scholarly journals Influence of model selection and data structure on the estimation of genetic parameters in honeybee populations

2022 ◽  
Author(s):  
Manuel Du ◽  
Richard Bernstein ◽  
Andreas Hoppe ◽  
Kaspar Bienefeld
Keyword(s):  
Genetic Parameters ◽  
Genetic Parameter ◽  
Estimation Algorithm ◽  
Parameter Estimates ◽  
Simplified Models ◽  
Parameter Estimations ◽  
Estimate Variance ◽  
Almost All ◽  
Variance Estimates ◽  
Genetic Contributions

Abstract Estimating genetic parameters of quantitative traits is a prerequisite for animal breeding. In honeybees, the genetic variance separates into queen and worker effects. However, under data paucity, parameter estimations that account for this peculiarity often yield implausible results. Consequently, simplified models which attribute all genetic contributions to either the queen (queen model) or the workers (worker model) are often used to estimate variance components in honeybees. However, the causes for estimations with the complete model (colony model) to fail and the consequences of simplified models for variance estimates are little understood. We newly developed the necessary theory to compare parameter estimates that were achieved by the colony model with those of the queen and worker models. Furthermore, we performed computer simulations to quantify the influence of model choice, estimation algorithm, true genetic parameters, rates of controlled mating, apiary sizes, and phenotype data completeness on the success of genetic parameter estimations. We found that successful estimations with the colony model were only possible if at least some of the queens mated controlledly on mating stations. In that case, estimates were largely unbiased if more than 20% of the colonies had phenotype records. The simplified queen and worker models proved more stable and yielded plausible parameter estimates for almost all settings. Results obtained from these models were unbiased when mating was uncontrolled, but with controlled mating, the simplified models consistently overestimated heritabilities. This work elucidates the requirements for variance component estimation in honeybees and provides the theoretical groundwork for simplified honeybee models.

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.

scholarly journals Genetic parameter estimates for birth and weaning weights in Raeini goats

2010 ◽  
Vol 55 (No. 1) ◽  
pp. 30-36 ◽  
Author(s):  
M. Gholizadeh ◽  
G. Rahimi Mianji ◽  
M. Hashemi ◽  
H. Hafezian
Keyword(s):  
Birth Weight ◽  
Genetic Parameters ◽  
Genetic Parameter ◽  
Residual Effects ◽  
Parameter Estimates ◽  
Genetic Covariance ◽  
Weaning Weight ◽  
Variance And Covariance Components ◽  
Estimate Variance ◽  
Additive Genetic Effects

The aim of the present study was to estimate variance components and genetic parameters for birth and weaning weights in Raeini goats. The data were collected from the Breeding Centre of Raeini (BCR) cashmere goats in Kerman province of Iran from 1986 to 2008. Random effects included direct and maternal additive genetic effects, maternal permanent environmental effects with direct-maternal genetic covariance and random residual effects. Variance and covariance components and genetic parameters were estimated using the DFREML program by fitting six single-trait animal models. Depending on the model, h<sub>d</sub><sup>2</sup> varied from 0.057 to 0.323 for birth weight and from 0.043 to 0.229 for weaning weight. Estimates of <I>m</I><sup>2</sup> ranged from 0.016 to 0.289 for birth weight and from 0.01 to 0.184 for weaning weight. The maternal permanent environmental effect was significant for both traits and ignoring maternal effects in the model caused the overestimation of direct heritability.

scholarly journals Realized Sampling Variances of Estimates of Genetic Parameters and the Difference Between Genetic and Phenotypic Correlations

Genetics ◽  
1996 ◽  
Vol 143 (3) ◽  
pp. 1409-1416 ◽  
Author(s):  
Kenneth R Koots ◽  
John P Gibson
Keyword(s):  
Genetic Correlation ◽  
Genetic Parameters ◽  
Genetic Parameter ◽  
Genetic Correlations ◽  
Phenotypic Correlation ◽  
Parameter Estimates ◽  
Sampling Variance ◽  
Phenotypic Correlations ◽  
Genetic And Phenotypic Correlations ◽  
Heritability Estimates

Abstract A data set of 1572 heritability estimates and 1015 pairs of genetic and phenotypic correlation estimates, constructed from a survey of published beef cattle genetic parameter estimates, provided a rare opportunity to study realized sampling variances of genetic parameter estimates. The distribution of both heritability estimates and genetic correlation estimates, when plotted against estimated accuracy, was consistent with random error variance being some three times the sampling variance predicted from standard formulae. This result was consistent with the observation that the variance of estimates of heritabilities and genetic correlations between populations were about four times the predicted sampling variance, suggesting few real differences in genetic parameters between populations. Except where there was a strong biological or statistical expectation of a difference, there was little evidence for differences between genetic and phenotypic correlations for most trait combinations or for differences in genetic correlations between populations. These results suggest that, even for controlled populations, estimating genetic parameters specific to a given population is less useful than commonly believed. A serendipitous discovery was that, in the standard formula for theoretical standard error of a genetic correlation estimate, the heritabilities refer to the estimated values and not, as seems generally assumed, the true population values.

Genetic parameter estimates for feeding pattern and production traits in pigs

1997 ◽  
Vol 1997 ◽  
pp. 31-31
Author(s):  
A.D. Hall ◽  
W.G. Hill ◽  
P.R. Bampton ◽  
A.J. Webb
Keyword(s):  
Feed Intake ◽  
Genetic Parameters ◽  
Genetic Parameter ◽  
Feeding Pattern ◽  
Parameter Estimates ◽  
Group Housing ◽  
Production Traits ◽  
Production Environment ◽  
Feeding Patterns ◽  
Potential Benefits

Until recently, to enable accurate recording of feed intake, pigs were kept in individual pens. The advent of electronic feeders has allowed accurate records of feed intake and feeding patterns in group housing which is more similar to that found in the production environment. The objectives of this study were to estimate genetic parameters for these feeding pattern traits and their correlations with production traits to show potential benefits in selection.

Genetic parameter estimations and genomic insights for teat and udder structure in young and mature Canadian Angus cows

2021 ◽  
Author(s):  
K Devani ◽  
J J Crowley ◽  
G Plastow ◽  
K Orsel ◽  
T S Valente
Keyword(s):  
Animal Model ◽  
Genetic Correlation ◽  
Genetic Parameters ◽  
Genetic Parameter ◽  
Genetic Correlations ◽  
Age Groups ◽  
Morbidity And Mortality ◽  
Parameter Estimations ◽  
Angus Cattle ◽  
Genetic Evaluations

Abstract Poor teat and udder structure, frequently associated with older cows, impact cow production and health, as well as calf morbidity and mortality. However, producer culling, for reasons including age, production, feed availability, and beef markets, creates a bias in teat and udder scores assessed and submitted to the Canadian Angus Association for genetic evaluations towards improved mammary structure. In addition, due to the infancy of the reporting program, repeated scores are rare. Prior to adoption of genetic evaluations for teat and udder scores in Canadian Angus cattle, it is imperative to verify that teat and udder scores from young cows are the same trait as teat and udder scores estimated on mature cows. Genetic parameters for teat and udder scores from all cows (n=4,192), and then from young cows (parity 1 and 2) and from mature cows (parity ≥ 4) were estimated using a single trait animal model. Genetic correlations for the traits between the two cow age groups were estimated using a two-trait animal model. Estimates of heritability (PSD) were 0.32 (0.07) and 0.45 (0.07) for young teat and udder score, and 0.27 (0.07) and 0.31 (0.07) for mature teat and udder score, respectively. Genetic correlation (PSD) between the young and mature traits was 0.87 (0.13) for teat score and 0.40 (0.17) for udder score. GWAS were used to further explore the genetic and biological commonalities and differences between the two groups. Although there were no genes in common for the two udder scores, 12 genes overlapped for teat score in the two cow age groups. Interestingly, there were also 23 genes in common between teat and udder scores in mature cows. Based on these findings, it is recommended that producers collect teat and udder score on their cow herd annually.

scholarly journals Effects of Breeder Age on Genetic Parameter Estimates of Slaughter and Carcass Traits in Japanese Quail

2018 ◽  
Vol 6 (02) ◽  
Author(s):  
Eser Kemal Gurcan ◽  
Dogan Narinc ◽  
Selcuk Kaplan
Keyword(s):  
Genetic Parameter ◽  
Carcass Traits ◽  
Genetic Correlations ◽  
Abdominal Fat ◽  
Carcass Weight ◽  
Parameter Estimates ◽  
Slaughter Weight ◽  
Parameter Estimations ◽  
Breast Weight ◽  
Positive Results

This study aimed to determine the phenotypic values of the slaughter and carcass traits in the flocks of quails obtained when a flock of parent quails were at 12, 16, and 20 weeks of age and to estimate the heritabilities and the genetic correlations for these traits. For this purpose, a total of 1,346 Japanese quails were slaughtered at 8 weeks of age, and their slaughter weights as well as carcass, breast, leg, and abdominal fat weights and ratios were determined. Differences in all traits were detected between female and male quails (P<0.05). The averages of many important traits, primarily slaughter weight, carcass weight, and breast weight, increased with the increase in the breeder age. On the contrary, the carcass yield decreased (P<0.05). There were no significant variations in the phenotypic and genetic variances for the slaughter and carcass traits in the flocks obtained when the breeder flock was at different ages. The heritabilities for slaughter weight, carcass weight, and abdominal fat weight were estimated to be moderate, and the genetic correlations among them were estimated to be positive and high. In conclusion, it is possible to state that positive results might be obtained by using the carcass ratio as the criterion for selection in quails. Besides, the breeder age was discovered to have had no significant effect on the genetic parameter estimations.

scholarly journals Genetic parameter estimates for important traits on the fifth generation in red tilapia in Vietnam

2021 ◽  
Vol 20 (1) ◽  
pp. 49-57
Author(s):  
Sang V. Nguyen
Keyword(s):  
Body Weight ◽  
Survival Rate ◽  
Genetic Parameters ◽  
Genetic Parameter ◽  
Genetic Correlations ◽  
Parameter Estimates ◽  
Environment Interaction ◽  
Body Colour ◽  
Red Tilapia ◽  
Gxe Interaction

Genetic parameters comprising heritability, genetic correlation and genotype by environment interaction (GxE) for growth survival rate and body colour at harvest were estimated on the 5th selective generation of red tilapia grown in two environments, freshwater and brackishwater ponds. A total of 116 full-half-sib families was produced as well as 4,432 and 3,811 tagged individuals were tested in freshwater and brackishwater ponds, respectively. Genetic parameters were estimated by ASReml 4.1 software. The heritability for body weight and survival rate was high while medium heritability for body colour in freshwater was observed. The heritability for those traits of red tilapia in brackishwater. Together with the figures in earlier publication on previous generations (G1 to G4) in the same selective population, the expected medium to high response acquires if selection is done for each trait. Genetic correlations among harvest body weight, survival rate and body colour are insignificantly different and ranging from -0.25 to 0.37 (P > 0.05). These results implied that selection on one trait do not influence on responses of the other traits. GxE interaction for body weight and body colour between two tested environments is mostly negligible with genetic correlations ranging from 0.63 - 0.80 while it is important for survival trait (rg = -0.17 ± 0.40).

Genetic parameters for clinical mastitis in Holstein-Friesians in the United Kingdom: a Bayesian analysis

2001 ◽  
Vol 73 (2) ◽  
pp. 229-240 ◽  
Author(s):  
H. N. Kadarmideen ◽  
R. Rekaya ◽  
D. Gianola
Keyword(s):  
Genetic Parameters ◽  
Genetic Parameter ◽  
Mixed Linear Model ◽  
Clinical Mastitis ◽  
Parameter Estimates ◽  
Data Sets ◽  
Data Sampling ◽  
Environmental Variance ◽  
Data Set ◽  
Monte Carlo Techniques

AbstractA Bayesian threshold-liability model with Markov chain Monte Carlo techniques was used to infer genetic parameters for clinical mastitis records collected on Holstein-Friesian cows by one of the United Kingdom’s national recording schemes. Four data sets were created to investigate the effect of data sampling methods on genetic parameter estimates for first and multi-lactation cows, separately. The data sets were: (1) cows with complete first lactations only (8671 cows); (2) all cows, with first lactations whether complete or incomplete (10 967 cows); (3) cows with complete multi-lactations (32 948 records); and (4) all cows with multiple lactations whether complete or incomplete (44 268 records). A Gaussian mixed linear model with sire effects was adopted for liability. Explanatory variables included in the model varied for each data set. Analyses were conducted using Gibbs sampling and estimates were on the liability scale. Posterior means of heritability for clinical mastitis were higher for first lactations (0·11 and 0·10 for data sets 1 and 2, respectively) than for multiple lactations (0·09 and 0·07, for data sets 3 and 4, respectively). For multiple lactations, estimates of permanent environmental variance were higher for complete than incomplete lactations. Repeatability was 0·21 and 0·17 for data sets 3 and 4, respectively. This suggests the existence of effects, other than additive genetic effects, on susceptibility to mastitis that are common to all lactations. In first or multi-lactation data sets, heritability was proportionately 0·10 to 0·19 lower for data sets with all records (in which case the models had days in milk as a covariate) than for data with only complete lactation records (models without days in milk as a covariate). This suggests an effect of data sampling on genetic parameter estimates. The regression of liability on days in milk differed from zero, indicating that the probability of mastitis is higher for longer lactations, as expected. Results also indicated that a regression on days in milk should be included in a model for genetic evaluation of sires for mastitis resistance based on records in progress.

Designing complex research projects to estimate genetic parameters plus treatment and other effects - optimising the experimental design

2008 ◽  
Vol 48 (8) ◽  
pp. 1110 ◽  
Author(s):  
D. L. Robinson
Keyword(s):  
Experimental Design ◽  
Genetic Parameters ◽  
Genetic Parameter ◽  
Genetic Correlations ◽  
Research Centre ◽  
Parameter Estimates ◽  
Cooperative Research ◽  
Number Of Factors ◽  
Integrated Research ◽  
One Year

There is an increasing trend towards integrated research, in which several individuals or institutions pool their expertise and make use of common resources, collaborating towards a common set of scientific goals. Integrated research enables a larger number of factors to be investigated, and the most influential or important ones identified, providing information on how the different factors interact or fit together. Good experimental design is, however, required to ensure the aims can be achieved and resources spent wisely. Issues involved in the experimental design of the Australian Beef Cattle Cooperative Research Centre for Meat Quality are discussed. Theoretical results and simulation studies were used to determine optimal numbers of progeny per sire for estimating genetic parameters. For heritabilities of 0.2 and 0.5, the optima are respectively 21 and 9 progeny with recorded measurements. The curves surrounding the optima are quite flat, so aiming for 10–15 progeny with measurements per trait should provide reasonable accuracy in many situations. Estimates of heritabilities, genetic correlations and phenotypic variances have lower sampling correlations than genetic variances and covariances, suggesting that when results are pooled over different breeds or trials, it is better to pool estimates of heritabilities and genetic correlations than (co)variances. Using sires in more than one year increases the robustness of estimated sire effects and increases the accuracy of genetic parameter estimates for hard-to-measure traits (e.g. feed efficiency) that are not recorded on all animals. Unless sires can be chosen as a true random sample of the population, arrangements of link sires (and other effects such as treatments) should be chosen to provide accurate estimates when all terms in the model are fitted as fixed.

Genetic parameter estimates for juvenile body weight in indigenous Uttara chickens

2018 ◽  
Author(s):  
M. K. Singh ◽  
S. Kumar ◽  
R. K. Sharma ◽  
S. K. Singh ◽  
D. V. Singh
Keyword(s):  
Genetic Parameters ◽  
Genetic Parameter ◽  
Parameter Estimates ◽  
Mass Selection ◽  
Body Measurements ◽  
Body Measurement ◽  
Sex Dimorphism ◽  
Breeder Hens ◽  
Body Weights ◽  
The Individual

The aim of the present study was to estimate genetic parameters of juvenile body measurements in indigenous Uttara chickens. Body measurement records at birth of 1907 chicks sired by 25 breeder cocks and 200 breeder hens were used in heritability calculation. Genetic parameters were estimated for Uttara chicken juvenile body weights at hatching, and at 4 weeks, 8 weeks, 12 weeks, 16 weeks and 20 weeks of age. Heritability of all body measurements was estimated by paternal half-sib method. Heritability estimates can be used to improve body measurements of indigenous Uttara hens. The sex dimorphism effects were estimated at 2 weeks of age and were present at later ages. These results indicate that mass selection method based on the individual phenotype of the chickens at different ages can provide genetic improvement in the flock. Thus, early body measurements of the Uttara chickens could be used for prediction of the size of the adult Uttara.

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