Trop Anim Health Prod DOI 10.1007/s11250-014-0563-z
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Estimation of genetic parameters for preweaning growth traits of Brahman cattle in Southeastern Mexico Raciel J. Estrada-León & Juan G. Magaña-Monforte & José C. Segura-Correa
Accepted: 20 February 2014 # Springer Science+Business Media Dordrecht 2014
Abstract The genetic parameters for Brahman cattle under the tropical conditions of Mexico are scarce. Therefore, heritabilities, additive direct and maternal correlations, and genetic correlations for birth weight (BW) and 205 days adjusted weaning weight (WW205) were estimated in four Brahman cattle herds in Yucatan, Mexico. Parameters were estimated fitting a bivariate animal model, with 4,531 animals in the relationship matrix, of which 2,905 had BW and 2,264 had WW205. The number of sires and dams identified for both traits were 122 and 962, respectively. Direct heritability estimates for BW and WW205 were 0.41±0.09 and 0.43±0.09, and maternal heritabilities were 0.15±0.07 and 0.38±0.08, respectively. Genetic correlations between direct additive and maternal genetic effects for BW and WW205 were −0.41±0.22 and −0.50±0.15, respectively. The direct genetic, maternal, and phenotypic correlations between BW and WW205 were 0.77±0.09, 0.61±0.18, and 0.35, respectively. The moderate to high genetic parameter estimates suggest that genetic improvement by selection is possible for those traits. The maternal effects and their correlation with direct effects should be taken into account to reduce bias in genetic evaluations.
Keywords Heritability . Direct effects . Maternal effects . Tropics . Zebu R. J. Estrada-León Instituto Tecnológico Superior de Calkiní, Campeche, Mexico J. G. Magaña-Monforte : J. C. Segura-Correa (*) Facultad de Medicina Veterinaria y Zootecnia, Universidad Autónoma de Yucatán, Km. 15.5 carretera Mérida-Xmatkuil, A.P. 4-116, Itzimná, Mérida, Yucatán, México e-mail: [email protected] J. C. Segura-Correa e-mail: [email protected]
Introduction The tropical regions of Mexico are places of challenge to increase animal production through better management of animals and pastures, and of opportunity, because of land, water, and animal food availability at low cost (MagañaMonforte et al. 2006). In these tropical regions, beef cattle production is characterized by poor management and traditional production systems based on pastures of poor quality, scarce use of technology, and lack of genetic improvement programs (Rodríguez et al. 1998). Selection of the best animals as sires and dams is one option for improving animal production in the tropics. However, the beef production industry in the tropics of Mexico lacks a regional record-keeping program that provides data to estimate the genetic parameters to be used in genetic programs. In the tropical areas of Mexico, zebu-type cattle is the predominant one, of which the Brahman breed is the most popular. The main characteristics of the Brahman breed are its ability to withstand extreme climates (adaptability), rusticity, resistance to ectoparasites, and good response in crossbreeding programs (Razook et al. 1998). Because of the lack of farms that kept information on animal performance, few studies have been carried out to obtain genetic parameters for preweaning growth traits in zebu cattle in the tropics of Mexico. Genetic parameters are unique to the population in which they are estimated and they may change over time due to selection, environmental conditions, and management decisions. The estimation of direct genetic and maternal effects, under the tropical conditions of Mexico, is important to estimate the expected genetic values and response to selection. The objective of this study was to estimate the genetic parameters for some preweaning traits in Brahman cattle in Southeastern Mexico.
Trop Anim Health Prod
Materials and methods
Table 1 Structure and descriptive statistics of data from four Brahman cattle herds in Southeastern Mexico
Climate, management, and data structure
Concepts
BW
WW205
The data utilized in this study were obtained from the four farms located in the eastern region of Yucatan, Mexico. The climate of the region is tropical sub-humid with rain in summer (Aw0), with average monthly temperature of 26.6 °C and average annual rainfall of 1,105 mm. The farms had paddocks of Guinea grass (Panicum maximum) and small areas of Taiwan (Penicetum purpurium). Calves were weighed and identified by ear tattoo numbers within the first 3 days of birth, and they remained with their dams until approximately 8 months of age. In that period, calves were treated against internal and external parasites, as well as vaccinated against common diseases in the region. Also, the calves were supplemented (creep feeding) with commercial feed, with 14 % of crude protein and 2.8 Mcal ME/kg DM. Calves were weighed and identified with a hot iron number at weaning. Cows were kept in a rotational pasture system, and during the dry season they were supplemented with chopped grass, broiler litter, and molasses or with a commercial feed (11– 13 % crude protein and 2.2–2.4 Mcal ME/kg DM). Cows were managed under artificial insemination and natural mating during the whole year. Forty-five days after calving, heat detection was checked visually twice a day (morning and afternoon) and service was practiced 12 h after heat detection. Pregnancy diagnosis was practiced 60 days after the last service. Semen and bulls from Brahman sires from the USA were commonly used. Bulls were selected by appearance. The weaning weights were adjusted to 205 days (WW205) according to the Beef Improvement Federation (BIF 2002). Data with three standard deviations from the mean were deleted. Original identification of the animals was recorded using sequential numbers (according to birth date) in the pedigree file using RENUMERA program (Carolino and Gamma 2002). The connectedness of contemporary groups was evaluated using the AMC program (Roso and Schenkel 2006), from which the basis of related animals for each variable was derived (0.9 % of the data were deleted from the original data base because of the lack of connectability). The final pedigree file contained information on 4,531 calves, of which 2,905 had birth weights (BW) and 2,264 had weaning weights adjusted to 205 days. One hundred twenty-two sires and 962 dams with a least five calves/sire and a mean of three calves/dam were used. Thirteen sires (11.6 %) and 103 dams (10.7 %) had records as calves, and 47.9 % of dams had three or more calves with records. The complete structure of the data and some descriptive statistics are shown in Table 1, and the structure of the data by herd is shown in Table 2.
Mean ± SD (kg) Coefficient of variation (%) Males (%) No. of animals in A−1
33.10±4.65 14.06 54.2 4,531
204.05±37.71 18.48 50.8 4,531
No. of animals with records No. of paternal grandsires No. of maternal grandsires No. of sires No. of dams No. of dams with data as a calves Average number of records per dam Dams with one record (%) Dams with two records (%) Dams with ≥3 records (%)
2,902 9 42 122 962 103 3.02 30.9 21.2 47.9
2,261 6 36 112 761 82 2.98 29.9 22.9 47.2
A−1 inverse of the numerator relationship matrix, BW birth weight, WW205 weaning weight adjusted to 205 days
Statistical analyses The components of (co)variance and genetic parameters were obtained by restricted maximum likelihood (REML) method, fitting a bivariate animal model, using MTDFREML program (Boldman et al. 1995). The statistical model included the fixed effects of contemporary group (herd-year-season of birth); sex of the calf (female or male); parity number of the cow (1–5); and the random effects of direct additive (d), maternal additive (m), and the residual term (e), with covariance of d and m≠0. The environmental permanent effect was not included because the preliminary analysis did not show significance. The contemporary groups considered four herds, 9 years (1999–2007), and two seasons (rainy and dry) for a total of 72 fixed level effects, with at least three calves with data per level. In the matrix notation, the model was
y1 y2
¼
X1 0
0 X2
β1 Zd1 þ 0 β2
0 Zd2
Zm1 0
3 2 d1 7 0 6 6 d2 7 þ e1 Zm2 4 m1 5 e2 m2
where y1 = the vector of observations for BW; y2 = the vector of observations for WW205; β1 = the vector of solutions for the fixed effects for y1; β2 = the vector of solutions for the fixed effects for y2; d1 = vector of the direct additive genetic effects for y1; d2 = vector of the direct additive genetic effects for y2; m1 = vector of the maternal additive genetic effects for y1; m2 = vector of the maternal additive genetic effects for y2; e1 = vector of the residual effects for y1; e2 = vector of the
Trop Anim Health Prod Table 2 Structure of data by Brahman cattle herds in Southeastern Mexico Concepts
Herd 1
Herd 2
Herd 3
Herd 4
Total
No. of animals with records for BW No. of animals with records for WW No. of sires No. of dams No. of sires with data in different herds for BW and WW205 No. of dams with data in different herds for BW and WW205
682 623 61 214
1,662 1,230 67 539
229 160 25 112
329 248 28 120
2,902 2,261 181 962 59 24
BW birth weight, WW205 weaning weight adjusted to 205 days
residual effects for y2; and X1, X2, Zd1, Zd2, Zm1, Zm2 = incidence matrices.
The assumptions related to distributions of y, a, m, and e were as follows:
3 2 3 2 y Xβ ZGZ 0 þ WMW 0 þ ðZΦW 0 þ WΦZ 0 Þ þ R 6d 7 60 7 6 GZ 0 7 6 7 6 E6 4 m 5 ¼ 4 0 5; Var ¼ 4 MW 0 e 0 R 2
where G=A⊗G0, M=A⊗M0, Φ=A⊗Φ0 y R=I⊗R0; A is the numerator relationship matrix of an order equal to the number of individuals, G0, M0, Φ0 have formed a 4×4 matrix that include direct (σ2d), maternal (σ2m), and covariance between direct and maternal genetic effects (σdm), R is a 2×2 matrix with (co)variance error σ2e ; and I is the identity matrix. The convergent criterion used was the variance of the values in the likelihood function (−2log L), considered to be smaller than 10−9. The direct (h2d), maternal (h2m), and total (h2T) heritabilities were estimated as h2d ¼
σ2d σ2p
h2m ¼
σ2m σ2p
h2T ¼
σ2d þ 1:5σdm þ 0:5σ2m σ2p
where the phenotypic variance (σ 2p ) of the trait was σ2p =σ2d +σ2m +σdm +σ2e .
Results The means for BW and WW205 were 33.1±4.65 kg and 204.0 ± 37.7 kg, respectively (Table 1). The variance
ZG G Φ 0
WM Φ M 0
3 R 07 7 05 R
components and genetic parameter estimates for the preweaning growth traits are shown in Table 3. Genetic covariances between direct and maternal genetic effects were negative for both traits (Table 3). The genetic correlations between direct and maternal effects were moderately high and negative (−0.41 and −0.50, for BW and WW205, respectively). The h2T estimates for BW and WW205 were moderate (0.33 and 0.30, respectively). Also, direct genetic and maternal correlations between BW and WW205 (Table 4) were high (0.77 and 0.61, respectively), and phenotypic correlations were moderate (0.35).
Discussion The mean BW found in this study was slightly greater than the means reported for Brahman cattle in the other tropical regions of Mexico, Venezuela, and South Africa (Plasse et al. 2004; Pico et al. 2004; Parra-Bracamonte et al. 2007). Also, the mean WW205 was within the range of values reported in the places just mentioned (Pico et al. 2004; Plasse et al. 2004; Parra-Bracamonte et al. 2007). Although the cited studies were carried under tropical conditions, differences between estimates may be due to the management and genetic background of the populations studied. The data structure, in the present study, allows the partition of the maternal and direct additive genetic effects and agrees with the minimal recommendations of 10 % of dams with record as calves and more than 1.5 calves with records. The
Trop Anim Health Prod Table 3 Estimates of variance components and genetic parameters for birth weight (BW) and weaning weight adjusted to 205 days (WW205) Traits
Components of (co)variance σ2d σ2m 7.10 2.58 320.87 281.69 Genetic parameters h2d h2m
BW WW205
BW WW205
0.41±0.087 0.43±0.086
0.15±0.071 0.38±0.079
σdm −1.747 −151.436
σ2e 9.49 290.82
σ2p 17.43 741.96
rdm
e2
h2T
−0.41±0.216 −0.50±0.147
0.54±0.063 0.39±0.059
0.33 0.30
σ2d direct additive genetic variance, σ2m maternal additive genetic variance, σdm covariance between direct additive genetic and maternal genetic variances, σ2e residual variance, σ2p phenotypic variance, h2d direct heritability, h2m maternal heritability, rdm direct-maternal genetic correlation, e2 proportion of the phenotypic variance due to the residual variance, h2T total heritability
proportion of dams as calves with known phenotypic information and the number of progeny per dam influenced direct and maternal heritabilities, as well as the partition of maternal genetic and permanent environmental effects, which is important for the genetic evaluation of preweaning growth traits (Maniatis and Pollot 2003; Boligon et al. 2012). Similar data structures were used to estimate direct and maternal genetic effects for weaning weight in Brazilian Caracu (Cinachi et al. 2006). The direct additive genetic variances were larger than the maternal genetic variances for the two traits. Direct heritabilities (h2d) for BW and WW205 were moderate (0.41 and 0.43, respectively). The moderate direct additive heritability values indicate that the genetic improvement of preweaning growth traits can be achieved through selection based on those traits. The h2d for BW (0.41), estimated in this study, is within the range of those reported for Brahman cattle (0.28, 0.32, 0.42, 0.44) in South Africa (Pico et al. 2004), Mexico (ParraBracamonte et al. 2007), Venezuela (Plasse et al. 2004), and Philippines (Salces et al. 2002) but greater than 0.23, 0.27, and 0.31 reported for Guzerat (Martínez-González et al. 2009), Indubrazil (Ríos-Utrera et al. 2013) and Nellore cattle (Medina-Zaldivar et al. 2005) in Mexico, and for the average (0.33) reported for different Bos indicus beef breeds by Lira et al. (2008), in a review of genetic parameters. The differences among values could be explained by the differences in
Table 4 Estimates of covariance components (above the diagonal) and genetic correlations (below the diagonal) for birth weight (BW) and weaning weight adjusted to 205 days (WW205)
BW σ2d WW205 σ2d BW σ2m WW205 σ2m
BW σ2d
WW205 σ2d
BW σ2m
WW205 σ2m
1 0.77±0.087 −0.41±0.216 −0.26±0.209
36.521 1 −0.24±0.255 −0.50±0.147
−1.747 −6.886 1 0.61±0.179
−11.796 −151.436 16.463 1
σ2d direct additive genetic variance, σ2m maternal additive genetic variance, σ2p phenotypic variance
breeds, the population structure of the data, connectivity, and statistical models used. The h2d for WW205 (0.43) was greater than the values reported for Brahman cattle (0.22, 0.14, 0.13) in Mexico (ParraBracamonte et al. 2007), other countries (Salces et al. 2002; Pico et al. 2004; Plasse et al. 2004), and for the average (0.26) reported for the same breed by Ríos-Utrera (2008), in a review of genetic parameter estimates, as well as those reported for Nellore and Indubrazil cattle in Mexico (Martínez-González et al. 2010; Ríos-Utrera et al. 2013), but lower than the values reported by Martínez-González et al. (2009) for Guzerat cattle (0.53). The h2m estimate (0.15) for BW is higher than the values reported for Brahman cattle (0.11) in South Africa (Pico et al. 2004) and for Indubrazil cattle (0.10) in Mexico (Ríos-Utrera et al. 2013) but similar to the values reported for Brahman and Nellore cattle by Parra-Bracamonte et al. (2007) and Martínez-González et al. (2010) in Mexico (0.16 and 0.17, respectively). In contrast, lower estimates were reported for Brahman (0.10) and Nellore (0.09) by Ríos-Utrera (2008), as well as for different B. indicus beef breeds by Lira et al. (2008). Maternal effects are important in genetic evaluation programs for preweaning traits because they influence the phenotype performance of the calves through environmental or genetic effects of the dam (Willham 1972). The maternal effects on BW of the calves could be due to cytoplasmic effects (Pun et al. 2012), uterine environmental effects of the dam during pregnancy, and genes provided by the dam. The value of h2m for WW205 (0.38) was greater than those reported by Plasse et al. (2004) in Venezuela (0.14), Salces et al. (2002) in the Philippines (0.10), Pico et al. (2004) in South Africa (0.06), Parra-Bracamonte et al. (2007) in Mexico (0.08), and the average (0.13) reported for the same breed by Ríos-Utrera (2008), which was also greater than those reported for Nellore (0.17) and Indubrazil (0.09) cattle in Mexico (Martínez-González et al. 2010; Ríos-Utrera et al. 2013). For WW205, milk production is the main maternal effect, although the maternal ability of the cow is also of importance (Meyer et al. 1994); therefore, it is possible to increase WW205 of Brahman calves through selection.
Trop Anim Health Prod
The direct-maternal genetic correlation (rdm) value for BW was negative (−0.41) but slightly greater than the values reported for Brahman cattle (−0.36) by Pico et al. (2004). However, it was lower than the values reported (−0.87) by Parra-Bracamonte et al. (2007). Also, the value of rdm for WW205 was negative (−0.50) and greater than the values (0.27) reported for Indubrazil cattle in Mexico (Ríos-Utrera et al. 2013) and the average value (−0.13) reported by RíosUtrera (2008) for Brahman cattle but lower than value (−0.90) reported by Martínez-González et al. (2010) for the Nellore cattle in Mexico. The genetic correlations between direct and maternal genetic effects could be due to antagonistic pleiotropic mechanisms among genes that influence the maternal ability and the preweaning growth traits of the calves (Wilson and Réale 2006). The differences between breeds and selection criteria among populations, population structure, and statistical models used could partially explain the differences between the genetic correlations here obtained. The genetic correlations between direct and maternal genetic effects should be estimated with accuracy and should be included in the models for the estimation of genetic parameters of preweaning growth traits. Good information on family structures is required for beef cattle in order to obtain unbiased parameter estimates (Boligon et al. 2012). Other factors partially responsible for a high correlation between the direct additive and maternal effects could be the extra-variation due to a greater additive variance because of the importation of unrelated sires with high genetic values (Meyer 1997) and the lack of connectivity among herds (Kuehn et al. 2007). The h2T estimate, in this study, is lower than the direct heritability due to an antagonism between direct and maternal effects. This indicates that the heritability estimates using a model without maternal effects might be biased upwards. According to Willham (1972), h2T is a good parameter for the estimation of the expected response in the progeny. Also, it could be compared with values from other studies in a fair manner. The h2T for BW was similar to that reported by Plasse et al. (2004) despite the differences in the direct and maternal genetic effects estimated. However, lower values of h2T for WW205 (0.26, 0.11) were reported for Brahman and Indubrazil cattle in Mexico (Parra-Bracamonte et al. 2007; Ríos-Utrera et al. 2013). The genetic correlation between BW and WW205 for direct additive effects (0.77) showed a strong association between the two traits, which is slightly higher than the value (0.72) reported for Nellore cattle in Mexico (Medina-Zaldivar et al. 2005) but lower than that reported by Salces et al. (2002) for the same breed in the Philippines (0.29). Similarly, the genetic correlation between BW and WW205 for maternal additive effects was high (0.61) and higher than reported by Salces et al. (2002) in the Philippines (0.15). Both genetic
correlations (direct and maternal) were within the range of those (0.36–0.83) reported for different B. indicus beef breeds (Lira et al. 2008). According to the results, an increase of WW205 through selection would increase BW due to the high positive correlation for both direct additive and maternal effects. However, an increase in BW will be associated with dystocia. Therefore, selection strategies must be made using the best models. In conclusion, the heritability estimates of BW and WW205 were high, which indicates that under the tropical conditions of this study, genetic improvement for those traits is possible through selection. Also, maternal effects and their antagonistic association with the additive genetic effects must be considered in the statistical genetic models in order to reduce bias in genetic evaluations of sires and dams.
Conflict of interest The authors declare no conflict of interest regarding the publication of this article.
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REGULAR ARTICLES
Estimation of genetic parameters for preweaning growth traits of Brahman cattle in Southeastern Mexico Raciel J. Estrada-León & Juan G. Magaña-Monforte & José C. Segura-Correa
Accepted: 20 February 2014 # Springer Science+Business Media Dordrecht 2014
Abstract The genetic parameters for Brahman cattle under the tropical conditions of Mexico are scarce. Therefore, heritabilities, additive direct and maternal correlations, and genetic correlations for birth weight (BW) and 205 days adjusted weaning weight (WW205) were estimated in four Brahman cattle herds in Yucatan, Mexico. Parameters were estimated fitting a bivariate animal model, with 4,531 animals in the relationship matrix, of which 2,905 had BW and 2,264 had WW205. The number of sires and dams identified for both traits were 122 and 962, respectively. Direct heritability estimates for BW and WW205 were 0.41±0.09 and 0.43±0.09, and maternal heritabilities were 0.15±0.07 and 0.38±0.08, respectively. Genetic correlations between direct additive and maternal genetic effects for BW and WW205 were −0.41±0.22 and −0.50±0.15, respectively. The direct genetic, maternal, and phenotypic correlations between BW and WW205 were 0.77±0.09, 0.61±0.18, and 0.35, respectively. The moderate to high genetic parameter estimates suggest that genetic improvement by selection is possible for those traits. The maternal effects and their correlation with direct effects should be taken into account to reduce bias in genetic evaluations.
Keywords Heritability . Direct effects . Maternal effects . Tropics . Zebu R. J. Estrada-León Instituto Tecnológico Superior de Calkiní, Campeche, Mexico J. G. Magaña-Monforte : J. C. Segura-Correa (*) Facultad de Medicina Veterinaria y Zootecnia, Universidad Autónoma de Yucatán, Km. 15.5 carretera Mérida-Xmatkuil, A.P. 4-116, Itzimná, Mérida, Yucatán, México e-mail: [email protected] J. C. Segura-Correa e-mail: [email protected]
Introduction The tropical regions of Mexico are places of challenge to increase animal production through better management of animals and pastures, and of opportunity, because of land, water, and animal food availability at low cost (MagañaMonforte et al. 2006). In these tropical regions, beef cattle production is characterized by poor management and traditional production systems based on pastures of poor quality, scarce use of technology, and lack of genetic improvement programs (Rodríguez et al. 1998). Selection of the best animals as sires and dams is one option for improving animal production in the tropics. However, the beef production industry in the tropics of Mexico lacks a regional record-keeping program that provides data to estimate the genetic parameters to be used in genetic programs. In the tropical areas of Mexico, zebu-type cattle is the predominant one, of which the Brahman breed is the most popular. The main characteristics of the Brahman breed are its ability to withstand extreme climates (adaptability), rusticity, resistance to ectoparasites, and good response in crossbreeding programs (Razook et al. 1998). Because of the lack of farms that kept information on animal performance, few studies have been carried out to obtain genetic parameters for preweaning growth traits in zebu cattle in the tropics of Mexico. Genetic parameters are unique to the population in which they are estimated and they may change over time due to selection, environmental conditions, and management decisions. The estimation of direct genetic and maternal effects, under the tropical conditions of Mexico, is important to estimate the expected genetic values and response to selection. The objective of this study was to estimate the genetic parameters for some preweaning traits in Brahman cattle in Southeastern Mexico.
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Materials and methods
Table 1 Structure and descriptive statistics of data from four Brahman cattle herds in Southeastern Mexico
Climate, management, and data structure
Concepts
BW
WW205
The data utilized in this study were obtained from the four farms located in the eastern region of Yucatan, Mexico. The climate of the region is tropical sub-humid with rain in summer (Aw0), with average monthly temperature of 26.6 °C and average annual rainfall of 1,105 mm. The farms had paddocks of Guinea grass (Panicum maximum) and small areas of Taiwan (Penicetum purpurium). Calves were weighed and identified by ear tattoo numbers within the first 3 days of birth, and they remained with their dams until approximately 8 months of age. In that period, calves were treated against internal and external parasites, as well as vaccinated against common diseases in the region. Also, the calves were supplemented (creep feeding) with commercial feed, with 14 % of crude protein and 2.8 Mcal ME/kg DM. Calves were weighed and identified with a hot iron number at weaning. Cows were kept in a rotational pasture system, and during the dry season they were supplemented with chopped grass, broiler litter, and molasses or with a commercial feed (11– 13 % crude protein and 2.2–2.4 Mcal ME/kg DM). Cows were managed under artificial insemination and natural mating during the whole year. Forty-five days after calving, heat detection was checked visually twice a day (morning and afternoon) and service was practiced 12 h after heat detection. Pregnancy diagnosis was practiced 60 days after the last service. Semen and bulls from Brahman sires from the USA were commonly used. Bulls were selected by appearance. The weaning weights were adjusted to 205 days (WW205) according to the Beef Improvement Federation (BIF 2002). Data with three standard deviations from the mean were deleted. Original identification of the animals was recorded using sequential numbers (according to birth date) in the pedigree file using RENUMERA program (Carolino and Gamma 2002). The connectedness of contemporary groups was evaluated using the AMC program (Roso and Schenkel 2006), from which the basis of related animals for each variable was derived (0.9 % of the data were deleted from the original data base because of the lack of connectability). The final pedigree file contained information on 4,531 calves, of which 2,905 had birth weights (BW) and 2,264 had weaning weights adjusted to 205 days. One hundred twenty-two sires and 962 dams with a least five calves/sire and a mean of three calves/dam were used. Thirteen sires (11.6 %) and 103 dams (10.7 %) had records as calves, and 47.9 % of dams had three or more calves with records. The complete structure of the data and some descriptive statistics are shown in Table 1, and the structure of the data by herd is shown in Table 2.
Mean ± SD (kg) Coefficient of variation (%) Males (%) No. of animals in A−1
33.10±4.65 14.06 54.2 4,531
204.05±37.71 18.48 50.8 4,531
No. of animals with records No. of paternal grandsires No. of maternal grandsires No. of sires No. of dams No. of dams with data as a calves Average number of records per dam Dams with one record (%) Dams with two records (%) Dams with ≥3 records (%)
2,902 9 42 122 962 103 3.02 30.9 21.2 47.9
2,261 6 36 112 761 82 2.98 29.9 22.9 47.2
A−1 inverse of the numerator relationship matrix, BW birth weight, WW205 weaning weight adjusted to 205 days
Statistical analyses The components of (co)variance and genetic parameters were obtained by restricted maximum likelihood (REML) method, fitting a bivariate animal model, using MTDFREML program (Boldman et al. 1995). The statistical model included the fixed effects of contemporary group (herd-year-season of birth); sex of the calf (female or male); parity number of the cow (1–5); and the random effects of direct additive (d), maternal additive (m), and the residual term (e), with covariance of d and m≠0. The environmental permanent effect was not included because the preliminary analysis did not show significance. The contemporary groups considered four herds, 9 years (1999–2007), and two seasons (rainy and dry) for a total of 72 fixed level effects, with at least three calves with data per level. In the matrix notation, the model was
y1 y2
¼
X1 0
0 X2
β1 Zd1 þ 0 β2
0 Zd2
Zm1 0
3 2 d1 7 0 6 6 d2 7 þ e1 Zm2 4 m1 5 e2 m2
where y1 = the vector of observations for BW; y2 = the vector of observations for WW205; β1 = the vector of solutions for the fixed effects for y1; β2 = the vector of solutions for the fixed effects for y2; d1 = vector of the direct additive genetic effects for y1; d2 = vector of the direct additive genetic effects for y2; m1 = vector of the maternal additive genetic effects for y1; m2 = vector of the maternal additive genetic effects for y2; e1 = vector of the residual effects for y1; e2 = vector of the
Trop Anim Health Prod Table 2 Structure of data by Brahman cattle herds in Southeastern Mexico Concepts
Herd 1
Herd 2
Herd 3
Herd 4
Total
No. of animals with records for BW No. of animals with records for WW No. of sires No. of dams No. of sires with data in different herds for BW and WW205 No. of dams with data in different herds for BW and WW205
682 623 61 214
1,662 1,230 67 539
229 160 25 112
329 248 28 120
2,902 2,261 181 962 59 24
BW birth weight, WW205 weaning weight adjusted to 205 days
residual effects for y2; and X1, X2, Zd1, Zd2, Zm1, Zm2 = incidence matrices.
The assumptions related to distributions of y, a, m, and e were as follows:
3 2 3 2 y Xβ ZGZ 0 þ WMW 0 þ ðZΦW 0 þ WΦZ 0 Þ þ R 6d 7 60 7 6 GZ 0 7 6 7 6 E6 4 m 5 ¼ 4 0 5; Var ¼ 4 MW 0 e 0 R 2
where G=A⊗G0, M=A⊗M0, Φ=A⊗Φ0 y R=I⊗R0; A is the numerator relationship matrix of an order equal to the number of individuals, G0, M0, Φ0 have formed a 4×4 matrix that include direct (σ2d), maternal (σ2m), and covariance between direct and maternal genetic effects (σdm), R is a 2×2 matrix with (co)variance error σ2e ; and I is the identity matrix. The convergent criterion used was the variance of the values in the likelihood function (−2log L), considered to be smaller than 10−9. The direct (h2d), maternal (h2m), and total (h2T) heritabilities were estimated as h2d ¼
σ2d σ2p
h2m ¼
σ2m σ2p
h2T ¼
σ2d þ 1:5σdm þ 0:5σ2m σ2p
where the phenotypic variance (σ 2p ) of the trait was σ2p =σ2d +σ2m +σdm +σ2e .
Results The means for BW and WW205 were 33.1±4.65 kg and 204.0 ± 37.7 kg, respectively (Table 1). The variance
ZG G Φ 0
WM Φ M 0
3 R 07 7 05 R
components and genetic parameter estimates for the preweaning growth traits are shown in Table 3. Genetic covariances between direct and maternal genetic effects were negative for both traits (Table 3). The genetic correlations between direct and maternal effects were moderately high and negative (−0.41 and −0.50, for BW and WW205, respectively). The h2T estimates for BW and WW205 were moderate (0.33 and 0.30, respectively). Also, direct genetic and maternal correlations between BW and WW205 (Table 4) were high (0.77 and 0.61, respectively), and phenotypic correlations were moderate (0.35).
Discussion The mean BW found in this study was slightly greater than the means reported for Brahman cattle in the other tropical regions of Mexico, Venezuela, and South Africa (Plasse et al. 2004; Pico et al. 2004; Parra-Bracamonte et al. 2007). Also, the mean WW205 was within the range of values reported in the places just mentioned (Pico et al. 2004; Plasse et al. 2004; Parra-Bracamonte et al. 2007). Although the cited studies were carried under tropical conditions, differences between estimates may be due to the management and genetic background of the populations studied. The data structure, in the present study, allows the partition of the maternal and direct additive genetic effects and agrees with the minimal recommendations of 10 % of dams with record as calves and more than 1.5 calves with records. The
Trop Anim Health Prod Table 3 Estimates of variance components and genetic parameters for birth weight (BW) and weaning weight adjusted to 205 days (WW205) Traits
Components of (co)variance σ2d σ2m 7.10 2.58 320.87 281.69 Genetic parameters h2d h2m
BW WW205
BW WW205
0.41±0.087 0.43±0.086
0.15±0.071 0.38±0.079
σdm −1.747 −151.436
σ2e 9.49 290.82
σ2p 17.43 741.96
rdm
e2
h2T
−0.41±0.216 −0.50±0.147
0.54±0.063 0.39±0.059
0.33 0.30
σ2d direct additive genetic variance, σ2m maternal additive genetic variance, σdm covariance between direct additive genetic and maternal genetic variances, σ2e residual variance, σ2p phenotypic variance, h2d direct heritability, h2m maternal heritability, rdm direct-maternal genetic correlation, e2 proportion of the phenotypic variance due to the residual variance, h2T total heritability
proportion of dams as calves with known phenotypic information and the number of progeny per dam influenced direct and maternal heritabilities, as well as the partition of maternal genetic and permanent environmental effects, which is important for the genetic evaluation of preweaning growth traits (Maniatis and Pollot 2003; Boligon et al. 2012). Similar data structures were used to estimate direct and maternal genetic effects for weaning weight in Brazilian Caracu (Cinachi et al. 2006). The direct additive genetic variances were larger than the maternal genetic variances for the two traits. Direct heritabilities (h2d) for BW and WW205 were moderate (0.41 and 0.43, respectively). The moderate direct additive heritability values indicate that the genetic improvement of preweaning growth traits can be achieved through selection based on those traits. The h2d for BW (0.41), estimated in this study, is within the range of those reported for Brahman cattle (0.28, 0.32, 0.42, 0.44) in South Africa (Pico et al. 2004), Mexico (ParraBracamonte et al. 2007), Venezuela (Plasse et al. 2004), and Philippines (Salces et al. 2002) but greater than 0.23, 0.27, and 0.31 reported for Guzerat (Martínez-González et al. 2009), Indubrazil (Ríos-Utrera et al. 2013) and Nellore cattle (Medina-Zaldivar et al. 2005) in Mexico, and for the average (0.33) reported for different Bos indicus beef breeds by Lira et al. (2008), in a review of genetic parameters. The differences among values could be explained by the differences in
Table 4 Estimates of covariance components (above the diagonal) and genetic correlations (below the diagonal) for birth weight (BW) and weaning weight adjusted to 205 days (WW205)
BW σ2d WW205 σ2d BW σ2m WW205 σ2m
BW σ2d
WW205 σ2d
BW σ2m
WW205 σ2m
1 0.77±0.087 −0.41±0.216 −0.26±0.209
36.521 1 −0.24±0.255 −0.50±0.147
−1.747 −6.886 1 0.61±0.179
−11.796 −151.436 16.463 1
σ2d direct additive genetic variance, σ2m maternal additive genetic variance, σ2p phenotypic variance
breeds, the population structure of the data, connectivity, and statistical models used. The h2d for WW205 (0.43) was greater than the values reported for Brahman cattle (0.22, 0.14, 0.13) in Mexico (ParraBracamonte et al. 2007), other countries (Salces et al. 2002; Pico et al. 2004; Plasse et al. 2004), and for the average (0.26) reported for the same breed by Ríos-Utrera (2008), in a review of genetic parameter estimates, as well as those reported for Nellore and Indubrazil cattle in Mexico (Martínez-González et al. 2010; Ríos-Utrera et al. 2013), but lower than the values reported by Martínez-González et al. (2009) for Guzerat cattle (0.53). The h2m estimate (0.15) for BW is higher than the values reported for Brahman cattle (0.11) in South Africa (Pico et al. 2004) and for Indubrazil cattle (0.10) in Mexico (Ríos-Utrera et al. 2013) but similar to the values reported for Brahman and Nellore cattle by Parra-Bracamonte et al. (2007) and Martínez-González et al. (2010) in Mexico (0.16 and 0.17, respectively). In contrast, lower estimates were reported for Brahman (0.10) and Nellore (0.09) by Ríos-Utrera (2008), as well as for different B. indicus beef breeds by Lira et al. (2008). Maternal effects are important in genetic evaluation programs for preweaning traits because they influence the phenotype performance of the calves through environmental or genetic effects of the dam (Willham 1972). The maternal effects on BW of the calves could be due to cytoplasmic effects (Pun et al. 2012), uterine environmental effects of the dam during pregnancy, and genes provided by the dam. The value of h2m for WW205 (0.38) was greater than those reported by Plasse et al. (2004) in Venezuela (0.14), Salces et al. (2002) in the Philippines (0.10), Pico et al. (2004) in South Africa (0.06), Parra-Bracamonte et al. (2007) in Mexico (0.08), and the average (0.13) reported for the same breed by Ríos-Utrera (2008), which was also greater than those reported for Nellore (0.17) and Indubrazil (0.09) cattle in Mexico (Martínez-González et al. 2010; Ríos-Utrera et al. 2013). For WW205, milk production is the main maternal effect, although the maternal ability of the cow is also of importance (Meyer et al. 1994); therefore, it is possible to increase WW205 of Brahman calves through selection.
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The direct-maternal genetic correlation (rdm) value for BW was negative (−0.41) but slightly greater than the values reported for Brahman cattle (−0.36) by Pico et al. (2004). However, it was lower than the values reported (−0.87) by Parra-Bracamonte et al. (2007). Also, the value of rdm for WW205 was negative (−0.50) and greater than the values (0.27) reported for Indubrazil cattle in Mexico (Ríos-Utrera et al. 2013) and the average value (−0.13) reported by RíosUtrera (2008) for Brahman cattle but lower than value (−0.90) reported by Martínez-González et al. (2010) for the Nellore cattle in Mexico. The genetic correlations between direct and maternal genetic effects could be due to antagonistic pleiotropic mechanisms among genes that influence the maternal ability and the preweaning growth traits of the calves (Wilson and Réale 2006). The differences between breeds and selection criteria among populations, population structure, and statistical models used could partially explain the differences between the genetic correlations here obtained. The genetic correlations between direct and maternal genetic effects should be estimated with accuracy and should be included in the models for the estimation of genetic parameters of preweaning growth traits. Good information on family structures is required for beef cattle in order to obtain unbiased parameter estimates (Boligon et al. 2012). Other factors partially responsible for a high correlation between the direct additive and maternal effects could be the extra-variation due to a greater additive variance because of the importation of unrelated sires with high genetic values (Meyer 1997) and the lack of connectivity among herds (Kuehn et al. 2007). The h2T estimate, in this study, is lower than the direct heritability due to an antagonism between direct and maternal effects. This indicates that the heritability estimates using a model without maternal effects might be biased upwards. According to Willham (1972), h2T is a good parameter for the estimation of the expected response in the progeny. Also, it could be compared with values from other studies in a fair manner. The h2T for BW was similar to that reported by Plasse et al. (2004) despite the differences in the direct and maternal genetic effects estimated. However, lower values of h2T for WW205 (0.26, 0.11) were reported for Brahman and Indubrazil cattle in Mexico (Parra-Bracamonte et al. 2007; Ríos-Utrera et al. 2013). The genetic correlation between BW and WW205 for direct additive effects (0.77) showed a strong association between the two traits, which is slightly higher than the value (0.72) reported for Nellore cattle in Mexico (Medina-Zaldivar et al. 2005) but lower than that reported by Salces et al. (2002) for the same breed in the Philippines (0.29). Similarly, the genetic correlation between BW and WW205 for maternal additive effects was high (0.61) and higher than reported by Salces et al. (2002) in the Philippines (0.15). Both genetic
correlations (direct and maternal) were within the range of those (0.36–0.83) reported for different B. indicus beef breeds (Lira et al. 2008). According to the results, an increase of WW205 through selection would increase BW due to the high positive correlation for both direct additive and maternal effects. However, an increase in BW will be associated with dystocia. Therefore, selection strategies must be made using the best models. In conclusion, the heritability estimates of BW and WW205 were high, which indicates that under the tropical conditions of this study, genetic improvement for those traits is possible through selection. Also, maternal effects and their antagonistic association with the additive genetic effects must be considered in the statistical genetic models in order to reduce bias in genetic evaluations of sires and dams.
Conflict of interest The authors declare no conflict of interest regarding the publication of this article.
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