Variance components due to direct and maternal effects and estimation of breeding values for 12-week weight of Welsh Mountain lambs

1999 ◽  
Vol 69 (2) ◽  
pp. 345-352 ◽  
Author(s):  
M. Saatci ◽  
I. Ap Dewi ◽  
Z. Ulutas
Keyword(s):  
Maternal Effects ◽  
Variance Components ◽  
Fixed Effects ◽  
Additive Genetic Variance ◽  
Selection Index ◽  
Phenotypic Variance ◽  
Common Environment ◽  
Breeding Values ◽  
Lamb Growth ◽  
Selection Of

AbstractThe purpose of this study was to examine the importance of the genetic and maternal environmental factors influencing the 12-week weight (12WW) of Welsh Mountain lambs and to estimate genetic parameters for this trait. Records of 8880 Welsh Mountain lambs born between 1979 and 1995 were analysed. The records were from the nucleus flock of the CAMDA cooperative breeding group. In this flock selection of replacements had been based on a multi-trait index incorporating lamb growth and maternal ability as important objectives and 12WW as one of the selection criteria. Twelve models were examined, all including direct additive genetic variance and various combinations of genetic and environmental maternal effects. The most appropriate model was chosen based on log-likelihood ratio tests. It included appropriate fixed effects, and direct additive, maternal additive, maternal permanent environment and maternal common environment (litter) random effects that defined proportionally 0⋅21 (h2), 0⋅09 (m2), 0⋅06 (pe2) and 0⋅18 (ce2) of the phenotypic variance. Ignoring the additive maternal effect resulted in inflated estimates of direct heritability and ignoring the environmental effects associated with dam inflated the direct and maternal heritabilities. There was no correlation (P < 0⋅05) between the additive direct and additive maternal effects. Additive direct and maternal breeding values increased by 0⋅12 (s.e. 0⋅006) kg/year and 0Ό3 (s.e. 0⋅003) kg/year respectively. The results demonstrate the effective incorporation of selection index methodology in the context of a hill sheep flock and also the importance of several categories of maternal effects.

scholarly journals A note on genetic parameters and accuracy of estimated breeding values in honey bees

2019 ◽  
Vol 51 (1) ◽  
Author(s):  
Evert W. Brascamp ◽  
Piter Bijma
Keyword(s):  
Honey Bees ◽  
Variance Components ◽  
Genetic Parameters ◽  
Additive Genetic Variance ◽  
Breeding Value ◽  
Phenotypic Variance ◽  
Breeding Values ◽  
Estimated Breeding Values ◽  
Additive Genetic Relationship ◽  
The Relationship

Abstract Background In honey bees, observations are usually made on colonies. The phenotype of a colony is affected by the average breeding value for the worker effect of the thousands of workers in the colony (the worker group) and by the breeding value for the queen effect of the queen of the colony. Because the worker group consists of multiple individuals, interpretation of the variance components and heritabilities of phenotypes observed on the colony and of the accuracy of selection is not straightforward. The additive genetic variance among worker groups depends on the additive genetic relationship between the drone-producing queens (DPQ) that produce the drones that mate with the queen. Results Here, we clarify how the relatedness between DPQ affects phenotypic variance, heritability and accuracy of the estimated breeding values of replacement queens. Second, we use simulation to investigate the effect of assumptions about the relatedness between DPQ in the base population on estimates of genetic parameters. Relatedness between DPQ in the base generation may differ considerably between populations because of their history. Conclusions Our results show that estimates of (co)variance components and derived genetic parameters were seriously biased (25% too high or too low) when assumptions on the relationship between DPQ in the statistical analysis did not agree with reality.

Estimates of Genetic Variation for Angus Gestation Length

2021 ◽  
Vol 99 (Supplement_2) ◽  
pp. 14-15
Author(s):  
Carson Gilleland ◽  
Kelli J Retallick ◽  
Daniel H Poole ◽  
Zack Peppmeier ◽  
Mark Knauer
Keyword(s):  
Variance Components ◽  
Fixed Effects ◽  
Additive Genetic Variance ◽  
High Capacity ◽  
Gestation Length ◽  
Phenotypic Variance ◽  
Contemporary Group ◽  
Heritability Estimates ◽  
One Year ◽  
Estimate Variance

Abstract The objective of this study was to estimate variance components for gestation length within the American Angus breed. Data (n = 148,649) from the American Angus Association, containing cattle born between 2000 to 2020, were used for the analysis. Based on a cow’s reproductive biology, gestation length records were determined acceptable if between 266 and 290 days (n = 114,857). Gestation length mean and standard deviation were 278.6 and 4.6 days, respectively. Average Information Restricted Maximum Likelihood (AIREML) was used to estimate variance components for the gestation length. A single trait animal model included random effects of direct and maternal additive genetic variance and fixed effects of dam age rounded to the nearest year, calf gender and contemporary group. Contemporary group was determined as herd, year of birth and season of birth combinations. Contemporary groups containing less than five animals were excluded from analysis. Phenotypic variance for gestation length was estimated at 18.9. Direct and maternal heritability estimates for gestation length were 0.59±0.01 and 0.10±0.01, respectively. Further analysis evaluated the fixed effects of year and dam age on gestation length. From 2000 to 2020, an increase in one year decreased (P &lt; 0.01) gestation length by 0.09 days. Gestation length differed (P &lt; 0.01) by age of dam. Gestation length LSMEANS for 2, 3, 4, 5, 6, 7 and 8 year old cows were 277.7, 278.6, 279.0, 279.2, 279.3, 279.5 and 279.6, respectively. Heritability estimates within Angus breed suggest gestation length has a high capacity for genetic change. Results suggest gestation length has decreased over the past two decades and is shorter in younger cows.

scholarly journals Genetic parameters estimates for gestation length in beef cattle

2005 ◽  
Vol 57 (6) ◽  
pp. 784-791 ◽  
Author(s):  
J.C.M.C. Rocha ◽  
H. Tonhati ◽  
M.M. Alencar ◽  
R.B. Lôbo
Keyword(s):  
Beef Cattle ◽  
Variance Components ◽  
Fixed Effects ◽  
Genetic Parameters ◽  
Genetic Effect ◽  
Heritability Estimate ◽  
Gestation Length ◽  
Phenotypic Variance ◽  
Fitting Model ◽  
Selection Of

Variance components were estimated for gestation length fitting the additive direct effect of calf, maternal genetic effect and sire effect as random effects. The statistical models also included the fixed effects of contemporary group, that included the date of breeding (AI), date of birth, and sex of calf, and the covariate age of dam at calving (linear and quadratic). Two different models were used, model 1 considering GL as a trait of the calf, and model 2 considering GL as a trait of the dam. The means of gestation length for the purebred animals were 294.55 days (males) and 293.34 days (females), while for the crossbred animals they were 292.49 days (males) and 292.55 days (females). Variance components for the purebred animals, fitting model 1, were 14.47, 72.78 and 57.31, for the additive genetic (sigma2a), total phenotypic (sigma2p) and residual (sigma2e) effects, respectively, with a heritability estimate of 0.21. For the crossbred animals, variance components for sigma2a, sigma2p, sigma2e were 90.40, 127.35 and 36.95, respectively, with a heritability of 0.71. Fitting model 2, the estimated variance components for the purebred animals were 12.78, 5.01, 74.84 and 57.05 for sigma2a , sire of calf (sigma ²asire), sigma2p, and sigma2e , respectively. The sire effect accounted for 0.07 (c²) of the phenotypic variance and the coefficient of repeatability was 0.17. For the crossbred animals, the variance components were 22.11 (sigma2a ), 22.97 (sigma ²asire ), 127.70 (sigma2p) and 82.61 (sigma2e), while c² was 0.18 and repeatability was 0.17. Therefore, regarding selection of beef cattle, it is suggested to use the heritability estimate obtained by model 1, where GL is considered as a trait of the calf.

scholarly journals Evaluación fenotípica y genética para características de crecimiento en la raza criolla colombiana Costeño con Cuernos

2007 ◽  
Vol 7 (2) ◽  
pp. 12 ◽  
Author(s):  
Rodrigo Alfredo Martínez ◽  
Juan Esteban Pérez ◽  
Teófilo Herazo
Keyword(s):  
Birth Weight ◽  
Variance Components ◽  
Fixed Effects ◽  
Genetic Parameters ◽  
Growth Traits ◽  
Phenotypic Correlation ◽  
Phenotypic Variance ◽  
Direct Effects ◽  
Weaning Weight ◽  
Number Of Births

<p>Se establecieron componentes de varianza, así como parámetros fenotípicos y genéticos, respecto de las variables ‘peso al nacimiento’, ‘peso al destete’ (ajustado a los 270 días) y ‘peso a los 480 días’ en un hato del ganado criollo colombiano Costeño con Cuernos. Se analizaron 2.281 registros de pesos al nacer, 1.722 de pesos al destete  y 1.086 de pesos ajustados a los 480 días utilizando la metodología de máxima verosimilitud restringida (DFREML). También se ajustó un modelo animal que incluyó efectos genéticos directos, maternos y de ambiente permanente, asumiendo como efectos fijos el año de nacimiento, el sexo del ternero y el número de partos de la madre; finalmente, se estimaron los parámetros genéticos ‘heredabilidad’, ‘repetibilildad’ y se establecieron correlaciones genéticas y fenotípicas. Se reportan bajas estimaciones de heredabilidad de los efectos directos, que varían entre 0,17 ± 0,001 y 0,21 ± 0,074 para los pesos al nacer y al destete, respectivamente; así mismo, fue baja la heredabilidad de los efectos genéticos maternos con relación al peso al nacimiento, aunque estos estimados aumentaron respecto de los pesos al nacer y al destete. Las correlaciones entre efectos directos y maternos fueron negativas, pero el mayor valor se encontró para el peso al nacimiento (-0,89). La contribución del ambiente permanente como proporción de la varianza fenotípica total fue baja y disminuyó a medida que aumentó la edad del animal.</p><p> </p><p><strong>Genetic and phenotypic evaluation to characterize growth traits of the native Colombian breed Costeño con Cuernos</strong></p><p>For a herd of native Colombian breed of cattle -Costeño con Cuernos (CCC)- estimates of variance components for phenotypic and genetic parameters were obtained for birth weight, weight at weaning (adjusted to 270 days) and weight at 480 days. Using the restricted maximum likelihood (REMI) methodology, 2281 birth weight records (PN), 1722 weaning weight records and 1086 weight records adjusted to 480 days were analyze by fitting a model which included direct and maternal genetics effects as well as permanent environmental effects, assuming that fixed effects were year of birth weight, calf gender and the mother number of births. The genetic parameters for heritability, repeatability, genetic and phenotypic correlation were estimated and genotypic and phenotypic correlation was established. Heritability estimates for direct effects are low and range from 0.17 ± 0.001 and 0.21 ± 0.074 for birth and weaning weight respectively; while estimates for maternal genetics effects were also low for PN, they were higher for weaning weight and weight at 480 days. There was a negative correlation between direct and maternal effects, and the higher value was for PN (-0.89). The contribution of the variable permanent environment measured as the contribution of the phenotypic variance was low and diminished as animal age increased.</p>

Genetic variation within and between subpopulations of the Australian Merino breed

2016 ◽  
Vol 56 (1) ◽  
pp. 87 ◽  
Author(s):  
Andrew A. Swan ◽  
Daniel J. Brown ◽  
Julius H. J. van der Werf
Keyword(s):  
Genetic Variation ◽  
Variance Components ◽  
Additive Genetic Variance ◽  
Genetic Correlations ◽  
Fibre Diameter ◽  
Genetic Group ◽  
Additive Variance ◽  
Breeding Values ◽  
Genetic Groups ◽  
Australian Merino

Genetic variation within and between Australian Merino subpopulations was estimated from a large breeding nucleus in which up to 8500 progeny from over 300 sires were recorded at eight sites across Australia. Subpopulations were defined as genetic groups using the Westell–Quaas model in which base animals with unknown pedigree were allocated to groups based on their flock of origin if there were sufficient ‘expressions’ for the flock, or to one of four broad sheep-type groups otherwise (Ultra/Superfine, Fine/Fine-medium, Medium/Strong, or unknown). Linear models including genetic groups and additive genetic breeding values as random effects were used to estimate variance components for 12 traits: yearling greasy and clean fleece weight (ygfw and ycfw), yearling mean and coefficient of variation of fibre diameter (yfd and ydcv), yearling staple length and staple strength (ysl and yss), yearling fibre curvature (ycuv), yearling body wrinkle (ybdwr), post-weaning weight (pwt), muscle (pemd) and fat depth (pfat), and post-weaning worm egg count (pwec). For the majority of traits, the genetic group variance ranged from approximately equal to two times larger than the additive genetic (within group) variance. The exceptions were pfat and ydcv where the genetic group to additive variance ratios were 0.58 and 0.22, respectively, and pwec and yss where there was no variation between genetic groups. Genetic group correlations between traits were generally the same sign as corresponding additive genetic correlations, but were stronger in magnitude (either more positive or more negative). These large differences between genetic groups have long been exploited by Merino ram breeders, to the extent that the animals in the present study represent a significantly admixed population of the founding groups. The relativities observed between genetic group and additive genetic variance components in this study can be used to refine the models used to estimate breeding values for the Australian Merino industry.

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.

Estimation of additive and dominance genetic variance components for female fertility traits in Iranian Holstein cows

2018 ◽  
Vol 156 (4) ◽  
pp. 565-569
Author(s):  
H. Ghiasi ◽  
R. Abdollahi-Arpanahi ◽  
M. Razmkabir ◽  
M. Khaldari ◽  
R. Taherkhani
Keyword(s):  
Dairy Cows ◽  
Variance Components ◽  
Genetic Variance ◽  
Additive Genetic Variance ◽  
Genetic Effects ◽  
Information Criteria ◽  
Phenotypic Variance ◽  
Dominance Variance ◽  
Dominance Genetic Variance ◽  
Estimated Heritability

AbstractThe aim of the current study was to estimate additive and dominance genetic variance components for days from calving to first service (DFS), a number of services to conception (NSC) and days open (DO). Data consisted of 25 518 fertility records from first parity dairy cows collected from 15 large Holstein herds of Iran. To estimate the variance components, two models, one including only additive genetic effects and another fitting both additive and dominance genetic effects together, were used. The additive and dominance relationship matrices were constructed using pedigree data. The estimated heritability for DFS, NSC and DO were 0.068, 0.035 and 0.067, respectively. The differences between estimated heritability using the additive genetic and additive-dominance genetic models were negligible regardless of the trait under study. The estimated dominance variance was larger than the estimated additive genetic variance. The ratio of dominance variance to phenotypic variance was 0.260, 0.231 and 0.196 for DFS, NSC and DO, respectively. Akaike's information criteria indicated that the model fitting both additive and dominance genetic effects is the best model for analysing DFS, NSC and DO. Spearman's rank correlations between the predicted breeding values (BV) from additive and additive-dominance models were high (0.99). Therefore, ranking of the animals based on predicted BVs was the same in both models. The results of the current study confirmed the importance of taking dominance variance into account in the genetic evaluation of dairy cows.

scholarly journals Estimation of Additive and Dominance Genetic Effects on Body Weight, Carcass and Ham Quality Traits in Heavy Pigs

Animals ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 481
Author(s):  
Valentina Bonfatti ◽  
Roberta Rostellato ◽  
Paolo Carnier
Keyword(s):  
Variance Components ◽  
Genetic Variance ◽  
Additive Genetic Variance ◽  
Model Fitting ◽  
Genetic Effects ◽  
Phenotypic Variance ◽  
Genetic Response ◽  
Dominance Variance ◽  
Dry Cured Ham ◽  
Genetic Evaluations

Neglecting dominance effects in genetic evaluations may overestimate the predicted genetic response achievable by a breeding program. Additive and dominance genetic effects were estimated by pedigree-based models for growth, carcass, fresh ham and dry-cured ham seasoning traits in 13,295 crossbred heavy pigs. Variance components estimated by models including litter effects, dominance effects, or both, were compared. Across traits, dominance variance contributed up to 26% of the phenotypic variance and was, on average, 22% of the additive genetic variance. The inclusion of litter, dominance, or both these effects in models reduced the estimated heritability by 9% on average. Confounding was observed among litter, additive genetic and dominance effects. Model fitting improved for models including either the litter or dominance effects, but it did not benefit from the inclusion of both. For 15 traits, model fitting slightly improved when dominance effects were included in place of litter effects, but no effects on animal ranking and accuracy of breeding values were detected. Accounting for litter effects in the models for genetic evaluations would be sufficient to prevent the overestimation of the genetic variance while ensuring computational efficiency.

scholarly journals Bedeutung der Varianzkomponentenschätzung für die Zucht von landwirtschaftlichen Nutztieren – eine Übersicht

2000 ◽  
Vol 43 (5) ◽  
pp. 523-534
Author(s):  
R. Röhel ◽  
J. Krieter ◽  
R. Preisinger
Keyword(s):  
Variance Components ◽  
Genetic Relationships ◽  
Additive Genetic Variance ◽  
Period Change ◽  
Farm Animals ◽  
Selection Strategy ◽  
Sampling Variance ◽  
Breeding Values ◽  
Variance Components Estimation ◽  
Estimation Of Variance

Abstract. Title of the paper: The importance of variance components estimation in breeding of farm animals – a review The present paper showed the importance of variance components estimation in animal breeding. Beside the use of variance components for estimation of breeding values, the components have a high importance on further breeding aspects, such as indication of selection limits, optimisation of test period, change of Performance during growth, and determination of the best selection traits. Maternal and non-additive genetic variance components can be estimated and their high influence on choice of the optimal selection strategy are explained. Standard errors of crossbreeding parameters are influenced by genetic relationships and are only unbiased when using all genetic variances and covariances among animals. Genotype-environmental-interaction and heterogeneous variances, which result in high reduction in selection response, can be obtained in a variance components estimation. The high value of Bayesian methods in order to describe the sampling variance of variance components and to account for the Standard error of estimation of variance components in the estimation of breeding values is explained.

scholarly journals Additive genetic variance and covariance in some reproduetive disorders in Hungarian Holstein Friesian using multi-trait animal model

2000 ◽  
Vol 43 (6) ◽  
pp. 573-582
Author(s):  
A. A. Amin ◽  
T. Gere ◽  
W. H. Kishk
Keyword(s):  
Fixed Effects ◽  
Additive Genetic Variance ◽  
Selection Index ◽  
Ovarian Cysts ◽  
Separate Analysis ◽  
Retained Placenta ◽  
Milk Fever ◽  
Holstein Friesian ◽  
Heritability Estimates ◽  
Calving Difficulty

Abstract. Relationships between some reproduetive disorders in the first 3 lactations of Holstein Friesian cows were investigated for 1886 lactation records. Multiple-trait maximum likelihood procedure which included sire cow within sire as random effect and herd, parity, month and year of calving as fixed effects was used to estimate heritabilities and repeatabilities for the studied traits. Abortion within 60 days, retained placenta, ovarian cysts calving difficulty, dystocia, mastitis, and calving type were coded as 0 and 1 for heritability and repeatability estimations. Pooled and separate analysis were applied on the first 3 lactations. Abortion within 60 days retained placenta, ovarian cysts, calving difficulty, dystocia, mastitis, abortion no. and calving type had moderate heritability estimates which ranged from 0.15 to 0.24. Low heritability estimates and a weak sire variance component were obtained for milk fever. The most frequent disorder traits were mastitis, milk fever abortion no calving type and calving difficulty (0.37 to 0.72). Up word trend of heritability estimates with advancing order of lactation was observed for mastitis, abortion within 60 days, and abortion no. while heritability estimates for calving type, calving difficulty and dystocia had a back word trend. These results help in determining the suitable age of selection. Additive genetic variances and covariances among the studied traits have indicated reducing incidence rates if selection index procedure used in this filed. Strong negative genetic correlation between milk fever and abortion no. (−0.429) while negative phenotypic correlations between all studied traits were not more than −0.120 which was estimated for calving difficulty and abortion no.

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