scholarly journals Variance components, heritability estimates, and breeding values for performance test traits in Old Kladruber horses

2016 ◽  
Vol 61 (08) ◽  
pp. 369-376 ◽  
Author(s):  
A. Novotná ◽  
A. Svitáková ◽  
J. Schmidová ◽  
J. Přibyl ◽  
H. Vostrá-Vydrová
2008 ◽  
Vol 53 (No. 7) ◽  
pp. 273-283 ◽  
Author(s):  
J. Přibyl ◽  
J. Přibylová ◽  
H. Krejčová ◽  
N. Mielenz

The live weights of 8 243 performance-tested bulls from 100 to 400 days of age were analysed using random regression (RR) and single-trait animal models. Evaluations were done for live weight at 400 days of age and gains from 100 to 400 days of age at various monthly intervals. Estimates of variance components differed depending on the trait definition and model of analysis. Systematic environmental effects explained a higher proportion of variability in the RR for gains than for other definitions of growth. The expected average reliability of estimated breeding values was similar for all methods from 0.42 to 46, but the rankings of animals differed. Determinations (<I>r</I><sup>2</sup>) of breeding values between methods ranged from 0.64 to 0.94. Correlations of the breeding values of progeny at performance-test stations with parents were highest for the evaluation of gains in consecutive intervals evaluated by RR. Correlations of the breeding values of sires from their growth at performance-test stations with the breeding values of groups of progeny at progeny-test stations were from 0.26 to 0.38. Correlations were the highest for RR evaluations of gain using consecutive short intervals. Evaluation of the growth of animals according to daily gains in short consecutive intervals was preferred because more animals and more observations per animal were included in the evaluations, and the growth curve was separated into genetic and non-genetic parts. Simple evaluation of growth according to the final weight or daily gain in a long interval is not entirely correct, since environmental compensatory growth can occur.


2020 ◽  
Vol 98 (8) ◽  
Author(s):  
Alberto Cesarani ◽  
Jorge Hidalgo ◽  
Andre Garcia ◽  
Lorenzo Degano ◽  
Daniele Vicario ◽  
...  

Abstract This study aimed to evaluate the changes in variance components over time to identify a subset of data from the Italian Simmental (IS) population that would yield the most appropriate estimates of genetic parameters and breeding values for beef traits to select young bulls. Data from bulls raised between 1986 and 2017 were used to estimate genetic parameters and breeding values for four beef traits (average daily gain [ADG], body size [BS], muscularity [MUS], and feet and legs [FL]). The phenotypic mean increased during the years of the study for ADG, but it decreased for BS, MUS, and FL. The complete dataset (ALL) was divided into four generational subsets (Gen1, Gen2, Gen3, and Gen4). Additionally, ALL was divided into two larger subsets: the first one (OLD) combined data from Gen1 and Gen2 to represent the starting population, and the second one (CUR) combined data from Gen3 and Gen4 to represent a subpopulation with stronger ties to the current population. Genetic parameters were estimated with a four-trait genomic animal model using a single-step genomic average information restricted maximum likelihood algorithm. Heritability estimates from ALL were 0.26 ± 0.03 for ADG, 0.33 ± 0.04 for BS, 0.55 ± 0.03 for MUS, and 0.23 ± 0.03 for FL. Higher heritability estimates were obtained with OLD and ALL than with CUR. Considerable changes in heritability existed between Gen1 and Gen4 due to fluctuations in both additive genetic and residual variances. Genetic correlations also changed over time, with some values moving from positive to negative or even to zero. Genetic correlations from OLD were stronger than those from CUR. Changes in genetic parameters over time indicated that they should be updated regularly to avoid biases in genomic estimated breeding values (GEBV) and low selection accuracies. GEBV estimated using CUR variance components were less biased and more consistent than those estimated with OLD and ALL variance components. Validation results indicated that data from recent generations produced genetic parameters that more appropriately represent the structure of the current population, yielding accurate GEBV to select young animals and increasing the likelihood of higher genetic gains.


Genetics ◽  
2021 ◽  
Vol 217 (2) ◽  
Author(s):  
L E Puhl ◽  
J Crossa ◽  
S Munilla ◽  
P Pérez-Rodríguez ◽  
R J C Cantet

Abstract Cultivated bread wheat (Triticum aestivum L.) is an allohexaploid species resulting from the natural hybridization and chromosome doubling of allotetraploid durum wheat (T. turgidum) and a diploid goatgrass Aegilops tauschii Coss (Ae. tauschii). Synthetic hexaploid wheat (SHW) was developed through the interspecific hybridization of Ae. tauschii and T. turgidum, and then crossed to T. aestivum to produce synthetic hexaploid wheat derivatives (SHWDs). Owing to this founding variability, one may infer that the genetic variances of native wild populations vs improved wheat may vary due to their differential origin and evolutionary history. In this study, we partitioned the additive variance of SHW and SHWD with respect to their breed origin by fitting a hierarchical Bayesian model with heterogeneous covariance structure for breeding values to estimate variance components for each breed category, and segregation variance. Two data sets were used to test the proposed hierarchical Bayesian model, one from a multi-year multi-location field trial of SHWD and the other comprising the two species of SHW. For the SHWD, the Bayesian estimates of additive variances of grain yield from each breed category were similar for T. turgidum and Ae. tauschii, but smaller for T. aestivum. Segregation variances between Ae. tauschii—T. aestivum and T. turgidum—T. aestivum populations explained a sizable proportion of the phenotypic variance. Bayesian additive variance components and the Best Linear Unbiased Predictors (BLUPs) estimated by two well-known software programs were similar for multi-breed origin and for the sum of the breeding values by origin for both data sets. Our results support the suitability of models with heterogeneous additive genetic variances to predict breeding values in wheat crosses with variable ploidy levels.


2019 ◽  
Vol 51 (1) ◽  
Author(s):  
Evert W. Brascamp ◽  
Piter Bijma

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.


2017 ◽  
Vol 25 (4) ◽  
pp. 329 ◽  
Author(s):  
M. Sakthivel ◽  
D. Balasubramanyam ◽  
P. Kumarasamy ◽  
H. Gopi ◽  
A. Raja ◽  
...  

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.


2018 ◽  
Vol 63 (No. 6) ◽  
pp. 212-221 ◽  
Author(s):  
B.B. Teixeira ◽  
R.R. Mota ◽  
R.B. Lôbo ◽  
L.P. Silva ◽  
A.P. Souza Carneiro ◽  
...  

We aimed to evaluate different orders of fixed and random effects in random regression models (RRM) based on Legendre orthogonal polynomials as well as to verify the feasibility of these models to describe growth curves in Nellore cattle. The proposed RRM were also compared to multi-trait models (MTM). Variance components and genetic parameters estimates were performed via REML for all models. Twelve RRM were compared through Akaike (AIC) and Bayesian (BIC) information criteria. The model of order three for the fixed curve and four for all random effects (direct genetic, maternal genetic, permanent environment, and maternal permanent environment) fits best. Estimates of direct genetic, maternal genetic, maternal permanent environment, permanent environment, phenotypic and residual variances were similar between MTM and RRM. Heritability estimates were higher via RRM. We presented perspectives for the use of RRM for genetic evaluation of growth traits in Brazilian Nellore cattle. In general, moderate heritability estimates were obtained for the majority of studied traits when using RRM. Additionally, the precision of these estimates was higher when using RRM instead of MTM. However, concerns about the variance components estimates in advanced ages via Legendre polynomial must be taken into account in future studies.


1998 ◽  
Vol 1998 ◽  
pp. 192-192 ◽  
Author(s):  
Z. Ulutas ◽  
I. Ap Dewi ◽  
M. Saatci

Few Welsh Black Cattle breeders record their animals as part of formal selection schemes. However there are sale and pedigree data available on Welsh Black Cattle as recorded by the breed society. The aim of the current project was to examine the use of market price as a basis for selection. This is justified on the basis that detailed production records are not available and that price could be considered as an indicator that summarises physical characteristics.


2006 ◽  
Vol 36 (11) ◽  
pp. 1613-1624 ◽  
Author(s):  
JONNA KUNTSI ◽  
HANNAH ROGERS ◽  
GREER SWINARD ◽  
NORBERT BÖRGER ◽  
JAAP van der MEERE ◽  
...  

Background. For candidate endophenotypes to be useful for psychiatric genetic research, they first of all need to show significant genetic influences. To address the relative lack of previous data, we set to investigate the extent of genetic and environmental influences on performance in a set of theoretically driven cognitive-experimental tasks in a large twin sample. We further aimed to illustrate how test–retest reliability of the measures affects the estimates.Method. Four-hundred 7- to 9-year-old twin pairs were assessed individually on tasks measuring reaction time, inhibition, working memory and ‘delay aversion’ performance. Test–retest reliability data on some of the key measures were available from a previous study.Results. Several key measures of reaction time, inhibition and working-memory performance indicated a moderate degree of genetic influence. Combining data across theoretically related tasks increased the heritability estimates, as illustrated by the heritability estimates of 60% for mean reaction time and 50% for reaction-time variability. Psychometric properties (reliability or ceiling effects) had a substantial influence on the estimates for some measures.Conclusions. The data support the usefulness of several of the variables for endophenotype studies that aim to link genes to cognitive and motivational processes. Importantly, the data also illustrate specific conditions under which the true extent of genetic influences may be underestimated and hence the usefulness for genetic mapping studies compromised, and suggest ways to address this.


2016 ◽  
Vol 56 (1) ◽  
pp. 87 ◽  
Author(s):  
Andrew A. Swan ◽  
Daniel J. Brown ◽  
Julius H. J. van der Werf

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.


1998 ◽  
Vol 49 (4) ◽  
pp. 607 ◽  
Author(s):  
S. J. Schoeman ◽  
G. G. Jordaan

Postweaning liveweight gain records of 1610 young bulls obtained both in feedlot and under pasture were used to estimate (co)variance components using a multivariate restricted maximum likelihood analysis. The pedigree file included 3477 animals. Heritability estimates for liveweights and gain in both environments correspond to most previously reported estimates. The genetic correlation of gain between the 2 environments was -0·12, suggesting a large genotype testing environment interaction and re-ranking of animal breeding values across environments. Results of this analysis suggest the need for environment-specific breeding values for postweaning gain.


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