Estimation of variance components for body weight of grasscutters (Thryonomys swinderianus) using a repeatability model

2020 ◽  
Vol 47 (2) ◽  
pp. 33-36
Author(s):  
I. Udeh
Keyword(s):  
Animal Model ◽  
Body Weight ◽  
Variance Components ◽  
Genetic Parameters ◽  
Growth Potential ◽  
Likelihood Method ◽  
Mass Selection ◽  
Thryonomys Swinderianus ◽  
Estimate Variance ◽  
Estimation Of Variance

Genetic parameters for growth and other economically important traits of grasscutters are scant in literature. Therefore, the aim of this study was to estimate variance components,heritability and repeatability of body weight of grasscutters using restricted maxim um likelihood method in a repeatability animal model. Sixteen grasscutter families were used for the study. Each family was made up of one male and four females. Each grasscutter has four repeated records giving a total of 320. The pedigree consisted of 80 animals, progenies of 16 sires and 16 dams. Fixed factors included in the model were family and sex. The WOMBAT program was used for the analysis. The heritability of body weight of grasscutters ranged from 0.23±0.04 to 0.68±0.10, thus implying that mass selection will be appropriate for this population. The repeatability estimates ranged from 0.82±0.08 to 0.93±0.11. It can be concluded that the number of body weight records was a good indicator of the animal's growth potential and that mass selection will be reliable.

scholarly journals Schätzung von Varianzkomponenten mit Gruppenmittelwerten am Beispiel von Legehennen, gehalten in Gruppenkäfigen

2003 ◽  
Vol 46 (5) ◽  
pp. 491-498
Author(s):  
N. Mielenz ◽  
V. Nurgiartiningsih ◽  
M. Schmutz ◽  
L. Schüler
Keyword(s):  
Animal Model ◽  
Variance Components ◽  
Genetic Parameters ◽  
Genetic Relationships ◽  
Information Matrix ◽  
Egg Weight ◽  
Complex Relationships ◽  
Estimate Variance ◽  
Additive Genetic Effects ◽  
Estimation Of Variance

Abstract. Title of the paper: Estimation of variance components from group mean records of laying hens housed in group cages Two models are presented to estimate variance components if only group mean records are available. The first model accounts for additive genetic relationships and full-sib group effects (SIMIANER and GJERDE, 1991) and the second model contains the additive genetic effects of all animals from one cage by using modified design matrices. Estimates of the genetic parameters were obtained by the MIVQUE-method (RAO, 1971; LAMOTTE, 1973). The variances of the estimated heritabilities were derived from the information matrix. Estimations from individual records and from average records (cage average) were compared in a small application on laying hen data. The analysed trait was single egg weight measured on hens housed in group cages. It could be shown: If cage variance is negligible, than for the estimation of the heritabilities full-sib data can be used successfully. The application of the modified animal model is suggested, because this model can take into account more complex relationships between the animals of one cage.

scholarly journals Estimation of variance components, genetic parameters and genetic trends for litter size of swines

2010 ◽  
Vol 39 (10) ◽  
pp. 2155-2159 ◽  
Author(s):  
Leandro Barbosa ◽  
Paulo Sávio Lopes ◽  
Adair José Regazzi ◽  
Robledo de Almeida Torres ◽  
Mário Luiz Santana Júnior ◽  
...  
Keyword(s):  
Litter Size ◽  
Variance Components ◽  
Genetic Parameters ◽  
Random Effect ◽  
Additive Model ◽  
Fixed Effect ◽  
Likelihood Method ◽  
Phenotypic Variance ◽  
Estimation Of Variance ◽  
Genetic Trends

Records of Large White breed animals were used to estimate variance components, genetic parameters and trends for the character total number of born piglets (TNBP) as measure of litter size. For obtaining variance components and genetic parameters, it was used the Restricted Maximum Likelihood Method using MTDFREML software. Two mixed models (additive and repeatability) were evaluated. The additive model contained fixed effect of the contemporary group and the following random effects: direct additive genetic and residual effect for the first parturition. Repeatability model had the same effects of the additive model plus parturition order fixed effect and non-correlated animal permanent environment random effect for the second, third and forth parturition. Direct additive heritability estimates for TNBP were 0.15 and 0.20 for the additive and repeatability models, respectively. The estimate of the ration among variance of the non-correlated effect of animal permanent environment effect and the phenotypic variance, expressed as total variance proportion (c2) was 0.09. The estimates of yearly genetic trends obtained in the additive and repeatability models have similar behaviors (0.02 piglets/sow/year).

scholarly journals Estimation of variance components of milk, fat, and protein yields of Tunisian Holstein dairy cattle using Bayesian and REML methods

2016 ◽  
Vol 59 (2) ◽  
pp. 243-248 ◽  
Author(s):  
Hafedh Ben Zaabza ◽  
Abderrahmen Ben Gara ◽  
Hedi Hammami ◽  
Mohamed Amine Ferchichi ◽  
Boulbaba Rekik
Keyword(s):  
Dairy Cattle ◽  
Bayesian Methods ◽  
Milk Fat ◽  
Variance Components ◽  
Genetic Parameters ◽  
Genetic Correlations ◽  
Bayesian Procedure ◽  
Milk Traits ◽  
Residual Variances ◽  
Estimation Of Variance

Abstract. A multi-trait repeatability animal model under restricted maximum likelihood (REML) and Bayesian methods was used to estimate genetic parameters of milk, fat, and protein yields in Tunisian Holstein cows. The estimates of heritability for milk, fat, and protein yields from the REML procedure were 0.21 ± 0.05, 0.159 ± 0.04, and 0.158 ± 0.04, respectively. The corresponding results from the Bayesian procedure were 0.273 ± 0.02, 0.198 ± 0.01, and 0.187 ± 0.01. Heritability estimates tended to be larger via the Bayesian than those obtained by the REML method. Genetic and permanent environmental variances estimated by REML were smaller than those obtained by the Bayesian analysis. Inversely, REML estimates of the residual variances were larger than Bayesian estimates. Genetic and permanent correlation estimates were on the other hand comparable by both REML and Bayesian methods with permanent environmental being larger than genetic correlations. Results from this study confirm previous reports on genetic parameters for milk traits in Tunisian Holsteins and suggest that a multi-trait approach can be an alternative for implementing a routine genetic evaluation of the Tunisian dairy cattle population.

scholarly journals Estimates of (co)variance components and genetic parameters for body weights and growth efficiency traits in the New Zealand white rabbit

2017 ◽  
Vol 25 (4) ◽  
pp. 329 ◽  
Author(s):  
M. Sakthivel ◽  
D. Balasubramanyam ◽  
P. Kumarasamy ◽  
H. Gopi ◽  
A. Raja ◽  
...  
Keyword(s):  
Body Weight ◽  
New Zealand ◽  
Variance Components ◽  
Environmental Effect ◽  
Genetic Parameters ◽  
Growth Traits ◽  
Genetic Effect ◽  
Growth Efficiency ◽  
Body Weights ◽  
Heritability Estimates

The genetic parameters of growth traits in the New Zealand White rabbits kept at Sheep Breeding and Research Station, Sandynallah, The Nilgiris, India were estimated by partitioning the variance and covariance components. The (co)variance components of body weights at weaning (W42), post-weaning (W70) and marketing (W135) age and growth efficiency traits viz., average daily gain (ADG), relative growth rate (RGR) and Kleiber ratio (KR) estimated on a daily basis at different age intervals (42 to 70 d; 70 to 135 d and 42 to 135 d) from weaning to marketing were estimated by restricted maximum likelihood, fitting 6 animal models with various combinations of direct and maternal effects. Data were collected over a period of 15 yr (1998 to 2012). A log-likelihood ratio test was used to select the most appropriate univariate model for each trait, which was subsequently used in bivariate analysis. Heritability estimates for W42, W70 and W135 were 0.42±0.07, 0.40±0.08 and 0.27±0.07, respectively. Heritability estimates of growth efficiency traits were moderate to high (0.18 to 0.42). Of the total phenotypic variation, maternal genetic effect contributed 14 to 32% for early body weight traits (W42 and W70) and ADG1. The contribution of maternal permanent environmental effect varied from 6 to 18% for W42 and for all the growth efficiency traits except for KR2. Maternal permanent environmental effect on most of the growth efficiency traits was a carryover effect of maternal care during weaning. Direct maternal genetic correlations, for the traits in which maternal genetic effect was significant, were moderate to high in magnitude and negative in direction. Maternal effect declined as the age of the animal increased. The estimates of total heritability and maternal across year repeatability for growth traits were moderate and an optimum rate of genetic progress seems possible in the herd by mass selection. The genetic and phenotypic correlations among body weights and between growth efficiency traits were also estimated. Moderate to high heritability and higher genetic correlation in body weight traits promise good scope for genetic improvement provided measures are taken to keep the inbreeding at the lowest level.

scholarly journals Hybrid of Restricted and Penalized Maximum Likelihood Method for Efficient Genome-Wide Association Study

Genes ◽  
2020 ◽  
Vol 11 (11) ◽  
pp. 1286
Author(s):  
Wenlong Ren ◽  
Zhikai Liang ◽  
Shu He ◽  
Jing Xiao
Keyword(s):  
Maximum Likelihood ◽  
Variance Components ◽  
Statistical Power ◽  
Mixed Model ◽  
Single Locus ◽  
Genome Wide Association ◽  
Likelihood Method ◽  
Penalized Maximum Likelihood ◽  
Genome Wide ◽  
Estimation Of Variance

In genome-wide association studies, linear mixed models (LMMs) have been widely used to explore the molecular mechanism of complex traits. However, typical association approaches suffer from several important drawbacks: estimation of variance components in LMMs with large scale individuals is computationally slow; single-locus model is unsatisfactory to handle complex confounding and causes loss of statistical power. To address these issues, we propose an efficient two-stage method based on hybrid of restricted and penalized maximum likelihood, named HRePML. Firstly, we performed restricted maximum likelihood (REML) on single-locus LMM to remove unrelated markers, where spectral decomposition on covariance matrix was used to fast estimate variance components. Secondly, we carried out penalized maximum likelihood (PML) on multi-locus LMM for markers with reasonably large effects. To validate the effectiveness of HRePML, we conducted a series of simulation studies and real data analyses. As a result, our method always had the highest average statistical power compared with multi-locus mixed-model (MLMM), fixed and random model circulating probability unification (FarmCPU), and genome-wide efficient mixed model association (GEMMA). More importantly, HRePML can provide higher accuracy estimation of marker effects. HRePML also identifies 41 previous reported genes associated with development traits in Arabidopsis, which is more than was detected by the other methods.

Genetic parameter estimates for early growth traits in Naeini goat

2012 ◽  
Vol 52 (11) ◽  
pp. 1046 ◽  
Author(s):  
Hasan Baneh ◽  
Mojtaba Najafi ◽  
Ghodrat Rahimi
Keyword(s):  
Environmental Effects ◽  
Variance Components ◽  
Genetic Parameters ◽  
Growth Traits ◽  
Genetic Parameter ◽  
Average Daily Gain ◽  
Parameter Estimates ◽  
Estimate Variance ◽  
Daily Gain ◽  
Birth Type

The present study was carried out to estimate variance components for growth traits in Naeini goats. Bodyweight records were collected for two flocks under supervision of the Agriculture Organisation of the Esfahan province between 2000 and 2007. Investigated traits were birthweight (BW; n = 2483), weaning weight (WW; n = 1211) and average daily gain from birth to weaning (ADG; n = 1211). Environmental effects were investigated using fixed-effect models, while (co)variance components and genetic parameters were estimated with single- and three-trait analyses using REML methods and WOMBAT software. Six different animal models were fitted to the traits, with the best model for each trait determined by log-likelihood ratio tests (LRT). All traits were significantly influenced by herd, birth year, sex of the kid, birth type and dam age (P < 0.01). On the basis of LRT, maternal permanent environmental effects (c2) were significant for WW and ADG, while BW was affected only by direct genetic effects. Direct heritability estimates for BW, WW and ADG were 0.25 ± 0.05, 0.07 ± 0.06 and 0.21 ± 0.11, respectively. The estimate of c2 was 0.16 ± 0.06 for both WW and ADG. Estimates of genetic correlation for BW–ADG, BW–WW and ADG–WW were 0.49, 0.61 and 0.94, respectively. The estimated phenotypic correlations were positive and were between 0.03 (BW–ADG) and 0.95 (ADG–WW). These results indicate that selection can be used to improve growth traits in this goat breed.

Selection for fertility in Australian Merino sheep

1963 ◽  
Vol 14 (4) ◽  
pp. 460 ◽  
Author(s):  
SSY Young ◽  
HN Turner ◽  
CHS Dolling
Keyword(s):  
Body Weight ◽  
Genetic Correlations ◽  
Fibre Diameter ◽  
Likelihood Method ◽  
Mass Selection ◽  
Genetic Progress ◽  
Subsequent Performance ◽  
Fertility Trait ◽  
Selection For ◽  
The Difference

Phenotypic and genetic parameters for fertility in sheep, in terms of number of lambs born and number weaned, have been estimated in a flock of medium Peppin Merinos. Repeatability of fertility traits over all ages is low, but there is an age effect, the record at 3 years of age having a higher value than those at 2 or 4 years. The regression of subsequent performance on a difference of 1 lamb at the initial lambing was higher for the difference between 1 and 2 lambs than between 0 and 1 lamb, which indicated that selection for twins is likely to raise fertility in the current flock more rapidly than selection against barrenness. The estimate of heritability for 2 years of age was negligible for each fertility trait, but the estimates for the 3-year-old record were higher, the value for lambs born being over 0.3. Mass selection for number of lambs born at 3 years of age would thus be expected to lead to appreciable genetic progress, while there would be at least some progress in number of lambs weaned. Phenotypic and genetic correlations were also estimated between fertility at different ages and 10 sheep and wool traits measured at 15–16 months of age. Phenotypically, fertility is positively correlated with body weight and negatively with skin wrinkle score. Genetically, it is suggested from the estimates that fertility is positively correlated with body weight and staple length and negatively correlated with fibre diameter, clean scoured yield, and wrinkle score. No phenotypic or genetic correlation was found between greasy or clean wool weight and either measure of fertility. The application of the findings to breeding for higher fertility is discussed. In an appendix, a maximum likelihood method of estimating heritability for all-or-none traits in half-sib data is presented.

scholarly journals EFFECT OF FIXED FACTORS AND ESTIMATION OF GENETIC PARAMETERS OF GROWTH TRAITS FOR MOUNTAIN KIDS

2019 ◽  
Vol 50 (6) ◽  
Author(s):  
Hermiz & Baper
Keyword(s):  
Variance Components ◽  
Fixed Effects ◽  
Genetic Parameters ◽  
Maximum Likelihood Method ◽  
Growth Traits ◽  
Genetic Correlations ◽  
Likelihood Method ◽  
Phenotypic Correlations ◽  
Body Weights ◽  
Genetic And Phenotypic Correlations

Body weights at birth (469), weaning (394) and at six month of age (358) for kids utilized in this study were raised at private project in Duhok governorate, Iraq during two kidding season (2016-2017) and (2017-2018). GLM within SAS programme was used to analyze the data which include the fixed effects (age of doe, year and season of kidding, sex of kid and type of birth, regression on doe weight at kidding, and the regression of later weights of kids on earlier weights) influencing the studied traits. Restricted Maximum Likelihood Method was used to estimate repeatability, heritability, genetic and phenotypic correlations after adjusting the records for fixed effects. Variance components of random effects were tested for positive definite. Overall mean of weights at birth (BWT), weaning (WWT) and 6 month of age (WT6M) were 2.92, 15.32 and 24.45 kg, respectively. Differences among groups of age of doe in all studied traits were not significant, while year of kidding and sex of kid affect all traits significantly (p<0.01). Season of kidding affect BWT and WWT significantly (P<0.01). Single born kids were heavier (P<0.01) than twins in BWT only. Regression of BWT on doe weight at kidding (0.033 kg/kg) was significant (P<0.01), while the regressions of WWT and WT6M were not significant. The regression coefficients of WWT on BWT (1.906 kg/kg) and of WT6M on WWT (0.835 kg/kg) were highly significant (P<0.01). Repeatability estimates for BWT, WWT and WT6M were 0.47, 0.45 and 0.35, respectively; on the same order the estimates of heritability were 0.41, 0.61 and 0.79. Genetic correlations between BWT with each of WWT (0.45) and WT6M (0.55), and between WWT and WT6M (0.68) were highly significant. All phenotypic correlations between each pair of body weights were higher than genetic correlations and ranged between 0.48 and 0.73.

scholarly journals Varianzkomponentenschätzung unter Berücksichtigung von Dominanz an simulierten Reinzuchtlinien

2004 ◽  
Vol 47 (4) ◽  
pp. 387-395
Author(s):  
M. Wensch-Dorendorf ◽  
N. Mielenz ◽  
E. Groeneveld ◽  
M. Kovac ◽  
L. Schüler
Keyword(s):  
Animal Model ◽  
Variance Components ◽  
Random Mating ◽  
Phenotypic Variance ◽  
Dominance Relationship ◽  
Gene Model ◽  
Dominance Model ◽  
Dominance Variance ◽  
Simulation Based ◽  
Estimation Of Variance

Abstract. Title of the paper: Estimation of variance components under dominance with simulated purebred lines A stochastic simulation based on a gene model was used to investigate the estimation of variance with dominance and additive animal models. For a heritability in broad sense of 0.5 three ratios of dominance variance (5, 10 and 25%) on the phenotypic variance were investigated under different degrees of dominance. No additionally biased estimations of the variance components as consequence of different dominance degrees were found. By using the dominance model for random mating as well as for selection the differences between true parameters and estimation values were small for all dominance degrees and ratios of dominance variance. Small, but significantly, differences can be explained by the change of the allele frequencies over the generations due to the influence of selection. By using the additive animal model, that ignores the dominance relationship, for high ratios of the dominance variance (25% or greater) important biased estimations of the variances were observed. For dominance ratios of 5% no significantly overestimation of the additive variances with the reduced model were found under selection and random mating.

scholarly journals Estimation of variance components for bodyweight of grasscutters using expectation maximization algorithm of restricted maximum likelihood

2020 ◽  
Vol 44 (5) ◽  
pp. 5-8
Author(s):  
I. Udeh
Keyword(s):  
Body Weight ◽  
Maximum Likelihood ◽  
Expectation Maximization ◽  
Variance Components ◽  
Genetic Variance ◽  
Phenotypic Variability ◽  
Additive Genetic Variance ◽  
Expectation Maximization Algorithm ◽  
Estimation Of Variance ◽  
Selection Of

The objective of this study was to estimate the variance components and heritability of bodyweight of grasscutters at 4, 6 and 8 months of age using EM algorithm of REML procedures. The data used for the study were obtained from the bodyweight records of 20 grasscutters from four families at 4, 6 and 8 months of age. The heritability of bodyweight of grasscutters at 4, 6 and 8 months of age were 0.14, 0.10 and 0.12 respectively. This implies that about 10 – 14 % of the phenotypic variability of body weight in this grasscutter population was accounted by additive genetic variance while environmental and gene combination variance made a larger contribution. The implication is that selection of grasscutters in this population should not be based on the information on the animals alone but also information fromits relatives.

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