Genetic evaluation of growth traits in Nellore cattle through multi-trait and random regression models

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.

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Genetic evaluation of growth traits in beef cattle using random regression models

South African Journal of Animal Science ◽

10.4314/sajas.v42i5.6 ◽

2012 ◽

Vol 42 (5) ◽

Author(s):

FWC Neser ◽

JB Van Wyk ◽

MD Fair ◽

P Lubout

Keyword(s):

Beef Cattle ◽

Regression Models ◽

Growth Traits ◽

Genetic Evaluation ◽

Random Regression

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Genetic evaluation and genetic trend of growth traits of Zandi sheep in semi-arid Iran using random regression models

Small Ruminant Research ◽

10.1016/j.smallrumres.2013.07.005 ◽

2013 ◽

Vol 114 (2-3) ◽

pp. 195-201 ◽

Cited By ~ 3

Author(s):

M. Bohlouli ◽

H. Mohammadi ◽

S. Alijani

Keyword(s):

Regression Models ◽

Growth Traits ◽

Genetic Evaluation ◽

Random Regression ◽

Genetic Trend ◽

Semi Arid ◽

Zandi Sheep

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Genetic evaluation of growth in Nellore cattle by multiple-trait and random regression models

Journal of Animal Science ◽

10.2527/2003.814927x ◽

2003 ◽

Vol 81 (4) ◽

pp. 927-932 ◽

Cited By ~ 16

Author(s):

P. R. C. Nobre ◽

I. Misztal ◽

S. Tsuruta ◽

J. K. Bertrand ◽

L. O. C. Silva ◽

...

Keyword(s):

Regression Models ◽

Genetic Evaluation ◽

Random Regression ◽

Multiple Trait ◽

Nellore Cattle

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APPLICATION OF RANDOM REGRESSION MODELS FOR GROWTH TRAITS OF NELLORE CATTLE IN BRAZIL

Nucleus Animalium ◽

10.3738/1982.2278.1657 ◽

2016 ◽

Vol 8 (2) ◽

pp. 45-54

Author(s):

Wéverton José Lima Fonseca ◽

Amauri Felipe Evangelista ◽

Laylson Da Silva Borges ◽

Gleissa Mayone Silva Vogado ◽

Carlos Syllas Monteiro Luz ◽

...

Keyword(s):

Longitudinal Data ◽

Beef Cattle ◽

Regression Models ◽

Growth Traits ◽

Standard Procedure ◽

Random Regression ◽

Nellore Cattle ◽

Cattle Breeders ◽

Estimate Variance ◽

Genetic Evaluations

The purpose of this review is to show the increase in number of researches on covariance components and genetic evaluation using random regression models (RRM) for growth traits of Nellore cattle. Random regression models, also known as infinite-dimension models have been used to estimate variance components and genetic parameters for weight of beef cattle. In addition, those models are a standard alternative for genetic analyses of longitudinal data, however, the availibility of computational resources for performing genetic evaluations widely is an obstacle. Traits related to animal growth are adopted as selection criteria in beef cattle breeding programs, because the remuneration of cattle breeders is made based on the weight of carcasses. In recent years, RRM have been adopted as standard procedure in relation to the analysis of longitudinal data in animal breeding.

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APPLICATION OF RANDOM REGRESSION MODELS FOR GROWTH TRAITS OF NELLORE CATTLE IN BRAZIL

Nucleus Animalium ◽

10.3738/21751463.1657 ◽

2016 ◽

Vol 8 (2) ◽

pp. 45-54

Author(s):

Wéverton José Lima Fonseca ◽

Amauri Felipe Evangelista ◽

Laylson da Silva Borges ◽

Gleissa Mayone Silva Vogado ◽

Diego Helcias Cavalcante ◽

...

Keyword(s):

Regression Models ◽

Growth Traits ◽

Random Regression ◽

Nellore Cattle

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Analyses of growth curves of Nellore cattle by multiple-trait and random regression models

Journal of Animal Science ◽

10.2527/2003.814918x ◽

2003 ◽

Vol 81 (4) ◽

pp. 918-926 ◽

Cited By ~ 68

Author(s):

P. R. C. Nobre ◽

I. Misztal ◽

S. Tsuruta ◽

J. K. Bertrand ◽

L. O. C. Silva ◽

...

Keyword(s):

Regression Models ◽

Growth Curves ◽

Random Regression ◽

Multiple Trait ◽

Nellore Cattle

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Genetic parameters for post weaning growth of Nellore cattle using polinomyals and trigonometric functions in random regression models

Scientia Agricola ◽

10.1590/s0103-90162009000400014 ◽

2009 ◽

Vol 66 (4) ◽

pp. 522-528 ◽

Cited By ~ 2

Author(s):

Osmar Jesus Macedo ◽

Décio Barbin ◽

Gerson Barreto Mourão

Keyword(s):

Regression Models ◽

Growth Curves ◽

Information Criterion ◽

The Other ◽

Random Regression ◽

Trigonometric Functions ◽

Coefficient Estimates ◽

Covariance Functions ◽

Nellore Cattle ◽

Selection Of

Covariance functions and random regression models have been considered as an alternative for data adjustment, in sequence, stemming from the same animal along time and which presents a structured pattern of covariance. Aiming to evaluate the performance of random regression models based on the Legendre, modified Jacobi and trigonometric functions, data concerning the weights of Nellore breed animals were used from birth to the 800th day of life, in models that assumed direct additive and animal permanent environmental effects coefficients. The Schwarz Bayesian information criterion (BIC) led to the selection of the models Legendre of order six (ML6), Jacobi of order five (MJ5) and trigonometric of order six (MT6), the ML6 model presenting the lowest BIC. At the extremity of the interval, the MJ5 model presented lower variance of component estimates than those obtained through the ML6 model, however the estimates were in accordance to the medium part of the interval; while the estimates from the MT6 model were oscillating and different from those obtained through the other models. At the extremity of the interval, the heritability coefficient estimates (<img src="/img/revistas/sa/v66n4/h4_circ.gif" align="absmiddle">2) obtained through the MJ5 model were lower than those obtained through the ML6 model, however, in the medium part of the interval, they were in accordance, remaining between 0.2 and 0.3. The values obtained through the MT6 model were different from those obtained through the other models, remaining between 0.35 and 0.40 on the first 285th days and then dropping to 0.01 on the 800th days of life. The means of the estimated growth curves started to distance from the data mean tendency from the 470th days on, and in this interval, the MT6 model was the most suitable.

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

World Rabbit Science ◽

10.4995/wrs.2017.7057 ◽

2017 ◽

Vol 25 (4) ◽

pp. 329 ◽

Cited By ~ 1

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.

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