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1.
Correlations between genetic expression in lambs when dams were young (1 yr), middle-aged (2 and 3 yr), or older (older than 3 yr) were estimated with three-trait analyses for weight traits. Weights at birth (BWT) and weaning (WWT) and ADG from birth to weaning were used. Numbers of observations were 7,731, 9,518, 9,512, and 9,201 for Columbia (COLU), Polypay (POLY), Rambouillet (RAMB), and Targhee (TARG) breeds of sheep, respectively. When averaged, relative estimates for WWT and ADG were similar across breeds. Estimates were variable across breeds. On average, direct heritability was greater when environment was young dams (.44 for BWT and .34 for WWT) than when environment was dams of middle age or older (.24 and .28 for BWT and .20 and .16 for WWT, respectively). Maternal heritability was greater when dams were middle-aged or older (.28 and .22 vs .18) for BWT but was greater when dams were younger (.10 vs .05 and .04) for WWT. The estimates of genetic correlations for direct effects across age of dam environments averaged .32 for birth weight and averaged .70 for weaning weight. Average estimates of maternal genetic correlations across age of dam classes were .36 or less for both BWT and WWT. Average estimates of correlations among maternal permanent environmental effects were .49 or less across age of dam classes. Total maternal effects accounted for .33 to .42 of phenotypic variance for BWT and for .09 to .26 of phenotypic variance for WWT. The average estimates of genetic correlations between expressions of the same genotypes with different ages of dams suggest that measurements of BWT of lambs with dams in young, middle, and older age classes should be considered to be separate traits for genetic evaluation and that for WWT measurements with young age of dam class and combined middle and older age of dam classes should be considered to be separate traits for genetic evaluation.  相似文献   

2.
Genetic parameters for wool traits for Columbia, Polypay, Rambouillet, and Targhee breeds of sheep were estimated with single- and multiple-trait analyses using REML with animal models. Traits considered were fleece grade, fleece weight, and staple length. Total number of observations ranged from 11,673 to 34,746 for fleece grade and fleece weight and from 3,500 to 11,641 for staple length for the four breeds. For single-trait analyses, data were divided by age of ewe: young ages (age of 1 yr), middle ages (ages of 2 and 3 yr), and older ages (age greater than 3 yr). Heritability estimates averaged over breeds for fleece grade decreased from .42 at a young age to .37 for older ages. For fleece weight, heritability estimates averaged .52, .57, and .55 within the successively older groups. Heritability estimates for staple length averaged .54 for young and middle age classes. Few older ewes had staple length measurements. After single-trait analyses, new data sets were created for three-trait analyses with traits defined by three age classes when animals were measured. Heritability estimates with three-trait analyses, except for a few cases, were somewhat greater than those from single-trait analyses. For fleece grade, the genetic correlations averaged over breeds were .72 for young with middle, .42 for young with older, and .86 for middle with older age classes. For fleece weight, the average genetic correlations were .81, .83, and .98. For staple length, the average genetic correlation for young with middle age classes was .82. Estimates of genetic correlations across ages varied considerably among breeds. The average estimates of correlations suggest that fleece grade may need to be defined by age, especially for the Columbia and Rambouillet breeds. For fleece weight and staple length, however, the average correlations suggest no need to define those traits by age.  相似文献   

3.
Estimates of repeatability and heritability were obtained for the following productivity traits of ewes: litter weight at birth (LWB) and weaning (LWW), litter size at birth (LSB), litter size alive at birth (NBA), litter size at weaning (LSW), neonatal survival rate (SRB) and preweaning survival rate (SRW). Phenotypic and genetic correlations were estimated for litter traits. The data set contained 6,394 ewe breeding records from three state stations over 10 yr on 1,731 ewes that were the progeny of 488 sires among three breeds (Columbia, Suffolk and Targhee). Pooled intra-station estimates of repeatability ranged from .11 to .22 for LWB and LWW among the three breeds. For litter size at birth, number born alive and litter size at weaning these estimates varied from .09 to .17 and for the survival traits (SRB and SRW) the variation was from .11 to .20. Intra-station estimates of heritability for the three breeds varied from .12 to .28 for LWB and LWW, and for LSB, NBA and LSW estimates varied from .05 to .35. Heritability estimates for survival traits (SRB and SRW) were low, ranging from .00 to .14. Phenotypic correlations among LWB, LWW, NBA and LSW ranged from .35 to .92 among the breed-station subclasses, with higher correlations occurring where a part-whole relationship existed. The study suggests that selection of ewes with high litter size at birth or at weaning and(or) litter weight at birth or at weaning will genetically improve total litter weight at weaning per ewe lambing.  相似文献   

4.

This study used pedigree information and data collected from 1979 to 2012 at the Raeini Cashmere goat breeding station, located in Baft City in Kerman Province in southeastern Iran. Genetic and phenotypic parameters for early reproductive traits of breeding does, including total numbers of kids born at first kidding (LSB1), total numbers of kids weaned at first kidding (LSW1), total birth weight of all kids born at first kidding (LWB1), total weaning weight of all kids weaned at first kidding (LWW1), and age at first kidding (AFK), were estimated using a Bayesian approach via Gibbs sampling. Posterior means for heritability estimates of LSB1, LSW1, LWB1, LWW1, and AFK were statistically significant, with values of 0.12, 0.23, 0.17, 0.15, and 0.46, respectively. Low-to-moderate additive genetic variation was present for the studied reproductive traits. Estimated genetic correlations among LSB1, LSW1, LWB1, and LWW1 were statistically significant and ranged from 0.12 between LWB1 and LWW1 to 0.72 between LSB1 and LSW1. Corresponding phenotypic correlation estimates were also statistically significant and ranged from 0.04 between LWB1 and LWW1 to 0.55 between LSB1 and LSW1. Posterior means of genetic and phenotypic correlations between AFK and other studied traits were statistically significant only for LSB1 and LWB1. For LSB1, LSW1, LWB1, and LWW1, we conclude that genetic and phenotypic improvement in any of these traits in Raeini Cashmere does would favorably influence all of the other traits. However, does that first kidded at younger ages have smaller litters at birth and lower litter birth weights at their first parity.

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5.
The objective of this study was to estimate genetic parameters for reproductive traits in Shall sheep. Data included 1,316 records on reproductive performances of 395 Shall ewes from 41 sires and 136 dams which were collected from 2001 to 2007 in Shall breeding station in Qazvin province at the Northwest of Iran. Studied traits were litter size at birth (LSB), litter size at weaning (LSW), litter mean weight per lamb born (LMWLB), litter mean weight per lamb weaned (LMWLW), total litter weight at birth (TLWB), and total litter weight at weaning (TLWW). Test of significance to include fixed effects in the statistical model was performed using the general linear model procedure of SAS. The effects of lambing year and ewe age at lambing were significant (P?<?0.05). Genetic parameters were estimated using restricted maximum likelihood procedure, under repeatability animal models. Direct heritability estimates were 0.02, 0.01, 0.47, 0.40, 0.15, and 0.03 for LSB, LSW, LMWLB, LMWLW, TLWB, and TLWW, respectively, and corresponding repeatabilities were 0.02, 0.01, 0.73, 0.41, 0.27, and 0.03. Genetic correlation estimates between traits ranged from ?0.99 for LSW–LMWLW to 0.99 for LSB–TLWB, LSW–TLWB, and LSW–TLWW. Phenotypic correlations ranged from ?0.71 for LSB–LMWLW to 0.98 for LSB–TLWW and environmental correlations ranged from ?0.89 for LSB–LMWLW to 0.99 for LSB–TLWW. Results showed that the highest heritability estimates were for LMWLB and LMWLW suggesting that direct selection based on these traits could be effective. Also, strong positive genetic correlations of LMWLB and LMWLW with other traits may improve meat production efficiency in Shall sheep.  相似文献   

6.
This study reports on the phenotypic and genetic (co)variance components for reproductive traits in Zandi sheep, using between 1,859 and 2,588 records obtained from 577 ewes. The data were collected from the Khojir Breeding Station of Zandi sheep in Tehran, Iran from 1994 to 2008. The basic traits were litter size at birth (LSB), litter size at weaning (LSW), litter mean weight per lamb born (LMWLB), and litter mean weight per lamb weaned (LMWLW), and the composite traits were total litter weight at birth (TLWB) and total litter weight at weaning (TLWW). Genetic analyses were carried out using the restricted maximum likelihood method that was explored by fitting the additive direct genetic effects and permanent environmental effects of the ewes as random effects and the ewe age at lambing and lambing year as fixed effects for all of the investigated traits. Akaike’s information criterion was used to choose the most appropriate model. LSB, LSW, LMWLB, LMWLW, TLWB, and TLWW direct heritability estimates were 0.07, 0.05, 0.12, 0.10, 0.08, and 0.14, respectively. The estimated fractions of variance due to the permanent environmental effects of the ewe ranged from 0.03 for LMWLB to 0.08 for LMWLW and TLWW. Corresponding repeatability estimates ranged from 0.10 for LSW to 0.22 for TLWW. Direct genetic correlations varied from ?0.61 for LSB–LMWLB to 0.88 for LSB–LSW and LSB–TLWB. Results indicate that genetic change depends not only on the heritability of traits, but also on the observed phenotypic variation; therefore, improvement of non-genetic factors should be included in the breeding programs.  相似文献   

7.
We estimated genetic parameters in Landrace and Large White pig populations for litter traits at farrowing (total number born, number born alive, number stillborn, total litter weight at birth (LWB), and mean litter weight at birth) and those at weaning (litter size at weaning (LSW), total litter weight at weaning (LWW), mean litter weight at weaning (MWW), and survival rate from farrowing to weaning). We analyzed 65,579 records at farrowing and 6,306 at weaning for Landrace, and 52,557 and 5,360, respectively, for Large White. Single‐trait and two‐trait repeatability animal models were exploited to estimate heritability and genetic correlation respectively. Heritability estimates of LSW were 0.09 for Landrace and 0.08 for Large White. Genetic correlations of LSW with MWW were –0.43 for Landrace and –0.24 for Large White. Genetic correlations of LSW with LWW and LWB ranged from 0.5 to 0.6. The genetic correlation of MWW with LWW was positive, but that with LWB was negligible. The results indicate that utilizing LWW or LWB could improve LSW efficiently, despite the antagonistic genetic correlation between LSW and MWW.  相似文献   

8.
For the first time, the current study reports the genetic and phenotypic correlations between growth and reproductive traits in Zandi sheep. The data were comprised of 4,309 records of lamb growth traits from 1,378 dams and 273 sires plus 2,588 records of reproductive traits from 577 ewes. These data were extracted from available performance records at Khojir Breeding Station of Zandi sheep in Tehran, Iran, from 1993 to 2008. Correlations were estimated from two animal models in a bivariate analysis using restricted maximum likelihood procedure between lamb growth traits [birth weight (BW), weaning weight at 3 months of age (WW), as well as six-month weight (6 MW)] and ewe reproductive traits [litter size at birth (LSB), litter size at weaning (LSW), total litter weight at birth (TLWB), and total litter weight at weaning (TLWW)]. The genetic correlations between BW and reproductive traits varied from low to high ranges from 0.10 for BW–LSB to 0.86 for BW–TLWB. WW was moderately (0.37) to highly (0.96) correlated with all the reproductive traits. Moreover, the genetic correlations were observed between 6 MW and reproductive traits, varied from 0.19 to 0.95. Relationships between growth and reproductive traits ranged from 0.01 for BW–LSW to 0.28 for BW–TLWB in phenotypic effects. Results indicated that selection to improve WW would have high effect on genetic response in TLWW, and also, these results could be effective for all of the reproductive traits in Zandi sheep.  相似文献   

9.
Market data on 1,315 rabbits from 201 litters from Californian (CAL), New Zealand White (NZW), CAL X NZW and NZW X CAL dams bred to CAL, NZW and Flemish Giant sires were subjected to multiple regression and path analyses. Market traits observed in litters at 56 d included average kit weight (A56W), litter size (LS56), total litter weight (L56W) and within-litter uniformity in individual weights (LCV). Preweaning variables as covariates included in the model were dam metabolic body weight (DMW), litter born (LSB), litter birth weight (LBW), milk yield from 1 to 21 d (MY) and feed intake from 1 to 28 d of the dam and litter (FI). Results from multiple regression analyses indicated linear and quadratic effects (P less than .20) due to LSB and MY for all four market characters. The LBW influenced (P less than .05) LS56 and L56W, and FI affected (P less than .05) LS56, L56W and LCV. Separate analyses were conducted involving 28-d weaning and feed intake variables as covariates: litter size weaned (LSW), litter weaning weight (LWW) and litter feed intake from 28 to 56 d (LFI). The three weaning covariates were important (P less than .05) for all market traits except LS56 (LWW was not significant). The most accurate regression equations were obtained from the weaning model for prediction of L56W and LS56 (R2 = .68 and .78). Path analyses revealed that preweaning covariates generally had direct rather than indirect effects on market traits. Both direct and indirect effects of weaning covariates were important for market traits. Results suggest that litter market traits of size and weight can be predicted with a reasonable degree of accuracy.  相似文献   

10.
Improvement in litter traits is the key to profitable pig farming that directly enhances the economic standing of the farmers in developing countries. The present study aimed to explore oestrogen receptor (ESR), epidermal growth factor (EGF), follicle-stimulating hormone beta subunit (FSHβ), prolactin receptor (PRLR) and retinol-binding protein 4 (RBP4) genes as possible candidate genetic markers for litter traits in indigenous pigs of India. The breeds included in the study were Ghungroo, Mali, Niang Megha and Tenyi Vo, and the reproductive traits considered were litter size at birth (LSB), number born alive (NBA), litter weight at birth (LWB), litter size at weaning (LSW) and litter weight at weaning (LWW) at their first parity. PCR-RFLP and primer-based mutation detection methods were used to identify polymorphism, and associations between the genotypes and the traits were analysed using a general linear model. The Ghungroo pigs recorded the best litter performances among the breeds (p < .05, LWB p < .01). Different alleles and genotypes of the genes under study were detected. Short interspersed nuclear element (SINE) −/− genotype of FSHβ revealed significantly higher litter traits (p < .05, LSB p < .01). The LWW was also found to be significantly influenced by ESR BB and AB, EGF AB and BB, and PRLR CC genotypes (p < .05). Although we did not find statistically significant and consistently superior litter traits with respect to different genotypes of other studied genes than genotype SINE −/− of the FSHβ, PRLR CC genotype demonstrated superior performances for all the litter traits. Our study revealed the FSHβ as a potential candidate genetic marker for litter traits in indigenous pig breeds of India.  相似文献   

11.
This study was conducted in a four‐year rabbit project that aimed to develop a synthetic line named Moshtohor (M) by crossing Sinai Gabali breed (G) with the Spanish V‐line (V). The G, V, F1 (G × V), F2 (G × V)2 and M line were analysed. Traits of doe body weight at delivery (DBW), litter size at birth (LSB) and at weaning (LSW), milk production during the first, second, third and fourth week of lactation and total milk yield (TMY) were recorded. Data were analysed using a repeatability uni‐trait animal model to estimate the genetic parameters and estimable functions of genetic group effects. Based on them and the matrix of their variance–covariance, the crossbreeding parameters were also estimated. Estimates of heritabilities for all the studied traits were low ranging from 0.06 to 0.11 for DBW, LSB and LSW and from 0.0 to 0.06 for milk production traits. Permanent environmental effects were very low ranging from 0.0 to 0.10 for all the traits, except for DBW (0.41). Least square means of V line were superior (p < 0.05) in DBW (3253 versus 3037 g) and LSB (6.71 versus 6.28 young) relative to G breed. M line had superiority in LSB (6.94 young) compared with G breed. M line and G breed were better than V line for milk production traits (3415 and 3236 versus 2893 g for TMY). Significant effects of direct additive were observed for most traits studied (ranged from ?6.8 to 20.7%). Effects of individual heterosis for most milk production traits were significant and ranged from 2.1 to 13.9%, but they were not significant for DBW, LSB and LSW. On the opposite side, effects of maternal heterosis for all the traits were not significant.  相似文献   

12.
A five-years crossing scheme involving the Spanish V line (V) and Saudi Gabali (S) rabbits was practiced to produce 14 genetic groups: V, S, 1/2V1/2S, 1/2S1/2V, 3/4V1/4S, 3/4S1/4V, (1/2V1/2S)2, (1/2S1/2V)2, (3/4V1/4S)2, (3/4S1/4V)2, ((3/4V1/4S)2)2, ((3/4S1/4V)2)2, Saudi 2 (a new synthetic line) and Saudi 3 (another new synthetic line). A total of 3496 litters from 1022 dams were used to evaluate litter size at birth (LSB) and weaning (LSW), litter weight at birth (LWB), litter weight at 21 d (LW21) and litter weight at weaning (LWW), pre-weaning litter mortality (PLM), milk yield at lactation intervals of 0–7 d (MY07), 0–21 d (MY021), 0–28 d (TMY) and milk conversion ratio as g of litter gain per g of milk suckled during 21 d of lactation (MCR021). A generalized least squares procedure was used to estimate additive and heterotic effects (direct, maternal, and grand-maternal).The comparison among V, S, Saudi 2 and Saudi 3 showed a complementarity between V and S. Line V was superior for LSB, LSW, LWB, PLM, MY07, MY021 and TMY, while line S was superior for the other traits (LW21, LWW and MCR021). Saudi 2 and Saudi 3 had the means equal to or higher than the founder lines (V or S) for all traits. Saudi 2 showed better values in litter size and pre-weaning litter mortality compared to Saudi 3 with no significant differences for the other traits. Concerning crossbreeding parameters, direct additive effects were significant for all traits, ranging between 12.3% and 31.8% relative to the average of the means of V and S. All estimates for direct heterosis except LWB and MCR021 were significant and ranged from 5.3% to 27.5%. No estimates for maternal additive effects and grand-maternal additive and heterotic effects were significant. Only estimates for maternal heterotic effects of LSB and LSW were significant (8.6% and 10.6%, respectively).  相似文献   

13.
Records of 9,055 lambs from a composite population originating from crossing Columbia rams to Hampshire x Suffolk ewes at the U.S. Meat Animal Research Center were used to estimate genetic parameters among growth traits. Traits analyzed were weights at birth (BWT), weaning (7 wk, WWT), 19 mo (W19), and 31 mo (W31) and postweaning ADG from 9 to 18 or 19 wk of age. The ADG was also divided into daily gain of males (DGM) and daily gain of females (DGF). These two traits were analyzed with W19 and with W31 in three-trait analyses. (Co)variance components were estimated with REML for an animal model that included fixed effects of sex, age of dam, type of birth or rearing, and contemporary group. Random effects were direct and maternal genetic of animal and dam with genetic covariance, maternal permanent environmental, and random residual. Estimates of direct heritability were .09, .09, .35, .44, .19, .16, and .23 for BWT, WWT, W19, W31, ADG, DGM, and DGF, respectively. Estimates of maternal permanent environmental variance as a proportion of phenotypic variance were .09, .12, .03, .03, .03, .06, and .02, respectively. Estimates of maternal heritability were .17 and .09 for BWT and WWT and .01 to .03 for other traits. Estimates of genetic correlations were large among W19, W31, and ADG (.69 to .97), small between BWT and W31 or ADG, and moderate for other pairs of traits (.32 to .45). The estimate of genetic correlation between DGM and DGF was .94, and the correlation between maternal permanent environmental effects for these traits was .56. For the three-trait analyses, the genetic correlations of DGM and DGF with W19 were .69 and .82 and with W31 were .67 and .67, respectively. Results show that models for genetic evaluation for BWT and WWT should include maternal genetic effects. Estimates of genetic correlations show that selection for ADG in either sex can be from records of either sex (DGM or DGF) and that selection for daily gain will result in increases in mature weight but that BWT is not correlated with weight at 31 mo.  相似文献   

14.
Variance components for greasy fleece weight in Rambouillet sheep were estimated. Greasy fleece weight was modeled either as repeated measurements on the same trait or as different traits at different ages. The original data were separated according to the age of the ewe at shearing into three classes; 1 yr, 2 and 3 yr, and older than 3 yr. An animal model was used to obtain estimates of genetic parameters with a REML algorithm. Total numbers of animals in pedigrees for the different age classes were 696, 729, and 573, respectively, and 822 for the repeated measures model across ages. The animal model included direct genetic, permanent environmental, and residual environmental random effects and fixed effects for age of ewe, shearing date as contemporary group, and number of lambs born. Days between shearings was used as a covariate. Single-trait analyses were initially done to obtain starting values for multiple-trait analyses. A repeated measures model across ages was also used. Estimates of heritability by age group were .42, .50, and .58 from three-trait (age class) analyses and for the repeated measures model the estimate was .57. Estimates of genetic correlations between fleece yields for 1 yr and 2 and 3 yr, 1 yr and >3 yr, and 2 and 3 yr and >3 yr classes were .88, .89, and .97, respectively. These estimates of genetic correlations suggest that a repeated measures model for greasy fleece weight is adequate for making selection decisions.  相似文献   

15.
Records on 251,296 Yorkshire, 75,262 Duroc, 83,338 Hampshire, and 53,234 Landrace litters born between 1984 and April of 1999 in herds on the National Swine Registry Swine Testing and Genetic Evaluation System were analyzed. Animal model and restricted maximum likelihood procedures were used to estimate variances of animal genetic (a), maternal genetic (m), permanent environmental, and service sire, and the covariances between a and m for number born alive (NBA), litter weight at 21 d (L21WT), and number weaned (NW). Fixed effects of contemporary groups were included in the analysis. Based on a single-trait model, estimates of heritabilities were 0.10, 0.09, 0.08, and 0.08 for NBA; 0.08, 0.07, 0.08, and 0.09 for L21WT; and 0.05, 0.07, 0.05, and 0.05 for NW in the Yorkshire, Duroc, Hampshire, and Landrace breeds, respectively. Estimates of maternal genetic effects were low and ranged from 0.00 to 0.02 for all traits and all breeds. Estimates of permanent environmental effects ranged from 0.03 to 0.08. Estimates of service sire effects ranged from 0.02 to 0.05. A bivariate analysis was used to estimate the genetic correlations among traits. Average genetic correlations over the four breeds were 0.13, 0.15, and 0.71 for NBA with L21WT, NBA with NW, and L21WT with NW, respectively. Average genetic trends were 0.018 pigs/yr, 0.114 kg/yr, and 0.004 pigs/yr for NBA, L21WT, and NW, respectively. Although estimates of heritabilities for litter traits were low and similar across breeds, genetic variances for litter traits were sufficiently large to indicate that litter traits could be improved through selection. This study presents the first set of breed-specific estimates of genetic parameters available from large numbers of field records. It provides information for use in national genetic evaluations.  相似文献   

16.
Genetic parameters from both single-trait and bivariate analyses for prolificacy, weight and wool traits were estimated using REML with animal models for Columbia sheep from data collected from 1950 to 1998 at the U.S. Sheep Experiment Station (USSES), Dubois, ID. Breeding values from both single-trait and seven-trait analyses calculated using the parameters estimated from the single-trait and bivariate analyses were compared with respect to genetic trends. Number of observations were 31,401 for litter size at birth and litter size at weaning, 24,741 for birth weight, 23,903 for weaning weight, 29,572 for fleece weight and fleece grade, and 2,449 for staple length. Direct heritability estimates from single-trait analyses were 0.09 for litter size at birth, 0.06 for litter size at weaning, 0.27 for birth weight, 0.16 for weaning weight, 0.53 for fleece weight, 0.41 for fleece grade, and 0.55 for staple length. Estimate of direct genetic correlation between littersize at birth and weaning was 0.84 and between birth and weaning weights was 0.56. Estimate of genetic correlation between fleece weight and staple length was positive (0.55) but negative between fleece weight and fleece grade (-0.47) and between staple length and fleece grade (-0.70). Estimates of genetic correlations were positive but small between birth weight and litter size traits and moderate and positive between weaning weight and litter size traits. Fleece weight was lowly and negatively correlated with both litter size traits. Fleece grade was lowly and positively correlated with both litter size traits, while staple length was lowly and negatively correlated with the litter size traits. Estimates of correlations between weight traits and fleece weight were positive and low to moderate. Estimates of correlations between weight traits and fleece grade were negative and small. Estimates of correlations between staple length and birth weight (0.05) and weaning weight were small (-0.04). Estimated breeding values averaged by year of birth from both the single-trait and multiple-trait analyses for the prolificacy and weight traits increased over time, but were unchanged for the wool traits. Estimated changes in breeding values over time did not differ substantially for single-trait and multiple-trait analyses, except for traits highly correlated with another trait that was responding to selection.  相似文献   

17.
Genetic parameters from both single-trait and bivariate analyses for prolificacy, weight, and wool traits were estimated using REML with animal models for Targhee sheep from data collected from 1950 to 1998 at the U.S. Sheep Experiment Station, Dubois, ID. Breeding values from both single-trait and seven-trait analyses calculated with the parameters estimated from the single-trait and bivariate analyses were compared across years of birth with respect to genetic trends. The numbers of observations were 38,625 for litter size at birth and litter size at weaning, 33,994 for birth weight, 32,715 for weaning weight, 36,807 for fleece weight and fleece grade, and 3,341 for staple length. Direct heritability estimates from single-trait analyses were 0.10 for litter size at birth, 0.07 for litter size at weaning, 0.25 for birth weight, 0.22 for weaning weight, 0.54 for fleece weight, 0.41 for fleece grade, and 0.65 for staple length. Estimate of direct genetic correlation between litter size at birth and weaning was 0.77 and between birth and weaning weights was 0.52. The estimate of genetic correlation between fleece weight and staple length was positive (0.54), but was negative between fleece weight and fleece grade (-0.47) and between staple length and fleece grade (-0.69). Estimates of genetic correlations were near zero between birth weight and litter size traits and small and positive between weaning weight and litter size traits. Fleece weight was slightly and negatively correlated with both litter size traits. Fleece grade was slightly and positively correlated with both litter size traits. Estimates of correlations between staple length and litter size at birth (-0.14) and litter size at weaning (0.05) were small. Estimates of correlations between weight traits and fleece weight were positive and low to moderate. Estimates of correlations between weight traits and fleece grade were negative and small, whereas estimates between weight traits and staple length were positive and small. Estimated breeding values averaged by year of birth from both the single- and seven-trait analyses for the prolificacy and weight traits increased over time, whereas those for fleece weight decreased slightly and those for the other wool traits were unchanged. Estimated changes in breeding values over time did not differ substantially for the single-trait and seven-trait analyses, except for traits highly correlated with another trait that was responding to selection.  相似文献   

18.
The objectives of this study were to develop an efficient algorithm for calculating prediction error variances (PEVs) for genomic best linear unbiased prediction (GBLUP) models using the Algorithm for Proven and Young (APY), extend it to single-step GBLUP (ssGBLUP), and apply this algorithm for approximating the theoretical reliabilities for single- and multiple-trait models in ssGBLUP. The PEV with APY was calculated by block sparse inversion, efficiently exploiting the sparse structure of the inverse of the genomic relationship matrix with APY. Single-step GBLUP reliabilities were approximated by combining reliabilities with and without genomic information in terms of effective record contributions. Multi-trait reliabilities relied on single-trait results adjusted using the genetic and residual covariance matrices among traits. Tests involved two datasets provided by the American Angus Association. A small dataset (Data1) was used for comparing the approximated reliabilities with the reliabilities obtained by the inversion of the left-hand side of the mixed model equations. A large dataset (Data2) was used for evaluating the computational performance of the algorithm. Analyses with both datasets used single-trait and three-trait models. The number of animals in the pedigree ranged from 167,951 in Data1 to 10,213,401 in Data2, with 50,000 and 20,000 genotyped animals for single-trait and multiple-trait analysis, respectively, in Data1 and 335,325 in Data2. Correlations between estimated and exact reliabilities obtained by inversion ranged from 0.97 to 0.99, whereas the intercept and slope of the regression of the exact on the approximated reliabilities ranged from 0.00 to 0.04 and from 0.93 to 1.05, respectively. For the three-trait model with the largest dataset (Data2), the elapsed time for the reliability estimation was 11 min. The computational complexity of the proposed algorithm increased linearly with the number of genotyped animals and with the number of traits in the model. This algorithm can efficiently approximate the theoretical reliability of genomic estimated breeding values in ssGBLUP with APY for large numbers of genotyped animals at a low cost.  相似文献   

19.
The study was conducted to evaluate reproductive performances and estimate genetic parameters for reproduction traits in Arsi-Bale goats. A total of 792 kidding records collected from 2001 to 2007 were used. Parity of dam, year, season and type of kidding were investigated as fixed effects by PROC GLM of SAS. Derivative-Free Restricted Maximum Likelihood (DFREML) method was used to estimate genetic parameters by fitting four animal models. Parity of dam and year of kidding influenced (P < 0.05) all the traits. The overall means for age at first kidding (AFK), kidding interval (KI), litter size at birth (LSB), litter size at weaning (LSW), litter weight at birth (LWB), litter weight at weaning (LWW), abortion and dystocia were 574.9 ± 8.3 days, 280.0 ± 13.7 days, 1.6 ± 0.03, 1.37 ± 0.03, 3.7 ± 0.08 kg, 9.11 ± 0.38 kg, 3.8% and 0.13%, respectively. The estimates of direct additive heritability for the traits, except for abortion and dystocia, under the best model (direct animal for AFK and repeatability model for other traits) were 0.245 ± 0.19, 0.060 ± 0.08, 0.074 ± 0.05, 0.006 ± 0.05, 0.125 ± 0.05, 0.053 ± 0.07, respectively, while the corresponding permanent environmental effects were 0.00 ± 0.00, 0.07 ± 0.07, 0.08 ± 0.05, 0.172 ± 0.06, 0.03 ± 0.04 and 0.07 ± 0.05, respectively. Repeatability estimates for KI, LSB, LSW, LWB and LWW were 0.13, 0.15, 0.18, 0.16 and 0.12, respectively. Genetic correlations between reproductive traits vary from medium to high. Arsi-Bale goats have good reproductive performance with low incidence of reproductive disorder. Except for AFK, other traits have low estimates of heritabilities with high genetic correlation among the traits. Repeated measures of the traits are needed before deciding to keep or cull the animal.  相似文献   

20.
Records on 361,300 Yorkshire, 154,833 Duroc, 99,311 Hampshire, and 71,097 Landrace pigs collected between 1985 and April of 2000 in herds on the National Swine Registry Swine Testing and Genetic Evaluation System were analyzed. Animal model and REML procedures were used to estimate random effects of animal genetic, common litter, maternal genetic, and the covariances between animal and maternal for lean growth rate (LGR), days to 113.5 kg (DAYS), backfat adjusted to 113.5 kg (BF), and loin eye area adjusted to 113.5 kg (LEA). Fixed effects of contemporary group and sex were also in the statistical model. Based on the single-trait model, estimates of heritabilities were 0.44, 0.44, 0.46, and 0.39 for LGR; 0.35, 0.40, 0.44, and 0.40 for DAYS; 0.48, 0.48, 0.49, and 0.48 for BF; and 0.33, 0.32, 0.35, and 0.31 for LEA in the Yorkshire, Duroc, Hampshire, and Landrace breeds, respectively. Estimates of maternal genetic effects were low and ranged from 0.01 to 0.05 for all traits across breeds. Estimates of common litter effects ranged from 0.07 to 0.16. A bivariate analysis was used to estimate the genetic correlations between lean growth traits. Average genetic correlations over four breeds were -0.83, -0.37, 0.44, -0.07, 0.08, and -0.37 for LGR with DAYS, BF, and LEA, DAYS with BF and LEA, and BF with LEA, respectively. Average genetic trends were 2.35 g/yr, -0.40 d/yr, -0.39 mm/yr, and 0.37 cm2/yr for LGR, DAYS, BF, and LEA, respectively. Results indicate that selection based on LGR can improve leanness and growth rate simultaneously and can be a useful biological selection criterion.  相似文献   

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