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Research Article
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Genetic Parameters of Early Growth Traits in Mehraban Breed of Sheep |
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H. Mohammadi
and
M.A. Edriss
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ABSTRACT
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Genetic parameters were estimated for birth weight (BWT), weaning
weight (WWT) and pre-weaning Average Daily Gain (ADG) using Restricted
Maximum Likelihood (REML) procedures. Six different animal models were
fitted, differentiated by including or excluding maternal effects. The
direct heritability estimates (h2) ranged from 0.26 to 0.53,
0.18 to 0.32 and 0.15 to 0.33 for BWT, WWT and ADG, respectively. The
estimates were substantially higher when maternal effects, either genetic
or environmental, were ignored from the model. The maternal heritability
(m2) for BWT was the highest (0.25) when maternal genetic effect
alone was fitted in the basic model. It was decreased to 0.14 when the
maternal permanent environmental effect (c2) was employed.
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INTRODUCTION
Mehraban breed of sheep is originated in the western provinces of
Iran which are Hamadan, Zanjan and Kordestan. In Hamadan province, more
than 2 millions of sheep are raised which 40% of them are Mehraban. Estimates
of genetic parameters for early growth traits are importants in the design
of appropriate breeding programme aimed for maximizing genetic improvement.
In mammals, growth is influenced by the genes of the individual for growth,
by the environment provided by the dam and other environmental effects
(Albuquerque and Meyer, 2001). The main activities of sheep breeding are
estimation of genetic parameters for different traits, estimation of genetic
trends of flocks in stations, estimation of economic values and selection
criterias and improvement of carcass quality. Authors were not able to
find any structured breeding program, breeding objectives and/or selection
criteria, for Mehraban breed. The objectives of this study were to estimate
genetic parameters for birth weight, weaning weight and average daily
gain to weaning from 20 different Mehraban flocks as an indicator for
possible improvement through selection.
MATERIALS AND METHODS
Mehraban breed of sheep could be classified as a fat-tailed and
large frame size breed (Fig. 1). They are the most common
native breed of Iran adapted to harsh and rocky environments in the western
parts of the country including Hamadan, Zanjan and Kordestan provinces.
The study was conducted at Hamadan city, which is located at 48° 30` N latitude and an altitude of 1830 m above sea
level.
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Fig. 1: |
A picture of a male Mehraban sheep breed |
This breed reared primarily for meat production. They are mostly
light-brown color and head, face and throat are devoided of wool. They
are normally raised on pasture in spring and summer while they have access
to farm residual feeds during autumn. In winter time on cold and windy
days, they have access to dry hay and wheat straw as well as barley grain.
A total of 15555 performance records of 5043 animals were available from
20 different flocks from 1993 to 2004 in Hamadan province. The flocks
were under a recording system of newly established Mehraban Sheep Genetic
Evaluation Program. The maximum and minimum number of sheep in flocks
were ranging from 211 to 1089 sheep with an average of 570 sheep.
Table 1: |
Summary of data description in the present study |
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Most
of the flocks were practiced a kind of selection procedure which was consisted
of the heaviest rams and ewes as parents for the next generation. Ewes were
culled for old age or failure to conceive. Primary analysis of data which
was performed by SAS (1996) procedures is summarized in Table
1.
Statistical analysis: The General Linear Model (GLM) procedures of SAS (1996) were determined
whether any of the effects or interactions have an influence on the traits
(p<0.05). Those having an effect (p<0.05) were fitted in the subsequent
models to estimate the genetic parameters. The fitted fixed effects were
lambing year (1993 to 2004), sex (male, female), birth type (single, multiple),
age of dam and herd (20 flocks). Genetic parameters were estimated by
derivative-free REML (Meyer, 1998). The following models were used:
Where: y is the vector of observations, β is the vector of fixed
effects, a and m are the vectors of random direct and maternal additive
genetic effects, c is the vector of random maternal permanent environmental
effects and ε is the vector of residuals. X, Z1, Z2
and Z3 are the incidence matrices for β, a, m and c, respectively.
E (y) is Xβ, V (a), V (m), V © V (ε) are, δ2a,
δ2m, INd, δ2c and IN
δ2ε, respectively, where Nd is the number
of dams, N is the number of records, A is the numerator of the relationship
matrix among animals and I is an identity matrix. Heritability estimates
were obtained as ,
respectively, for direct and maternal genetic effects, where δ2p,
is the sum of all variance components estimated by the model of analysis.
RESULTS AND DISCUSSION
Estimates of (co) variance components, direct (h2) and
maternal (m2) heritabilities and values for the maternal permanent
environmental effects (c2) are shown in Table
2. For comparisons, published heritability estimates for BWT and WWT
are summarized in Table 3 and 4, respectively.
The log likelihood values obtained using six different models of analyses
are shown for each trait in Table 2. In this study, fitting
the maternal genetic effects as the only random effect in addition to
the direct genetic effect resulted in larger log likelihood ratios than
in the models that ignored the maternal genetic effects. The estimates
of h2 were also larger than both the m2 and c2
estimates for BWT, WWT and ADG. The h2 estimates for BWT ranged
from moderate to high (h2 = 0.26 to 0.53). In Model 1, where
maternal effects were ignored, the h2 estimates were higher
and most likely biased upwards. However, fitting either or both of the
maternal effects reduced δ2a and h2 estimates
from 0.18 to 0.09 and from 0.53 to 0.26, respectively. Likewise, failure
to account for maternal permanent environmental effects (c2)
resulted in a higher maternal genetic variances (δ2m)
and the corresponding m2 estimates. Thus, when the maternal
permanent environmental effect (c2) was ignored, the total
variance was attributed to the maternal genetic variance (δ2m),
probably resulting in an overestimation of m2. Thus, it is
an evident that the relative values of h2 and m2
were greatly influenced by the model used in the analysis. As in BWT,
h2 estimates for WWT decreased when either of the maternal
effects was fitted in the model. When the maternal permanent environmental
effects (c2) were fitted in the model, the variance due to
the maternal genetic effects (δ2m) and the corresponding
estimate of m2 decreased. As opposed to BWT, both the maternal
genetic and maternal permanent environmental effects were smaller than
the direct genetic effects under all models. For ADG, the estimates of
the direct and maternal genetic and maternal permanent environmental variances
followed the same pattern as for WWT and they were of approximately similar
magnitude.
Estimates of h2 for BWT obtained in the present study are
within the range of the animal model estimates, which varied from 0.07
(Tosh and Kemp, 1994) to 0.62 (Behzadi and Eftekhar-Shahroodi, 2002) (Table
3). Estimates of h2 for WWT obtained from the different
models were also within the ranges of published values. The h2
estimates for WWT in the literature ranged from 0.067 (Khalili et al.,
2002) to 0.59 (Behzadi and Eftekhar-Shahroodi, 2002) (Table
4). The estimates for ADG ranged from 0.03 (Seid Alian et al.,
2004) to 0.48 (Behzadi and Eftekhar-Shahroodi, 2002).
Table 2: |
Estimation of variance components for pre-weaning traits |
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δ2a Direct Additive var., δ2m =Maternal additive var., δ2c = Pennanent maternal environmental var., δam = Direct maternal genetic covar., δ2ε=Residual var., h2 (se) =Direct heritability, m2 (se) =Maternal heritability, c 2(se) = Ratio ofpennanent maternal environmental var. to total var., ram= Correlation of additive genetic effect and maternal genetic effect and log L =The highest value shows the best model for each trait |
In all three traits, estimates of h2 ranging from 0.15 to
0.35 were computed after maternal effects were taken into account. In
contrast, failure to take account of these effects gave estimates ranging
from 0.33 to 0.53. This indicates the extent to which estimates of h2
can be biased if maternal effects, either genetic or environmental, are
ignored using an animal model. The h2 of BWT in particular
was halved when either or both of the maternal effects were fitted compared
to the estimate obtained under Model 1 (h2 = 0.53). Several
corresponding results have been reported in the literature (Torshizi et
al., 1996; Ligda et al., 2000; Edriss et al., 2002).
Snyman et al. (1995) reported that ignoring maternal effects, if
these effects have a significant influence, leads to the over-estimation
of direct as well as total heritabilities. In the present study, the magnitude
of the h2 estimates obtained for BWT was greater than for both
the m2 and c2 estimates. In some other investigations,
c2 also tended to be higher than both the h2 and
m2 estimates (Table 3). In the present study,
the m2 estimates were, however, lower than the h2
estimates for both WWT and ADG. In general, the values for m2
in the present study varied from low to medium and were influenced by
the model fitted (Table 2). It accounted for about 0.25
of the phenotypic variance when the maternal permanent environmental effect
was ignored from the model, but was reduced to 0.14 when the latter was
fitted in the model. Snyman et al. (1995) also indicated that the
exclusion of the maternal permanent environmental effect, when it has
a significant influence, could cause estimates of m2 to be
biased upwards. The maternal permanent environmental effect (c2)
for BWT (Model 2) was lower than the direct genetic effect (h2),
which is in accordance with results of several other studies (Table
3). The c2 estimates were in agreement with some of the
estimates reported for WWT (Table 3). Both Snyman et
al. (1995) and Neser et al. (2001) reported an estimate of
0.12, while Edriss et al. (2002) found an estimate of 0.07 for
the permanent environmental effect of the dam in BWT. They ascribed this
value of the permanent environmental effect to the influence of the uterus
and the effect of multiple births. Relatively large c2 estimates
for WWT and ADG most likely reflected differences in rearing abilities
of dams that might be influenced by environmental fluctuations between
years or her birth/weaning status.
Generally, results showed a trend of increasing direct variance ratios
and maternal variance ratios from birth to weaning. The increasing h2
of lamb weight at weaning is most likely caused by an increased expression
of genes with direct effects on body development (Yazdi et al.,
1997). This also confirms the idea of Snyman et al. (1995), who
concluded that maternal effects in mammals diminish with age. In general,
results of this study showed that maternal, genetic and environmental,
factors are important for BWT and need to be considered in selection.
The correlation estimates between direct and maternal genetic effects
(ram) for BWT of Mehraban sheep are higher than most of the
previously reported estimates (Table 3). The estimate
of -0.43 reported by Torshizi et al. (1996) for BWT contradicts
the positive estimates found in this study. This study reported positive
correlation estimates for WWT. In the present study, the signs of these
estimates for WWT were in agreement with those reported by Duguma et al. (2002), Snyman et al. (1995) and Yazdi et al. (1997).
Table 3: |
Summary of reported direct (h2), maternal genetic
(m2), permanent environmental (c2) estimates and correlations
between direct and maternal genetic effects (ram) for
birth weight |
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h2 = Direct heritability, m2 =
Maternal heritability, c2 = Ratio of Permanent maternal
environmental var. to total var., ram = Correlation of
additive genetic effect and maternal genetic effect |
Table 4: |
Summary of reported direct (h2), maternal genetic
(m2), permanent environmental (c2) estimates and correlations
between direct and maternal genetic effects (ram) for
weaning weight |
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h2 = Direct heritability, m2 =
Maternal heritability, c2 = Ratio of Permanent maternal
environmental var. to total var., ram = Correlation of
additive genetic effect and maternal genetic effect |
However, the positive genetic correlations ranging
from 0.05 to 0.56 reported by these authors were higher than those reported
in this study, which were very small, ranging from 0.03 to 0.07. This suggest,
that selection for increased live weight of the lamb would not negatively affect
the maternal ability of the ewe. Cloete et al. (2001) also found no significant
correlation between the direct and the maternal effects in Merino flocks. The
estimates for ADG ranged from -0.01 to 0.04, slightly higher than the -0.17
reported range by Seid-Alian et al. (2004). Edriss et al. (2002) reported negative estimates ranging from -0.23 to -0.33 for ADG.
A negative estimate of the direct and maternal genetic covariance has
mostly been observed in field data while it has by and large been absent
in experimental data sets (Meyer, 1997), which has indicated that this
could have been attributed to factors like more uniform management and
lack of preferential treatment. Alternatively, it may also reflect better
identification of contemporary or management groups. Early growth traits
in sheep are mostly characterized by negative ram estimates
(Table 3 and 4). These estimates may
be considerable and could be affected by small data sets (El Fadili et
al., 2000; Al-Shorepy, 2001), the models fitted or poor pedigree structure
for estimation of both the direct and maternal heritabilities and the
genetic correlations between animal effects (Lee et al., 2000).
The antagonism between the effects of an individual`s genes for growth
and those of its dam for a maternal contribution may also be due to natural
selection for an intermediate optimum (Tosh and Kemp, 1994). Heritability
estimates of early growth traits from the different models ranged from
moderate to moderately high. It seems that, ignoring maternal effects,
both maternal genetic and environmental effects lead to an overestimation
of the h2 estimates. Likewise, exclusion of maternal permanent
environmental effects of the dam resulted in overestimation of m2
estimates, particularly for BWT. Thus, they need to be considered when
carrying out genetic evaluations of early growth traits, in addition to
the direct genetic effects. The absence of a genetic antagonism for WWT
obtained between the direct and the maternal genetic effects, suggests
that genetic improvement could be obtained in both direct and maternal
performances if selection is based on individual weaning weight performance.
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