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Impact of Maternal Components on Ranking of Animal Models in Genetic Parameter Estimation for Daily Gain Traits in Egyptian Rahmani Lambs



Hend A. Radwan and Nazem A. Shalaby
 
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ABSTRACT

Background and Objective: Average daily gain trait of lambs at different ages has a very important effect on the profitability of sheep production systems. Developments of effective selecting and breeding programs for genetic optimization the growth rate of the lambs require accurate covariance components and genetic parameters estimates. The aim of this study was to estimate variance, covariance components and genetic parameters for average daily gain traits from birth to weaning (ADG0,3), from weaning to 6 months (ADG3,6) and from birth to 6 months age (ADG0,6) in Rahmani sheep flock maintained at El-Serw Experimental Station, over a period of 10 years (1991-2001), show the effect of the including or excluding maternal components during the genetic evaluation of the traits under study, clarify the most appropriate animal model and rank them according to Akaike Information Criterion (AIC). Materials and Methods: Records of growth traits of 5879 lambs, offspring of 1766 ewes and 299 rams were used in the study. Analysis were carried out by 6 single and multi-trait animal models based on including or excluding to maternal components and locating the most appropriate model for the analysis average pre and post-weaning weight gain traits by determining the akiake information criterion and testing the log likelihood values. Results: Since, the log likelihood of the first and second models were non-significant, which indicates the amount of maternal permanent environmental effect was negligible. Conclusion: It could be concluded that the simple model is the best model in designing of breeding programs for average daily gain traits in Rahmani lambs. A modest rate of genetic improvement could be achieved in the flock through selection. Maternal permanent environmental effects contributed 7 and 29% of the total phenotypic variation in ADG0,3 in single and multi-trait analysis, respectively.

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  How to cite this article:

Hend A. Radwan and Nazem A. Shalaby, 2017. Impact of Maternal Components on Ranking of Animal Models in Genetic Parameter Estimation for Daily Gain Traits in Egyptian Rahmani Lambs. Asian Journal of Animal Sciences, 11: 23-31.

DOI: 10.3923/ajas.2017.23.31

URL: https://scialert.net/abstract/?doi=ajas.2017.23.31
 
Received: August 03, 2016; Accepted: November 24, 2016; Published: April 27, 2019


Copyright: © 2017. This is an open access article distributed under the terms of the creative commons attribution License, which permits unrestricted use, distribution and reproduction in any medium, provided the original author and source are credited.

INTRODUCTION

Egyptian sheep breeds are characterized by high fertility rate, extended breeding season and low prolificacy1. Egyptian sheep population comprises of about 4,200,000 heads which approximately 6% of total red meat produced in Egypt, Rahmani breed numbering 990,000 is one of the most important mutton breed among Egyptian breeds, Rahmani sheep well known by their resistance to subtropical changes, large bodies, fatty tail, satisfactory fertility and their ability to breed allover the year2. Rahmani breed is believed to have some resistance to internal parasites. The twinning rate is relatively high. They are the largest of the Egyptian sheep breeds. They produce coarse/carpet wool and have a fat-tail. Their color is brown, which fades with age.

Average daily weight gain of lambs at different ages has effect on the profitability of sheep production systems3. Development of effective programs for genetic improvement the growth rate of the lambs need accurate covariance components and genetic parameters estimates as mentioned by Kushwaha et al.4.

Several studies had attributed most of differences in lamb weights to maternal effect5,6. Maternal effect includes maternal additive genetic effect which means genetic ability of the dam to provide suitable conditions to embryo plus maternal permanent environmental effect which include both maternal non additive genetic effect of the dam and the dam’s mothering capacity as reported by Gudex et al.7. Genetic part or maternal additive part usually disappeared after 3 months, whereas 6 months weight was affected by maternal temporary environmental effect3.

Furthermore, Falconer8 reported early growth and body weight traits until weaning age are affected by maternal components of the dam including the dam’s own genes (maternal additive genetic effect), other constant effects among all lambs provided by the dam (maternal permanent environmental effect) and other specific effects specially for individual lamb (maternal temporary environmental effect).

Influence of direct and maternal genetic effect on lamb’s growth rate was studied by most of literatures9,10. Therefore, maximize genetic gain and use the best fitting animal models for estimation covariance components and genetic parameters are required to determine the importance of inclusion to direct additive effect, maternal genetic, maternal permanent environmental effect and their covariances11.

Development of effective genetic assessments and accurate selection of sires required in calculation of genetic parameters of studied traits enable the breeder to predict weather these traits respond to genetic improvement and can use as selection criteria or not according to Tamioso et al.12. Accuracy of probability forecasting of the genetic merit of the trait and ranking of animals according to their excellence in genetic evaluation is the main goal of the breeder as stated by Assan13.

This study was aimed to estimate variance, covariance components and genetic parameters of average daily gain traits pre and post-weaning in Rahmani lambs, show the effect of including or excluding maternal components during the genetic assessment of the traits under study, elucidate the most appropriate animal model and rank them according to Akaike Information Criterion (AIC).

MATERIALS AND METHODS

Source of data: The data used in the current study were collected over 10 years started in 1991 and ended in 2001 at El-Serw Experimental Station (North Nile Delta) belonging to Animal Production Research Institute, Ministry of Agriculture, Egypt. Records on 5879 Rahmani lambs descended from 1766 ewes and 299 rams.

Flock housing and husbandry: The animals were housed in semi-open yards and freely allowed to exercise. Routine veterinary practices were followed against infectious diseases. Animals were sheared twice a year, in March or April and September. The flock was managed under an intensive production system of three matings per 2 years by mating every 8 months (May, January and September). The following lambing seasons took place in October, June and February, respectively. Ewes and rams were mated for the 1st time at about 14-18 months of age based on phenotypic characteristics. Ewes grouped in 30-35 to mating with 1 fertile ram in a separate pen. Regarding feeding program, during the period from December to May, the flocks were fed Egyptian clover Berseem hay (Trifolium alexandrinum). In summer and autumn seasons, the ewes were fed on hay or by feeding stubble or green fodder if available, in addition to the pelleted concentrate feed mixture. All animals were fed twice daily at 7 a.m. and 4 p.m. Fresh water was available for flock twice daily during winter and 3 times during summer. Mineralized salt blocks were available to all ewes. Two weeks before the starting of breeding season, 0.25 kg concentrate supplement were offered for each ewe/day and also during the last 2-4 weeks of pregnancy. At lambing, lambs were ear tagged and kept with their dams to suckle them until weaning at 3-4 months age. Each lamb was weighted within 24 h of birth at 30 days intervals.

Traits definition: Studied traits were pre-weaning gain or average daily weight gain from birth to weaning age (ADG0,3), average daily weight gain from weaning to 6 months age (ADG3,6) as a post-weaning gain trait and average daily weight gain from birth to 6 months age (ADG0,6).

Statistical procedures: By including or excluding various random effects, 6 univariate and multivariate animal models were fitted for each trait applying the package VCE according to Groeneveld et al.14. Additive direct genetic effect was included in 6 models and only the random effect in the 1st model. Various combinations of maternal components (maternal genetic and maternal permanent environmental effects) were included in the other models. Model 2 included to maternal permanent environmental effect. Models 3 and 4 included to maternal genetic effect without and with covariance between direct and maternal effect, respectively. Models 5 and 6 included both maternal components without and with covariance between direct and maternal effect, respectively. The six animal models were described are as shown below:

•  Model 1: Y = XB+Z1a+e
•  Model 2: Y = XB+Z1a+Z2c+e
•  Model 3: Y = XB+Z1a+Z3m+e with Cov (a,m) = 0
•  Model 4: Y = XB+Z1a+Z3m+e with Cov (a,m) = Aσam
•  Model 5: Y = XB+Z1a+Z3m+Z2c+e with Cov (a,m) = 0
•  Model 6: Y = XB+Z1a+Z3m+Z2c+e with Cov (a,m) = Aσam

where, Y is the vector of records for traits studied, B, a, m, c and e are vectors of fixed effects, direct additive genetic, maternal genetic, maternal permanent environmental effects and the residual effects. The X, Z1, Z2 and Z3 are corresponding design matrices associating the fixed, direct genetic, maternal genetic, maternal permanent environmental effects to vector of Y. With assumption of direct additive genetic, maternal additive genetic, maternal permanent environmental effects and residual effects are normally distributed with the mean zero.

The model had to following distributional assumptions:

•  E (Y) = XB
•  E (a) = 0
•  E (m) = 0
•  E (c) = 0
•  E (e) = 0

The inverse of the numerator relationship matrix (A–1) was considered and the variances and co-variances were:

•  Var (a) = A σ2a
•  Var (m) = A σ2m
•  Var (c) = I σ2c
•  Var (e) = I σ2e

where, σ2a, σ2m, σ2c and σ2e are variances due to direct additive genetic, maternal genetic effect, maternal permanent environmental effects and random error, respectively. A is the additive genetic relationship matrix and I is the identity matrix according to El Fadili et al.15. Standard errors of genetic correlations were obtained using the approximate formula as described by Robertson16 in Falconer and Mackay17. An Akaike Information Criterion (AIC) test was applied on models with different orders and number of parameters to locate the best model for estimating covariance components for studied traits according to Akaike18. The AIC calculated as follows:

AICi = -2 log Li+2Pi

where, log Li is the maximized log likelihood (REML) of the particularistic model i at convergence and Pi is the number of parameters obtained from each model. The model with the lowest AIC was chosen as the most suitable model. The random effect was considered when its inclusion causes a significant increase in the log likelihood ratio than that model which ignored this effect. Usually, model with the minimum effects was selected as the most appropriate model where the log likelihood values were not differ significantly as described by Singh et al.19.

RESULTS

Least squares means and standard deviations (Table 1) of 5879 Rahmani lambs for ADG0,3, ADG3,6 and ADG0,6 were 148.499±42.008, 90.759±40.396 and 121.508±31.914 g day–1, respectively. Total number of records for average daily gain trait are decreased with maturation of the lambs being 5402 and 4084 records for ADG0,3 and ADG3,6, respectively. Referring to standard deviations and coefficient of variations, there are wide ranges of SD among studied traits ranged from 31.914 (ADG0,6) to 42.008 g (ADG0,3). Increasing CV% of post-weaning gain trait (ADG3,6) being 44.49% than those ADG0,3 (28.29%) and ADG0,6 (26.27%).

Table 1: Least squares means, Standard Deviations (SD) and coefficient of variations (CV%) for studied traits in Rahmani lambs
Image for - Impact of Maternal Components on Ranking of Animal Models in
Genetic Parameter Estimation for Daily Gain Traits in Egyptian
Rahmani Lambs

Based on models with different orders, number of parameters obtained from each model and testing the improvement of the log likelihood, the AIC values were calculated as shown in Table 2 to choose the most appropriate model for genetic analysis average daily gain weight traits. The best model was the simple model with the lowest AIC value (model included to direct additive genetic effect). Whereas, the second best model was model 2 which included to maternal permanent environmental effect.

Covariance components for average daily gain traits from 6 different single and multi-trait animal model analysis are presented in Table 3 and 4. Based on logarithm of likelihood function and AIC, full animal model was best model for average daily gain traits.

Table 2: Log likelihood test ranking of animal models
Image for - Impact of Maternal Components on Ranking of Animal Models in
Genetic Parameter Estimation for Daily Gain Traits in Egyptian
Rahmani Lambs
AIC: Akaike information criterion

Table 3: Variance and covariance components of studied traits obtained by single-trait analysis in Rahmani lambs
Image for - Impact of Maternal Components on Ranking of Animal Models in
Genetic Parameter Estimation for Daily Gain Traits in Egyptian
Rahmani Lambs
ADG0,3: Average daily gain from birth to weaning age (g), ADG3,6: Average daily gain from weaning to 6 months age (g), ADG0,6: Average daily gain from birth to 6 months age (g), σ2a: Direct additive genetic variance, σ2m: Maternal additive genetic variance, σam: Additive-maternal additive genetic covariance, σ2e: Residual variance, σ2p: Phenotypic variance, h2a: Direct heritability, h2m: Maternal heritability, ram: Additive-maternal additive genetic correlation

Table 4: Variance and covariance components of studied traits obtained by multi-trait analysis in Rahmani lambs
Image for - Impact of Maternal Components on Ranking of Animal Models in
Genetic Parameter Estimation for Daily Gain Traits in Egyptian
Rahmani Lambs
ADG0,3: Average daily gain from birth to weaning age (g), ADG3,6: Average daily gain from weaning to 6 months age (g), ADG0,6: Average daily gain from birth to 6 months age (g), σ2a: Direct additive genetic variance, σ2m: Maternal additive genetic variance, σam: Additive-maternal additive genetic covariance, σ2e: Residual variance, σ2p: Phenotypic variance, h2a: Direct heritability, h2m: Maternal heritability, ram: Additive-maternal additive genetic correlation

However, addition of maternal components, such as maternal genetic effect (model 4) and maternal permanent environmental effect (model 6) with Cov (a,m) = Aσam as well as high negative σam and ram, inflated both variance components and heritability estimates than those models not included to maternal genetic effect (model 1) and models included to maternal genetic effect with Cov (a,m) = 0.0 (models 2, 3 and 5) for pre and post-weaning gain traits. As a whole, σ2a for average daily gain traits were higher than σ2m. Also, maternal genetic variances were high in pre-weaning gain (ADG0,3) being 317.37 and 289.48 g than that post-weaning gain being 137.10, 134.47 g and 96.12, 91.78 g for ADG3,6 and ADG0,6 in single and multi-trait analyses, respectively.

Maternal permanent environmental variances were higher in the second best model (88.83 g) which considered maternal permanent environmental effect for all gain traits than those models included to maternal genetic effect with Cov (a,m) = Aσam (model 6) and with Cov (a,m) = 0 (model 5) in single-trait analysis. However, the highest σ2c in multi-trait analysis was in model 5 (425.92 g). Collectively, variances of maternal permanent environment for ADG0,3 were higher than those both ADG3,6 and ADG0,6.

Coefficients of breeding values for average daily weight gain traits by 6 univariate and multivariate animal models are presented in Table 5. A simple model was the best which included only additive genetic effect and the range of all pedigree animals breeding values for average daily gain weight traits were in the same range among different models. However, inclusion of at least one maternal components (model 4) or two maternal components (model 6) with Cov (a,m) = Aσam inflated their values to be the highest than those in the other models free from maternal components or included to maternal components with Cov (a,m) = 0. Furthermore, Spearman’s rank correlation coefficients among additive genetic values of different models provided by single and multi-trait analyses (Table 6) showed high positive significant correlation coefficients to be in the range of 0.71 and 1.00 among different models for all gain traits investigated in this study.

DISCUSSION

According to the descriptive statistics of the studied traits, Mohammadi et al.3 calculated means, SD and CV% for ADG0,3 being 213.21, 48.93 g and 22.53%, respectively for 4261 Shal lambs records which were higher than those calculated in the present study except for CV%. Decreasing mean of pre-weaning gain in Rahmani lambs than any other gain traits may originate from the nature of weather and availability of forage in Egypt as mentioned by El-Awady20.

In previous study, calculated higher standard deviations for ADG0,3, than that ADG3,6 being 31.51 and 24.69 g, respectively20. This study supported the current study.

Table 5:Means, Standard Deviations (SD), minimum, maximum and range of estimated breeding values of average daily gain traits for all animals obtained from multi and single-trait analyses
Image for - Impact of Maternal Components on Ranking of Animal Models in
Genetic Parameter Estimation for Daily Gain Traits in Egyptian
Rahmani Lambs

Table 6:
Spearman’s rank correlation coefficients between breeding values average daily gain traits in 6 animal models for all animals obtained from multi and single-trait analysis in Rahmani lambs
Image for - Impact of Maternal Components on Ranking of Animal Models in
Genetic Parameter Estimation for Daily Gain Traits in Egyptian
Rahmani Lambs
**All correlation coefficients were significant at p<0.01

Increasing SD in pre-weaning gain trait than that post-weaning gain one may be attributed to increase maternal genetic effect pre-weaning period.

Choosing the full animal model to be the best model and model 2 to be the second best model may be explained as the log likelihood values obtained from these models were non-significant which denotes the amount of maternal permanent environmental effect was negligible. Therefore, the main effect caused variation in average daily gain among lambs is the effect of animal’s own genes and direct additive genetic effect would be enough for genetic evaluation gain weight traits in sheep flock. The previous finding is in concordant with the findings of Ved Prakash et al.21 on Mapura lambs for ADG3,6, Singh et al.19 on Marwari lambs. Conversely, Rashidi et al.5 on Kermani lambs, Ved Prakash et al.21 on Mapura lambs for ADG0,3 and ADG0,6 reported that model included both direct additive genetic effect and maternal permanent environment effect to be the most appropriate model for evaluation daily gain traits genetically in sheep flock. Moreover, Mohammadi et al.3 and Tamioso et al.12 reported that model included to direct additive genetic, maternal genetic and permanent environmental effects with Cov (a,m) = 0 is the best model for genetic evaluation gain weight traits in Shal and Suffolk lambs, respectively.

In the best model, σ2a in the present study were higher than those variances calculated by Singh et al.19 being 169.25 and 72.47 g for ADG0,3 and ADG3,6, respectively. However, h2a obtained by the same researchers were higher than those obtained in this study to be 0.26±0.05, 0.16±0.04 and 0.31±0.06, respectively19. Medium to high direct heritability coefficients for average daily gain weight traits indicate that additive genetic effect constitutes the most part of phenotypic variation proposing modest genetic improvement would be predicted through direct selecting method. This interpretation was disagreed with finding of Mohammadi et al.3. Increase variation among lambs in their own additive genes for gain weight traits suggested increase genetic selection and possibility for future improvement. Moreover, increase variation in ADG0,3 than those both ADG3,6 and ADG0,6 may be originate from inclusion to the maternal effect. The previous findings are agreed with Singh et al.19.

In numerous studies by Yazdi et al.22 and El Fadili et al.15, they reported maternal effect during pregnancy and lactation is more prominent than that effect after weaning as maternal effect decline with maturation and complete separation of lambs from their mothers. This study supports the current findings.

In the same connection with the present study, Singh et al.19 worked on growth traits in Marwari sheep, they estimated σ2c to be high in model included to maternal permanent environmental variance being 32.45 and 0.01 g for ADG0,3 and ADG3,6, respectively which agreed with present study. Furthermore, they argued that σ2c for average daily gain traits decreased with maturation of lambs which may originate from decrease maternal effect at the expense of other temporary environmental conditions, such as management, feeding and health programs applied in the flock.

Conflicting results were reported by Tamioso et al.12, they estimated σ2a, σ2c, σ2m, σ2p, h2a and h2m in the best model to be 2.67, 1.41, 2.11 and 39.56 g, 0.07 and 0.05, respectively for ADG0,3 which were lower than those values obtained in the current study. Ghafouri-Kesbi et al.23 argued that maternal effects should be included during estimation genetic parameters of growth traits, since ignoring of these effects overestimated these parameters.

Negative σam and ram are similar to the finding of Singh et al.19 to be -322.17 and -318.53 for σam and -0.97 and -0.99 for ram in case of ADG0,3, -61.72 and -43.17 for σam and -1.00 for ram in case of ADG3,6 and -99.07 and -30.53 for σam and -1.00 for ram in case of ADG3,6. Negative genetic correlation between direct and maternal effect could be attributed to small data sets, nature of pedigree information, managemental and environmental circumstances as mentioned by Maria et al.9 or may originate from negative effect of the dams on the maternal ability of their female lambs through over feeding as reported by El-Awady20. The association between additive direct and maternal genetic effect were negative for growth traits, such as Ligda et al.24 on Chios sheep. Genetic correlations between different daily gain traits were negative due to kin and contemporary competition effect as reviewed by Gowane et al.25. However, positive relationship between direct and maternal genetic effect for growth traits was reported by Yazdi et al.22 on Baluchi sheep. Increasing phenotypic variance with the advancement of the lamb’s age probably resulted from increase the effect of permanent environment and decrease the effect of the dam post-weaning. In a study by Mohammadi et al.3, they estimated σ2p being 85.13 g for daily gain traits by the best model to be lower than those phenotypic variances in the current study.

Furthermore, Mohammadi and Edriss26 and Singh et al.19 calculated direct heritability estimate for ADG0,3 from the best fitted animal model (full model) to be approximately 0.26±0.050 in Mehraban and Marwari lambs, respectively. However, the lower estimate was recorded by Prince et al.10 being 0.15±0.04.

Regarding ADG3,6 in the simple model, σ2a was recorded by Prince et al.10 being 0.15±0.04 on Avikalin sheep and approximately the same to estimate that calculated in the present study to be 0.26±0.050 by Singh et al.19 indicating modest genetic gain for the trait through selection. Moreover, Tamioso et al.12 estimated σ2m for ADG0,3 in the best model being 0.05±0.02 which was slightly lower than those values obtained in the current study from the same model (model 5) being 0.09±0.01 and 0.08±0.01 for both single and multi-trait analyses, respectively. Low maternal heritability estimates in the current study denotes that maternal genetic effect constitutes a negligible part of phenotypic variance which may resulted from absence of covariance between direct and maternal genetic effects suggesting slow genetic progress in case of direct selecting method.

Declining the coefficients of maternal permanent environmental variance to phenotypic variance with maturation of lambs and obtaining the highest ratios from the second best model were similar to reports of Singh et al.19 they calculated c2 in ADG0,3 and ADG3,6 to be 0.05 and 0.0, respectively. Low coefficients of c2 for daily weight gain traits suggested that additive genetic effect constitutes the major part of phenotypic variation. In contrast to the above, Zamani et al.27 reported that c2 tended to increase with maturation of Moghani sheep. Variations in c2 could be originated from differences in populations under study, type and models used in analysis of data sets, climatic and managerial conditions21.

In the best simple model, there was a modest range of breeding values which could be explained from the modest coefficient of h2a suggested the existence of medium genetic variations among animals and hence the modest possibility of selection of daughter’s daily gain traits based on additive genetic effect. Improvement of average daily gain weight traits genetically in the subsequent generations is a target of the breeder to improve mutton production.

Distinct positive significant Spearman’s rank correlation coefficients between additive genetic values among different animal models for gain weight traits in this study denoted that there is no significant difference between rankings of models to animals in calculating additive genetic values for each trait. Inclusion of direct additive genetic effect is sufficient for improving these traits genetically in Rahmani lambs.

CONCLUSION

Current study entailed that simple animal model is the most suitable model for genetic evaluation of gain weight traits and additive genetic effect constitute the most part of phenotypic variation in weight gain traits, consequently direct selecting method is an effective method for selection and genetic improvement for gain weight traits in Egyptian Rahmani lambs.

SIGNIFICANCE STATEMENT

Assessment of effective selecting and breeding plans for genetic improvement the weight gain trait of the Rahmani lambs through; using various combinations of animal models to determine the importance of inclusion to direct additive effect, maternal genetic, maternal permanent environmental effect and their covariances. Ranking models according to Akaike Information Criterion and test the significance of log likelihood test. Locate and use the best fitting model for estimating covariance components and genetic parameters for studied traits.

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