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 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.

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.

scholarly journals Random regression models to estimate genetic parameters for milk production of Guzerat cows using orthogonal Legendre polynomials

2014 ◽  
Vol 49 (5) ◽  
pp. 372-383 ◽  
Author(s):  
Maria Gabriela Campolina Diniz Peixoto ◽  
Daniel Jordan de Abreu Santos ◽  
Rusbel Raul Aspilcueta Borquis ◽  
Frank Ângelo Tomita Bruneli ◽  
João Cláudio do Carmo Panetto ◽  
...  
Keyword(s):  
Milk Production ◽  
Legendre Polynomial ◽  
Legendre Polynomials ◽  
Regression Models ◽  
Environmental Effect ◽  
Genetic Parameters ◽  
Genetic Effect ◽  
Random Regression ◽  
Additive Genetic Effect ◽  
Fifth Order

The objective of this work was to compare random regression models for the estimation of genetic parameters for Guzerat milk production, using orthogonal Legendre polynomials. Records (20,524) of test-day milk yield (TDMY) from 2,816 first-lactation Guzerat cows were used. TDMY grouped into 10-monthly classes were analyzed for additive genetic effect and for environmental and residual permanent effects (random effects), whereas the contemporary group, calving age (linear and quadratic effects) and mean lactation curve were analized as fixed effects. Trajectories for the additive genetic and permanent environmental effects were modeled by means of a covariance function employing orthogonal Legendre polynomials ranging from the second to the fifth order. Residual variances were considered in one, four, six, or ten variance classes. The best model had six residual variance classes. The heritability estimates for the TDMY records varied from 0.19 to 0.32. The random regression model that used a second-order Legendre polynomial for the additive genetic effect, and a fifth-order polynomial for the permanent environmental effect is adequate for comparison by the main employed criteria. The model with a second-order Legendre polynomial for the additive genetic effect, and that with a fourth-order for the permanent environmental effect could also be employed in these analyses.

scholarly journals Genetic effects on reproductive traits in Warmblood horses

2009 ◽  
Vol 89 (2) ◽  
pp. 215-218 ◽  
Author(s):  
A. Wolc ◽  
G. Torzynski ◽  
T. Szwaczkowski
Keyword(s):  
Key Words ◽  
Fixed Effects ◽  
Genetic Parameters ◽  
Genetic Effect ◽  
Reproductive Traits ◽  
Additive Genetic Effect ◽  
Reproductive Efficiency ◽  
Horse Breeding ◽  
Estimate Heritability ◽  
Genetic Trends

Reproductive efficiency is an important issue in horse breeding. However, almost no estimates of genetic parameters of reproductive traits in horses can be found in the literature. The objective of the study was to estimate heritability and genetic trends of foaling rate and number of reproductive seasons in Warmblood horses. The records of 3965 mares from six studs were analyzed. Mares were on average kept for 7.3 reproductive seasons with a foaling rate of 66%. Models included fixed effects of stud, period of birth, breed and random additive genetic effect. Heritability estimates were 0.12 for foaling rate and 0.17 for number of reproductive seasons. Key words: Heritability, reproduction, horse

Genetic Studies of the Offspring of Identical Twins - A Model for the Analysis of Quantitative Inheritance in Man

1976 ◽  
Vol 25 (1) ◽  
pp. 103-113 ◽  
Author(s):  
Walter E. Nance
Keyword(s):  
Birth Weight ◽  
Genetic Variance ◽  
Genetic Model ◽  
Genetic Effect ◽  
Identical Twins ◽  
Additive Genetic Effect ◽  
Quantitative Inheritance ◽  
Ridge Count ◽  
Environmental Variance ◽  
Genetic Studies

In conjunction with full-sib and parental observations, half-sib analysis permits an estimation of the genetic and environmental variance as well as a partitioning of the genetic variance into its additive, dominance and epistatic components. The offspring of identical twins are a unique class of human half-sibs who provide an unusual opportunity to resolve and measure several additional potentially important sources of human variation including maternal effects, the influences of common environmental factors and assortative mating.The genetic model thus developed for the analysis of quantitative inheritance in man has been applied to the analysis of total ridge count and birth weight, confirming the existence of a major additive genetic effect on ridge count and a significant maternal effect on birth weight.

Estimates of genetic parameters for ultrasound-measured carcass traits in sheep

2004 ◽  
Vol 84 (3) ◽  
pp. 361-365 ◽  
Author(s):  
T. L. Fernandes ◽  
J. W. Wilton ◽  
J. J. Tosh
Keyword(s):  
Genetic Improvement ◽  
Variance Component ◽  
Genetic Parameters ◽  
Genetic Correlations ◽  
Genetic Effect ◽  
Backfat Thickness ◽  
Additive Genetic Effect ◽  
Multiple Trait ◽  
Breed Group ◽  
Variance Component Estimates

Data on ultrasound traits (loin depth, average backfat thickness, and loin width) were collected from lambs (n = 3483) across Ontario, born between 1997 and 1999. The data were analysed with a REML procedure in a multiple-trait mixed-animal model to obtain (co)variance component estimates. Analyses of all traits included the additive genetic effect of the lamb, sex of the lamb, contemporary group, and breed group effects. Weight or age was included as a covariate in two separate analyses. Estimates of direct additive heritabilities for loin depth, average backfat thickness, and loin width were 0.29, 0.29 and 0.26 respectively, with genetic correlations of -0.17 between loin depth and average backfat thickness, 0.43 between loin depth and loin width, and 0.23 between loin width and average backfat thickness for the weight constant analysis. When the data were analysed using age in the regression analysis, corresponding estimates of direct additive heritabilities were 0.38, 0.35 and 0.30, and genetic correlations between traits were all positive, 0.29 between loin depth and average backfat thickness, 0.61 between loin depth and loin width, and 0.44 between loin width and average backfat thickness. Results indicate that it is possible to make genetic improvement if selection is based on ultrasound information. Key words: Sheep, genetic parameters, heritability, ultrasound

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.

Genetic parameters of milk traits in Latxa dairy sheep

2001 ◽  
Vol 73 (3) ◽  
pp. 407-412 ◽  
Author(s):  
A. Legarra ◽  
E. Ugarte
Keyword(s):  
Milk Fat ◽  
Fixed Effects ◽  
Genetic Parameters ◽  
Genetic Correlations ◽  
Selection Criterion ◽  
Genetic Effect ◽  
Milk Composition ◽  
Additive Genetic Effect ◽  
Dairy Sheep ◽  
Milk Traits

AbstractA total of 7444 lactation records which include milk, fat and protein yields (MY, FY, PY) and fat and protein content (F%, P%) from 6429 Black-Faced Latxa ewes were employed to estimate genetic parameters for milk traits. Traits were standardized to 120 days of lactation. For the calculation of composition traits, not all test-days had their composition measured and therefore a correction taking this into account was included in the analysis. A first-derivative restricted maximum likelihood algorithm was used on an animal model with repeatability analysis, using models including fixed effects (flock-year-season of lambing, age-parity at lambing, number of lambs, interval between lambing and first milk recording and the combination of sampled test-days) and random effects (the additive genetic effect and the permanent environmental effect). The resulting heritabilities were 0·20, 0·16, 0·18, 0·14 and 0·38 for MY, FY, PY, F% and P% respectively. Heritability of F% was much lower than expected, probably due to problems derived from the recording method. Genetic correlations were high and positive between yields and moderately positive between F% and P%, and negative or null between yields and composition, as has been reported for other European dairy sheep breeds. As most of the milk produced by Latxa dairy sheep is processed into cheese, the inclusion of milk sampling in official milk recording and a change in the selection criterion are recommended to avoid a long-term worsening in milk composition.

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).

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