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1.
用随机回归模型估计SD-Ⅱ系猪体重的遗传和表型协方差函数 总被引：1，自引：0，他引：1
用6个世代的686头SD-Ⅱ系猪的生长记录估计作为经度数据的体重的遗传和表型协方差函数。配合将年龄的勒让德多项式作为自变量的随机回归模型，用平均信息约束最大似然（AIREML）法估计回归系数间的协方差，从而得到加性遗传和永久环境协方差函数的系数。结果表明，协方差函数可以反映出体重在连续的年龄尺度上的遗传和表型变异。当多项式的配合阶数k=3，即降阶配合时，便可充分描述SD-Ⅱ系猪体重的生长变化。降价配合涉及的参数较少，同时可以缓和协方差估值间的差异。 相似文献
2.
用随机回归模型对507头中国荷斯坦奶牛的第1胎日产奶量进行了分析，将时间配合勒让德多项式作为自变量，再用平均信息约束最大似然法（AIREML）进行估计。然后通过协方差函数对时间轴上的时间点间估计协方差值，再用Excel绘制三维图。结果表明：配合M6-5-10时，能对月间隔的测定日产奶量数据进行分析，并能反映出整个时间轴上的加性遗传效应和永久环境效应的变异，且能得到光滑的三维图形。降价配合涉及的参数比较少，同时能够很好地缓和协方差函数估计值间的差异。 相似文献
3.
《黑龙江畜牧兽医》2020,(17)
为计算贵州黑山羊生长性状的遗传参数,试验建立了三种不同混合模型,运用平均信息-期望最大约束似然法(EM-AI REML)对贵州黑山羊初生重、3月龄体重、12月龄体重和24月龄体重的遗传力进行估计,最后使用赤池信息法则(AIC)对各模型进行验证。结果表明:不同的模型对遗传力的估计存在差异,当模型中只设加性效应为随机效应时,模型对贵州黑山羊12月龄体重和24月龄体重的遗传力估计最准确;当设加性效应和母体遗传效应为随机效应时,模型对初生重和3月龄体重的遗传力估计最准确。说明贵州黑山羊初生重、3月龄体重受母体遗传效应的影响较大,而12月龄体重和24月龄体重受母体遗传效应影响较小;贵州黑山羊的生长性状属于中等遗传力性状。 相似文献
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5.
《畜牧与兽医》2014,(7):37-40
采用平均信息与期望最大结合约束似然法用不同混合动物模型估计贵州半细毛羊的生长性状遗传参数,并采用赤池信息量准则(AIC)指数对不同模型进行比较。各模型中均包含固定效应、随机效应和残差效应。不同模型对随机效应做了不同的考虑:模型1中随机效应包括个体加性遗传效应、模型2中包括个体加性遗传效应、母体遗传效应;模型3中包括个体加性遗传效应、永久环境效应。各模型估计的初生重遗传力为:0.208 90.380 2;断奶重遗传力为:0.253 60.380 2;断奶重遗传力为:0.253 60.292 6;周岁重遗传力范围:0.224 60.292 6;周岁重遗传力范围:0.224 60.344 2;成年体重遗传力范围:0.221 20.344 2;成年体重遗传力范围:0.221 20.399 6;模型间比较结果表明:对于初生重和断奶重,模型2估计效果最优;对于周岁重和成年重,模型1估计效果最优。生长性状中初生重、断奶重受母体遗传效应影响显著;周岁重和成年重受母体效应影响不显著。 相似文献
6.
《中国草食动物科学》2020,(3)
用多性状动物模型估计考力代羊体重的遗传参数,从而获得较准确的遗传参数估值。使用1 269只考力代羊的生长发育记录3 332个,用多性状动物模型,分不考虑误差间协方差和考虑误差间协方差两种情况估计考力代羊生长性状的遗传参数。结果表明:不考虑误差间协方差时,直接遗传力估值依次为0.28、0.79、0.77、0.64和0.65;考虑误差间协方差时,则为0.28、0.33、0.30、0.23和0.21。遗传和表型相关在两种情况下都有相同的特点,月龄相差越大,相关越小。说明当不考虑误差间协方差时,分析结果遗传力被过高地估计。 相似文献
7.
本研究旨在对内蒙古白绒山羊产羔数进行遗传评估,进一步提高其繁殖性能.试验数据来源于内蒙古白绒山羊种羊场1998-2013年的繁殖性能记录,首先,利用SAS软件的GLM程序确定影响产羔数的固定效应;其次,应用重复力动物模型的约束最大似然法(REML)估计产羔数的遗传力,该模型中考虑的随机效应包括个体加性效应和母体永久环境效应.结果表明,母羊年龄和产羔年份对产羔数影响极显著(P< 0.01),群对产羔数影响显著(P< 0.05),其他因素均不显著(P >0.05).产羔数的遗传力为0.13,属于中等偏低遗传.表明根据表型直接选择,产羔数的遗传进展可能会慢一些. 相似文献
8.
依据调查记录的育种数据资料,运用多性状非求导约束最大似然法(multiple traits derivative free restricted maximum likelihood,MTDFREML)数学模型,对湘村黑猪繁殖性状进行了遗传参数估计。结果表明,窝总产仔数(TNB)、产活仔数(NBA)、初生窝重(LW)和21日龄窝重(LW21)的遗传力分别是0.18、0.15、0.07、0.09。母体效应率、窝效应率的变化范围分别是0.07~0.11、0.14~0.33;性状间遗传相关、永久环境相关、残差相关、表型相关范围分别为0.40~0.91、0.68~0.97、0.33~0.62、0.31~0.87。 相似文献
9.
本文以三河牛第一泌乳期测定日产奶量记录为研究材料,通过建立随机回归模型,对固定效应和随机效应(加性遗传效应和永久环境效应)配合不同阶数的legendre多项式,应用似然比及残差方差等作为综合评价指标,得到了用于测定日产奶量遗传评估的最优模型,并估计了第一泌乳期的表型和遗传变化规律。研究得出:产奶量的最适遗传评估模型为LP8-3-5;产奶量第一泌乳期遗传相关表现为:第153与第228测定日间遗传相关最高(0.943),第5与第305测定日之间存在负的遗传相关(-0.507);第228测定日遗传力最高(0.71),泌乳初期最低(0.184)。 相似文献
10.
用MTDFREML估计中国美利奴羊(新疆型)产毛性状的遗传参数 总被引：1，自引：0，他引：1
利用新疆巩乃斯种羊场饲养的2001-2005年出生的5 425只中国美利奴羊(新疆型)周岁资料,采用动物模型多性状非求导约束最大似然法(MTDFREML),估计了中国美利奴羊(新疆型)在新疆自然条件下产毛性状的遗传参数.结果表明:毛长度、剪毛后体重、产毛量和纤维直径的遗传力估计值分别为0.13、0.29、0.22和0.36. 相似文献
11.
Molina A Menéndez-Buxadera A Valera M Serradilla JM 《Journal of animal science》2007,85(11):2830-2839
A total of 88,727 individual BW records of Spanish Merino lambs, obtained from 30,214 animals between 2 and 92 d of age, were analyzed using a random regression model (RRM). These animals were progeny of 546 rams and 15,586 ewes raised in 30 flocks, between 1992 and 2002, with a total of 45,941 animals in the pedigree. The contemporary groups (animals of the same flock, year, and season, with 452 levels), the lambing number (11 levels), the combination sex of lambs with type of litter (4 levels), and a fixed regression coefficient of age on BW were included as fixed effects. A total of 7 RRM were compared, and the best fit was obtained for a model of order 3 for the direct and maternal genetic effects and for the individual permanent environmental effect. For the maternal permanent environmental effect the best model had an order 2. The residual variance was assumed to be heterogeneous with 10 age classes; the covariance between both genetic effects was included. According to the results of the selected RRM, the heritability for both genetic effects (h(a)2 and h(m)2) increased with age, with estimates of 0.123 to 0.186 for h(a)2 and of 0.059 to 0.108 for h(m)2. The correlations between direct and genetic maternal effects were -0.619 to -0.387 during the first 45 d of age and decreased as age increased, until reaching values from -0.366 to -0.275 between 45 to 75 d of age. Important changes in ranking of the animals were found based on the breeding value estimation with the current method and with the random regression procedure. The use of RRM to analyze the genetic trajectory of growth in this population of Merino sheep is highly recommended. 相似文献
12.
Maternal effects are an important source of variation in early growth and body traits in sheep but are often excluded from genetic analyses. Maternal additive genetic, maternal environmental, and cytoplasmic effects were investigated in a large Suffolk breeding scheme using a range of models involving different combinations of these effects with the direct additive genetic effect. Weights at 8 wk of age and at scanning (mean age 146 d) and ultrasonically measured muscle and fat depth were analyzed using an animal model on 55,683 (8-wk weight) and 28,947 (scanning traits) lamb records. Simple additive models always overestimated the heritability of all traits when compared to more complex models. The successive inclusion of maternal environmental, maternal genetic, and the covariance between direct and maternal additive effects in the model significantly improved the fit for almost all models and all traits, as indicated by a likelihood ratio test. Under the full model, the heritability of both weight traits was low (0.14 and 0.20 for 8-wk and scanning weight, respectively). The maternal additive and maternal environmental effects, as a proportion of the phenotypic variance, were similar (0.10 and 0.08 for 8-wk weight and 0.07 and 0.06 for scanning weight). The two scanning traits had higher heritabilities (0.29 and 0.27 for muscle depth and fat depth, respectively) with low levels of maternal genetic and maternal environmental variance. No evidence was found of a cytoplasmic effect on any of the traits studied under the full model. Breeding schemes for early growth and body traits in sheep should account for maternal effects in their genetic evaluations in order to improve their accuracy. The exact model to use will depend on the trait and individual circumstances of the scheme. 相似文献
13.
E. Negussie M. Koivula E.A. Mäntysaari & M. Lidauer 《Zeitschrift für Tierzüchtung und Züchtungsbiologie》2006,123(4):224-238
A test‐day (TD) random regression model (RRM) was described for the genetic evaluation of somatic cell score (SCS) where first and later lactations were considered as two different but correlated traits. A two‐step covariance function procedure was used to estimate variance–covariances and associated genetic parameters. Analysis of estimated breeding values (EBV), ranking of top bulls and cows and some computational aspects were used to compare RRM with TD repeatability model (RPM) and lactation average model (LAM). Residuals were analysed to assess the relative fit of TD models. Comparison between RRM and RPM showed that RRM has lower mean squared error and gave better fit to the data. For young bulls and cows, the standard deviation (SD) of EBVs was highest for RRM and lowest for LAM implying efficient utilization of information on SCS, in terms of revealing more genetic variation. A much lower correlation of EBVs ranging from 0.80 to 0.92 and significant re‐ranking of top bulls and cows were observed between RRM and LAM. The lower across‐lactation correlation between RRM and LAM indicated that LAM is directed to give more weight to first lactation breeding values. The RRM, where SCS in the first and later lactations was considered as two different but correlated traits was able to make effective use of available information on young bulls and cows, and could offer an opportunity to breeders to utilize EBVs for first and later lactations. 相似文献
14.
The genotype of an individual and the environment as the maternal ability of its dam have substantial effects on the phenotype expression of many production traits. The aim of the present study was to estimate the (co)variance components for worm resistance, wool and growth traits in Merino sheep, testing the importance of maternal effects and to determine the most appropriate model for each trait. The traits analyzed were Greasy Fleece Weight (GFW), Clean Fleece Weight (CFW), average Fibre Diameter (FD), Coefficient of Variation of FD (CVFD), Staple Length (SL), Comfort Factor (CF30), Weaning Weight (WWT), Yearling Body Weight (YWT) and Faecal worm Egg Count (FEC). The data were recorded during a 15-year period from 1995 to 2010, from Uruguayan Merino stud flocks. A Bayesian analysis was performed to estimate (co)variance components and genetic parameters. By ignoring or including maternal genetic or environmental effects, five different univariate models were fitted in order to determine the most effective for each trait. For CVFD and YWT, the model fitting the data best included direct additive effects as the only significant random source of variation. For GFW, CFW, FD, SL and CF30 the most appropriate model included direct-maternal covariance; while for FEC included maternal genetics effects with a zero direct-maternal covariance. The most suitable model for WWT included correlated maternal genetic plus maternal permanent environmental effects. The estimates of direct heritability were moderate to high and ranged from 0.15 for log transformed FEC to 0.74 for FD. Most of the direct additive genetic correlation (rg) estimations were in the expected range for Merino breed. However, the estimate of rg between FEC and FD was unfavourable (−0.18±0.03). In conclusion, there is considerable genetic variation in the traits analyzed, indicating the potential to make genetic progress on these traits. This study showed that maternal effects are influencing most of traits analyzed, thus these effects should be considered in Uruguayan Merino breeding programs; since the implementation of an appropriate model of analysis is critical to obtain accurate estimates. 相似文献
15.
F. Baldi L.G. Albuquerque M.M. Alencar 《Zeitschrift für Tierzüchtung und Züchtungsbiologie》2010,127(4):289-299
The objective of this work was to estimate covariance functions for direct and maternal genetic effects, animal and maternal permanent environmental effects, and subsequently, to derive relevant genetic parameters for growth traits in Canchim cattle. Data comprised 49 011 weight records on 2435 females from birth to adult age. The model of analysis included fixed effects of contemporary groups (year and month of birth and at weighing) and age of dam as quadratic covariable. Mean trends were taken into account by a cubic regression on orthogonal polynomials of animal age. Residual variances were allowed to vary and were modelled by a step function with 1, 4 or 11 classes based on animal’s age. The model fitting four classes of residual variances was the best. A total of 12 random regression models from second to seventh order were used to model direct and maternal genetic effects, animal and maternal permanent environmental effects. The model with direct and maternal genetic effects, animal and maternal permanent environmental effects fitted by quadric, cubic, quintic and linear Legendre polynomials, respectively, was the most adequate to describe the covariance structure of the data. Estimates of direct and maternal heritability obtained by multi‐trait (seven traits) and random regression models were very similar. Selection for higher weight at any age, especially after weaning, will produce an increase in mature cow weight. The possibility to modify the growth curve in Canchim cattle to obtain animals with rapid growth at early ages and moderate to low mature cow weight is limited. 相似文献
16.
J. Posta S. Malovhr S. Mihók I. Komlósi 《Zeitschrift für Tierzüchtung und Züchtungsbiologie》2010,127(4):280-288
The aim of this study was to estimate the genetic parameters for show‐jumping competition performance of Hungarian Sporthorses using a random regression model. There were 21 210 records from 739 horses collected in Hungary between 1996 and 2004. Performance was expressed as shifted Blom normalized ranks and as the difference between fence height and fault points. The random regression model (RRM) included fixed effects for sex, year, location, and obstacle height and random effects for animal, rider and permanent environment. Regressions for the random effects in the RRM were modelled with Legendre polynomials from first to fifth order of fit. The model focused on performance of horses from 4 to 11 years of age, with heterogeneous residual variances considered. The heritabilities were low to moderate for both variables. Genetic and phenotypic correlations between different ages decreased with increasing distance between the ages. 相似文献
17.
K. Meyer 《Zeitschrift für Tierzüchtung und Züchtungsbiologie》2005,122(2):73-85
Estimates of covariance functions and genetic parameters were obtained for growth of Angus cattle from birth to 820 days of age. Data comprised 84 533 records on 20 731 animals in 43 herds, with a high proportion of animals with 4 or more weights recorded. Changes in weights were modelled through random regression on orthogonal polynomials of age at recording. A total of 11 combinations of quadratic, cubic, quartic and quintic polynomials to model direct and maternal genetic effects and permanent environmental effects were considered. Results showed good agreement for all models at ages with many records, but differed at the highest ages and at very early ages with few weights available. Cubic polynomials appeared to be most problematic. The order of polynomial fit for permanent environmental effects of the animal dominated estimates of phenotypic variances and mean squares for residual errors. A model fitting a quartic polynomial for these effects and quadratic polynomials for the other random effects, appeared to be the best compromise between detailedness of the model which could be supported by the data, plausibility of results, and fit, measured as mean square error. 相似文献
18.
R. Morales A. Menéndez‐Buxadera C. Avilés A. Molina 《Zeitschrift für Tierzüchtung und Züchtungsbiologie》2013,130(6):425-434
The direct and maternal genetic effects were estimated for the preweaning growth of Retinta calves with a multitrait model across parities, using a longitudinal approach with random regression models (RRM). The 120 (P120) and 180 days (P180) weights (5972 calves) were considered as different traits in each calving. The heritability of direct effect across parities was on average 0.37 for P120 and 0.58 for P180, slightly higher than the estimates by univariate (0.30 and 0.56) and bivariate models (0.30 and 0.51, respectively). The heritability for maternal effects was 0.16 for P120 and 0.26 for P180 and very similar by uni‐ (0.16 and 0.23) and multivariate model (0.16 and 0.22, respectively). The correlation between direct and maternal effects by RRM showed a pronounced antagonism ?0.64 for P120 and ?0.78 for P180), likewise uni‐ (?0.62 and ?0.72) and multivariate case (?0.64 and ?0.74, respectively). The preweaning weights should be considered as different traits across parities, because the genetic correlations were different from unity. The RRM also allowed us to estimate all the parameters throughout the calving trajectory of the cow. The use of multiple traits RRM across parities can provide very useful information for the breeding programmes. 相似文献
19.
Data from the first four cycles of the Germplasm Evaluation program at the U.S. Meat Animal Research Center were used to evaluate weights of Angus, Hereford, and F1 cows produced by crosses of 22 sire and 2 dam (Angus and Hereford) breeds. Four weights per year were available for cows from 2 through 8 yr of age (AY) with age in months (AM). Weights (n = 61,798) were analyzed with REML using covariance function-random regression models (CF-RRM), with regression on orthogonal (Legendre) polynomials of AM. Models included fixed regression on AM and effects of cow line, age in years, season of measurement, and their interactions; year of birth; and pregnancy-lactation codes. Random parts of the models fitted RRM coefficients for additive (a) and permanent environmental (c) effects. Estimates of CF were used to estimate covariances among all ages. Temporary environmental effects were modeled to account for heterogeneity of variance by AY. Quadratic fixed regression was sufficient to model population trajectory and was fitted in all analyses. Other models varied order of fit and rank of coefficients for a and c. A parsimonious model included linear and quartic regression coefficients for a and c, respectively. A reduced cubic order sufficed for c. Estimates of all variances increased with age. Estimates for older ages disagreed with estimates using traditional bivariate models. Plots of covariances for c were smooth for intermediate, but erratic for extreme ages. Heritability estimates ranged from 0.38 (36 mo) to 0.78 (94 mo), with fluctuations especially for extreme ages. Estimates of genetic correlations were high for most pairs of ages, with the lowest estimate (0.70) between extreme ages (19 and 103 mo). Results suggest that although cow weights do not fit a repeatability model with constant variances as well as CF-RRM, a repeatability model might be an acceptable approximation for prediction of additive genetic effects. 相似文献