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Estimates of genetic parameters for lifetime reproductive performance traits in Makuie ewes
Small Ruminant Research 139 (2016) 67–72
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Estimates of genetic parameters for lifetime reproductive performance traits in Makuie ewes Shoja Jafari a,∗ , Ghader Manafiazar b,c a b c
Young Researchers and Elite Club, Maku Branch, Islamic Azad University, Maku, Iran West Azerbaijan Agriculture and Natural Resource Research Center, Urmia, Iran Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, Canada
a r t i c l e
i n f o
Article history: Received 26 May 2015 Received in revised form 26 March 2016 Accepted 8 May 2016 Available online 11 May 2016 Keywords: Direct genetic Maternal effects Heritability Reproductive performance Makuie sheep
a b s t r a c t The objective of this study was to estimate genetic parameters for lifetime (over 2–5 years of age) reproductive performance traits in Makuie ewes. The data were extracted from Makuie Sheep Breeding and Raising Station dataset between 1989 and 2015. The studied traits were average of lifetime fertility, fecundity, survival, stay-ability, and total of lifetime female lambs born per ewe joined, female lambs weaned per ewe joined, weight of lambs born, weight of lambs weaned, and pregnancy days. Each trait was fitted by four different animal models, which were differentiated by including or excluding maternal effects. The Akaike information criterion was used to select the most appropriate model for each trait. In addition, series of bivariate animal models were implemented to estimate genetic and phenotypic correlations between traits. Estimates of direct heritability for traits were ranged from 0.00 to 0.15, which indicated that some traits (average fertility, average fecundity, and total weight of lambs born) had low additive genetic basis but others had no or very lower genetic basis. Maternal effects (both genetic and permanent environment) had very little or no effect on the studied traits. Genetic and phenotypic correlations between traits ranged from −0.92 to 0.99 and −0.01 to 0.97, respectively. The results indicated that fertility, fecundity, and total weight of lambs born could be improved by inclusion in the selection index due to their heritability estimation of greater than 0.12. For other traits genetic gain through conventional genetic selection method may be useless in Makuie sheep due to their low heritability estimates. However, these traits could be improved by providing better environment and management techniques. © 2016 Published by Elsevier B.V.
1. Introduction Reproduction efficiency is one of the most important factors affecting profitability of livestock industries. Therefore, improving reproductive traits could potentially reduce the operational costs (Notter, 2000). Performance of reproductive traits is the product of many other complex traits such as puberty, ovulation, estrus, fertilization, individual body fat deposition management, etc. (Snowder, 2008; Lee et al., 2009b; Gowane et al., 2014). These component traits have low to moderate genetics basis (Safari et al., 2005), and their genetic expression is highly affected by environmental factors such as climatic conditions and management techniques. It is concluded that knowledge on genetic parameters of economically important traits, particularly those related to reproduction, is necessary for genetic improvement programs (Safari et al., 2005).
∗ Corresponding author. E-mail address: [email protected] (S. Jafari). http://dx.doi.org/10.1016/j.smallrumres.2016.05.006 0921-4488/© 2016 Published by Elsevier B.V.
From seed stock producers’ perspective, it is also recommended to analysis the reproductive traits over a lifetime cycle because the reproductive traits are highly influenced by environmental factors over the years (Lee et al., 2009a) and may have different performance over the years compared with single year. Reproductive performance overlife time cycle can be investigated using two approaches considering their genetic basis and environment factors that the animals were exposed (Lee et al., 2009a): betweenewes within years that is called lifetime analysis, and within-ewe between years that is called single-year analysis. Lifetime analysis covers more variation in reproductive performance, and it could improve accuracy of estimations and ultimately improve the genetic gain compared with single-year analysis (Lee et al., 2009a). Lifetime reproductive traits can be considered as the average performance of the ewes at first three or four years of their reproductive life after maturity such as fertility, fecundity, survival and stay-ability, or it could be considered as accumulated traits over three or four years performance for the traits such as total female lambs born per ewe joined, total female lambs weaned per
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the ewe joined, total weight of lambs born, total weight of lambs weaned and total pregnancy days (Duguma et al., 2002; Van Wyk et al., 2003; Zishiri et al., 2013). Sheep breeds are categorized mainly into three groups of tailed, semi-tailed, and fat-tailed based on their tail shape. Fat-tail breeds account for 25% of global sheep population, mainly distributed in middle-east and some of African countries. Fat-tailed sheep are adapted to harsh environment, and when there is plenty of food, sheep accumulate fat in baggy deposit in hind parts on both sides of their tail. Depending on the breed and feast season, size of fat-tail could be up to 30 kg (Kashan et al., 2005). This fat is subsequently used for maintenance and support production performance during dry season/or in the winter. Fat-tail could be a good source also to support reproductive performance, but some believed that it could also prevent rams from having a successful mating with ewes, and consequently affecting reproductive outcomes. There are published results on genetic parameters of some lifetime traits in tailed sheep breeds. Although, it is believed that fat deposition could have substantial effect on reproductive performance and fat-tail could affect reproductive outcomes, to the best of our knowledge, there is no report on genetic parameters of lifetime reproductive traits in fat-tailed sheep breeds. Moreover, lifetime reproductive traits can also be influenced by maternal effects which are overlooked by most of the available reports, so study of these effects on the variation of lifetime reproductive traits deserve further investigation (Duguma et al., 2002; Van Wyk et al., 2003; Gowane et al., 2014). Ultimately, considering maternal and permanent environmental random effects in the mixed model may provide unbiased parameter estimations (Hoque et al., 2008). Number of reports have been published studying genetic basis of production traits in Makuie breed (Jafari et al., 2012; Jafari et al., 2014; Jafari and Hashemi, 2014a,b). However, based on literature review on lifetime reproductive performance, it is concluded that there is a lack of report, to the best of our knowledge, on genetic parameters of reproductive traits using fat-tail breed data and most of the available reports on tailed breed did not considered maternal and permanent environmental effects in the estimations. Therefore, objectives of the present study were to estimate genetic parameters for lifetime reproductive performance in Makuie sheep breed, a fat-tailed breed, applying different mixed models and to reveal any associations between the traits by using bivariate analysis.
Iran, and since then data on their production and reproduction traits have been recorded. The records were acquired from MSBRS database from 1989 to 2015. The details of herd management were presented by Jafari et al. (2014). In short, the base animals were purchased at 1989 from local producers. The minimum and maximum of lambing age were 18 and 72 months, respectively. The ewes were selected based on their growth, fleece records, and body measurement traits at their first breeding year. Besides, fertility, fitness, mothering ability, and the records of offspring played main role in the culling of the ewes. The ewes and rams were kept in the herd for a maximum of 6 parity and 4 breeding seasons, respectively. 2.2. Traits definition Nine lifetime reproductive traits (over 2–5 years) were considered in this study. They were: average fertility (FER) = number of successful lambing by the ewe in the first four lambing opportunities divided by 4. The FER trait was calculated for all ewes joined. Practically, most of the fat-tailed sheep breeds including Makuie breed have seasonal breeding, starting late summer (August) and ending early fall (October) within which all ewes are exposed to rams. If an ewe had successful lambing at all of her first four lambing season, her average fertility score was 1 (4 lambing/4 years) whereas an ewe with 3 successful lambings got the score of 0.75 (3 lambing/4 years) etc. Average fecundity (FEC) = number of lambs born alive per ewe lambing in the first four lambing opportunities divided by 4, and this trait was calculated for ewes lambing. Survival (SUR) = average number of lambs weaned in the first four lambing opportunities divided by the number of lambs born. The number of lamb born ranged from 4 to 8 (Lee et al., 2009b). Average stay-ability (STA) = number of lifetime breeding opportunities of the ewe joined divided by 4. The STA determines a ewe chance being in the herd depending on her other merits such as disease resistance along with her reproductive performance since producer may decide to keep a ewe in the herd though she did not have a successful lambing. The other traits were total female lambs born (TFB), and weaned per the ewe joined (TFW), total weight of lambs born (TWB), and weaned (TWW), and total number of days a ewe was pregnant (TPD). Both TFB and TFW determine an ewe’s ability to produce female replacements in the flock which are the main part of the herd. 2.3. Statistical analysis
2. Materials and methods 2.1. Animals and herd management A total of 6060 animals, progeny of 172 sires and 1600 dams was used in this study. Of the 6060 animals, 4288 were without records either because they did not meet imposed selection criteria or were males sold for market. Base animals were animals without identifiable parents bought from local producers at the time of establishing MSBRS station in 1986. Only 1215 ewes had useable records for this study. Since including relatives of individuals increases the power of genetic analyses, all animals (6060) were included in the pedigree analysis and genetic estimations. Makuie sheep is a native breed to West-Azerbaijan province of Iran, and their population is estimated at approximately 2.7 million (Abbasi and Ghafouri-Kesbi, 2011). This sheep is fat-tailed mediumsized breed with white color body and black rings around eyes, noses, and feet. Makui sheep breed has been well adapted to cold and highland environments. In order to improve production and reproduction performance of this breed, Makuie Sheep Breeding and Raising Station (MSBRS) was established in 1986 at Maku city,
The GLM procedure of SAS (2005) software was used to test significance (P < 0.05) of the fixed effects that required to be considered in the animal models. The fixed effects were birth year and birth type of the ewe, and her dam’s age with 20, 3, and 6 levels, respectively. Variance and covariance components were estimated based on animal model with restricted maximum likelihood (REML) approach using a derivate-free (DF) algorithm (Meyer, 1989) in WOMBAT package (Meyer 2007). Four different univariate models were fitted for each trait, and they differed in accounting for various random effects. The basic model (I) included individual additive genetic effect; in Models II, III, and IV the random effects of maternal permanent environment, maternal genetic, or both effects were added to the basic model (Meyer, 1992). The linear forms of the four fitted models were: Model I : Y ijklm = + YR i + BTj + ADk + ANl + eijklm Model II : Y ijklmn = + YR i + BTj + ADk + ANl + PEm + eijklmn Model III : Y ijklmn = + YR i + BTj + ADk + ANl + Mm + eijklmn
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Table 1 Descriptive statistics for lifetime reproductive performances of Makuie ewes. Trait
No. of records
Mean
SD
CV, %
Minimum
Maximum
Significance of tested fixed effects YBE
EBT
ADE
FER FEC SUR STA TFB TFW TWB TWW TPD
1215 759 759 1215 551 551 551 551 408
0.93 1.08 0.96 0.80 1.99 2.34 13.83 76.30 550.74
0.13 0.16 0.10 0.27 1.12 1.42 5.67 18.35 83.07
14.46 14.38 10.49 34.36 56.21 60.69 41.01 24.05 15.08
0.00 0.75 0.40 0.25 0.00 0.00 2.20 18.20 152.00
1.00 2.00 1.00 1.00 6.00 7.00 29.40 129.60 610.00
0.0001*** 0.0276* 0.1090NS 0.0903NS 0.5600NS 0.1485NS 0.1023NS 0.0094** 0.0001***
0.7865NS 0.0444* 0.2090NS 0.4629NS 0.3343NS 0.8293NS 0.8612NS 0.1072NS 0.8625NS
0.0910NS 0.6599NS 0.1917NS 0.6264NS 0.1145NS 0.0492* 0.7657NS 0.6431NS 0.2229NS
Fertility FER = number of successful lambing by the ewe in the first four lambing opportunities divided by 4; Fecundity FEC = number of lambs born alive in the first four lambing opportunities divided by 4; Survival (SUR) = average number of lambs weaned in the first four lambing opportunities divided by lamb born. Average stay-ability (STA) = number of lifetime breeding opportunities of the ewe joined divided by 4. TFW, total female lambs weaned per the ewe joined; TWB, total weight of lambs born; TWW, total weight of lambs weaned; TPD, total pregnant days; SD, standard deviation; CV, coefficient of variation; YBE, Year of birth of the ewe; EBT, birth type of the ewe; ADE, age of dam of the ewe.
Model IV : Y ijklmno = + YR i + BTj + ADk + ANl + PEm + Mn + eijklmno where Yijkl = an observation of an underlying trait belongs to its appropriate group; = overall mean of population; YRi = fixed effect of ith birth year of the ewe; BTj = fixed effect of birth type of the ewe; ADk = fixed effect of dam’s age of the ewe; ANl = random effect of individual additive genetic effect of animal m; PEm = random effect of permanent maternal environment; Mm = maternal genetic effect; eijkl = residual random effect of each observation. Akaike information criterion (AIC) (Akaike, 1974) was used to determine the most appropriate model by which the most appropriate model had lowest AIC value. AICi = −2 log Li + 2 pi ; where, log Li is the maximized log likelihood of model i at convergence, and pi is the number of parameters estimated from each model. Direct heritability (h2 ), maternal heritability (m2 ), and variance ratio due to permanent environmental component (c2 ) were estimated using selected appropriate models. Genetic and phenotypic correlations between traits were estimated using series of bivariate models implementing model I. 3. Results and discussion 3.1. Descriptive statistics Descriptive statistics of the traits are presented in Table 1. The mean for the traits were in the range reported by other researchers (Lee et al., 2009b; Gowane et al., 2014). Coefficient of variation is a criterion to show variation of a trait around mean (Salako, 2006). The results showed that FER, FEC and SUR had the least phenotypic variation, whereas the TFB, TFW, and TWB had the most variation among the traits in this study. The lower CV estimate for lifetime FEC was also reported by Lee et al. (2009b) in Merino ewes. 3.2. Fixed effects Fixed effects could be monitored from management point of view to control environment effects on the traits in addition to their importance in genetic analysis to adjust non-genetic factors. Fixed effects along with their significance levels for each trait are presented in Table 1. The effect of birth year of the ewe was significant (p < 0.0001) on FER, FEC, TWW and TPD. Differences in management system, feed availability, disease, and climatic condition may result in the phenotypic variation of the traits across years. Birth type of the ewe had significant effect on FEC (Table 1). The number of lambs born had an important role in the accelerating of FEC because it was a component in the FEC equation (lambs born/ewe
lambing). It was also showed that ewes that were born as multiples were significantly (p < 0.05) more suitable to produce more lambs over lifetime than their single born contemporaries (Duguma et al., 2002). The number of female lambs weaned by ewes with older dams (>4 parities) was significantly (p < 0.05) more (0.02 heads) than the ewes having younger dams. The significant effect of birth year of the ewe on the lifetime TWW was also reported by Duguma et al., 2002 in Merino ewes.
3.3. Heritability estimates Estimated heritabilities implementing different models along with models’ AIC values for the traits are presented in Table 2. The results of model selection based on AIC showed that the direct additive genetic was the main source of variation among the random effects. The estimates of direct heritability for lifetime reproduction traits ranged from zero for TFB to 0.15 for FEC. The direct heritability was estimated 0.12 for FER, and it may be improved by genetic selection, as one of the main drivers for profit in the sheep flock. In other breeds such as Merino sheep, the direct heritability estimates of FER reported in a range of 0.01–0.20 depending the flocks under study (Lee et al., 2009b), and in Dorper breed the lifetime h2 of FER was reported at 0.21 (Zishiri et al., 2013). Fecundity was defined as the ability of the ewe to produce more than one offspring. It had the highest direct heritability (0.15) among the studied traits of the present study. It could be more convenient to include FEC in the selection index, because it is easier to measure, and it had greater h2 estimation compared with FER. However, the estimate of h2 for FEC was lower than that of 0.19–0.26 reported by Lee et al., 2009b. In another study, the h2 has been reported at 0.07 for FEC by using annual records (Safari et al., 2007) for Australian Merino sheep. This discrepancy in the results could be due to the differences between populations, geographies, climates, management practices, and environments. Direct heritability for lifetime lamb survival was 0.04 (Table 2), and similar to the present study limited genetic variation also reported by other researchers (Van Wyk et al., 2003; Safari et al., 2007; Lee et al., 2009b). Lamb survival is a complex trait influenced by the lamb’s own ability to survive and by its dam’s rearing ability (Burfening, 1993; Van Wyk et al., 2003). There was no maternal genetic basis for SUR trait at the present study, similar to 0.02 reported by Gowane et al. (2014) in Malpura sheep. In general, the maternal effects diminish with age, and they are important in the phenotypic variation of the traits that are recorded from birth until weaning (Jafari et al., 2012; Zishiri et al., 2013).
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Table 2 Genetic parameter estimates of lifetime reproductive performance of Makuie ewes using four different models. Trait
MF
h2a
C2
h2m
AIC
FER
I II III IV I II III IV I II III IV I II III IV I II III IV I II III IV I II III IV I II III IV I II III IV
0.12 ± 0.03 0.10 ± 0.03 0.12 ± 0.04 0.10 ± 0.02 0.15 ± 0.04 0.15 ± 0.04 0.05 ± 0.01 0.05 ± 0.01 0.04 ± 0.02 0.04 ± 0.01 0.04 ± 0.02 0.04 ± 0.02 0.06 ± 0.01 0.06 ± 0.01 0.06 ± 0.01 0.06 ± 0.01 0.00 ± 0.02 0.00 ± 0.02 0.00 ± 0.02 0.00 ± 0.02 0.00 ± 0.04 0.00 ± 0.04 0.00 ± 0.04 0.00 ± 0.04 0.12 ± 0.01 0.07 ± 0.01 0.12 ± 0.01 0.07 ± 0.01 0.09 ± 0.03 0.08 ± 0.04 0.09 ± 0.04 0.08 ± 0.04 0.08 ± 0.05 0.08 ± 0.05 0.05 ± 0.02 0.05 ± 0.03
– 0.02 ± 0.04 – 0.02 ± 0.04 – 0.00 ± 0.02 – 0.00 ± 0.02 – 0.00 ± 0.01 – 0.00 ± 0.04 – 0.00 ± 0.01 – 0.00 ± 0.01 – 0.00 ± 0.04 – 0.00 ± 0.03 – 0.00 ± 0.04 – 0.00 ± 0.04 – 0.05 ± 0.05 – 0.05 ± 0.05 – 0.01 ± 0.03 – 0.01 ± 0.03 – 0.00 ± 0.01 – 0.00 ± 0.04
– – 0.00 ± 0.02 0.00 ± 0.02 – – 0.10 ± 0.03 0.10 ± 0.02 – – 0.00 ± 0.04 0.00 ± 0.03 – – 0.00 ± 0.01 0.00 ± 0.01 – – 0.00 ± 0.03 0.00 ± 0.03 – – 0.00 ± 0.04 0.00 ± 0.04 – – 0.00 ± 0.06 0.00 ± 0.06 – – 0.00 ± 0.03 0.00 ± 0.03 – – 0.03 ± 0.03 0.03 ± 0.02
−2139.37 −2137.39 −2137.39 −2135.39 −1353.54 −1351.54 −1351.54 −1349.54 −1809.58 −1807.64 −1807.64 −1805.64 −2018.72 −2016.87 −2016.87 −2014.87 988.4566 990.2812 990.2812 992.2812 1324.844 1326.696 1326.696 1328.696 5307.143 5309.143 5309.143 5311.143 5062.283 5064.283 5064.283 5066.283 3779.239 3780.799 3781.239 3782.799
FEC
SUR
STA
TFB
TFW
TWB
TWW
TPD
FER, fertility; FEC, fecundity; SUR, survival; STA, stay ability; TFB, total female lambs born per ewe joined; TFW, total female lambs weaned per the ewe joined; TWB, total weight of lambs born; TWW, total weight of lambs weaned; TPD, total pregnant days; MF, model fitted; h2 a, direct heritability; C2 , variance ratio due to permanent environmental component, h2 m, maternal heritability; AIC, Akaike information criterion.
In recent years, the evaluation of STA trait of the ewe in flock has been stressed by some researchers due to the great impact of this trait on profitability of the herd (Zishiri et al., 2013). Indeed, ewes that stay longer in the flock produce more lambs compared to ewes culled at younger ages (Borg, 2007; Zishiri et al., 2013). A direct heritability of 0.06 was estimated for STA, while maternal heritability and variance ratio due to permanent environmental component were estimated to be 0.00 (Table 2). In other breeds of sheep, the h2 for STA averaged 0.08 by using single year analysis (Zishiri et al., 2013). There were no direct genetic, maternal genetic, and maternal permanent environment bases for TFB and TFW traits (Table 2), which were in line with Gowane et al. (2014). This could satisfy the available females to replacement by selection if the traits had genetic basis (Gowane et al., 2014). In addition, it is reported that the rate at which the female animals replace themselves in the herd is an essential component in the breeding systems with natural selection (Gowane et al., 2014). The traits with this aspect could help breeder to get required number of progenies to have more efficient selection program. Ewe’s lifetime TWB and TWW had low to moderate h2 (0.09–0.12), and the genetic parameters for both traits were in line with several literature estimates (Van Wyk et al., 2003; Safari et al., 2005; Zishiri et al., 2013). Total weight of lambs weaned is a function of the growth rate of the lamb, fertility of the ewe, litter size, mothering ability, and lamb survival; therefore, these traits
also could be improved by improving total weight of lamb weaned (Olivier et al., 2001). The direct heritability was estimated at 0.08 for total pregnancy days. There was no report for lifetime pregnancy days in sheep; however, the h2 estimate of the present study was lower than that of several reports by using single year analysis (Osinowo et al., 1993; Babar, 2008). Vatankhah et al. (2000) using the single year analysis revealed that selection for a reduction in gestation length may indirectly increase prolificacy. 3.4. Correlation estimates Series of bivariate models were used to estimate correlations between traits, and the phenotypic and genetic correlations among the traits are presented in Table 3. Genetic and phenotypic correlations ranged from −0.92 to 0.99 and −0.01 to 0.97, respectively. The most favorable genetic correlations (above 0.90) were between SUR and TFW, TFW and TWW, STA and TPD, TFW and TPD. The most unfavorable genetic correlations were estimated between FEC and TFB, STA and TFB, FER and TFW, SUR and TWB, FEC and TPD, TFB and TPD. Genetic and phenotypic correlations of total weight of lamb born and weaned with the other reproduction traits were generally high. The results were in agreement with reports in Dormer sheep (Van Wyk et al., 2003). Genetic correlations between TFB per ewe and other studied traits were moderate to high (0.00–0.79) except for fecundity, stay-ability and total pregnancy days, which was −0.22, −0.33 and −0.92, respectively. The estimate of −0.92
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Table 3 Genetic (above diagonal) and phenotypic (below diagonal) correlations (±S.E) between lifetime reproductive performance traits in Makuie ewes. FER FER FEC SUR STA TFB TFW TWB TWW TPD
0.71 ± 0.13 0.01 ± 0.08 0.86 ± 0.10 0.10 ± 0.05 0.10 ± 0.05 0.72 ± 0.12 0.59 ± 0.21 0.72 ± 0.14
FEC
SUR
STA
TFB
TFW
TWB
TWW
TPD
0.09 ± 0.04
0.45 ± 0.15 0.39 ± 0.10
0.77 ± 0.21 0.56 ± 0.10 0.73 ± 0.15
0.00 ± 0.05 −0.22 ± 0.13 0.39 ± 0.05 −0.33 ± 0.02
−0.19 ± 0.10 0.33 ± 0.05 0.97 ± 0.02 0.41 ± 0.09 0.62 ± 0.20
0.15 ± 0.2 0.79 ± 0.08 −0.31 ± 0.07 0.86 ± 0.08 0.51 ± 0.15 0.87 ± 0.06
0.46 ± 0.11 0.78 ± 0.10 −0.03 ± 0.05 0.84 ± 0.10 0.79 ± 0.05 0.99 ± 0.01 0.88 ± 0.10
0.43 ± 0.08 −0.32 ± 0.10 0.59 ± 0.23 0.99 ± 0.01 −0.92 ± 0.04 0.92 ± 0.04 0.30 ± 0.15 0.36 ± 0.09
0.48 ± 0.13 0.84 ± 0.11 0.61 ± 0.15 0.61 ± 0.30 0.81 ± 0.14 0.61 ± 0.23 -0.01 ± 0.06
0.43 ± 0.18 0.33 ± 0.15 0.38 ± 0.10 0.06 ± 0.09 0.59 ± 0.06 0.03 ± 0.08
0.20 ± 0.11 0.50 ± 0.23 0.85 ± 0.10 0.80 ± 0.19 0.83 ± 0.10
0.97 ± 0.02 0.57 ± 0.30 0.55 ± 0.04 0.53 ± 0.16
0.58 ± 0.30 0.58 ± 0.29 0.54 ± 0.20
0.92 ± 0.04 0.27 ± 0.08
0.41 ± 0.22
FER, fertility; FEC, fecundity; SUR, survival; STA, stay ability; TFB, total female lambs born per ewe joined; TFW, total female lambs weaned per the ewe joined; TWB, total weight of lambs born; TWW, total weight of lambs weaned; TPD, total pregnant days.
between TFB and TPD showed that female lambs had a lower tendency to remain in the uterus compared with male lambs. This study attempted to determine the correlation between TFB and TPD where published data are currently unavailable. Thus, we cannot yet offer an extensive direct comparison of the results of this study with other work. Implementing FER in the genetic selection index could result in genetic progress of the other traits (except TFW) due to a moderate to high genetic correlation (Table 3). This suggested that more fertile ewes produced low number of female replacements. By considering the relationship between FER and other traits, the most favorable genetic and phenotypic correlation were estimated between FER and STA. This indicated that the ewes had more lambs, consequently, they had more opportunity to remain in the herd. Although Zishiri et al. (2013) reported a negligible relationship between FER and STA by using single year analysis. The genetic and phenotypic correlations between FEC, TWB and TWW were highly favorable (0.61–0.81) in this study. This suggested that the more lambs born by an ewe in her lifetime would result in a higher production of lambs due to the nature of fecundity calculation. These findings were in accordance with a literature reported by using single year analysis (Rosati et al., 2002). The favorable genetic and phenotypic correlation between survival and stay ability showed that the genetic progress of each of these traits is possible by including one of them in the selection program. However, these findings were contradictory to other findings on STA in the second parity of the Dorper ewes (Zishiri et al., 2013). High genetic and phenotypic correlations (above 0.50) were estimated between TFB, TFW, TWB and TWW (Table 3). This suggested that the achievement to a higher number of females for replacement can be applied by focusing on the genetic selection on TWB and TWW; however, there are no literature estimates to be compared with.
4. Conclusion Reproductive traits are substantial components to the profitability of sheep breeding, and inclusion of them in the selection program may increase net income. The results showed that traits such as fertility, fecundity, and total weight of lams born had greater than 0.12 direct heritability and potentially could be improved by genetic selection. However, further research on possibility and consequence of implementing these traits in the breeding program is encouraged. The results of the present study revealed that the upcoming selection strategies of the herd can be also based on indirect selection because of an overall acceptable relationship between investigated traits. The obtained results in the present study may be used as a criterion in other sheep breeds especially Iranian fat-tailed sheep breeding programs which have more similar breeding and raising condition to the Makuie sheep.
Acknowledgment The authors are grateful to the staff of the Makuie Sheep Breeding and Raising Station for accurate data collection and management practices. References Abbasi, M.A., Ghafouri-Kesbi, F., 2011. Genetic co (variance) components for body weight and body measurements in Makooei sheep. Asian Aust. J. Anim. Sci. 24, 739–743. Akaike, H., 1974. A new look at the statistical model identification. IEEE Trans. Autom. Control. 19, 716–723. Babar, M.E., 2008. Heritability estimate of ewe traits in Lohi sheep. Acta Agric. Scad. Anim. Sci. 58, 61–64. Borg, R.C., 2007. Phenotypic and genetic evaluation of fitness characteristics of sheep under range conditions. In: Ph.D. Thesis. Virginia Polytechnic Institute and State University. Burfening, P.J., 1993. Direct and maternal genetic effects on lamb survival. Small Rumin. Res. 11, 267–274. Duguma, G., Schoeman, S.J., Cloete, S.W.P., Jordaan, G.F., 2002. Genetic and environmental parameters for ewe productivity in Merinos. S. Afr. J. Anim. Sci. 32 (3), 154–159. Gowane, G.R., Prince, L.L.L., Paswan, C., Misra, S.S., Sharma, R.C., Naqvi, S.M.K., 2014. Genetic analysis of reproductive and fitness traits of malpura sheep in semi-arid tropics of India. Agric. Res. 3 (1), 75–82. Hoque, M.A., Kadowaki, H., Shibata, T., Suzuki, K., 2008. Maternal and direct genetic parameters for production traits and maternal correlations among production and feed efficiency traits in duroc pigs. Asian Aust. J. Anim. Sci. 21 (7), 961–966. Jafari, S., Hashemi, A., 2014a. Genetic analysis of fleece and post-weaning body weight traits in Makuie sheep. Genet. Mol. Res. 13 (1), 1079–1087. Jafari, S., Hashemi, A., 2014b. Estimation of genetic parameters for body measurements and their association with yearling live weight in the Makuie sheep breed. S. Afr. J. Anim. Sci. 44 (2), 140–147. Jafari, S., Hashemi, A., Manafiazer, G., Darvishzadeh, R., Razzagzadeh, S., Farhadian, M., 2012. Genetic analysis of growth traits in Iranian Makuie sheep breed. Ital. J. Anim. Sci. 11, 98–102. Jafari, S., Hashemi, A., Darvishzadeh, R., Manafiazar, G., 2014. Genetic parameters of live body weight, body measurements, greasy fleece weight, and reproduction traits in Makuie sheep breed. Span. J. Agric. Res. 12 (3), 653–663. Kashan, N.E.J., Manafiazar, G.H., Afzalzadeh, A., Salehi, A., 2005. Growth performance and carcass quality of fattening lambs from fat-tailed and tailed sheep breeds. Small Rumin. Res. 60, 267–271. Lee, G.J., Atkins, K.D., Sladek, M.A., 2009a. Heterogeneity of lifetime reproductive performance, its components and associations with wool production and live weight of Merino ewes. Anim. Prod. Sci. 49, 624–629. Lee, G.J., Atkins, K.D., Sladek, M.A., 2009b. Genetic parameters for lifetime reproductive performance of merino ewes. Proc. Assoc. Adv. Anim. Breed. Genet. 18, 382–385. 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., 1989. Restricted maximum likelihood to estimate variance components for animal models with several random effects using a derivative-free algorithm. Genet. Sel. Evol. 21, 317–340. Meyer, K., 2007. WOMBAT—a tool for mixed model analyses in quantitative genetics by REML. J. Zhejiang Univ. Sci. B 8, 815–821. Notter, D.R., 2000. Potential for hair sheep in the United States. J. Anim. Sci. 77, 1–8. Olivier, W.J., Snyman, M.A., Olivier, J.J., Van Wyk, J.B., Erasmus, G.J., 2001. Direct and correlated responses to selection for total weight of lamb weaned in Merino sheep. S. Afr. J. Anim. Sci. 31, 115–121. Osinowo, O.A., Abubakar, B.Y., Trimnell, A.R., 1993. Genetic and phenotypic relationships between gestation length: litter size and litter birth weight in Yankasa sheep. Anim. Reprod. Sci. 34, 111–118.
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Rosati, A., Mousa, E., Van Vleck, L.D., Young, L.D., 2002. Genetic parameters of reproductive traits in sheep. Small Rumin. Res. 43, 65–74. SAS, 2005. SAS/STAT software, vers. 6. SAS Inst. Inc., Cary, NC, USA. Safari, E., Fogarty, N.M., Gilmour, A.R., 2005. A review of genetic parameter estimates for wool, growth, meat and reproduction traits in sheep. Livest. Prod. Sci. 92, 271–289. Safari, E., Fogarty, N.M., Gilmour, A.R., Atkins, K.D., Mortimer, S.I., Swan, A.A., Brien, F.D., Greeff, J.C., Van der Werf, J.H.J., 2007. Across population genetic parameters for wool, growth, and reproduction traits in Australian Merino sheep. 1. Data structure and non-genetic effects. Aust. J. Agric. Res. 58 (2), 169–175. Salako, A.E., 2006. Principal component factor analysis of the morpho structure of immature Uda sheep. Int. J. Morphol. 24, 571–574.
Snowder, G.D., 2008. Genetic improvement of overall reproductive success in sheep; a review. Assoc. Lat. Am. Prod. Anim. 16, 32–40. Van Wyk, J.B., Fair, M.D., Cloete, S.W.P., 2003. Revised models and genetic parameter estimates for production and reproduction traits in the Elsenburg Dormer sheep stud. S. Afr. J. Anim. Sci. 33 (4), 213–222. Vatankhah, M., Edris, M.A., Salehi, A., 2000. Study on gestation length and its relationship with numbers: sex and birth weight of lambs in each delivery in Bakhtiari sheep. Pajouhesh-vaSazandegi 46, 122–125. Zishiri, O.T., Cloete, S.W.P., Olivier, J.J., Dzama, K., 2013. Genetic parameters for growth, reproduction and fitness traits in the South African Dorper sheep breed. Small Rumin. Res. 112, 39–48.
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Small Ruminant Research journal homepage: www.elsevier.com/locate/smallrumres
Estimates of genetic parameters for lifetime reproductive performance traits in Makuie ewes Shoja Jafari a,∗ , Ghader Manafiazar b,c a b c
Young Researchers and Elite Club, Maku Branch, Islamic Azad University, Maku, Iran West Azerbaijan Agriculture and Natural Resource Research Center, Urmia, Iran Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, Canada
a r t i c l e
i n f o
Article history: Received 26 May 2015 Received in revised form 26 March 2016 Accepted 8 May 2016 Available online 11 May 2016 Keywords: Direct genetic Maternal effects Heritability Reproductive performance Makuie sheep
a b s t r a c t The objective of this study was to estimate genetic parameters for lifetime (over 2–5 years of age) reproductive performance traits in Makuie ewes. The data were extracted from Makuie Sheep Breeding and Raising Station dataset between 1989 and 2015. The studied traits were average of lifetime fertility, fecundity, survival, stay-ability, and total of lifetime female lambs born per ewe joined, female lambs weaned per ewe joined, weight of lambs born, weight of lambs weaned, and pregnancy days. Each trait was fitted by four different animal models, which were differentiated by including or excluding maternal effects. The Akaike information criterion was used to select the most appropriate model for each trait. In addition, series of bivariate animal models were implemented to estimate genetic and phenotypic correlations between traits. Estimates of direct heritability for traits were ranged from 0.00 to 0.15, which indicated that some traits (average fertility, average fecundity, and total weight of lambs born) had low additive genetic basis but others had no or very lower genetic basis. Maternal effects (both genetic and permanent environment) had very little or no effect on the studied traits. Genetic and phenotypic correlations between traits ranged from −0.92 to 0.99 and −0.01 to 0.97, respectively. The results indicated that fertility, fecundity, and total weight of lambs born could be improved by inclusion in the selection index due to their heritability estimation of greater than 0.12. For other traits genetic gain through conventional genetic selection method may be useless in Makuie sheep due to their low heritability estimates. However, these traits could be improved by providing better environment and management techniques. © 2016 Published by Elsevier B.V.
1. Introduction Reproduction efficiency is one of the most important factors affecting profitability of livestock industries. Therefore, improving reproductive traits could potentially reduce the operational costs (Notter, 2000). Performance of reproductive traits is the product of many other complex traits such as puberty, ovulation, estrus, fertilization, individual body fat deposition management, etc. (Snowder, 2008; Lee et al., 2009b; Gowane et al., 2014). These component traits have low to moderate genetics basis (Safari et al., 2005), and their genetic expression is highly affected by environmental factors such as climatic conditions and management techniques. It is concluded that knowledge on genetic parameters of economically important traits, particularly those related to reproduction, is necessary for genetic improvement programs (Safari et al., 2005).
∗ Corresponding author. E-mail address: [email protected] (S. Jafari). http://dx.doi.org/10.1016/j.smallrumres.2016.05.006 0921-4488/© 2016 Published by Elsevier B.V.
From seed stock producers’ perspective, it is also recommended to analysis the reproductive traits over a lifetime cycle because the reproductive traits are highly influenced by environmental factors over the years (Lee et al., 2009a) and may have different performance over the years compared with single year. Reproductive performance overlife time cycle can be investigated using two approaches considering their genetic basis and environment factors that the animals were exposed (Lee et al., 2009a): betweenewes within years that is called lifetime analysis, and within-ewe between years that is called single-year analysis. Lifetime analysis covers more variation in reproductive performance, and it could improve accuracy of estimations and ultimately improve the genetic gain compared with single-year analysis (Lee et al., 2009a). Lifetime reproductive traits can be considered as the average performance of the ewes at first three or four years of their reproductive life after maturity such as fertility, fecundity, survival and stay-ability, or it could be considered as accumulated traits over three or four years performance for the traits such as total female lambs born per ewe joined, total female lambs weaned per
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the ewe joined, total weight of lambs born, total weight of lambs weaned and total pregnancy days (Duguma et al., 2002; Van Wyk et al., 2003; Zishiri et al., 2013). Sheep breeds are categorized mainly into three groups of tailed, semi-tailed, and fat-tailed based on their tail shape. Fat-tail breeds account for 25% of global sheep population, mainly distributed in middle-east and some of African countries. Fat-tailed sheep are adapted to harsh environment, and when there is plenty of food, sheep accumulate fat in baggy deposit in hind parts on both sides of their tail. Depending on the breed and feast season, size of fat-tail could be up to 30 kg (Kashan et al., 2005). This fat is subsequently used for maintenance and support production performance during dry season/or in the winter. Fat-tail could be a good source also to support reproductive performance, but some believed that it could also prevent rams from having a successful mating with ewes, and consequently affecting reproductive outcomes. There are published results on genetic parameters of some lifetime traits in tailed sheep breeds. Although, it is believed that fat deposition could have substantial effect on reproductive performance and fat-tail could affect reproductive outcomes, to the best of our knowledge, there is no report on genetic parameters of lifetime reproductive traits in fat-tailed sheep breeds. Moreover, lifetime reproductive traits can also be influenced by maternal effects which are overlooked by most of the available reports, so study of these effects on the variation of lifetime reproductive traits deserve further investigation (Duguma et al., 2002; Van Wyk et al., 2003; Gowane et al., 2014). Ultimately, considering maternal and permanent environmental random effects in the mixed model may provide unbiased parameter estimations (Hoque et al., 2008). Number of reports have been published studying genetic basis of production traits in Makuie breed (Jafari et al., 2012; Jafari et al., 2014; Jafari and Hashemi, 2014a,b). However, based on literature review on lifetime reproductive performance, it is concluded that there is a lack of report, to the best of our knowledge, on genetic parameters of reproductive traits using fat-tail breed data and most of the available reports on tailed breed did not considered maternal and permanent environmental effects in the estimations. Therefore, objectives of the present study were to estimate genetic parameters for lifetime reproductive performance in Makuie sheep breed, a fat-tailed breed, applying different mixed models and to reveal any associations between the traits by using bivariate analysis.
Iran, and since then data on their production and reproduction traits have been recorded. The records were acquired from MSBRS database from 1989 to 2015. The details of herd management were presented by Jafari et al. (2014). In short, the base animals were purchased at 1989 from local producers. The minimum and maximum of lambing age were 18 and 72 months, respectively. The ewes were selected based on their growth, fleece records, and body measurement traits at their first breeding year. Besides, fertility, fitness, mothering ability, and the records of offspring played main role in the culling of the ewes. The ewes and rams were kept in the herd for a maximum of 6 parity and 4 breeding seasons, respectively. 2.2. Traits definition Nine lifetime reproductive traits (over 2–5 years) were considered in this study. They were: average fertility (FER) = number of successful lambing by the ewe in the first four lambing opportunities divided by 4. The FER trait was calculated for all ewes joined. Practically, most of the fat-tailed sheep breeds including Makuie breed have seasonal breeding, starting late summer (August) and ending early fall (October) within which all ewes are exposed to rams. If an ewe had successful lambing at all of her first four lambing season, her average fertility score was 1 (4 lambing/4 years) whereas an ewe with 3 successful lambings got the score of 0.75 (3 lambing/4 years) etc. Average fecundity (FEC) = number of lambs born alive per ewe lambing in the first four lambing opportunities divided by 4, and this trait was calculated for ewes lambing. Survival (SUR) = average number of lambs weaned in the first four lambing opportunities divided by the number of lambs born. The number of lamb born ranged from 4 to 8 (Lee et al., 2009b). Average stay-ability (STA) = number of lifetime breeding opportunities of the ewe joined divided by 4. The STA determines a ewe chance being in the herd depending on her other merits such as disease resistance along with her reproductive performance since producer may decide to keep a ewe in the herd though she did not have a successful lambing. The other traits were total female lambs born (TFB), and weaned per the ewe joined (TFW), total weight of lambs born (TWB), and weaned (TWW), and total number of days a ewe was pregnant (TPD). Both TFB and TFW determine an ewe’s ability to produce female replacements in the flock which are the main part of the herd. 2.3. Statistical analysis
2. Materials and methods 2.1. Animals and herd management A total of 6060 animals, progeny of 172 sires and 1600 dams was used in this study. Of the 6060 animals, 4288 were without records either because they did not meet imposed selection criteria or were males sold for market. Base animals were animals without identifiable parents bought from local producers at the time of establishing MSBRS station in 1986. Only 1215 ewes had useable records for this study. Since including relatives of individuals increases the power of genetic analyses, all animals (6060) were included in the pedigree analysis and genetic estimations. Makuie sheep is a native breed to West-Azerbaijan province of Iran, and their population is estimated at approximately 2.7 million (Abbasi and Ghafouri-Kesbi, 2011). This sheep is fat-tailed mediumsized breed with white color body and black rings around eyes, noses, and feet. Makui sheep breed has been well adapted to cold and highland environments. In order to improve production and reproduction performance of this breed, Makuie Sheep Breeding and Raising Station (MSBRS) was established in 1986 at Maku city,
The GLM procedure of SAS (2005) software was used to test significance (P < 0.05) of the fixed effects that required to be considered in the animal models. The fixed effects were birth year and birth type of the ewe, and her dam’s age with 20, 3, and 6 levels, respectively. Variance and covariance components were estimated based on animal model with restricted maximum likelihood (REML) approach using a derivate-free (DF) algorithm (Meyer, 1989) in WOMBAT package (Meyer 2007). Four different univariate models were fitted for each trait, and they differed in accounting for various random effects. The basic model (I) included individual additive genetic effect; in Models II, III, and IV the random effects of maternal permanent environment, maternal genetic, or both effects were added to the basic model (Meyer, 1992). The linear forms of the four fitted models were: Model I : Y ijklm = + YR i + BTj + ADk + ANl + eijklm Model II : Y ijklmn = + YR i + BTj + ADk + ANl + PEm + eijklmn Model III : Y ijklmn = + YR i + BTj + ADk + ANl + Mm + eijklmn
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Table 1 Descriptive statistics for lifetime reproductive performances of Makuie ewes. Trait
No. of records
Mean
SD
CV, %
Minimum
Maximum
Significance of tested fixed effects YBE
EBT
ADE
FER FEC SUR STA TFB TFW TWB TWW TPD
1215 759 759 1215 551 551 551 551 408
0.93 1.08 0.96 0.80 1.99 2.34 13.83 76.30 550.74
0.13 0.16 0.10 0.27 1.12 1.42 5.67 18.35 83.07
14.46 14.38 10.49 34.36 56.21 60.69 41.01 24.05 15.08
0.00 0.75 0.40 0.25 0.00 0.00 2.20 18.20 152.00
1.00 2.00 1.00 1.00 6.00 7.00 29.40 129.60 610.00
0.0001*** 0.0276* 0.1090NS 0.0903NS 0.5600NS 0.1485NS 0.1023NS 0.0094** 0.0001***
0.7865NS 0.0444* 0.2090NS 0.4629NS 0.3343NS 0.8293NS 0.8612NS 0.1072NS 0.8625NS
0.0910NS 0.6599NS 0.1917NS 0.6264NS 0.1145NS 0.0492* 0.7657NS 0.6431NS 0.2229NS
Fertility FER = number of successful lambing by the ewe in the first four lambing opportunities divided by 4; Fecundity FEC = number of lambs born alive in the first four lambing opportunities divided by 4; Survival (SUR) = average number of lambs weaned in the first four lambing opportunities divided by lamb born. Average stay-ability (STA) = number of lifetime breeding opportunities of the ewe joined divided by 4. TFW, total female lambs weaned per the ewe joined; TWB, total weight of lambs born; TWW, total weight of lambs weaned; TPD, total pregnant days; SD, standard deviation; CV, coefficient of variation; YBE, Year of birth of the ewe; EBT, birth type of the ewe; ADE, age of dam of the ewe.
Model IV : Y ijklmno = + YR i + BTj + ADk + ANl + PEm + Mn + eijklmno where Yijkl = an observation of an underlying trait belongs to its appropriate group; = overall mean of population; YRi = fixed effect of ith birth year of the ewe; BTj = fixed effect of birth type of the ewe; ADk = fixed effect of dam’s age of the ewe; ANl = random effect of individual additive genetic effect of animal m; PEm = random effect of permanent maternal environment; Mm = maternal genetic effect; eijkl = residual random effect of each observation. Akaike information criterion (AIC) (Akaike, 1974) was used to determine the most appropriate model by which the most appropriate model had lowest AIC value. AICi = −2 log Li + 2 pi ; where, log Li is the maximized log likelihood of model i at convergence, and pi is the number of parameters estimated from each model. Direct heritability (h2 ), maternal heritability (m2 ), and variance ratio due to permanent environmental component (c2 ) were estimated using selected appropriate models. Genetic and phenotypic correlations between traits were estimated using series of bivariate models implementing model I. 3. Results and discussion 3.1. Descriptive statistics Descriptive statistics of the traits are presented in Table 1. The mean for the traits were in the range reported by other researchers (Lee et al., 2009b; Gowane et al., 2014). Coefficient of variation is a criterion to show variation of a trait around mean (Salako, 2006). The results showed that FER, FEC and SUR had the least phenotypic variation, whereas the TFB, TFW, and TWB had the most variation among the traits in this study. The lower CV estimate for lifetime FEC was also reported by Lee et al. (2009b) in Merino ewes. 3.2. Fixed effects Fixed effects could be monitored from management point of view to control environment effects on the traits in addition to their importance in genetic analysis to adjust non-genetic factors. Fixed effects along with their significance levels for each trait are presented in Table 1. The effect of birth year of the ewe was significant (p < 0.0001) on FER, FEC, TWW and TPD. Differences in management system, feed availability, disease, and climatic condition may result in the phenotypic variation of the traits across years. Birth type of the ewe had significant effect on FEC (Table 1). The number of lambs born had an important role in the accelerating of FEC because it was a component in the FEC equation (lambs born/ewe
lambing). It was also showed that ewes that were born as multiples were significantly (p < 0.05) more suitable to produce more lambs over lifetime than their single born contemporaries (Duguma et al., 2002). The number of female lambs weaned by ewes with older dams (>4 parities) was significantly (p < 0.05) more (0.02 heads) than the ewes having younger dams. The significant effect of birth year of the ewe on the lifetime TWW was also reported by Duguma et al., 2002 in Merino ewes.
3.3. Heritability estimates Estimated heritabilities implementing different models along with models’ AIC values for the traits are presented in Table 2. The results of model selection based on AIC showed that the direct additive genetic was the main source of variation among the random effects. The estimates of direct heritability for lifetime reproduction traits ranged from zero for TFB to 0.15 for FEC. The direct heritability was estimated 0.12 for FER, and it may be improved by genetic selection, as one of the main drivers for profit in the sheep flock. In other breeds such as Merino sheep, the direct heritability estimates of FER reported in a range of 0.01–0.20 depending the flocks under study (Lee et al., 2009b), and in Dorper breed the lifetime h2 of FER was reported at 0.21 (Zishiri et al., 2013). Fecundity was defined as the ability of the ewe to produce more than one offspring. It had the highest direct heritability (0.15) among the studied traits of the present study. It could be more convenient to include FEC in the selection index, because it is easier to measure, and it had greater h2 estimation compared with FER. However, the estimate of h2 for FEC was lower than that of 0.19–0.26 reported by Lee et al., 2009b. In another study, the h2 has been reported at 0.07 for FEC by using annual records (Safari et al., 2007) for Australian Merino sheep. This discrepancy in the results could be due to the differences between populations, geographies, climates, management practices, and environments. Direct heritability for lifetime lamb survival was 0.04 (Table 2), and similar to the present study limited genetic variation also reported by other researchers (Van Wyk et al., 2003; Safari et al., 2007; Lee et al., 2009b). Lamb survival is a complex trait influenced by the lamb’s own ability to survive and by its dam’s rearing ability (Burfening, 1993; Van Wyk et al., 2003). There was no maternal genetic basis for SUR trait at the present study, similar to 0.02 reported by Gowane et al. (2014) in Malpura sheep. In general, the maternal effects diminish with age, and they are important in the phenotypic variation of the traits that are recorded from birth until weaning (Jafari et al., 2012; Zishiri et al., 2013).
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Table 2 Genetic parameter estimates of lifetime reproductive performance of Makuie ewes using four different models. Trait
MF
h2a
C2
h2m
AIC
FER
I II III IV I II III IV I II III IV I II III IV I II III IV I II III IV I II III IV I II III IV I II III IV
0.12 ± 0.03 0.10 ± 0.03 0.12 ± 0.04 0.10 ± 0.02 0.15 ± 0.04 0.15 ± 0.04 0.05 ± 0.01 0.05 ± 0.01 0.04 ± 0.02 0.04 ± 0.01 0.04 ± 0.02 0.04 ± 0.02 0.06 ± 0.01 0.06 ± 0.01 0.06 ± 0.01 0.06 ± 0.01 0.00 ± 0.02 0.00 ± 0.02 0.00 ± 0.02 0.00 ± 0.02 0.00 ± 0.04 0.00 ± 0.04 0.00 ± 0.04 0.00 ± 0.04 0.12 ± 0.01 0.07 ± 0.01 0.12 ± 0.01 0.07 ± 0.01 0.09 ± 0.03 0.08 ± 0.04 0.09 ± 0.04 0.08 ± 0.04 0.08 ± 0.05 0.08 ± 0.05 0.05 ± 0.02 0.05 ± 0.03
– 0.02 ± 0.04 – 0.02 ± 0.04 – 0.00 ± 0.02 – 0.00 ± 0.02 – 0.00 ± 0.01 – 0.00 ± 0.04 – 0.00 ± 0.01 – 0.00 ± 0.01 – 0.00 ± 0.04 – 0.00 ± 0.03 – 0.00 ± 0.04 – 0.00 ± 0.04 – 0.05 ± 0.05 – 0.05 ± 0.05 – 0.01 ± 0.03 – 0.01 ± 0.03 – 0.00 ± 0.01 – 0.00 ± 0.04
– – 0.00 ± 0.02 0.00 ± 0.02 – – 0.10 ± 0.03 0.10 ± 0.02 – – 0.00 ± 0.04 0.00 ± 0.03 – – 0.00 ± 0.01 0.00 ± 0.01 – – 0.00 ± 0.03 0.00 ± 0.03 – – 0.00 ± 0.04 0.00 ± 0.04 – – 0.00 ± 0.06 0.00 ± 0.06 – – 0.00 ± 0.03 0.00 ± 0.03 – – 0.03 ± 0.03 0.03 ± 0.02
−2139.37 −2137.39 −2137.39 −2135.39 −1353.54 −1351.54 −1351.54 −1349.54 −1809.58 −1807.64 −1807.64 −1805.64 −2018.72 −2016.87 −2016.87 −2014.87 988.4566 990.2812 990.2812 992.2812 1324.844 1326.696 1326.696 1328.696 5307.143 5309.143 5309.143 5311.143 5062.283 5064.283 5064.283 5066.283 3779.239 3780.799 3781.239 3782.799
FEC
SUR
STA
TFB
TFW
TWB
TWW
TPD
FER, fertility; FEC, fecundity; SUR, survival; STA, stay ability; TFB, total female lambs born per ewe joined; TFW, total female lambs weaned per the ewe joined; TWB, total weight of lambs born; TWW, total weight of lambs weaned; TPD, total pregnant days; MF, model fitted; h2 a, direct heritability; C2 , variance ratio due to permanent environmental component, h2 m, maternal heritability; AIC, Akaike information criterion.
In recent years, the evaluation of STA trait of the ewe in flock has been stressed by some researchers due to the great impact of this trait on profitability of the herd (Zishiri et al., 2013). Indeed, ewes that stay longer in the flock produce more lambs compared to ewes culled at younger ages (Borg, 2007; Zishiri et al., 2013). A direct heritability of 0.06 was estimated for STA, while maternal heritability and variance ratio due to permanent environmental component were estimated to be 0.00 (Table 2). In other breeds of sheep, the h2 for STA averaged 0.08 by using single year analysis (Zishiri et al., 2013). There were no direct genetic, maternal genetic, and maternal permanent environment bases for TFB and TFW traits (Table 2), which were in line with Gowane et al. (2014). This could satisfy the available females to replacement by selection if the traits had genetic basis (Gowane et al., 2014). In addition, it is reported that the rate at which the female animals replace themselves in the herd is an essential component in the breeding systems with natural selection (Gowane et al., 2014). The traits with this aspect could help breeder to get required number of progenies to have more efficient selection program. Ewe’s lifetime TWB and TWW had low to moderate h2 (0.09–0.12), and the genetic parameters for both traits were in line with several literature estimates (Van Wyk et al., 2003; Safari et al., 2005; Zishiri et al., 2013). Total weight of lambs weaned is a function of the growth rate of the lamb, fertility of the ewe, litter size, mothering ability, and lamb survival; therefore, these traits
also could be improved by improving total weight of lamb weaned (Olivier et al., 2001). The direct heritability was estimated at 0.08 for total pregnancy days. There was no report for lifetime pregnancy days in sheep; however, the h2 estimate of the present study was lower than that of several reports by using single year analysis (Osinowo et al., 1993; Babar, 2008). Vatankhah et al. (2000) using the single year analysis revealed that selection for a reduction in gestation length may indirectly increase prolificacy. 3.4. Correlation estimates Series of bivariate models were used to estimate correlations between traits, and the phenotypic and genetic correlations among the traits are presented in Table 3. Genetic and phenotypic correlations ranged from −0.92 to 0.99 and −0.01 to 0.97, respectively. The most favorable genetic correlations (above 0.90) were between SUR and TFW, TFW and TWW, STA and TPD, TFW and TPD. The most unfavorable genetic correlations were estimated between FEC and TFB, STA and TFB, FER and TFW, SUR and TWB, FEC and TPD, TFB and TPD. Genetic and phenotypic correlations of total weight of lamb born and weaned with the other reproduction traits were generally high. The results were in agreement with reports in Dormer sheep (Van Wyk et al., 2003). Genetic correlations between TFB per ewe and other studied traits were moderate to high (0.00–0.79) except for fecundity, stay-ability and total pregnancy days, which was −0.22, −0.33 and −0.92, respectively. The estimate of −0.92
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Table 3 Genetic (above diagonal) and phenotypic (below diagonal) correlations (±S.E) between lifetime reproductive performance traits in Makuie ewes. FER FER FEC SUR STA TFB TFW TWB TWW TPD
0.71 ± 0.13 0.01 ± 0.08 0.86 ± 0.10 0.10 ± 0.05 0.10 ± 0.05 0.72 ± 0.12 0.59 ± 0.21 0.72 ± 0.14
FEC
SUR
STA
TFB
TFW
TWB
TWW
TPD
0.09 ± 0.04
0.45 ± 0.15 0.39 ± 0.10
0.77 ± 0.21 0.56 ± 0.10 0.73 ± 0.15
0.00 ± 0.05 −0.22 ± 0.13 0.39 ± 0.05 −0.33 ± 0.02
−0.19 ± 0.10 0.33 ± 0.05 0.97 ± 0.02 0.41 ± 0.09 0.62 ± 0.20
0.15 ± 0.2 0.79 ± 0.08 −0.31 ± 0.07 0.86 ± 0.08 0.51 ± 0.15 0.87 ± 0.06
0.46 ± 0.11 0.78 ± 0.10 −0.03 ± 0.05 0.84 ± 0.10 0.79 ± 0.05 0.99 ± 0.01 0.88 ± 0.10
0.43 ± 0.08 −0.32 ± 0.10 0.59 ± 0.23 0.99 ± 0.01 −0.92 ± 0.04 0.92 ± 0.04 0.30 ± 0.15 0.36 ± 0.09
0.48 ± 0.13 0.84 ± 0.11 0.61 ± 0.15 0.61 ± 0.30 0.81 ± 0.14 0.61 ± 0.23 -0.01 ± 0.06
0.43 ± 0.18 0.33 ± 0.15 0.38 ± 0.10 0.06 ± 0.09 0.59 ± 0.06 0.03 ± 0.08
0.20 ± 0.11 0.50 ± 0.23 0.85 ± 0.10 0.80 ± 0.19 0.83 ± 0.10
0.97 ± 0.02 0.57 ± 0.30 0.55 ± 0.04 0.53 ± 0.16
0.58 ± 0.30 0.58 ± 0.29 0.54 ± 0.20
0.92 ± 0.04 0.27 ± 0.08
0.41 ± 0.22
FER, fertility; FEC, fecundity; SUR, survival; STA, stay ability; TFB, total female lambs born per ewe joined; TFW, total female lambs weaned per the ewe joined; TWB, total weight of lambs born; TWW, total weight of lambs weaned; TPD, total pregnant days.
between TFB and TPD showed that female lambs had a lower tendency to remain in the uterus compared with male lambs. This study attempted to determine the correlation between TFB and TPD where published data are currently unavailable. Thus, we cannot yet offer an extensive direct comparison of the results of this study with other work. Implementing FER in the genetic selection index could result in genetic progress of the other traits (except TFW) due to a moderate to high genetic correlation (Table 3). This suggested that more fertile ewes produced low number of female replacements. By considering the relationship between FER and other traits, the most favorable genetic and phenotypic correlation were estimated between FER and STA. This indicated that the ewes had more lambs, consequently, they had more opportunity to remain in the herd. Although Zishiri et al. (2013) reported a negligible relationship between FER and STA by using single year analysis. The genetic and phenotypic correlations between FEC, TWB and TWW were highly favorable (0.61–0.81) in this study. This suggested that the more lambs born by an ewe in her lifetime would result in a higher production of lambs due to the nature of fecundity calculation. These findings were in accordance with a literature reported by using single year analysis (Rosati et al., 2002). The favorable genetic and phenotypic correlation between survival and stay ability showed that the genetic progress of each of these traits is possible by including one of them in the selection program. However, these findings were contradictory to other findings on STA in the second parity of the Dorper ewes (Zishiri et al., 2013). High genetic and phenotypic correlations (above 0.50) were estimated between TFB, TFW, TWB and TWW (Table 3). This suggested that the achievement to a higher number of females for replacement can be applied by focusing on the genetic selection on TWB and TWW; however, there are no literature estimates to be compared with.
4. Conclusion Reproductive traits are substantial components to the profitability of sheep breeding, and inclusion of them in the selection program may increase net income. The results showed that traits such as fertility, fecundity, and total weight of lams born had greater than 0.12 direct heritability and potentially could be improved by genetic selection. However, further research on possibility and consequence of implementing these traits in the breeding program is encouraged. The results of the present study revealed that the upcoming selection strategies of the herd can be also based on indirect selection because of an overall acceptable relationship between investigated traits. The obtained results in the present study may be used as a criterion in other sheep breeds especially Iranian fat-tailed sheep breeding programs which have more similar breeding and raising condition to the Makuie sheep.
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