addition to those in Model 2, the maternal additive genetic effect was included. After comparing models through the likelihood ratio test (LRT), model 3 was chosen as the most appropriate to estimate heritability for BW, WW and ADG1. Model 2 was considered as the best to estimate the coefficient of heritability for W180 and ADG2, and model 1 for ADG3. Direct heritability estimates were inflated when maternal effects were ignored. According to the most suitable models, the heritability estimates for BW, WW, W180, ADG1, ADG2 and ADG3 were 0.06, 0.08, 0.09, 0.07, 0.08 and 0.07, respectively, indicating low possibility of genetic gain through individual selection. The results show the importance of including maternal effects in the models to properly estimate genetic parameters even at post-weaning ages.

scholarly journals Use of individual race results in the estimation of genetic parameters of trotting performance for Finnhorse and Standardbred trotters

1999 ◽  
Vol 8 (4-5) ◽  
pp. 353-363 ◽  
Author(s):  
T. THUNEBERG-SELONEN ◽  
J. PÖSÖ ◽  
E. MÄNTYSAARI
Keyword(s):  
Animal Model ◽  
Maximum Likelihood ◽  
Variance Components ◽  
Fixed Effects ◽  
Environmental Effect ◽  
Genetic Parameters ◽  
Genetic Effect ◽  
Additive Genetic Effect ◽  
Performance Traits ◽  
Estimation Of Genetic Parameters

The heritability and repeatability for trotting performance traits were estimated from individual race results. Data comprised of records from 1991 to 1995 for 4808 Finnhorses and from 1993 to 1995 for 5869 Standardbred trotters. The statistical model included the additive genetic effect of an animal and two permanent environmental effects, and the fixed effects of sex, age, starting method*starting lane combination, driver and race. The first permanent environmental effect described repeatability over a horse’s career while the second one characterized repeatability within a racing year. Variance components for three trotting performance traits were estimated by the animal model and the method of restricted maximum likelihood (REML). Heritability and repeatability estimates were moderately high for time at finish (h 2 =0.23–0.28 and r=0.50–0.57), moderate for ranking within a race (h 2 =0.12 and r=0.25) and low for earnings (h 2 =0.05–0.09 and r=0.15–0.18). Time at finish seemed to be the most usable measure of trotting performance because of its wide information substance. However, time at finish does not take into account records of disqualified horses or of those which did not finish, but use of earnings, either from individual race results or preferably from annual records, is one possible way to consider records of such horses.;

scholarly journals Sensitivity of breeding values of meat quail as a result of tryptophan: lysine ratios in the diet

2018 ◽  
Vol 19 (4) ◽  
pp. 403-414
Author(s):  
Rúbia Francielle Moreira Rodrigues ◽  
Mariele Freitas Sousa ◽  
Valdecy Aparecida Rocha Cruz ◽  
Thaiza da Silva Campideli ◽  
Leonardo da Silva Costa ◽  
...  
Keyword(s):  
Genetic Effect ◽  
Genotype X Environment Interaction ◽  
Reaction Norms ◽  
Random Regression ◽  
Additive Genetic Effect ◽  
Residual Variance ◽  
Environment Interaction ◽  
Breeding Values ◽  
Genotype X Environment ◽  
Best Fit

SUMMARY We aimed to evaluate the random regression models that promote the best fit of residual variance predicting the breeding values of quail body weights and the sensitivity of its breeding values to the variations of different tryptophan:lysine ratios in the diets via reaction norms. A total of 1112 meat quails from LF1 and LF2 lines with 35 days of age were evaluated. During the period of 1 to 21 days of age, birds were fed with different tryptophan:lysine ratios (0.17, 0.20, 0.23, 0.26 and 0.29%) containing 2900 kcal ME/kg and 26.10% crude protein, followed by basal diet provided up to 35 days. The best model fit for residual variance was evaluated comparing heterogeneity (2, 3 and 4 classes) and homogeneity (1 class), including sex as fixed effect and the additive genetic effect as random. The second order Legendre polynomial was used to analyze the genotype x environment interaction using reaction norms. The model considering two classes of residual variance was the one that promoted the best fit of the data, being adopted to predict the breeding values. Thus, we observed changes in the sensitivity of the breeding values, characterized by the rearrangement of the breeding values, according to the different ratios of amino acids, suggesting the genotype x environment interaction.

scholarly journals Estimation of Genetic Parameters and Breeding Values of Milk Yield Using Test Day Model with Cubic Splines and Legendre Polynomials in Chinese Holstein Cattle

2021 ◽  
Vol 25 (02) ◽  
pp. 354-360
Author(s):  
Wan Lv
Keyword(s):  
Milk Yield ◽  
Legendre Polynomials ◽  
Environmental Effect ◽  
Genetic Parameters ◽  
Genetic Effect ◽  
Information Criterion ◽  
Additive Genetic Effect ◽  
Optimal Model ◽  
Breeding Values ◽  
Estimation Of Genetic Parameters

This study aimed to estimate the genetic parameters and breeding values of milk yield traits of Holstein cows in Shandong Province using the best model identified by a comparison between a numbers of alternative random regression test day models (RRMs). The data included 585,702 test day records of milk yield in the first lactation of 88,215 Holstein cows, covering 219 cattle farms in Shandong Province during the period from 2005 to 2016. Different models were investigated, which differed in the number of knots of Spline functions to improve the fitting of population lactation curve and in orders (2, 3, or 4) of Legendre polynomials to fit additive genetic effect and permanent environmental effect. The optimal test day model was screened out by Akaike information criterion (AIC) and Bayesian information criterion (BIC) criteria. Detailed analysis of genetic parameters and accuracy of estimation of breeding values were performed using the optimal model. In the results, the optimal model (Sp15-La4-Lp3) for analyzing the milk yield data was the one with 15 knots of Splines, 4 orders of Legendre polynomials for additive genetic effect and 3 orders of Legendre polynomials for permanent environmental effect. Using the optimal model, estimates of additive genetic variances of milk yield at different days in milk (DIM) during the whole lactation ranged from 8.54 to 15.39, the permanent environmental variance ranged from 17.65 to 31.42. Correspondingly, the heritability ranged from 0.20 to 0.30, and repeatability ranged from 0.43 to 0.54. Rank correlations between EBV of bull with different number of daughters and the bull’s parent average ranged from 0.79 to 0.94, and the correlations between EBV of bulls and the sire-maternal grandsire index ranged from 0.48 to 0.86. In conclusion, Sp15-La4-Lp3 could be the optimal model for estimation of genetic parameters and prediction of breeding values of milk in Shandong Holstein population. The amount of progeny information is critical to the conventional genetic evaluation of bulls. © 2021 Friends Science Publishers

scholarly journals Genetic evaluation of body weight traits in Iranian native Ghezel sheep

Genetika ◽  
2018 ◽  
Vol 50 (1) ◽  
pp. 275-284 ◽  
Author(s):  
H. Baneh ◽  
J. Ahmadpanah
Keyword(s):  
Body Weight ◽  
Genetic Parameters ◽  
Growth Traits ◽  
Univariate Analysis ◽  
Genetic Effect ◽  
Additive Genetic Effect ◽  
Pedigree Information ◽  
Breeding Values ◽  
Maternal Heritability ◽  
Genetic Trends

The aim of the current study was to estimate genetic parameters and trends for body weight traits at different ages in Ghezel lambs. Traits included were birth weight (BW), 3-month weight (3MW), 6-month weight (6MW), 9-month weight (9MW), and yearling weight (YW). Data and pedigree information used in the present study were collected at the Breeding Station of Ghezel sheep during 1986-2009. (Co) variance components were estimated using REML procedure and breeding values of animals were predicted with Best Linear Unbiased Prediction (BLUP) methodology under univariate analysis. Three different animal models were fitted. The models consisted of the direct additive genetic effect but differed in combinations of maternal additive genetic and maternal permanent environmental effects. Genetic trends for each trait were obtained by regressing the means of predicted breeding values on year of birth. The estimates of direct heritability were 0.285, 0.371, 0.388, 0.450 and 0.179, respectively. Also, the maternal heritability was estimated 0.113, 0.031, 0.021 and 0.030 for BW, WW, 6MW and 9MW, respectively. Direct genetic trends were positive and significant for BW, WW, 6MW (p<0.01), 9MW and YW (p<0.05) and were obtained 2.34, 46.20, 55.11, 33.40 and 24.01 (g/year), respectively. Also, maternal trends for BW, WW, 6MW and YW were positive and highly significant (p<0.01) and were 3.37, 17.05, 12.56 and 16.30 (g/year), respectively. The results indicated that considering maternal effects in the statistical model make accurate estimates of genetic parameters. Also, improvement of growth traits in Ghezel sheep seems to be likely in selection programs.

Personal Goals of Older Female Twins

2009 ◽  
Vol 14 (2) ◽  
pp. 160-167 ◽  
Author(s):  
Katariina Salmela-Aro ◽  
Sanna Read ◽  
Jari-Erik Nurmi ◽  
Markku Koskenvuo ◽  
Jaakko Kaprio ◽  
...  
Keyword(s):  
Physical Exercise ◽  
Independent Living ◽  
Environmental Effect ◽  
Close Relationships ◽  
Environmental Influence ◽  
Genetic Effect ◽  
Additive Genetic Effect ◽  
Personal Goals ◽  
Cultural Activities ◽  
The Individual

This study examined genetic and environmental influences on older women’s personal goals by using data from the Finnish Twin Study on Aging. The interview for the personal goals was completed by 67 monozygotic (MZ) pairs and 75 dizygotic (DZ) pairs. The tetrachoric correlations for personal goals related to health and functioning, close relationships, and independent living were higher in MZ than DZ twins, indicating possible genetic influence. The pattern of tetrachoric correlations for personal goals related to cultural activities, care of others, and physical exercise indicated environmental influence. For goals concerning health and functioning, independent living, and close relationships, additive genetic effect accounted for about half of the individual variation. The rest was the result of a unique environmental effect. Goals concerning physical exercise and care of others showed moderate common environmental effect, while the rest of the variance was the result of a unique environmental effect. Personal goals concerning cultural activities showed unique environmental effects only.

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