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Estimation of direct and maternal (co)variance components for pre-weaning growth traits in Muzaffarnagari sheep
Livestock Science 99 (2006) 79 – 89 www.elsevier.com/locate/livsci
Estimation of direct and maternal (co)variance components for pre-weaning growth traits in Muzaffarnagari sheep Ajoy Mandal a,*, F.W.C Neser b, P.K. Rout a, R. Roy a, D.R. Notter c a Genetics and Breeding Division, Central Institute for Research on Goats, Makhdoom, Mathura-281 122, Uttar Pradesh, India Department of Animal Wildlife and Grassland Sciences, Faculty of Natural and Agriculture Sciences, Bloemfontein, South Africa c Department of Animal and Poultry Sciences, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061-0306, USA b
Received 6 October 2004; received in revised form 7 April 2005; accepted 9 June 2005
Abstract Genetic parameters and (co)variance components were estimated for weight at birth and at 15, 30, 45, 60 and 75 days of age for a flock of Muzaffarnagari sheep maintained at the Central Institute for Research on Goats, Makhdoom, Mathura over a period of 27 years (1976–2002). Records on 5201 lambs descended from 1568 ewes and 170 rams were included in the analysis. Analyses were carried out by REML fitting an animal model and ignoring or including maternal genetic or permanent environmental effects. Six different animal models were fitted for all traits, and the best model was chosen after testing improvements in log-likelihood values. Direct heritability estimates were inflated substantially for all traits when maternal effects were ignored. Direct heritability estimates were 0.08 F 0.02 for birth weight and 0.02 F 0.02, 0.02 F 0.02, 0.27 F 0.08, 0.09 F 0.04, and 0.29 F 0.08 for weights at 15, 30, 45, 60, and 75 days, respectively. Maternal genetic effects contributed only 4 to 8% of the total phenotypic variance from birth to 30 days of age, and this effect diminished further with increasing age. Maternal heritability was low for pre-weaning growth traits and should have only a small effect on selection response. Estimates of the fraction of variance due to maternal permanent environmental effects were 0.09 F 0.02, 0.15 F 0.04, 0.12 F 0.03, 0.11 F 0.04, 0.14 F 0.02, and 0.08 F 0.04 for body weights at birth and at 15, 30, 45, 60, and 75 days, respectively. These results indicate that selecting for improved maternal and/or direct effects in Muzaffarnagari sheep would generate only slow genetic progress in early growth traits. D 2005 Elsevier B.V. All rights reserved. Keywords: Muzaffarnagari sheep; Growth traits; Maternal effects; Variance components; Heritability; Animal model
1. Introduction
* Corresponding author. Tel.: +91 565 2763280x293; fax: +91 565 2763246. E-mail address: [email protected] (A. Mandal). 0301-6226/$ - see front matter D 2005 Elsevier B.V. All rights reserved. doi:10.1016/j.livsci.2005.06.001
Early growth traits are important factors influencing profitability in any meat producing enterprise. The birth weight of an animal and its early growth rate, in particular until weaning, are determined not only by
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A. Mandal et al. / Livestock Science 99 (2006) 79–89
Table 1 A summary of published values for animal model additive direct (h 2), additive maternal (m 2) and permanent environmental (c 2) variance ratios, genetic correlation between direct and maternal effects (r am), total heritability (h2t), and repeatability of ewe performance (t m) for different growth traits in sheep Breed
Age (days)
h2
m2
c2
r ama
h2b t
t mb
References
Birth weight Dohne Merino Romanov Various
Birth Birth Birth
0.04 0.04 0.20–0.34
0.10 0.22 0.30–0.65
0.17 0.10 –
0.09 0.02 0.14–0.33
0.28 0.24 0.33–0.43
Afrino Various
Birth Birth
0.22 0.07–0.39
0.09 0.13–0.31
0.12 0.32–0.37
0.27 0.12–0.25
0.27 0.46–0.54
Cloete et al. (1998) Maria et al. (1993) Burfening and Kress (1993) Snyman et al. (1995) Tosh and Kemp (1994)
Various
Birth
0.16–0.22
0.18–0.24
0.09–0.11
0.24–0.34
0.32–0.37
Bromley et al. (2000)
Swedish finewool
Birth
0.07
0.30
–
– 0.99 0.18– ( 0.74) – 0.13– ( 0.56) 0.08– ( 0.20) 0.11
0.24
0.33
Baluchi Dormer Chios Dorper Local Sabi Sabi Timahdite
Birth Birth Birth Birth Birth Birth Birth Birth
0.14–0.20 0.16 0.18 0.11 0.42 0.27 0.25 0.05
0.07–0.12 0.43 0.19 0.10 0.33 0.24 0.12 0.05
0.04–0.12 – 0.17 0.12 0.00 – 0.08 0.00
0.15–0.18 0.35 0.44 0.04 0.60 1.00 – 0.55
0.24–0.27 0.24 0.16 0.21 0.17 0.77 0.31 0.03
0.22–0.26 0.38 0.32 0.25 0.21 0.56 0.26 0.04
Turkish Merino
Birth
0.11
0.11
0.20
0.48
0.08
0.28
Nasholm and Danell (1996) Yazdi et al. (1997) van Wyk et al. (1993) Ligda et al. (2000) Neser et al. (2001) Al-Shorepy (2001) Assan et al. (2002) Matika et al. (2003) Boujenane and Kansari (2002) Ekiz et al. (2004)
Postnatal weights Polypay Suffolk Targhee
30,60 30,60 60
0.07–0.08 0.14–0.16 0.01
0.07–0.17 0.04–0.05 0.10
0.15 0.11–0.19 0.09
– – –
0.11–0.15 0.16–0.18 0.06
0.24–0.34 0.19–0.27 0.19
Moroccan Timahdit
30,70
0.31–0.54
0.34–0.38
–
0.01–0.05
0.06–0.10
Timahdite
30,70
0.02–0.07
0.07–0.08
0.00
0.03–0.05
0.06
Belgian Texel
30,70
0.06–0.11
0.13–0.22
0.10–0.15
–
–
Sabi Dorset Composite
30,60 45,60
0.11–0.13 0.23–0.24
0.03–0.06 0.00–0.03
0.06–0.11 0.11–0.13
0.97– ( 1.0) 0.50– ( 0.51) 0.02– ( 0.06) – –
0.13–0.16 0.23–0.25
0.15–0.17 0.17–0.22
Swedish finewool
21
0.07
0.17
–
0.22
0.28
Dorset Composite
60
0.04
0.10
0.05
–
0.09
0.16
S.A. Mutton Merino
36,42,50
0.27–0.37
0.13–0.49
0.09–0.16
0.00–0.13
0.19–0.28
Dorper Romanov Chios Norwegian
42 40 42 47
0.28 0.34 0.17 0.20
0.10 0.25 0.07 0.14
0.11 0.00 0.08 0.08
0.76– ( 1.00) 0.11 0.98 0.26 0.04
0.17 0.03 0.17 0.28
0.26 0.05 0.16 0.28
a
0.37
Notter (1998) Notter (1998) Notter and Hough (1997) El Fadili et al. (2000) Boujenane and Kansari (2002) Janssens et al. (2000) Matika et al. (2003) Fossceco and Notter (1995) Nasholm and Danell (1996) Al-Shorepy and Notter (1996) Neser et al. (2000) Neser et al. (2001) Maria et al. (1993) Ligda et al. (2000) Larsgard and Olesen (1998)
An estimate of the additive–maternal genetic correlation (r am) is shown only when this parameter was included in the preferred model presented in the published work. In all other cases, r am was assumed to be zero in calculation of h2t and t m. b This parameter was calculated from published estimates of h 2 , m 2 , c 2 and r am in cases where h2t and/or t m were not presented in the cited work.
A. Mandal et al. / Livestock Science 99 (2006) 79–89
its own genetic potential but also by the maternal environment. These maternal effects reflect mainly the dam’s milk production and mothering ability, though effects of the uterine environment and extrachromosomal inheritance may also contribute. These maternal effects have three causes (Falconer, 1989): those due to the dam’s own genotype for milking and mothering ability (maternal additive effects); those consistent among all lambs produced by a dam but not of additive genetic origin (permanent environmental effects); and those specific to individual lambs (temporary environmental effects). The genotype of the dam therefore affects the phenotype of the young through a sample of half of her direct, additive genes for growth as well as through her genotype for maternal effects on growth. Bradford (1972) and Robison (1981) argued that traits recorded in early life are most affected by maternal ability. When some of these growth traits are included in the breeding goal, both the direct and maternal component should be taken into account to achieve optimum progress in a selection programme. Robison (1981) postulated that understanding of the relationship between direct and maternal effects would facilitate formulation of optimum breeding programmes and improvement of selection efficiency. The partitioning of additive direct, additive maternal, and permanent environmental maternal effects requires data on the performance of related (commonly half-sib) ewes in pedigreed matings across several lambing years. The availability of restricted maximum likelihood (REML) algorithms for fitting animal models has simplified the estimation of (co)variance components due to maternal effects (Meyer, 1997). However, meaningful partitioning of direct and maternal effects still requires an adequate underlying data structure. The possible existence of genetic correlations between direct and maternal additive effects introduces additional difficulties in fitting maternaleffects model (Hanrahan, 1976; Willham, 1980). Numerous studies have reported a negative correlation between additive direct and additive maternal effects on growth traits of various sheep breeds (Maria et al., 1993; Tosh and Kemp, 1994; Notter, 1998; Ligda et al., 2000). In many cases, these estimates have been too large (b 0.8) to be biologically reasonable. However, positive relationships have also been reported (Nasholm and Danell, 1996; Yazdi et al., 1997). Pub-
81
lished estimates of maternal variances and heritabilites for pre-weaning growth traits in various breeds of sheep are summarized in Table 1. Estimates of (co)variance components and genetic parameters for growth traits by REML procedures have not been reported for Muzaffarnagari sheep. Most reported heritabilities of growth traits for this breed are based on ratios of variance components estimated mainly by paternal half-sib method, without consideration of maternal effects. Therefore, the present study was conducted to estimate variance and covariance components due to direct genetic effects, maternal genetic effects and maternal permanent environmental effects for different pre-weaning growth traits in Muzaffarnagari sheep.
2. Materials and methods 2.1. The breeding flock and management The Muzaffarnagari sheep, an important mutton breed of India, is known for its relatively rapid growth (Singh, 1995), high feed conversion efficiency (Mandal et al., 2000), and very good adaptability (Mandal et al., 2003) in the semi-arid region of the country. Data were collected from an experimental breeding flock of Muzaffarnagari sheep maintained at Central Institute for Research on Goats (CIRG), Makhdoom, Uttar Pradesh, India, under the All-India Coordinated Research Project on Sheep Breeding for Mutton Production for a period of 27 years (1976–2002). The location of the experimental flock as well as its natural habitat, description, and husbandry practices were described by Mandal et al. (2000). Briefly, the flock was composed of 250 breeding ewes reared under semi-intensive feeding. All animals grazed during the day (6 to 7 h) on natural pasture with supplementation depending upon the status and age category of the animals and were penned at night. Generally, controlled mating was practiced. Ewes in heat were mated with selected sires in the morning. Sheep were bred twice at each oestrus. Ewes were first exposed to rams at about 12 months of age. One breeding ram was allowed to mate with 20 to 25 ewes. There were two breeding seasons in May–June and October–November, with lambing in October–November and March–April. At birth each lamb was identified and date of birth, sex, type of birth
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and weight were recorded. Lambs were normally weaned at 3 months of age. 2.2. Data The data included 5201 lamb records from 1568 ewes sired by 170 rams and born in the periods 1976– 2002. Traits considered for analysis were weight at birth and at 15, 30, 45, 60 and 75 days (Table 2). Data on some postnatal weights were not collected over the entire 27 years, yielding dissimilar numbers of records for different traits; numbers of records analysed ranged from 1301 to 5201. Characteristics of the data structure are summarized in Table 2. 2.3. Analyses Variance and covariance components for pre-weaning growth traits were estimated by fitting a series of univariate animal models using a derivative-free REML algorithm (DFREML, Meyer, 2000). With DFREML the maximum of the log-likelihood value was found by the Simplex method. Convergence was considered to be reached when the variance of function values in the Simplex was less than 10 8. Analyses were restarted from converged values to check that a global rather than local maximum had been reached. When estimates did not change, convergence was assumed. Depending on the model, the log-likelihood function was maximized with respect to the direct and maternal additive variances, the permanent environmental variance of the dam and the genetic covariance between direct and maternal genetic effects. Standard errors of the parameters estimated as a part of the DFREML programme were calculated as described by Meyer (2000).
Mandal et al. (2003) found that the fixed effects that significantly influenced the weight of the lambs were year and season of birth, parity of dam, sex of lamb and type of birth. The weight of the dams at lambing was considered by including the linear regression of body weights of the lamb on weight of the ewe in the statistical model. In the present study, a preliminary least squares analysis of variance (Harvey, 1990) confirmed that fixed effects of birth year, season of birth, parity of dam, sex and birth status of lamb were all highly significant ( P b 0.01) and hence were included in the model. Single trait animal models were fitted for all traits. By ignoring or including maternal genetic or environmental effects, the following six models were fitted for each trait: y ¼ Xb þ Z1 a þ e
ð1Þ
y ¼ Xb þ Z1 a þ Z3 c þ e
ð2Þ
y ¼ Xb þ Z1 a þ Z2 m þ e with Covða; mÞ ¼ 0
ð3Þ
y ¼ Xb þ Z1 a þ Z2 m þ e with Covða; mÞ ¼ Aram ð4Þ y ¼ Xb þ Z1 a þ Z2 m þ Z3 c þ e with Covða; mÞ ¼ 0 ð5Þ y ¼ Xb þ Z1 a þ Z2 m þ Z3 c þ e with Covða; mÞ ¼ Aram
ð6Þ
where y is the n 1 vector of observations for each trait and X is the incidence matrix that relates data to
Table 2 Characteristics of the data structure for pre-weaning weights of Muzaffarnagari sheep
No. of records No. of animals No. of sires with progeny record No. of dams with progeny record Average weight (kg) Standard deviation (kg) CV (%) Years of records
Birth wt.
15-day wt.
30-day wt.
45-day wt.
60-day wt.
75-day wt.
5201 5456 170 1568 3.47 0.73 21.04 27
2705 3124 71 922 5.77 1.41 24.44 16
2988 3415 78 981 7.71 2.01 26.07 17
1392 1646 40 420 8.97 2.50 27.87 9
2886 3291 78 955 11.49 2.99 26.02 17
1301 1535 40 395 12.50 3.58 28.64 9
A. Mandal et al. / Livestock Science 99 (2006) 79–89
the unknown vector of fixed effects b. Incidence matrices Z1 and Z2 relate unknown vectors of direct (a) and maternal (m) breeding values, respectively, to y. The incidence matrix Z3 relates an unknown additional random vector of permanent maternal environmental effects (c) to y. The unknown vector e contains random residuals due to environmental effects peculiar to individual records. A is the numerator relationship matrix, and r am is the covariance between direct and maternal additive genetic effects. It was assumed that V(a) = Ar a2, V(m) = Ar m2, V(c) = Ir c2, and V(e) = Ir e2 where I is an identity matrix and r a2, r m2, r c2 and r e2 are direct additive genetic, maternal additive genetic, maternal permanent environmental, and residual variances, respectively. Estimates of heritability (h 2), maternal heritability (m 2) and relative permanent maternal environmental (c 2) effects were calculated as ratios of estimates of r a2, r m2, and r c2, respectively, to the phenotypic variance (r p2). The direct–maternal correlation (r am) was computed as the ratio of the estimated direct–maternal covariance (r am) to the product of the square roots of estimates of r a2 and r m2. The repeatability for ewe performance was also calculated as t m = H h 2 + m 2 + c 2 + mr amh, and the heritability of the total genetic contribution to a maternally influenced trait was calculated as h2t = h 2 + 0.5 m 2 + 1.5 mr amh (Willham, 1972). To test the significance of random effects and identify the most appropriate model for each trait, likelihood ratios tests were conducted (Meyer, 1992). Likelihoods must increase when additional parameters are included in the model, and an effect was considered to have a significant influence when its inclusion caused a significant increase in log-likelihood, compared to a model in which it was ignored. Significance was tested at the level of P b 0.05 by comparing the difference in log-likelihoods to the value of a chisquare distribution with degrees of freedom equal to the difference in the number of (co)variance components fitted for the two models.
3. Results and discussion Phenotypic means, standard deviations and coefficients of variations for body weights at birth and at 15, 30, 45, 60 and 75 days are shown in Table 2. For these lambs, 50.9% were male and 49.1% were female.
83
Single- and twin-born lambs represented 91.3% and 8.7% of the data, respectively. Coefficients of variation for pre-weaning weights ranged from 21.0% for birth weight to 28.6% for 75-day weight and were within the range of previously reported values for other sheep breeds (Ligda et al., 2000; Neser et al., 2001; Matika et al., 2003). 3.1. Pre-weaning growth traits Estimates of (co)variance components and genetic parameters for different pre-weaning growth traits obtained under the six different models are summarized in Tables 3 and 4. The most appropriate models based on likelihood ratio tests are presented in Table 5. 3.1.1. Birth weight Estimates of heritability for birth weight (Table 3) depended on the model used, ranging from 0.08 to 0.25. For this trait, ignoring maternal effects (Model 1) yielded substantially higher estimates of r a2 and h 2 than other models. Fitting a permanent environmental maternal effect (Model 2) markedly increased the loglikelihood value over that for Model 1 (Table 5), indicating a significant maternal effect accounting for 16% of the total variance in this trait while correspondingly reducing the estimate r a2. Fitting a maternal genetic (Model 3) rather than permanent environmental effect also resulted in an increase in log-likelihood over Model 1 but the resulting likelihood was very similar to that of Model 2. The estimate of maternal heritability from Model 3 was 17%, with a corresponding decrease in the estimate of direct heritability to 8%. In Model 4, the estimate of direct–maternal genetic covariance (r am) was negative ( 0.009), accounting for almost to 3% of r p2. The direct maternal genetic correlation (r am) was 0.23, but the difference in likelihoods between Models 3 and 4 was small. Fitting both genetic and environmental components of the dam effect (Model 5) resulted in a significantly better fit compared to other models (Table 5). Inclusion of both genetic and environmental components of the dam effect (m 2 + c 2) reduced the estimate of r m2. When permanent environmental effects due to dam were not fitted (Models 3 and 4), these tended to be dpicked upT in the estimate of r m2, inflating m 2 by 9%. In Model 6, the
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A. Mandal et al. / Livestock Science 99 (2006) 79–89
Table 3 Estimates of (co)variance components (kg2) and genetic parameters for birth weight and for 15- and 30-day weights of sheep
Table 4 Estimates of (co)variance components (kg2) and genetic parameters for 45-, 60- and 75-day weights of sheep
Traitsa Model 1 Model 2 Model 3 Model 4 Model 5 Model 6
Traitsa Model 1 Model 2 Model 3 Model 4 Model 5 Model 6
Birth weight r2a 0.076 r m2 – – r am r2c – r2e 0.224 0.300 r 2p h2 0.25 m2 – c am – – r am c2 – h 2t 0.25 tm –
0.030 – – 0.046 0.215 0.291 0.10 – – – 0.16 0.10 0.19
0.023 0.051 – – 0.225 0.298 0.08 0.17 – – – 0.16 0.19
0.026 0.058 0.009 – 0.223 0.298 0.09 0.19 0.03 0.23 – 0.14 0.18
0.024 0.022 – 0.028 0.218 0.292 0.08 0.08 – – 0.09 0.12 0.19
0.027 0.027 0.007 0.028 0.216 0.292 0.09 0.09 0.02 0.26 0.10 0.10 0.19
45-day r2a r m2 r am r2c r2e r 2p h2 m2 c am r am c2 h2t tm
weight 1.477 – – – 2.338 3.816 0.39 – – – – 0.39 –
1.009 – – 0.403 2.334 3.746 0.27 – – – 0.11 0.27 0.18
0.927 0.347 – – 2.472 3.746 0.25 0.09 – – – 0.29 0.15
1.250 0.977 0.719 – 2.264 3.772 0.33 0.26 0.19 0.65 – 0.17 0.15
1.007 0.000 – 0.403 2.335 3.745 0.27 0.00 – – 0.11 0.27 0.18
1.367 0.094 0.358 0.544 2.131 3.778 0.36 0.02 0.10 1.00 0.14 0.23 0.16
15-day r2a r m2 r am r2c r2e r 2p h2 m2 c am r am c2 h2t tm
weight 0.184 – – – 0.928 1.112 0.16 – – – – 0.16 –
0.029 – – 0.223 0.842 1.095 0.03 – – – 0.20 0.03 0.21
0.019 0.206 – – 0.883 1.108 0.02 0.19 – – – 0.11 0.20
0.047 0.288 0.086 – 0.860 1.109 0.04 0.26 0.08 0.74 – 0.06 0.19
0.022 0.063 – 0.166 0.845 1.096 0.02 0.06 – – 0.15 0.05 0.21
0.039 0.106 0.040 0.158 0.834 1.097 0.04 0.10 0.04 0.62 0.14 0.03 0.21
60-day r2 r m2 r am r2c r2e r 2p h2 m2 c am r am c2 h2t tm
weight 1.152 – – – 4.384 5.537 0.21 – – – – 0.21 –
0.501 – – 0.754 4.187 5.443 0.09 – – – 0.14 0.09 0.16
0.451 0.648 – – 4.393 5.491 0.08 0.12 – – – 0.14 0.14
0.978 1.637 1.070 – 4.027 5.572 0.17 0.29 0.19 0.85 – 0.03 0.14
0.499 0.000 – 0.755 4.189 5.443 0.09 0.00 – – 0.14 0.09 0.16
0.809 0.381 0.492 0.786 3.990 5.474 0.15 0.07 0.09 0.89 0.14 0.05 0.16
30-day r2a r m2 r am r2c r2e r 2p h2 m2 c am r am c2 h 2t tm
weight 0.326 – – – 2.081 2.408 0.14 – – – – 0.13 –
0.049 – – 0.382 1.945 2.377 0.02 – – – 0.16 0.02 0.17
0.038 0.353 – – 2.011 2.402 0.02 0.15 – – – 0.09 0.16
0.109 0.550 0.201 – 1.952 2.410 0.04 0.23 0.08 0.82 – 0.03 0.16
0.042 0.102 – 0.289 1.948 2.380 0.02 0.04 – – 0.12 0.04 0.17
0.088 0.213 0.105 0.273 1.915 2.384 0.04 0.09 0.04 0.77 0.11 0.02 0.16
75-day r2a r m2 r am r2c r2e r 2p h2 m2 c am r am c2 h2t tm
weight 3.004 – – – 5.138 8.143 0.37 – – – – 0.37 –
2.336 – – 0.656 5.059 8.051 0.29 – – – 0.08 0.29 0.15
2.272 0.529 – – 5.258 8.059 0.28 0.07 – – – 0.31 0.14
3.087 2.247 1.924 – 4.720 8.130 0.38 0.28 0.24 0.73 – 0.16 0.14
2.344 0.000 – 0.657 5.052 8.054 0.29 0.00 – – 0.08 0.29 0.15
3.228 0.361 1.080 1.065 4.550 8.126 0.40 0.04 0.13 1.00 0.13 0.22 0.14
a r2a = additive direct genetic variance; r m2 = additive maternal genetic variance; r am = direct–maternal additive genetic covariance; r2c = permanent environmental maternal variance; r2e =environmental variance; r 2p = phenotypic variance; h 2 = direct heritability; m 2 = maternal heritability; c am = r am / r 2p ; r am = direct–maternal genetic correlation; c 2 = r2c / r 2p; h 2t = h 2 + 0.5 m2 + 1.5 mr amh is the total heritability; t m = H h 2 + m 2 + c 2 + mr amh is the repeatability of ewe performance.
a
See Table 3 for abbreviations.
estimate of r am was also negative ( 0.007) but resulted in little change in likelihood compared to Model 5. The estimate for r am was about 0.02 with a corresponding estimate of r am of 0.26. The most appropriate model (Table 6) for birth weight
A. Mandal et al. / Livestock Science 99 (2006) 79–89
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Table 5 Log-likelihood valuesa obtained for each trait under the six different models with the best model in bold Traits
Model 1
Model 2
Model 3
Model 4
Model 5
Model 6
Birth wt. 15-day wt. 30-day wt. 45-day wt. 60-day wt. 75-day wt
72.3** 47.33** 34.05** 5.91* 24.04** 3.74y
10.24** 2.99y 2.40 0.82 1.47 1.01
11.11** 10.1** 7.49** 3.43y 10.48** 2.47
10.18** 7.56** 4.95* 2.19 6.80* 1.11
0.88 0.96 1.19 0.82 1.47 1.01
0 0 0 0 0 0
a As deviations from the model with the highest value. * P b 0.05. ** P b 0.01. y P b 0.10.
ings of Snyman et al. (1995) in Afrino sheep. The estimate of the permanent environmental maternal effect (c 2) for birth weight was in agreement with the findings of Maria et al. (1993) and Bromley et al. (2000). However, estimates reported by Tosh and Kemp (1994) in Hampshire, Polled Dorset, and Romanov sheep, by Snyman et al. (1995) in Afrino sheep, by Neser et al. (2001) in Dorper sheep, and by Ekiz et al. (2004) in Turkish Merino lambs were higher than our estimates. Meyer (1992) indicated that the relative values of h 2, m 2 and c 2 are influenced by the specific model. As shown by comparison of Models 2, 3, and 5, estimates of m 2 and c 2 are biased upwards if both are important but only one is included in the analytical model. The estimate of h 2 from Model 1 is likewise biased upward by failure to include significant maternal effects. The total heritability (Table 3) can be used to calculate the expected response to phenotypic selection for birth weight and was moderate in magnitude (0.12), indicating some scope for selection response in this trait. The total heritability for birth weight observed in this study was comparable to the findings of Burfening and Kress (1993) and Ekiz et al. (2004).
included both maternal genetic and permanent environmental effects but did not include the additive direct–maternal covariance. The estimate of direct heritability of birth weight in the present study (0.08, Model 5) was similar to the findings of Tosh and Kemp (1994), Nasholm and Danell (1996) and Ekiz et al. (2004) in other breeds of sheep (Table 1). A similar paternal half-sib estimate of heritability for birth weight (0.07) was reported by Mandal et al. (2003) in Muzaffarnagari sheep. However, higher heritability estimates of birth weight were reported for other breeds (Burfening and Kress, 1993; Snyman et al., 1995; Yazdi et al., 1997; Al-Shorepy, 2001; Assan et al., 2002; Matika et al., 2003). Lower heritability estimates were reported by Maria et al. (1993) in Romanov, Cloete et al. (1998) in Dohne Merino, and Boujenane and Kansari (2002) in Timahdite sheep. Low heritability estimates for birth weight in our study can perhaps be explained by a generally poor nutritional level of ewes creating a large environmental variation. The maternal heritability estimate for birth weight (0.08) from Model 5 was in accordance with find-
Table 6 Estimated parameters and their standard errors from the best model for each traita Traits
Model
h2
Birth wt. 15-day wt. 30-day wt. 45-day wt. 60-day wt. 75-day wt
5 5 5 2 2 2
0.08 0.02 0.02 0.27 0.09 0.29
a
(0.02) (0.02) (0.02) (0.08) (0.04) (0.08)
m2
c2
0.08 (0.02) 0.06 (0.03) 0.04 (0.03) – – –
0.09 0.15 0.12 0.11 0.14 0.08
(0.02) (0.04) (0.03) (0.04) (0.02) (0.04)
r2a
r m2
r2c
r2e
r 2p
0.024 0.022 0.042 1.009 0.501 2.336
0.022 0.063 0.102 – – –
0.028 0.166 0.289 0.403 0.754 0.656
0.218 0.845 1.948 2.334 4.187 5.059
0.292 1.096 2.380 3.746 5.443 8.051
Figures in parentheses are standard errors of the estimate. See Table 3 for abbreviations.
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A. Mandal et al. / Livestock Science 99 (2006) 79–89
Higher estimates of total heritability were obtained by, van Wyk et al. (1993), Snyman et al. (1995), Nasholm and Danell (1996), Neser et al. (2001) and Assan et al. (2002), in different breeds of sheep. Estimates reported by Maria et al. (1993) in Romanov sheep (0.02) and Boujenane and Kansari (2002) in Timahdite sheep (0.03) were lower than those observed in our study; both were associated with large negative estimates of r am. The estimate of repeatability of ewe effects on birth weight includes both total maternal and ewe transmitted additive effects and was 0.19 under the best model. Our maternal repeatability estimates for birth weight (Table 3) were lower than those reported in Table 1 except for that of Boujenane and Kansari (2002). Estimates of t m for birth weight in Table 3 were essentially the same for Models 2 through 6, suggesting that the repeatability of ewe performance was estimated consistently across the different maternal-effects models. 3.1.2. Postnatal weights Genetic parameters and (co)variance components for postnatal weights are shown in Tables 3 and 4. In Model 1, where maternal effects were ignored, heritability was biased upward for all postnatal weights. Introducing permanent environmental effects associated with the dam (Model 2) explained 20%, 16%, 11%, 14% and 8% of total phenotypic variance for weights at 15, 30, 45, 60 and 75 days, respectively, and the corresponding reduction in direct heritability was 81%, 86%, 31%, 57% and 22% in comparison with Model 1. Fitting a c 2 effect also increased the likelihood significantly over that for a simple animal model. Model 3, which included maternal genetic effects in place of permanent environmental maternal effects, also detected significant maternal effects contributing 19, 15, 9, 12 and 7% of total variation at 15, 30, 45, 60 and 75 days, respectively, and also yielded large reductions in estimates of h 2 relative to Model 1. Fitting a non-zero covariance (r am) along with a maternal genetic effect (Model 4) resulted in large negative direct–maternal covariance estimates for all weights but gave no significant improvement in likelihood compared to Model 3. Model 5 attempted to disentangle genetic and environmental components of the dam effect. Estimates of m 2 from Model 5 were much smaller than those obtained from Model 3 and
were null after 30 days. Allowing for a direct–maternal covariance in Model 6 yielded large negative estimates of r am, which ranged from 0.62 to 1.00 and accounted for 4 to 13% of total variance but did not produce a significant improvement in likelihood compared to Model 5. The model with only a permanent environmental effect due to the dam (Model 2) was clearly most suitable for 45-, 60-, and 75-day weights (Table 6). For 15- and 30day weights, Model 5 was not significantly superior to Model 2. However, the gradual decline in additive maternal variance from birth through 30 days revealed by Model 5 was considered to be the more biologically consistent model, even though a significant additive maternal effect on these weights could not be documented. The direct heritability for 30-day weight in the present study (0.02) was within the range of findings of Boujenane and Kansari (2002), and the estimate of maternal heritability for lamb 30-day weight observed in this study was similar to those reported by Notter (1998), Ligda et al. (2000) and Matika et al. (2003) in different breeds of sheep (Table 1). The estimates of direct heritability for 45-day weight in Muzaffarnagari lambs were close to the estimates of Fossceco and Notter (1995) and Neser et al. (2000, 2001). The direct heritability for 60-day weight was well within the range of the results of other investigators (Notter and Hough, 1997; Notter, 1998; Matika et al., 2003). Estimates of direct heritability were high for weights at 45 and 75 days, ranging from 0.27 to 0.29. However, these weights were not recorded in all years, so these estimates are not directly comparable to those for weights at 15, 30, and 60 days. Maternal heritabilities for pre-weaning weights decreased with age, which confirms findings of Tosh and Kemp (1994), Snyman et al. (1995), Nasholm and Danell (1996), Yazdi et al. (1997), and El Fadili et al. (2000) who also observed that maternal effects were substantial in young animals but diminished with age. The low direct additive effects on body weights at 15, 30, and 60 days suggest that only slow genetic progress may be obtained from selection under the prevailing management system. Notter and Hough (1997) and Matika et al. (2003) explained that low direct additive estimates for early body weights may be due to the fact that lambs did not receive creep feed and were raised in a generally poor nutri-
A. Mandal et al. / Livestock Science 99 (2006) 79–89
tional environment, resulting in lambs not expressing their genetic potential. All the estimates of maternal heritability were relatively low, ranging from 0.04 to 0.08 in the present study. The low productivity and poor environment could partially explain low maternal effects in Muzaffarnagari sheep. At young ages, insufficient milk production by the ewe may also give rise to variation in environmental effects and result in low heritabilities. Contrary to some carry-over effects exhibited in other breeds, maternal effects were small and not significant after 45 days. The low maternal effect on pre-weaning growth indicates that the maternal effect would have less effect on selection response for these traits. The c 2 effect on pre-weaning weights accounted for 8 to 15% of the total phenotypic variance. These results are also in accord with those found in the literature (Table 1). The c 2 effect increased from birth to 60 days and thereafter declined. However, Tosh and Kemp (1994) observed that the permanent environmental effect consistently decreased in importance as lambs became increasingly independent of the ewe. Estimates of permanent environmental effects due to dam were higher than those for maternal heritability in the present study. This could be an indication of the large influence of environment on milk production of the ewe. Total heritabilities for postnatal weights were low to moderate in magnitude, ranging from 0.04 to 0.29. Estimates of total heritability for 15-, 30- and 60-day weights were within the range of other estimates made at similar ages (Neser et al., 2000; Boujenane and Kansari, 2002). The low to moderate estimates indicate the existence of scope for some selection progress for these traits. The genetic covariance between additive direct and maternal effects did not appear in the most appropriate model for any of the traits under consideration. The true value of r am in this population is a matter of some concern, however, as indicated by the substantially lower values of h2t in models that included an additive direct–maternal covariance (i.e., Models 3 versus 4 and 5 versus 6). Selection to improve preweaning growth will be less effective if there is genetic antagonism between direct and maternal additive effects. However, accurate estimation of r am has proven difficult (Robinson, 1996). Repeatabilities of ewe effects on lamb weights at 15, 30, 45, 60 and 75 days were 0.21, 0.17, 0.18, 0.16, and
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0.15 respectively, under the best model. The repeatability of ewe performance was largest at 15 days and then slowly declined at more advanced ages. At a fixed age, estimates of t m were quite consistent across models. The various estimates of t m reflect the overall repeatability of ewe performance and as such are both relatively accurately determined in data sets of this size and, so long as maternal effects are included in the model, are relatively robust to the model actually fitted. In contrast, partition of the overall ewe effect into its components (h 2, m 2, c 2 and r am) is much more challenging, requiring repeated records on related ewes. Knowledge of t m is adequate to predict future ewe performance and the phenotypic response to culling, but prediction of genetic responses to selection requires accurate estimates of m 2, h 2 and r am. The current data appeared to potentially meet these design criteria (Table 2), but difficulties in separating effects of m 2 and c 2 and in estimation of r am were still encountered. Similar consistency of t m across models was reported by Notter and Hough (1997), who likewise observed some difficulty in achieving reliable partitioning of t m into its components. The estimate of repeatability of 30-day weight in the present study was lower than those of Notter (1998) in Suffolk and Polypay sheep. The t m value for 60-day weight in Muzaffarnagari sheep was similar to that found by Fossceco and Notter (1995) who reported that t m = 0.17 with m 2 = 0, c 2 = 0.11, and r am set to 0 in a composite breed. However, a lower estimate of t m at 60 days (0.05) was observed by Maria et al. (1993) in Romanov sheep while higher estimates were reported by Tosh and Kemp (1994), Al-Shorepy and Notter (1996), Notter and Hough (1997), and Notter (1998) in different breeds of sheep.
4. Conclusions The findings of the present study confirmed the importance of implementing the correct model for estimation of (co)variance components and genetic parameters for pre-weaning growth traits of Muzaffarnagari sheep. For example, ignoring maternal effects in the model leads to overestimation of direct and total heritability, and exclusion of a significant permanent environmental maternal effect result in overestimation of maternal heritability. Large nega-
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tive estimates of the additive–maternal genetic covariance were observed and would have a substantial negative impact on total predicted selection response but were not statistically significant. In these data, the maternal influence diminished as age increases, but modest genetic progress appears possible for all pre-weaning growth traits analyzed for the Muzaffarnagari sheep. Acknowledgements The authors thank Dr. Karin Meyer, Principal Biometrician, University of New England, Armidale, New South Wales, Australia, for granting kind permission to use the DFREML programme and Dr. (late) K.P. Pant and Dr. N.K. Bhattacharyya, former Directors of the Institute for inspiring us to work in this direction. Help extended by Director, CIRG, is also duly acknowledged for providing facilities for preparation of this manuscript. References Al-Shorepy, S.A., 2001. Estimates of genetic parameters for direct and maternal effects on birth weight of local sheep in United Arab Emirates. Small Rumin. Res. 39, 219 – 224. Al-Shorepy, S.A., Notter, D.R., 1996. Genetic variation and covariation for ewe reproduction, lamb growth, and lamb scrotal circumference in a fall-lambing sheep flock. J. Anim. Sci. 74, 1490 – 1498. Assan, N., Makuza, S., Mhlanga, F., Mabuku, O., 2002. Genetic evaluation and selection response of birth weight and weaning weight in indigenous Sabi sheep. Asian–Australas. J. Anim. Sci. 15, 1690 – 1694. Boujenane, I., Kansari, J., 2002. Estimates of (co)variances due to direct and maternal effects for body weights in Timahdite sheep. Anim. Sci. 74, 409 – 414. Bradford, G.E., 1972. The role of maternal effects in animal breeding. VII. Maternal effects in sheep. J. Anim. Sci. 35, 1324 – 1334. Bromley, C.M., Snowder, G.D., Van Vleck, L.D., 2000. Genetic parameters among weight, prolificacy and wool traits of Columbia, Polypay. Rambouillet and Targhee sheep. J. Anim. Sci. 78, 846 – 858. Burfening, P.J., Kress, D.D., 1993. Direct and maternal effects on birth and weaning weight in sheep. Small Rumin. Res. 10, 153 – 163. Cloete, S.W.P., Scholtz, A.J., Aucamp, B.B., 1998. Environmental effects, heritability estimates and genetic trends in a Western Cape Dohne Merino nucleus flock. S. Afr. J. Anim. Sci. 28, 185 – 195.
¨ zcan, M., Yilmaz, A., Ceyhan, A., 2004. Estimates of Ekiz, B., O genetic parameters for direct and maternal effects with six different models on birth and weaning weights of Turkish Merino lambs. Turk. J. Vet. Anim. Sci. 28, 383 – 389. El Fadili, M., Michaux, C., Detilleux, J., Leroy, P.L., 2000. Genetic parameters for growth traits of the Moroccan Timahdit breed of sheep. Small Rumin. Res. 37, 203 – 208. Falconer, D.S., 1989. Introduction to Quantitative Genetics, 3rd ed. Longman Scientific and Technical, UK, pp. 438. Fossceco, S.L., Notter, D.R., 1995. Heritabilites and genetic correlations of body weight, testis growth and ewe lamb reproductive traits in crossbred sheep. Anim. Sci. 60, 185 – 195. Hanrahan, J.P., 1976. Maternal effects and selection response with an application to sheep data. Anim. Prod. 22, 359 – 369. Harvey, W.R., 1990. User’s Guide for LSMLMW MIXMDL Mixed Model Least Squares and Maximum Likelihood Computer Program. PC-2 Version, Mimeograph, Ohio State University Press, Columbus, OH USA. Janssens, S., Geysen, D., Vandepitte, W., 2000. Genetic parameters for live weight in Belgain Texel sheep. 51st Annual meeting of the European Assoc. for Anim. Prod., August 21–24, 2000, Den Haag, Nederland, Comm. On Sheep and Goat Prod., Session 1.6, pp. 1 – 8. Larsgard, A.G., Olesen, I., 1998. Genetic parameters for direct and maternal effects on weights and ultrasonic muscle and fat depth of lambs. Livest. Prod. Sci. 55, 273 – 278. Ligda, Ch., Gabriilidis, G., Papadopoulos, Th., Georgoudis, A., 2000. Investigation of direct and maternal genetic effects on birth and weaning weight of Chios lambs. Livest. Prod. Sci. 67, 75 – 80. Mandal, A., Singh, L.B., Rout, P.K., 2000. The Muzaffarnagari sheep, a mutton breed in India. Anim. Genet. Resour. Inf., vol. 28. Food and Agricultural Organization, Rome, pp. 19 – 25. Mandal, A., Pant, K.P., Nandy, D.K., Rout, P.K., Roy, R., 2003. Genetic analysis of growth traits in Muzaffanagari sheep. Trop. Anim. Health Prod. 35, 271 – 284. Maria, G.A., Boldman, K.G., Van Vleck, L.D., 1993. Estimates of variances due to direct and maternal effects for growth traits of Romanov sheep. J. Anim. Sci. 71, 845 – 849. Matika, O., van Wyk, J.B., Erasmus, G.J., Baker, R.L., 2003. Genetic parameter estimates in Sabi sheep. Livest. Prod. Sci. 79, 17 – 28. Meyer, K., 1992. Variance components due to direct and maternal effects for growth traits of Australian beef cattle. Livest. Prod. Sci. 31, 179 – 204. Meyer, K., 1997. Estimates of genetic parameters for weaning weight of beef cattle accounting for direct–maternal environmental covariances. Livest. Prod. Sci. 52, 187 – 199. Meyer, K., 2000. DFREML programs to estimate variance components by restricted maximum likelihood using a derivative-free algorithm—User Notes. Nasholm, A., Danell, O., 1996. Genetic relationships of lamb weight, maternal ability and mature ewe weight in Swedish finewool sheep. J. Anim. Sci. 74, 329 – 339. Neser, F.W.C., Erasmus, G.J., van Wyk, J.B., 2000. Genetic studies on the South African Mutton Merino growth traits. S. Afr. J. Anim. Sci. 30, 172 – 177.
A. Mandal et al. / Livestock Science 99 (2006) 79–89 Neser, F.W.C., Erasmus, G.J., van Wyk, J.B., 2001. Genetic parameter estimates for pre-weaning weight traits in Dorper sheep. Small Rumin. Res. 40, 197 – 202. Notter, D.R., 1998. The U.S. National sheep improvement program: across flock genetic evaluations and new trait development. J. Anim. Sci. 76, 2324 – 2330. Notter, D.R., Hough, J.D., 1997. Genetic parameters for growth and fleece characteristics in Targhee sheep. J. Anim. Sci. 75, 1729 – 1737. Robison, O.W., 1981. The influence of maternal effects on the efficiency of selection. Livest. Prod. Sci. 8, 121 – 137. Robinson, D.L., 1996. Models which might explain negative correlations between direct and maternal genetic effects. Livest. Prod. Sci. 45, 111 – 122. Singh, R.N., 1995. Status Paper, Network Project on Sheep Improvement. Central Sheep and Wool Research Institute, Avikanagar (Rajasthan), India, p. 85. Snyman, M.A., Erasmus, G.J., van Wyk, J.B., 1995. Direct and maternal (co)variance components and heritability estimates for
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body weight at different ages and fleece traits in Afrino sheep. Livest. Prod. Sci. 44, 229 – 235. Tosh, J.J., Kemp, R.A., 1994. Estimation of variance components of lamb weights in three sheep populations. J. Anim. Sci. 72, 1184 – 1190. van Wyk, J.B., Erasmus, G.J., Konstantinov, K.V., 1993. Variance components and heritability estimates of early growth traits in the Elsenburg Dormer sheep stud. S. Afr. J. Anim. Sci. 23, 72 – 76. Willham, R.L., 1972. The role of maternal effects in Animal breeding: III. Biometrical aspects of maternal effects in animal. J. Anim. Sci. 35, 1288 – 1293. Willham, R.L., 1980. Problems in estimating maternal effects. Livest. Prod. Sci. 7, 405 – 418. Yazdi, M.H., Engstrom, G., Nasholm, A., Johansson, K., Jorjani, H., Liljedahl, L.E., 1997. Genetic parameters for lamb weight at different ages and wool production in Baluchi sheep. Anim. Sci. 65, 247 – 255.
Estimation of direct and maternal (co)variance components for pre-weaning growth traits in Muzaffarnagari sheep Ajoy Mandal a,*, F.W.C Neser b, P.K. Rout a, R. Roy a, D.R. Notter c a Genetics and Breeding Division, Central Institute for Research on Goats, Makhdoom, Mathura-281 122, Uttar Pradesh, India Department of Animal Wildlife and Grassland Sciences, Faculty of Natural and Agriculture Sciences, Bloemfontein, South Africa c Department of Animal and Poultry Sciences, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061-0306, USA b
Received 6 October 2004; received in revised form 7 April 2005; accepted 9 June 2005
Abstract Genetic parameters and (co)variance components were estimated for weight at birth and at 15, 30, 45, 60 and 75 days of age for a flock of Muzaffarnagari sheep maintained at the Central Institute for Research on Goats, Makhdoom, Mathura over a period of 27 years (1976–2002). Records on 5201 lambs descended from 1568 ewes and 170 rams were included in the analysis. Analyses were carried out by REML fitting an animal model and ignoring or including maternal genetic or permanent environmental effects. Six different animal models were fitted for all traits, and the best model was chosen after testing improvements in log-likelihood values. Direct heritability estimates were inflated substantially for all traits when maternal effects were ignored. Direct heritability estimates were 0.08 F 0.02 for birth weight and 0.02 F 0.02, 0.02 F 0.02, 0.27 F 0.08, 0.09 F 0.04, and 0.29 F 0.08 for weights at 15, 30, 45, 60, and 75 days, respectively. Maternal genetic effects contributed only 4 to 8% of the total phenotypic variance from birth to 30 days of age, and this effect diminished further with increasing age. Maternal heritability was low for pre-weaning growth traits and should have only a small effect on selection response. Estimates of the fraction of variance due to maternal permanent environmental effects were 0.09 F 0.02, 0.15 F 0.04, 0.12 F 0.03, 0.11 F 0.04, 0.14 F 0.02, and 0.08 F 0.04 for body weights at birth and at 15, 30, 45, 60, and 75 days, respectively. These results indicate that selecting for improved maternal and/or direct effects in Muzaffarnagari sheep would generate only slow genetic progress in early growth traits. D 2005 Elsevier B.V. All rights reserved. Keywords: Muzaffarnagari sheep; Growth traits; Maternal effects; Variance components; Heritability; Animal model
1. Introduction
* Corresponding author. Tel.: +91 565 2763280x293; fax: +91 565 2763246. E-mail address: [email protected] (A. Mandal). 0301-6226/$ - see front matter D 2005 Elsevier B.V. All rights reserved. doi:10.1016/j.livsci.2005.06.001
Early growth traits are important factors influencing profitability in any meat producing enterprise. The birth weight of an animal and its early growth rate, in particular until weaning, are determined not only by
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A. Mandal et al. / Livestock Science 99 (2006) 79–89
Table 1 A summary of published values for animal model additive direct (h 2), additive maternal (m 2) and permanent environmental (c 2) variance ratios, genetic correlation between direct and maternal effects (r am), total heritability (h2t), and repeatability of ewe performance (t m) for different growth traits in sheep Breed
Age (days)
h2
m2
c2
r ama
h2b t
t mb
References
Birth weight Dohne Merino Romanov Various
Birth Birth Birth
0.04 0.04 0.20–0.34
0.10 0.22 0.30–0.65
0.17 0.10 –
0.09 0.02 0.14–0.33
0.28 0.24 0.33–0.43
Afrino Various
Birth Birth
0.22 0.07–0.39
0.09 0.13–0.31
0.12 0.32–0.37
0.27 0.12–0.25
0.27 0.46–0.54
Cloete et al. (1998) Maria et al. (1993) Burfening and Kress (1993) Snyman et al. (1995) Tosh and Kemp (1994)
Various
Birth
0.16–0.22
0.18–0.24
0.09–0.11
0.24–0.34
0.32–0.37
Bromley et al. (2000)
Swedish finewool
Birth
0.07
0.30
–
– 0.99 0.18– ( 0.74) – 0.13– ( 0.56) 0.08– ( 0.20) 0.11
0.24
0.33
Baluchi Dormer Chios Dorper Local Sabi Sabi Timahdite
Birth Birth Birth Birth Birth Birth Birth Birth
0.14–0.20 0.16 0.18 0.11 0.42 0.27 0.25 0.05
0.07–0.12 0.43 0.19 0.10 0.33 0.24 0.12 0.05
0.04–0.12 – 0.17 0.12 0.00 – 0.08 0.00
0.15–0.18 0.35 0.44 0.04 0.60 1.00 – 0.55
0.24–0.27 0.24 0.16 0.21 0.17 0.77 0.31 0.03
0.22–0.26 0.38 0.32 0.25 0.21 0.56 0.26 0.04
Turkish Merino
Birth
0.11
0.11
0.20
0.48
0.08
0.28
Nasholm and Danell (1996) Yazdi et al. (1997) van Wyk et al. (1993) Ligda et al. (2000) Neser et al. (2001) Al-Shorepy (2001) Assan et al. (2002) Matika et al. (2003) Boujenane and Kansari (2002) Ekiz et al. (2004)
Postnatal weights Polypay Suffolk Targhee
30,60 30,60 60
0.07–0.08 0.14–0.16 0.01
0.07–0.17 0.04–0.05 0.10
0.15 0.11–0.19 0.09
– – –
0.11–0.15 0.16–0.18 0.06
0.24–0.34 0.19–0.27 0.19
Moroccan Timahdit
30,70
0.31–0.54
0.34–0.38
–
0.01–0.05
0.06–0.10
Timahdite
30,70
0.02–0.07
0.07–0.08
0.00
0.03–0.05
0.06
Belgian Texel
30,70
0.06–0.11
0.13–0.22
0.10–0.15
–
–
Sabi Dorset Composite
30,60 45,60
0.11–0.13 0.23–0.24
0.03–0.06 0.00–0.03
0.06–0.11 0.11–0.13
0.97– ( 1.0) 0.50– ( 0.51) 0.02– ( 0.06) – –
0.13–0.16 0.23–0.25
0.15–0.17 0.17–0.22
Swedish finewool
21
0.07
0.17
–
0.22
0.28
Dorset Composite
60
0.04
0.10
0.05
–
0.09
0.16
S.A. Mutton Merino
36,42,50
0.27–0.37
0.13–0.49
0.09–0.16
0.00–0.13
0.19–0.28
Dorper Romanov Chios Norwegian
42 40 42 47
0.28 0.34 0.17 0.20
0.10 0.25 0.07 0.14
0.11 0.00 0.08 0.08
0.76– ( 1.00) 0.11 0.98 0.26 0.04
0.17 0.03 0.17 0.28
0.26 0.05 0.16 0.28
a
0.37
Notter (1998) Notter (1998) Notter and Hough (1997) El Fadili et al. (2000) Boujenane and Kansari (2002) Janssens et al. (2000) Matika et al. (2003) Fossceco and Notter (1995) Nasholm and Danell (1996) Al-Shorepy and Notter (1996) Neser et al. (2000) Neser et al. (2001) Maria et al. (1993) Ligda et al. (2000) Larsgard and Olesen (1998)
An estimate of the additive–maternal genetic correlation (r am) is shown only when this parameter was included in the preferred model presented in the published work. In all other cases, r am was assumed to be zero in calculation of h2t and t m. b This parameter was calculated from published estimates of h 2 , m 2 , c 2 and r am in cases where h2t and/or t m were not presented in the cited work.
A. Mandal et al. / Livestock Science 99 (2006) 79–89
its own genetic potential but also by the maternal environment. These maternal effects reflect mainly the dam’s milk production and mothering ability, though effects of the uterine environment and extrachromosomal inheritance may also contribute. These maternal effects have three causes (Falconer, 1989): those due to the dam’s own genotype for milking and mothering ability (maternal additive effects); those consistent among all lambs produced by a dam but not of additive genetic origin (permanent environmental effects); and those specific to individual lambs (temporary environmental effects). The genotype of the dam therefore affects the phenotype of the young through a sample of half of her direct, additive genes for growth as well as through her genotype for maternal effects on growth. Bradford (1972) and Robison (1981) argued that traits recorded in early life are most affected by maternal ability. When some of these growth traits are included in the breeding goal, both the direct and maternal component should be taken into account to achieve optimum progress in a selection programme. Robison (1981) postulated that understanding of the relationship between direct and maternal effects would facilitate formulation of optimum breeding programmes and improvement of selection efficiency. The partitioning of additive direct, additive maternal, and permanent environmental maternal effects requires data on the performance of related (commonly half-sib) ewes in pedigreed matings across several lambing years. The availability of restricted maximum likelihood (REML) algorithms for fitting animal models has simplified the estimation of (co)variance components due to maternal effects (Meyer, 1997). However, meaningful partitioning of direct and maternal effects still requires an adequate underlying data structure. The possible existence of genetic correlations between direct and maternal additive effects introduces additional difficulties in fitting maternaleffects model (Hanrahan, 1976; Willham, 1980). Numerous studies have reported a negative correlation between additive direct and additive maternal effects on growth traits of various sheep breeds (Maria et al., 1993; Tosh and Kemp, 1994; Notter, 1998; Ligda et al., 2000). In many cases, these estimates have been too large (b 0.8) to be biologically reasonable. However, positive relationships have also been reported (Nasholm and Danell, 1996; Yazdi et al., 1997). Pub-
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lished estimates of maternal variances and heritabilites for pre-weaning growth traits in various breeds of sheep are summarized in Table 1. Estimates of (co)variance components and genetic parameters for growth traits by REML procedures have not been reported for Muzaffarnagari sheep. Most reported heritabilities of growth traits for this breed are based on ratios of variance components estimated mainly by paternal half-sib method, without consideration of maternal effects. Therefore, the present study was conducted to estimate variance and covariance components due to direct genetic effects, maternal genetic effects and maternal permanent environmental effects for different pre-weaning growth traits in Muzaffarnagari sheep.
2. Materials and methods 2.1. The breeding flock and management The Muzaffarnagari sheep, an important mutton breed of India, is known for its relatively rapid growth (Singh, 1995), high feed conversion efficiency (Mandal et al., 2000), and very good adaptability (Mandal et al., 2003) in the semi-arid region of the country. Data were collected from an experimental breeding flock of Muzaffarnagari sheep maintained at Central Institute for Research on Goats (CIRG), Makhdoom, Uttar Pradesh, India, under the All-India Coordinated Research Project on Sheep Breeding for Mutton Production for a period of 27 years (1976–2002). The location of the experimental flock as well as its natural habitat, description, and husbandry practices were described by Mandal et al. (2000). Briefly, the flock was composed of 250 breeding ewes reared under semi-intensive feeding. All animals grazed during the day (6 to 7 h) on natural pasture with supplementation depending upon the status and age category of the animals and were penned at night. Generally, controlled mating was practiced. Ewes in heat were mated with selected sires in the morning. Sheep were bred twice at each oestrus. Ewes were first exposed to rams at about 12 months of age. One breeding ram was allowed to mate with 20 to 25 ewes. There were two breeding seasons in May–June and October–November, with lambing in October–November and March–April. At birth each lamb was identified and date of birth, sex, type of birth
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and weight were recorded. Lambs were normally weaned at 3 months of age. 2.2. Data The data included 5201 lamb records from 1568 ewes sired by 170 rams and born in the periods 1976– 2002. Traits considered for analysis were weight at birth and at 15, 30, 45, 60 and 75 days (Table 2). Data on some postnatal weights were not collected over the entire 27 years, yielding dissimilar numbers of records for different traits; numbers of records analysed ranged from 1301 to 5201. Characteristics of the data structure are summarized in Table 2. 2.3. Analyses Variance and covariance components for pre-weaning growth traits were estimated by fitting a series of univariate animal models using a derivative-free REML algorithm (DFREML, Meyer, 2000). With DFREML the maximum of the log-likelihood value was found by the Simplex method. Convergence was considered to be reached when the variance of function values in the Simplex was less than 10 8. Analyses were restarted from converged values to check that a global rather than local maximum had been reached. When estimates did not change, convergence was assumed. Depending on the model, the log-likelihood function was maximized with respect to the direct and maternal additive variances, the permanent environmental variance of the dam and the genetic covariance between direct and maternal genetic effects. Standard errors of the parameters estimated as a part of the DFREML programme were calculated as described by Meyer (2000).
Mandal et al. (2003) found that the fixed effects that significantly influenced the weight of the lambs were year and season of birth, parity of dam, sex of lamb and type of birth. The weight of the dams at lambing was considered by including the linear regression of body weights of the lamb on weight of the ewe in the statistical model. In the present study, a preliminary least squares analysis of variance (Harvey, 1990) confirmed that fixed effects of birth year, season of birth, parity of dam, sex and birth status of lamb were all highly significant ( P b 0.01) and hence were included in the model. Single trait animal models were fitted for all traits. By ignoring or including maternal genetic or environmental effects, the following six models were fitted for each trait: y ¼ Xb þ Z1 a þ e
ð1Þ
y ¼ Xb þ Z1 a þ Z3 c þ e
ð2Þ
y ¼ Xb þ Z1 a þ Z2 m þ e with Covða; mÞ ¼ 0
ð3Þ
y ¼ Xb þ Z1 a þ Z2 m þ e with Covða; mÞ ¼ Aram ð4Þ y ¼ Xb þ Z1 a þ Z2 m þ Z3 c þ e with Covða; mÞ ¼ 0 ð5Þ y ¼ Xb þ Z1 a þ Z2 m þ Z3 c þ e with Covða; mÞ ¼ Aram
ð6Þ
where y is the n 1 vector of observations for each trait and X is the incidence matrix that relates data to
Table 2 Characteristics of the data structure for pre-weaning weights of Muzaffarnagari sheep
No. of records No. of animals No. of sires with progeny record No. of dams with progeny record Average weight (kg) Standard deviation (kg) CV (%) Years of records
Birth wt.
15-day wt.
30-day wt.
45-day wt.
60-day wt.
75-day wt.
5201 5456 170 1568 3.47 0.73 21.04 27
2705 3124 71 922 5.77 1.41 24.44 16
2988 3415 78 981 7.71 2.01 26.07 17
1392 1646 40 420 8.97 2.50 27.87 9
2886 3291 78 955 11.49 2.99 26.02 17
1301 1535 40 395 12.50 3.58 28.64 9
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the unknown vector of fixed effects b. Incidence matrices Z1 and Z2 relate unknown vectors of direct (a) and maternal (m) breeding values, respectively, to y. The incidence matrix Z3 relates an unknown additional random vector of permanent maternal environmental effects (c) to y. The unknown vector e contains random residuals due to environmental effects peculiar to individual records. A is the numerator relationship matrix, and r am is the covariance between direct and maternal additive genetic effects. It was assumed that V(a) = Ar a2, V(m) = Ar m2, V(c) = Ir c2, and V(e) = Ir e2 where I is an identity matrix and r a2, r m2, r c2 and r e2 are direct additive genetic, maternal additive genetic, maternal permanent environmental, and residual variances, respectively. Estimates of heritability (h 2), maternal heritability (m 2) and relative permanent maternal environmental (c 2) effects were calculated as ratios of estimates of r a2, r m2, and r c2, respectively, to the phenotypic variance (r p2). The direct–maternal correlation (r am) was computed as the ratio of the estimated direct–maternal covariance (r am) to the product of the square roots of estimates of r a2 and r m2. The repeatability for ewe performance was also calculated as t m = H h 2 + m 2 + c 2 + mr amh, and the heritability of the total genetic contribution to a maternally influenced trait was calculated as h2t = h 2 + 0.5 m 2 + 1.5 mr amh (Willham, 1972). To test the significance of random effects and identify the most appropriate model for each trait, likelihood ratios tests were conducted (Meyer, 1992). Likelihoods must increase when additional parameters are included in the model, and an effect was considered to have a significant influence when its inclusion caused a significant increase in log-likelihood, compared to a model in which it was ignored. Significance was tested at the level of P b 0.05 by comparing the difference in log-likelihoods to the value of a chisquare distribution with degrees of freedom equal to the difference in the number of (co)variance components fitted for the two models.
3. Results and discussion Phenotypic means, standard deviations and coefficients of variations for body weights at birth and at 15, 30, 45, 60 and 75 days are shown in Table 2. For these lambs, 50.9% were male and 49.1% were female.
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Single- and twin-born lambs represented 91.3% and 8.7% of the data, respectively. Coefficients of variation for pre-weaning weights ranged from 21.0% for birth weight to 28.6% for 75-day weight and were within the range of previously reported values for other sheep breeds (Ligda et al., 2000; Neser et al., 2001; Matika et al., 2003). 3.1. Pre-weaning growth traits Estimates of (co)variance components and genetic parameters for different pre-weaning growth traits obtained under the six different models are summarized in Tables 3 and 4. The most appropriate models based on likelihood ratio tests are presented in Table 5. 3.1.1. Birth weight Estimates of heritability for birth weight (Table 3) depended on the model used, ranging from 0.08 to 0.25. For this trait, ignoring maternal effects (Model 1) yielded substantially higher estimates of r a2 and h 2 than other models. Fitting a permanent environmental maternal effect (Model 2) markedly increased the loglikelihood value over that for Model 1 (Table 5), indicating a significant maternal effect accounting for 16% of the total variance in this trait while correspondingly reducing the estimate r a2. Fitting a maternal genetic (Model 3) rather than permanent environmental effect also resulted in an increase in log-likelihood over Model 1 but the resulting likelihood was very similar to that of Model 2. The estimate of maternal heritability from Model 3 was 17%, with a corresponding decrease in the estimate of direct heritability to 8%. In Model 4, the estimate of direct–maternal genetic covariance (r am) was negative ( 0.009), accounting for almost to 3% of r p2. The direct maternal genetic correlation (r am) was 0.23, but the difference in likelihoods between Models 3 and 4 was small. Fitting both genetic and environmental components of the dam effect (Model 5) resulted in a significantly better fit compared to other models (Table 5). Inclusion of both genetic and environmental components of the dam effect (m 2 + c 2) reduced the estimate of r m2. When permanent environmental effects due to dam were not fitted (Models 3 and 4), these tended to be dpicked upT in the estimate of r m2, inflating m 2 by 9%. In Model 6, the
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Table 3 Estimates of (co)variance components (kg2) and genetic parameters for birth weight and for 15- and 30-day weights of sheep
Table 4 Estimates of (co)variance components (kg2) and genetic parameters for 45-, 60- and 75-day weights of sheep
Traitsa Model 1 Model 2 Model 3 Model 4 Model 5 Model 6
Traitsa Model 1 Model 2 Model 3 Model 4 Model 5 Model 6
Birth weight r2a 0.076 r m2 – – r am r2c – r2e 0.224 0.300 r 2p h2 0.25 m2 – c am – – r am c2 – h 2t 0.25 tm –
0.030 – – 0.046 0.215 0.291 0.10 – – – 0.16 0.10 0.19
0.023 0.051 – – 0.225 0.298 0.08 0.17 – – – 0.16 0.19
0.026 0.058 0.009 – 0.223 0.298 0.09 0.19 0.03 0.23 – 0.14 0.18
0.024 0.022 – 0.028 0.218 0.292 0.08 0.08 – – 0.09 0.12 0.19
0.027 0.027 0.007 0.028 0.216 0.292 0.09 0.09 0.02 0.26 0.10 0.10 0.19
45-day r2a r m2 r am r2c r2e r 2p h2 m2 c am r am c2 h2t tm
weight 1.477 – – – 2.338 3.816 0.39 – – – – 0.39 –
1.009 – – 0.403 2.334 3.746 0.27 – – – 0.11 0.27 0.18
0.927 0.347 – – 2.472 3.746 0.25 0.09 – – – 0.29 0.15
1.250 0.977 0.719 – 2.264 3.772 0.33 0.26 0.19 0.65 – 0.17 0.15
1.007 0.000 – 0.403 2.335 3.745 0.27 0.00 – – 0.11 0.27 0.18
1.367 0.094 0.358 0.544 2.131 3.778 0.36 0.02 0.10 1.00 0.14 0.23 0.16
15-day r2a r m2 r am r2c r2e r 2p h2 m2 c am r am c2 h2t tm
weight 0.184 – – – 0.928 1.112 0.16 – – – – 0.16 –
0.029 – – 0.223 0.842 1.095 0.03 – – – 0.20 0.03 0.21
0.019 0.206 – – 0.883 1.108 0.02 0.19 – – – 0.11 0.20
0.047 0.288 0.086 – 0.860 1.109 0.04 0.26 0.08 0.74 – 0.06 0.19
0.022 0.063 – 0.166 0.845 1.096 0.02 0.06 – – 0.15 0.05 0.21
0.039 0.106 0.040 0.158 0.834 1.097 0.04 0.10 0.04 0.62 0.14 0.03 0.21
60-day r2 r m2 r am r2c r2e r 2p h2 m2 c am r am c2 h2t tm
weight 1.152 – – – 4.384 5.537 0.21 – – – – 0.21 –
0.501 – – 0.754 4.187 5.443 0.09 – – – 0.14 0.09 0.16
0.451 0.648 – – 4.393 5.491 0.08 0.12 – – – 0.14 0.14
0.978 1.637 1.070 – 4.027 5.572 0.17 0.29 0.19 0.85 – 0.03 0.14
0.499 0.000 – 0.755 4.189 5.443 0.09 0.00 – – 0.14 0.09 0.16
0.809 0.381 0.492 0.786 3.990 5.474 0.15 0.07 0.09 0.89 0.14 0.05 0.16
30-day r2a r m2 r am r2c r2e r 2p h2 m2 c am r am c2 h 2t tm
weight 0.326 – – – 2.081 2.408 0.14 – – – – 0.13 –
0.049 – – 0.382 1.945 2.377 0.02 – – – 0.16 0.02 0.17
0.038 0.353 – – 2.011 2.402 0.02 0.15 – – – 0.09 0.16
0.109 0.550 0.201 – 1.952 2.410 0.04 0.23 0.08 0.82 – 0.03 0.16
0.042 0.102 – 0.289 1.948 2.380 0.02 0.04 – – 0.12 0.04 0.17
0.088 0.213 0.105 0.273 1.915 2.384 0.04 0.09 0.04 0.77 0.11 0.02 0.16
75-day r2a r m2 r am r2c r2e r 2p h2 m2 c am r am c2 h2t tm
weight 3.004 – – – 5.138 8.143 0.37 – – – – 0.37 –
2.336 – – 0.656 5.059 8.051 0.29 – – – 0.08 0.29 0.15
2.272 0.529 – – 5.258 8.059 0.28 0.07 – – – 0.31 0.14
3.087 2.247 1.924 – 4.720 8.130 0.38 0.28 0.24 0.73 – 0.16 0.14
2.344 0.000 – 0.657 5.052 8.054 0.29 0.00 – – 0.08 0.29 0.15
3.228 0.361 1.080 1.065 4.550 8.126 0.40 0.04 0.13 1.00 0.13 0.22 0.14
a r2a = additive direct genetic variance; r m2 = additive maternal genetic variance; r am = direct–maternal additive genetic covariance; r2c = permanent environmental maternal variance; r2e =environmental variance; r 2p = phenotypic variance; h 2 = direct heritability; m 2 = maternal heritability; c am = r am / r 2p ; r am = direct–maternal genetic correlation; c 2 = r2c / r 2p; h 2t = h 2 + 0.5 m2 + 1.5 mr amh is the total heritability; t m = H h 2 + m 2 + c 2 + mr amh is the repeatability of ewe performance.
a
See Table 3 for abbreviations.
estimate of r am was also negative ( 0.007) but resulted in little change in likelihood compared to Model 5. The estimate for r am was about 0.02 with a corresponding estimate of r am of 0.26. The most appropriate model (Table 6) for birth weight
A. Mandal et al. / Livestock Science 99 (2006) 79–89
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Table 5 Log-likelihood valuesa obtained for each trait under the six different models with the best model in bold Traits
Model 1
Model 2
Model 3
Model 4
Model 5
Model 6
Birth wt. 15-day wt. 30-day wt. 45-day wt. 60-day wt. 75-day wt
72.3** 47.33** 34.05** 5.91* 24.04** 3.74y
10.24** 2.99y 2.40 0.82 1.47 1.01
11.11** 10.1** 7.49** 3.43y 10.48** 2.47
10.18** 7.56** 4.95* 2.19 6.80* 1.11
0.88 0.96 1.19 0.82 1.47 1.01
0 0 0 0 0 0
a As deviations from the model with the highest value. * P b 0.05. ** P b 0.01. y P b 0.10.
ings of Snyman et al. (1995) in Afrino sheep. The estimate of the permanent environmental maternal effect (c 2) for birth weight was in agreement with the findings of Maria et al. (1993) and Bromley et al. (2000). However, estimates reported by Tosh and Kemp (1994) in Hampshire, Polled Dorset, and Romanov sheep, by Snyman et al. (1995) in Afrino sheep, by Neser et al. (2001) in Dorper sheep, and by Ekiz et al. (2004) in Turkish Merino lambs were higher than our estimates. Meyer (1992) indicated that the relative values of h 2, m 2 and c 2 are influenced by the specific model. As shown by comparison of Models 2, 3, and 5, estimates of m 2 and c 2 are biased upwards if both are important but only one is included in the analytical model. The estimate of h 2 from Model 1 is likewise biased upward by failure to include significant maternal effects. The total heritability (Table 3) can be used to calculate the expected response to phenotypic selection for birth weight and was moderate in magnitude (0.12), indicating some scope for selection response in this trait. The total heritability for birth weight observed in this study was comparable to the findings of Burfening and Kress (1993) and Ekiz et al. (2004).
included both maternal genetic and permanent environmental effects but did not include the additive direct–maternal covariance. The estimate of direct heritability of birth weight in the present study (0.08, Model 5) was similar to the findings of Tosh and Kemp (1994), Nasholm and Danell (1996) and Ekiz et al. (2004) in other breeds of sheep (Table 1). A similar paternal half-sib estimate of heritability for birth weight (0.07) was reported by Mandal et al. (2003) in Muzaffarnagari sheep. However, higher heritability estimates of birth weight were reported for other breeds (Burfening and Kress, 1993; Snyman et al., 1995; Yazdi et al., 1997; Al-Shorepy, 2001; Assan et al., 2002; Matika et al., 2003). Lower heritability estimates were reported by Maria et al. (1993) in Romanov, Cloete et al. (1998) in Dohne Merino, and Boujenane and Kansari (2002) in Timahdite sheep. Low heritability estimates for birth weight in our study can perhaps be explained by a generally poor nutritional level of ewes creating a large environmental variation. The maternal heritability estimate for birth weight (0.08) from Model 5 was in accordance with find-
Table 6 Estimated parameters and their standard errors from the best model for each traita Traits
Model
h2
Birth wt. 15-day wt. 30-day wt. 45-day wt. 60-day wt. 75-day wt
5 5 5 2 2 2
0.08 0.02 0.02 0.27 0.09 0.29
a
(0.02) (0.02) (0.02) (0.08) (0.04) (0.08)
m2
c2
0.08 (0.02) 0.06 (0.03) 0.04 (0.03) – – –
0.09 0.15 0.12 0.11 0.14 0.08
(0.02) (0.04) (0.03) (0.04) (0.02) (0.04)
r2a
r m2
r2c
r2e
r 2p
0.024 0.022 0.042 1.009 0.501 2.336
0.022 0.063 0.102 – – –
0.028 0.166 0.289 0.403 0.754 0.656
0.218 0.845 1.948 2.334 4.187 5.059
0.292 1.096 2.380 3.746 5.443 8.051
Figures in parentheses are standard errors of the estimate. See Table 3 for abbreviations.
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Higher estimates of total heritability were obtained by, van Wyk et al. (1993), Snyman et al. (1995), Nasholm and Danell (1996), Neser et al. (2001) and Assan et al. (2002), in different breeds of sheep. Estimates reported by Maria et al. (1993) in Romanov sheep (0.02) and Boujenane and Kansari (2002) in Timahdite sheep (0.03) were lower than those observed in our study; both were associated with large negative estimates of r am. The estimate of repeatability of ewe effects on birth weight includes both total maternal and ewe transmitted additive effects and was 0.19 under the best model. Our maternal repeatability estimates for birth weight (Table 3) were lower than those reported in Table 1 except for that of Boujenane and Kansari (2002). Estimates of t m for birth weight in Table 3 were essentially the same for Models 2 through 6, suggesting that the repeatability of ewe performance was estimated consistently across the different maternal-effects models. 3.1.2. Postnatal weights Genetic parameters and (co)variance components for postnatal weights are shown in Tables 3 and 4. In Model 1, where maternal effects were ignored, heritability was biased upward for all postnatal weights. Introducing permanent environmental effects associated with the dam (Model 2) explained 20%, 16%, 11%, 14% and 8% of total phenotypic variance for weights at 15, 30, 45, 60 and 75 days, respectively, and the corresponding reduction in direct heritability was 81%, 86%, 31%, 57% and 22% in comparison with Model 1. Fitting a c 2 effect also increased the likelihood significantly over that for a simple animal model. Model 3, which included maternal genetic effects in place of permanent environmental maternal effects, also detected significant maternal effects contributing 19, 15, 9, 12 and 7% of total variation at 15, 30, 45, 60 and 75 days, respectively, and also yielded large reductions in estimates of h 2 relative to Model 1. Fitting a non-zero covariance (r am) along with a maternal genetic effect (Model 4) resulted in large negative direct–maternal covariance estimates for all weights but gave no significant improvement in likelihood compared to Model 3. Model 5 attempted to disentangle genetic and environmental components of the dam effect. Estimates of m 2 from Model 5 were much smaller than those obtained from Model 3 and
were null after 30 days. Allowing for a direct–maternal covariance in Model 6 yielded large negative estimates of r am, which ranged from 0.62 to 1.00 and accounted for 4 to 13% of total variance but did not produce a significant improvement in likelihood compared to Model 5. The model with only a permanent environmental effect due to the dam (Model 2) was clearly most suitable for 45-, 60-, and 75-day weights (Table 6). For 15- and 30day weights, Model 5 was not significantly superior to Model 2. However, the gradual decline in additive maternal variance from birth through 30 days revealed by Model 5 was considered to be the more biologically consistent model, even though a significant additive maternal effect on these weights could not be documented. The direct heritability for 30-day weight in the present study (0.02) was within the range of findings of Boujenane and Kansari (2002), and the estimate of maternal heritability for lamb 30-day weight observed in this study was similar to those reported by Notter (1998), Ligda et al. (2000) and Matika et al. (2003) in different breeds of sheep (Table 1). The estimates of direct heritability for 45-day weight in Muzaffarnagari lambs were close to the estimates of Fossceco and Notter (1995) and Neser et al. (2000, 2001). The direct heritability for 60-day weight was well within the range of the results of other investigators (Notter and Hough, 1997; Notter, 1998; Matika et al., 2003). Estimates of direct heritability were high for weights at 45 and 75 days, ranging from 0.27 to 0.29. However, these weights were not recorded in all years, so these estimates are not directly comparable to those for weights at 15, 30, and 60 days. Maternal heritabilities for pre-weaning weights decreased with age, which confirms findings of Tosh and Kemp (1994), Snyman et al. (1995), Nasholm and Danell (1996), Yazdi et al. (1997), and El Fadili et al. (2000) who also observed that maternal effects were substantial in young animals but diminished with age. The low direct additive effects on body weights at 15, 30, and 60 days suggest that only slow genetic progress may be obtained from selection under the prevailing management system. Notter and Hough (1997) and Matika et al. (2003) explained that low direct additive estimates for early body weights may be due to the fact that lambs did not receive creep feed and were raised in a generally poor nutri-
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tional environment, resulting in lambs not expressing their genetic potential. All the estimates of maternal heritability were relatively low, ranging from 0.04 to 0.08 in the present study. The low productivity and poor environment could partially explain low maternal effects in Muzaffarnagari sheep. At young ages, insufficient milk production by the ewe may also give rise to variation in environmental effects and result in low heritabilities. Contrary to some carry-over effects exhibited in other breeds, maternal effects were small and not significant after 45 days. The low maternal effect on pre-weaning growth indicates that the maternal effect would have less effect on selection response for these traits. The c 2 effect on pre-weaning weights accounted for 8 to 15% of the total phenotypic variance. These results are also in accord with those found in the literature (Table 1). The c 2 effect increased from birth to 60 days and thereafter declined. However, Tosh and Kemp (1994) observed that the permanent environmental effect consistently decreased in importance as lambs became increasingly independent of the ewe. Estimates of permanent environmental effects due to dam were higher than those for maternal heritability in the present study. This could be an indication of the large influence of environment on milk production of the ewe. Total heritabilities for postnatal weights were low to moderate in magnitude, ranging from 0.04 to 0.29. Estimates of total heritability for 15-, 30- and 60-day weights were within the range of other estimates made at similar ages (Neser et al., 2000; Boujenane and Kansari, 2002). The low to moderate estimates indicate the existence of scope for some selection progress for these traits. The genetic covariance between additive direct and maternal effects did not appear in the most appropriate model for any of the traits under consideration. The true value of r am in this population is a matter of some concern, however, as indicated by the substantially lower values of h2t in models that included an additive direct–maternal covariance (i.e., Models 3 versus 4 and 5 versus 6). Selection to improve preweaning growth will be less effective if there is genetic antagonism between direct and maternal additive effects. However, accurate estimation of r am has proven difficult (Robinson, 1996). Repeatabilities of ewe effects on lamb weights at 15, 30, 45, 60 and 75 days were 0.21, 0.17, 0.18, 0.16, and
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0.15 respectively, under the best model. The repeatability of ewe performance was largest at 15 days and then slowly declined at more advanced ages. At a fixed age, estimates of t m were quite consistent across models. The various estimates of t m reflect the overall repeatability of ewe performance and as such are both relatively accurately determined in data sets of this size and, so long as maternal effects are included in the model, are relatively robust to the model actually fitted. In contrast, partition of the overall ewe effect into its components (h 2, m 2, c 2 and r am) is much more challenging, requiring repeated records on related ewes. Knowledge of t m is adequate to predict future ewe performance and the phenotypic response to culling, but prediction of genetic responses to selection requires accurate estimates of m 2, h 2 and r am. The current data appeared to potentially meet these design criteria (Table 2), but difficulties in separating effects of m 2 and c 2 and in estimation of r am were still encountered. Similar consistency of t m across models was reported by Notter and Hough (1997), who likewise observed some difficulty in achieving reliable partitioning of t m into its components. The estimate of repeatability of 30-day weight in the present study was lower than those of Notter (1998) in Suffolk and Polypay sheep. The t m value for 60-day weight in Muzaffarnagari sheep was similar to that found by Fossceco and Notter (1995) who reported that t m = 0.17 with m 2 = 0, c 2 = 0.11, and r am set to 0 in a composite breed. However, a lower estimate of t m at 60 days (0.05) was observed by Maria et al. (1993) in Romanov sheep while higher estimates were reported by Tosh and Kemp (1994), Al-Shorepy and Notter (1996), Notter and Hough (1997), and Notter (1998) in different breeds of sheep.
4. Conclusions The findings of the present study confirmed the importance of implementing the correct model for estimation of (co)variance components and genetic parameters for pre-weaning growth traits of Muzaffarnagari sheep. For example, ignoring maternal effects in the model leads to overestimation of direct and total heritability, and exclusion of a significant permanent environmental maternal effect result in overestimation of maternal heritability. Large nega-
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tive estimates of the additive–maternal genetic covariance were observed and would have a substantial negative impact on total predicted selection response but were not statistically significant. In these data, the maternal influence diminished as age increases, but modest genetic progress appears possible for all pre-weaning growth traits analyzed for the Muzaffarnagari sheep. Acknowledgements The authors thank Dr. Karin Meyer, Principal Biometrician, University of New England, Armidale, New South Wales, Australia, for granting kind permission to use the DFREML programme and Dr. (late) K.P. Pant and Dr. N.K. Bhattacharyya, former Directors of the Institute for inspiring us to work in this direction. Help extended by Director, CIRG, is also duly acknowledged for providing facilities for preparation of this manuscript. References Al-Shorepy, S.A., 2001. Estimates of genetic parameters for direct and maternal effects on birth weight of local sheep in United Arab Emirates. Small Rumin. Res. 39, 219 – 224. Al-Shorepy, S.A., Notter, D.R., 1996. Genetic variation and covariation for ewe reproduction, lamb growth, and lamb scrotal circumference in a fall-lambing sheep flock. J. Anim. Sci. 74, 1490 – 1498. Assan, N., Makuza, S., Mhlanga, F., Mabuku, O., 2002. Genetic evaluation and selection response of birth weight and weaning weight in indigenous Sabi sheep. Asian–Australas. J. Anim. Sci. 15, 1690 – 1694. Boujenane, I., Kansari, J., 2002. Estimates of (co)variances due to direct and maternal effects for body weights in Timahdite sheep. Anim. Sci. 74, 409 – 414. Bradford, G.E., 1972. The role of maternal effects in animal breeding. VII. Maternal effects in sheep. J. Anim. Sci. 35, 1324 – 1334. Bromley, C.M., Snowder, G.D., Van Vleck, L.D., 2000. Genetic parameters among weight, prolificacy and wool traits of Columbia, Polypay. Rambouillet and Targhee sheep. J. Anim. Sci. 78, 846 – 858. Burfening, P.J., Kress, D.D., 1993. Direct and maternal effects on birth and weaning weight in sheep. Small Rumin. Res. 10, 153 – 163. Cloete, S.W.P., Scholtz, A.J., Aucamp, B.B., 1998. Environmental effects, heritability estimates and genetic trends in a Western Cape Dohne Merino nucleus flock. S. Afr. J. Anim. Sci. 28, 185 – 195.
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