Comparison of Breeding Values for Daily Gains of Bulls Estimated with Multi-Trait and Random Regression Models

Abstract. In this study, random regression models with Legendre polynomials of the 2nd, 3rd and 4th degree (RR2, RR3 and RR4) are compared with regard to the estimation of breeding values for the average daily gain of Czech Pied bulls (Simmental type). The data were prepared such that a multi-trait model (MTM) could be used as reference model. For each bull, 8 repeated records or fewer were available for the testing period from the 12th to the 420th day of life. For the modeling of the expected value structure, the fixed regression coefficients of the Legendre polynomials were subordinated hierarchically to the herd-year-season effects (HYS). For the comparison of the random regression models with the reference model, rank correlations between the estimated breeding values of various animal groups were calculated and a variety of top-lists were analyzed. In general, models RR3 and RR4 returned higher rank correlations with MTM in comparison to model RR2. Additionally, the number of common animals in the 1% and 10% top-lists showed that models RR3 and RR4 are to be preferred over RR2 when it comes to the estimation of breeding values.

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Reliability of breeding values between random regression and 305-day lactation models

Pesquisa Agropecuária Brasileira ◽

10.1590/s0100-204x2016001100007 ◽

2016 ◽

Vol 51 (11) ◽

pp. 1848-1856

Author(s):

Alessandro Haiduck Padilha ◽

◽

Jaime Araujo Cobuci ◽

Darlene dos Santos Daltro ◽

José Braccini Neto

Keyword(s):

Legendre Polynomials ◽

Regression Models ◽

Protein Yield ◽

Random Regression ◽

Holstein Cattle ◽

Average Increase ◽

Data Set ◽

Breeding Values ◽

Estimated Breeding Values ◽

Genetic Evaluations

Abstract The objective of this work was to verify the gain in reliability of estimated breeding values (EBVs), when random regression models are applied instead of conventional 305-day lactation models, using fat and protein yield records of Brazilian Holstein cattle for future genetic evaluations. Data set contained 262,426 test-day fat and protein yield records, and 30,228 fat and protein lactation records at 305 days from first lactation. Single trait random regression models using Legendre polynomials and single trait lactation models were applied. Heritability for 305-day yield from lactation models was 0.24 (fat) and 0.17 (protein), and from random regression models was 0.20 (fat) and 0.21 (protein). Spearman correlations of EBVs, between lactation models and random regression models, for 305-day yield, ranged from 0.86 to 0.97 and 0.86 to 0.98 (bulls), and from 0.80 to 0.89 and 0.81 to 0.86 (cows), for fat and protein, respectively. Average increase in reliability of EBVs for 305-day yield of bulls ranged from 2 to 16% (fat) and from 4 to 26% (protein), and average reliability of cows ranged from 24 to 38% (fat and protein), which is higher than in the lactation models. Random regression models using Legendre polynomials will improve genetic evaluations of Brazilian Holstein cattle due to the reliability increase of EBVs, in comparison with 305-day lactation models.

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Comparison of different traits to evaluate the growth of bulls

Czech Journal of Animal Science ◽

10.17221/357-cjas ◽

2008 ◽

Vol 53 (No. 7) ◽

pp. 273-283 ◽

Cited By ~ 5

Author(s):

J. Přibyl ◽

J. Přibylová ◽

H. Krejčová ◽

N. Mielenz

Keyword(s):

Variance Components ◽

Performance Test ◽

Live Weight ◽

Random Regression ◽

Breeding Values ◽

Final Weight ◽

Estimated Breeding Values ◽

Simple Evaluation ◽

Growth Of Animals ◽

Daily Gain

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.

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Stability of estimated breeding values for average daily gain in Pannon White rabbits

Czech Journal of Animal Science ◽

10.17221/2398-cjas ◽

2011 ◽

Vol 56 (No. 8) ◽

pp. 365-369 ◽

Cited By ~ 3

Author(s):

I. Nagy ◽

J. Farkas ◽

P. Gyovai ◽

I. Radnai ◽

Z. Szendrő

Keyword(s):

Average Daily Gain ◽

Rank Correlation ◽

Correlation Coefficients ◽

The Other ◽

Breeding Value ◽

Breeding Values ◽

Spearman’S Rank Correlation ◽

The Common ◽

Estimated Breeding Values ◽

Daily Gain

Stability of estimated breeding values for average daily gain (ADG) between 5 and 10 weeks of age was analysed for 47 242 Pannon White rabbits, reared in 7470 litters and born between 2000 and 2008. The dataset was divided into 5 successive 5-year periods: (1) 2000–2004, (2) 2001–2005, (3) 2002–2006, (4) 2003–2007, and (5) 2004–2008. Then, after selecting the appropriate part of the pedigree for these sub-datasets, genetic parameters and breeding values were estimated for ADG using REML and BLUP methods. In the applied models sex, year-month, animal and random litter effects were considered. Estimated heritabilities for all 5 periods from 1 to 5 were moderate and stable (0.28 ± 0.01, 0.28 ± 0.02, 0.29 ± 0.02, 0.27 ± 0.02, and 0.28 ± 0.02). Magnitudes of random litter effects were low and stable (0.14 ± 0.01, 0.15 ± 0.01, 0.15 ± 0.01, 0.16 ± 0.01, and 0.16 ± 0.01). After breeding value estimation the dataset of period 5 was merged pair-wise with the other periods 4, 3, 2 and 1 using an inner join. Thus only the common records of the datasets representing the periods 5-4, 5-3, 5-2, and 5-1 were included in the merged datasets. In these merged datasets each rabbit had two breeding values for ADG based on two different periods. Spearman's rank correlation coefficients were calculated between the breeding values based on the dataset of period 5 and the other periods. With the successive years the rank correlation coefficients decreased (0.989, 0.979, 0.965 and 0.924). The correlation coefficients between ranks remained moderately high, even when the proportion of the common rabbits in the merged datasets was low. However, a reasonable re-ranking occurred among the top animals. Rank correlations for the top 100 and 1000 animals varied from 0.41 to 0.55 and from 0.37 to 0.54, respectively, which could influence selection efficiency if the rolling base were used for genetic evaluation.

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Genetic evaluation of daily gains of dual-purpose bulls using a random regression model

Czech Journal of Animal Science ◽

10.17221/360-cjas ◽

2008 ◽

Vol 53 (No. 6) ◽

pp. 227-237 ◽

Cited By ~ 2

Author(s):

H. Krejčová ◽

J. Přibyl ◽

J. Přibylová ◽

M. Štípková ◽

N. Mielenz

Keyword(s):

Environmental Effects ◽

Legendre Polynomials ◽

Regression Models ◽

Compensatory Growth ◽

Genetic Correlations ◽

Random Regression ◽

Dual Purpose ◽

Random Regression Model ◽

Additive Genetic Effects ◽

Daily Gain

Daily gains of 8 243 dual-purpose bulls from 100 to 400 days of age during the years 1971 to 2007 were analyzed by random regression models. Orthogonal Legendre polynomials (LP) of degree 4 were applied to daily gains calculated at 30-day intervals over the test period. Fixed curves were estimated within the station-year-season of birth. The models also included a fixed station-year-season of weighing, animal additive genetic effects and animal permanent environmental effects. The peak daily gain was attained between 230 and 280 days of age, which corresponded to the period of the lowest variance in daily gains. Heritability estimates of daily gain were in the range of 0.014 to 0.043. The reliability of composite trait – cumulative gains over the entire period was 0.87. Genetic correlations between gains at different ages were high for adjacent ages and decreased with increasing difference in ages. Correlations of permanent environmental effects were high for adjacent ages, but became negative for ages that were far apart, indicating the possibility of compensatory growth. The phenotypic correlations were close to zero. The correlations for cumulative daily gains were higher than those for individual daily gains.

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Definition of subgroups for fixed regression in the test-day animal model for milk production ofHolsteincattle in theCzech Republic

Czech Journal of Animal Science ◽

10.17221/3976-cjas ◽

2011 ◽

Vol 50 (No. 1) ◽

pp. 7-13 ◽

Cited By ~ 3

Author(s):

L. Zavadilová ◽

E. Němcová ◽

J. Přibyl ◽

J. Wolf

Keyword(s):

Animal Model ◽

Milk Production ◽

Legendre Polynomials ◽

Environmental Effect ◽

Random Regression ◽

Breeding Values ◽

Regression Test ◽

Days Open ◽

Calving Season ◽

Definition Of

The investigation was based on roughly 3.9, 2.7 and 1.7 million test-day records from first, second and third lactation, respectively, sampled from 596 200 Czech Holstein cows between the years 1991 and 2002. Breeding values were estimated from multi-lactation random-regression test-day models which contained the fixed effect of herd-test day, fixed regression on days in milk and random regressions on the animal level and the permanent environmental effect. Third degree Legendre polynomials (with four coefficients) were used for both the fixed and random regressions. The models differed in fixed regression. In Analysis I, 96 subclasses were defined according to age at calving, season and year of calving within lactation. In Analysis II, days open were additionally included as a grouping factor resulting in 480 subclasses. Rank correlations over 0.98 between both analyses were observed for breeding values for sires. Grouping according to Analysis I was recommended.  

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Random regression models using different functions to estimate genetic parameters for milk production in Holstein Friesians

Ciência Rural ◽

10.1590/0103-8478cr20150473 ◽

2016 ◽

Vol 46 (9) ◽

pp. 1649-1655

Author(s):

Mariana de Almeida Dornelles ◽

Paulo Roberto Nogara Rorato ◽

Luis Telo Lavadinho da Gama ◽

Fernanda Cristina Breda ◽

Carlos Bondan ◽

...

Keyword(s):

Milk Production ◽

Legendre Polynomials ◽

Fixed Effects ◽

Regression Models ◽

Genetic Parameters ◽

Random Regression ◽

Residual Variance ◽

Lower Estimation ◽

The One ◽

Residual Variances

ABSTRACT: The objective of this study was to compare the functions of Wilmink and Ali and Schaeffer with Legendre polynomials in random regression models using heterogeneous residual variances for modeling genetic parameters during the first lactation in the Holstein Friesian breed. Five thousand eight hundred and eighty biweekly records of test-day milk production were used. The models included the fixed effects of group of contemporaries and cow age at calving as covariable. Statistical criteria indicated that the WF.33_HE2, LEG.33_HE2, and LEG.55_HE4 functions best described the changes in the variances that occur throughout lactation. Heritability estimates using WF.33_HE2 and LEG.33_HE2 models were similar, ranging from 0.31 to 0.50. The LEG.55_HE4 model diverged from these models, with higher estimates at the beginning of lactation and lower estimates after the 16th fortnight. The LEG55_HE4, among the three better models indicated by the index, is the one with highest number of parameters (14 vs 34) and resulted in lower estimation of residual variance at the beginning and at the end of lactation, but overestimated heritability in the first fortnight and presented a greater difficulty to model genetic and permanent environment correlations among controls. Random regression models that used the Wilmink and Legendre polynomials functions with two residual variance classes appropriately described the genetic variation during lactation of Holstein Friesians reared in Rio Grande do Sul.

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

Pesquisa Agropecuária Brasileira ◽

10.1590/s0100-204x2014000500007 ◽

2014 ◽

Vol 49 (5) ◽

pp. 372-383 ◽

Cited By ~ 4

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.

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