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PubMed1992

The effects of genetic and phenotypic production potential on response to recombinant bovine somatotropin.

Evidence was sought for an interaction between both phenotypic and genetic production potential and response of milk production to administration of bST in three trials of 38, 43, and 35 cows. In each trial, bST was administered in doses of 0, 10.3, 20.6, and, in trial 1 only, 41.2 mg/d for 38 wk from wk 4 of lactation. Data were analyzed for each experiment separately and combined across experiments. Analyses included separate regressions for treated and untreated animals for milk production during the production period on pretreatment production and estimated breeding value for milk production. Breeding value was estimated as the sire's estimated transmitting ability plus one-half of the maternal grandsire's estimated transmitting ability. With the exception of regression on estimated breeding value in trial 1 and in combined data, differences between treated and untreated animals in the regression of milk production on pretreatment milk production or on estimates of breeding value were not statistically significant. However, regressions on pretreatment production were substantially lower for treated than for untreated animals in each of the three trials. Regressions on breeding value estimated from sire and maternal grandsire estimated transmitting abilities were substantially, but not significantly, lower for untreated than for treated animals in all three trials. The results suggest that cows with high production potential for nongenetic reasons may show diminished response to bST, whereas cows with genetically high production potential show enhanced response. However, borderline statistical significance argues for considerable further examination before drawing firm conclusions.

Animals↗

PubMed1990

Alternative animal models with maternal effects and foster dams.

Effects of foster dams can be included in genetic evaluations using animal models with maternal effects in several ways. The alternatives discussed involve minor changes in computing strategies from strategies used with reduced animal models that predict breeding values for direct and maternal effects. The easiest alternative is to assign foster dams to groups by breed and time period and add equations for fixed effects of breed-period. Random and, assumed, independent effects of foster dams can be nested in breed-period groups. If foster dams do not repeat, then those effects can be absorbed into equations for other fixed effects, additive direct breeding value and breed-period effects by slightly modifying least squares contributions to coefficients of those equations. A third alternative for foster dams of the same breed is to add breeding values for foster dams for direct and maternal effects to solution vectors for breeding values. Equations are similar to those without foster dams, except that least squares contributions to coefficient matrix and right-hand sides are to equations for maternal breeding values and nongenetic maternal effects of foster dams rather than biological dams. Relationships and covariance between direct and maternal effects contribute mixed-model coefficients to direct and maternal breeding value equations of biological dams. This alternative basically requires only larger solution vectors for direct and maternal breeding values to accommodate foster dams that might not be included. The fourth alternative includes a vector of maternal breeding values for foster dams of each breed of foster dams and would require using rules of Westell to calculate coefficients due to relationships and fixed maternal genetic groups within each breed of foster dam. These alternatives do not require much additional computational effort compared with full or reduced animal model equations when the transformation to predict breeding values is used with Westell's rules to calculate coefficients due to relationships and genetic group effects due to prior genetic selection.

Animals↗

PubMed1992

Reduced animal model with differential genetic grouping for direct and maternal effects.

Mixed-model equations for the reduced animal model with maternal effects and different genetic grouping of unknown parents for additive direct and maternal effects are derived. The matrices that relate the expected value and the variance of the breeding values of non-parents to the parents, as well as the different contributions of parental and non-parental breeding values, to the resulting mixed-model equations are presented. Mis-specification of additive maternal variance and the additive covariance between direct and maternal effects, arising from missing information on the dams of known individuals with records, is discussed. To avoid an incorrect specification of the variance-covariance matrix of the records without having to invert a nondiagonal variance of the residual terms, the breeding values of the unknown dams of individuals with records are included in the equations. Breeding values of non-parents are back-solved after the solutions for genetic groups and breeding values of parents are computed as simply as in cases in which maternal effects are absent. A numerical example is included to illustrate the derivations.

Animals↗

PubMed2002

Genetic evaluation of carcass yield using ultrasound measures on young replacement beef cattle.

Live weight and ultrasound measures of fat thickness and longissimus muscle area were available on 404 yearling bulls and 514 heifers, and carcass measures of weight, longissimus muscle area, and fat thickness were available on 235 steers. Breeding values were initially estimated for carcass weight, longissimus muscle area, and fat thickness using only steer carcass data. Breeding values were also estimated for weight and ultrasound muscle area and fat thickness using live animal data from bulls and heifers, with traits considered sex-specific. The combination of live animal and carcass data were also used to estimate breeding values in a full animal model. Breeding values from the carcass model were less accurate and distributed more closely around zero than those from the live data model, which could at least partially be explained by differences in relative amounts of data and in phenotypic mean and heritability. Adding live animal data to evaluation models increased the average accuracy of carcass trait breeding values 91, 75, and 51% for carcass weight, longissimus muscle area, and fat thickness, respectively. Rank correlations between breeding values estimated with carcass vs live animal data were low to moderate, ranging from 0.16 to 0.43. Significant rank changes were noted when breeding values for similar traits were estimated exclusively with live animal vs carcass data. Carcass trait breeding values estimated with both live animal and carcass data were most accurate, and rank correlations reflected the relative contribution of carcass data and their live animal indicators. The addition of live animal data to genetic evaluation of carcass traits resulted in the most significant carcass trait breeding value accuracy increases for young replacements that had not yet produced progeny with carcass data.

Adipose Tissue↗

PubMed1988

Genetic evaluation of dairy goats for milk and fat yield with an animal model.

An animal model was applied to evaluate 120,073 Alpine, LaMancha, Nubian, Saanen, and Toggenburg bucks and does. Parities higher than six were excluded. The model included fixed herd-year-season and random herd-sire interaction, permanent environmental breeding value, and residual effects. Breeding value included additive genetic value and fixed accumulated group effect. A doe's records in different herds were accommodated by predicting a separate permanent environmental effect for each herd. Lactations were weighted according to lactation length. Does of all breeds were used as contemporaries. Breed differences were accounted for with a grouping strategy that grouped unknown parents by breed, sex of parent, sex of progeny, and birth year of progeny. Evaluations for milk and fat were computed as separate traits during the same processing. To achieve three-digit accuracy, 100 iterations were completed, each requiring slightly over 4 s of central processing unit time on a Cray X-MP/48 computer. Predicted producing ability was computed as sum of predicted breeding value, herd-sire interaction, and permanent environmental effects for use in ranking does on expected yield in next lactation. Evaluations of goats served as a test for the animal model evaluation system under development for dairy cattle.

Animals↗

PubMed2000

Genetic evaluation for longevity of Dutch dairy bulls.

Parameters needed for survival analysis of longevity records of cows to predict breeding values of their sires were estimated with data on Dutch Black and White and Red and White cows. The heritabilities of functional productive life were 0.041 and 0.036 on the log scale for Black and White and Red and White cows, respectively. Although the heritabilities and other parameters differed between both breeds, the resulting breeding values were hardly affected: the correlation between breeding values of Red and White bulls using either Red and White parameters or Black and White parameters was 0.992. Genetic correlations between the direct breeding value for functional longevity (based solely on longevity of sires' daughters) and breeding values for conformation, health, and fertility traits were calculated. Several alternative selection indices were investigated using these correlations. Based on the resulting reliabilities, it was concluded that the Dutch breeding value for functional longevity should be based on longevity, rump angle, teat placement, udder depth, feet and legs, and somatic cell count. The index was expressed on a scale with average of 100 and a standard deviation of 4 points (at 80% reliability). The economic value was Dfl. 65 per genetic standard deviation, which was 0.46 times the economic value of INET (Net Milk Revenue Index). For the breeding value for functional longevity that was first published in August 1999, slight modifications in the model were made.

Animals↗

PubMed2001

Monthly model for genetic evaluation of laying hens 1. Fixed regression.

1. This paper addresses the possibility of using a monthly model for the genetic evaluation of laying hens, based on the definition of a test day model with fixed regression as used in dairy cattle, in which monthly records were treated as repeated measurements of the same trait. 2. Production records of 6450 hens, daughters of 180 sires and 1335 dams were analysed using an animal model with restricted maximum likelihood (REML). The traits considered were individual monthly egg production and cumulative egg production in 11 months. Four different models were fitted to various combinations of monthly and cumulative records. The covariates were derived from the regression of Ali and Schaeffer (1987). 3. Spearman rank correlations were computed to compare breeding values from different models. Two types of correlations were computed: between individual breeding values and between sire breeding values based on subsets of full-sib records. 4. The results indicated that a monthly model with nested covariates produced higher heritability and permanent environmental variance than the models with non-nested or without covariates. The estimates of heritability obtained from monthly model were lower than the estimates from the cumulative model. The monthly model resulted in higher correlations of sire breeding values between two subsets of full-sib records than those from cumulative models. 5. In conclusion, the monthly model with nested covariates appears to be better than the model with non-nested covariates or without covariate. Although the heritability estimates obtained from the monthly model were lower, the monthly model with nested covariates could be better than the cumulative model for genetic evaluation of laying hens in the 1st cycle of laying period when using either full or part records. The use of information from odd months of production could be of interest for the evaluation of full records.

Analysis of Variance↗

PubMed1990

Absorption of equations for non-parents for an animal model with maternal effects and genetic groups.

Rules for forming the mixed-model equations for the reduced animal model with all relationships and including maternal effects have been set out by Quaas and Pollak. They also have shown how to simplify the mixed-model equations when genetic group effects are included in the model with what has become known as the Q-P transformation. Westell has given rules for calculating the coefficients for the Q-P transformed equations that are associated with the inverse of the numerator relationship matrix and genetic group effects. Those rules can be extended to include maternal effects and genetic groups for maternal as well as direct effects. As with the rules of Quaas and Pollak for the equations for the reduced animal model, a similar set of rules can be obtained for the genetic groups model after the Q-P transformation. The rules are derived easily by examining the algebraic results of absorbing the direct and maternal breeding value equations for non-parents into the parent breeding value, group and fixed effects equations. These rules involve Westell's rules and the inverse elements of the genetic (co)variance matrix for direct and maternal additive genetic effects. The rules make calculation of breeding values for parents for models including direct and maternal genetic group effects nearly as easy as for models without genetic group effects. Back solution for direct and maternal breeding values of non-parents similarly is as simple as when genetic group effects are not in the model.

Animals↗

PubMed2005

Survival analysis applied to genetic evaluation for female fertility in dairy cattle.

The objective of this research was to study whether survival analysis results in a more accurate genetic evaluation for female fertility traits compared with the usual methodology based on linear models. The fertility trait studied was interval between calving and last insemination. A stochastic simulation describing the reproductive cycle of first-parity cows was done, in which true breeding values for conception rate were created. A model containing effects of sire and herd was used both with survival analysis and with mixed linear model analysis to predict sire breeding values. Correlations between true breeding values for conception rate and breeding values for calving to last insemination predicted by the best survival analysis model or the best linear model were 0.77 and 0.68, respectively. The results showed that when pregnancy status is known, survival analysis is a better method than linear models for genetic evaluation of conception rate when using observations on the interval between calving and last insemination.

Animals↗

PubMed2001

Weighting factors of sire daughter information in international genetic evaluations.

International genetic evaluations of dairy bulls are currently based on national genetic evaluation results. Total number of daughters in a country is used to weight national information, but may not optimally reflect the precision of a sire's daughter contribution to international genetic evaluations. This study investigates the impact of alternative weighting factors on international evaluation results. A conventional progeny test scheme was simulated for two dairy cattle populations, with semen exchange at a fixed rate after each generation. True breeding values for both populations were generated as bivariate normal deviates. Each cow had three lactation records in one country only. After 10 generations of selection, all records were used in national breeding value prediction. National breeding values of bulls were used as input to international evaluations. Seven different weighting factors were evaluated: 1) total number of daughters; 2) total number of lactations; 3) as (one) also adjusted for finite contemporary group size; 4) as (three) also adjusted for distribution of daughters over contemporary groups; 5) effective daughter contribution considering finite contemporary group size and correlation between repeated records; 6) as (five) also considering the reliability of the daughter dam evaluation; and 7) as (five) also considering the reliability of the daughter female ancestors' evaluations. Using the last two weighting factors yielded empirically unbiased estimates of sire variance. Using total number of daughters overestimated genetic variance by up to 7%. In general, international breeding values were marginally affected by choice of weighting factor. The effect was larger when different national evaluation models had been applied in the two countries. International reliabilities for the last two weighting factors were close to expectation, whereas using total number of daughters resulted in 1 to 4% negative bias. In practice, different countries apply a wide range of national evaluation models, and genetic ties may be weak between some populations, thereby increasing the potential effect of weighting factors on international comparisons. The weighting factor developed in this study, which considers contemporary group structure, correlation between repeated records, and reliability of dams of daughters, should replace total number of daughters in international genetic evaluations of dairy sires.

Animals↗

PubMed1994

Adjustment factors and genetic evaluation for somatic cell score and relationships with other traits of Canadian Holsteins.

Test day SCC records were obtained from the Ontario DHI and converted to somatic cell score using a logarithmic transformation. Adjustment factors for stage of lactation and calendar month were obtained for first and later lactations. Effects of stage of lactation were significant and followed a systematic pattern. Seasonal effects were small. Sire estimated breeding values for lactation mean adjusted test day somatic cell scores were obtained from an animal model based on first, later, and all lactations, assuming a heritability of .11 and repeatability of .27. Mean accuracy of estimated breeding values for sires with at least 30 daughters was .64 for first lactation, .76 for second to fifth, and .86 for all lactations. Genetic trends for somatic cell score were not significant. The correlation of breeding values estimated from first lactations with estimates based on later lactations was .62 for sires with at least 50 daughters, which resulted in an approximate genetic correlation of .72. Correlations of sire estimated breeding values for somatic cell score from first lactation with estimated breeding values for milk, fat, protein, fat percentage, protein percentage, and milking speed were .12, .05, .11, -.09, -.02, and .20. Correlations between sire estimated breeding values for somatic cell score and type traits were generally small, but favorable with mammary system, -.13, and fore udder, -.16, and unfavorable with dairy character, .24. Somatic cell score should be considered as an auxiliary trait in dairy cattle breeding programs.

Animal Husbandry↗

PubMed1993

Efficiency of an approximate animal model for maternal and direct genetic effects of litter size in swine.

A simulated population of 120 sows and 24 boars in service per year was used to compare genetic evaluations for first-parity litter size and selection response when approximate and complete animal models were used. The complete animal model included maternal and direct effects. The approximate model did not account for covariances between maternal breeding values, or between maternal and direct breeding values, but included a random litter effect of birth of sow. After 10 yr of selection, the overall response (maternal plus direct) was 2.94, 1.61, and .77 pigs using the approximate model and 3.11, 1.65, and .67 pigs using the complete model with equal weighting of maternal and direct genetic effects in the aggregated breeding value for genetic correlations between maternal and direct effects of 0, -.5, and -.9, respectively. Higher reduction was obtained in direct genetic response that was 5, 8, and 19% lower using the approximate model than the complete model for genetic correlations of 0, -.5, and -.9, respectively. Use of the approximate model over 10 yr of selection resulted in a bias of estimation of direct genetic trend of .24, .54, and .48 pigs and in bias in estimated overall response (maternal plus direct) of -.49, .67, and 1.28 pigs for genetic correlations between maternal and direct effects of 0, -.5, and -.9, respectively. Bias in environmental trend estimated from year-season effects was of the same magnitude as the bias in estimated overall response but with an opposite sign. With the approximate model, maternal genetic response was due to a correlation between maternal genetic effects and direct EBV, which for an embedded trait such as maternal genetic effects occurred even when there was no correlation between their true genetic effects. Findings suggested that over the short term the approximate model can be used without substantial loss of overall response but the use of the complete model was recommended because of unbiased estimates in genetic and environmental trend and higher direct genetic response.

Animals↗

PubMed1985

Simulated selection for reproductive rate in beef cattle.

Computer simulation was used to evaluate four selection strategies for reproductive success in beef cattle. The strategies were no culling; culling of nonpregnant heifers; culling of nonpregnant heifers and cows nonpregnant twice; culling all nonpregnant females. In addition, simulations were conducted utilizing method four for 20 yr, then changed to method three for an additional 20 yr. Cows were removed from the herd at age 10 if not previously culled. Because reproduction is a threshold character, an underlying normally distributed liability that influences whether or not a cow will produce a calf was assumed with a heritability estimate of .2, a mean of zero and a standard deviation of one. Regressions of breeding value for reproduction and calving rate on year of selection were calculated assuming initial calving rates of 80 and 90%. Linear and quadratic effects for breeding value were present for all selection methods at both initial rates. All primary breeding value regressions were different than that for no culling. At the 90% initial calving rate, methods three and four were different from method two. There were no differences among any regressions for calving rate. Progress for breeding value was more regular than for calving rate; maximum progress for breeding value in 40 yr was approximately .32 standard deviations for selection method four. Calving rate was more erratic, although calving rate increased approximately 7% as a result of 40 yr of selection using method four at the 80% initial calving rate. It appears that much of the improvement attained by any method of selection occurred in the first 20 yr.(ABSTRACT TRUNCATED AT 250 WORDS)

Animals↗

PubMedDate not supplied

Effects of data structure on the estimation of covariance functions to describe genotype by environment interactions in a reaction norm model.

Covariance functions have been proposed to predict breeding values and genetic (co)variances as a function of phenotypic within herd-year averages (environmental parameters) to include genotype by environment interaction. The objective of this paper was to investigate the influence of definition of environmental parameters and non-random use of sires on expected breeding values and estimated genetic variances across environments. Breeding values were simulated as a linear function of simulated herd effects. The definition of environmental parameters hardly influenced the results. In situations with random use of sires, estimated genetic correlations between the trait expressed in different environments were 0.93, 0.93 and 0.97 while simulated at 0.89 and estimated genetic variances deviated up to 30% from the simulated values. Non random use of sires, poor genetic connectedness and small herd size had a large impact on the estimated covariance functions, expected breeding values and calculated environmental parameters. Estimated genetic correlations between a trait expressed in different environments were biased upwards and breeding values were more biased when genetic connectedness became poorer and herd composition more diverse. The best possible solution at this stage is to use environmental parameters combining large numbers of animals per herd, while losing some information on genotype by environment interaction in the data.

Analysis of Variance↗

PubMed2006

Effect of carcass price fluctuations on genetic and economic evaluation of carcass traits in Japanese Black cattle.

The objectives of this study were 1) to investigate the effect of changes in carcass market prices due to bovine spongiform encephalopathy (BSE) occurrences on estimates of genetic parameters and economic weights for carcass traits; and 2) to compare direct and indirect approaches for prediction of genetic merit of Japanese Black cattle for profitability of their progeny. The direct approach utilized estimated breeding values of carcass prices, whereas in the indirect approach, selection indices were constructed as products of economic weights and breeding values of component traits. Data were composed of 80,191 carcass records divided into 5 periods based on changes in carcass prices as a result of occurrences of BSE in Japan and the United States. The periods ranged from a period before occurrence of BSE in Japan to a period of beef import restrictions and a rise in prices. Carcass traits analyzed included HCW, LM area, rib thickness, subcutaneous fat thickness, and marbling score (MS). Price traits included carcass unit price and carcass sale price. Estimates of heritability for price traits were moderate (0.32 to 0.46) and slightly sensitive to changes in carcass market prices. Genetic correlations of HCW and LM area with price traits increased and that between MS and carcass sale price decreased with period, whereas estimates of genetic correlation between MS and carcass unit price were high in all periods (0.96 to 0.98). Economic weights for carcass traits varied with periods because carcass prices were highly sensitive to economic importance of traits. Nevertheless, correlations between within-period breeding values for price traits estimated using direct and indirect approaches were high (0.92 to 0.99). This result indicates that selection realized by direct and indirect approaches will provide very similar results. A comparison among within-approach breeding values estimated in different periods showed that the largest differences in breeding values of sires for price traits were between the periods after occurrences of BSE in Japan and in the United States. Economic effects of BSE occurrences influenced the importance of carcass traits and economic merits of price traits through a change of carcass prices from period to period, irrespective of the approach taken in determining the genetic merit of breeding animals for profitability of their progeny.

Animals↗

PubMed2004

Estimation of genetic parameters based on individual and group mean records in laying hens.

(1) The study was conducted to estimate the heritability, genetic correlations and breeding values of laying hens based on individual records and group mean records. (2) Records of two pure lines from a commercial breeding programme of White Leghorns from three generations housed in single cages and in group cages were used. A total of 8483 and 8817 individual records of lines A and D, respectively, and a total of 1358 (line A) and 1161 (line D) group mean records were analysed. (3) An animal model using Restricted Maximum Likelihood (REML) was used to estimate variance components of individual records. Group mean records were analysed using the sire model, taking heterogeneity of error variance and correlated residual effects into account. Breeding values of sires were estimated based on the BLUP method using a multivariate sire model. Spearman Rank correlations were used to compare sire breeding values estimated from individual records and from group mean records. The traits studied were monthly egg production, cumulative production and egg weight. (4) Heritability estimates based on individual records were higher than from group mean records. Heritabilities for cumulative production records were higher than for monthly production, based on individual as well as group mean records. The estimates of genetic correlations between monthly egg production and cumulative production were moderate to high. Egg production and egg weight recorded individually were highly genetically correlated with those recorded on group means. Sire breeding values estimated from individual records showed high correlations with those from group mean records. (5) Differences in the ranking of sire breeding values estimated from individual vs group mean records were negligible, indicating that no genotype x environment interaction exists. Selection based on individual performance records of laying hens housed in single cages could give a good response on performance of laying hens housed in group cages. Cumulative egg production over periods 1 to 6 is the best trait for the selection programme.

Animals↗

PubMed1993

Development of an animal model for across-herd genetic evaluation of number born alive in swine.

An animal model and computer software were developed to conduct across-herd genetic evaluations using data from producers participating in the Sow Productivity Index program of the American Yorkshire Club. The final data set consisted of 61,596 litter records from 1986 to early 1990. The animal model included fixed contemporary group effects and random additive direct, service sire, permanent environmental, and residual effects. Additive genetic relationships among animals were included. A separate relationship matrix for service sires and their sires was also included. A data set similar to the Yorkshire field data was simulated to use in testing the animal model. The simulated data set consisted of 40 herds, each with 120 reproducing dams and either four or five sires. Six generations of simulated data were produced, resulting in 20,605 litter records. These records were then evaluated using the animal model for number of pigs born alive. Finally, correlations between the true breeding values from the simulation and the predicted breeding values were computed. The correlation between the 918 true and predicted sire breeding values was considerably lower for the animal model without a service sire effect than when it was included (.53 vs .74, respectively). However, the difference was cut in half (.66 vs .77) when only sires with greater than five daughter records were included. The high accuracy of the animal model with a random service sire effect indicates that the proposed model adequately accounts for the variation found in records for number of pigs born alive.

Animals↗

PubMed2006

Genetic analysis of gain from birth to weaning, milk production, and udder conformation in Line 1 Hereford cattle.

The objective of this research was to partition phenotypic variation in calf gain from birth to weaning, and milk production measured, by the weigh-suckle-weigh method, and udder score of cows into genetic and nongenetic components. Data were from the Line 1 Hereford population maintained by USDA-ARS at Miles City, MT, and included observations of pre-weaning gain (n = 6,835) from 2,172 dams, milk production (n = 692) from 403 cows, and udder score (n = 1,686) from 622 cows. Data were analyzed using a Gibbs sampler for multiple-trait animal models. Results are reported as means +/- SD derived from the posterior distributions of parameter estimates. Mean estimates of the phenotypic variance of preweaning gain, milk production, and udder score were 476.3 kg2, 8.88 kg2, and 1.89 (1 to 9 scale), respectively. Estimates of phenotypic correlations between preweaning gain and milk production, preweaning gain and udder score, and milk production and udder score were 0.37 +/- 0.04, - 0.07 +/- 0.04, and - 0.09 +/- 0.05, respectively. Estimates of heritability for direct and maternal preweaning gain, milk production, and udder score were 0.13 +/- 0.03, 0.25 +/- 0.04, 0.25 +/- 0.06, and 0.23 +/- 0.05, respectively. Genetic correlations of milk production with maternal preweaning gain and udder score were estimated as 0.80 +/- 0.08 and - 0.36 +/- 0.16, respectively. Posterior distributions of the other genetic correlations all contained 0.00 within the respective 90% probability density posterior intervals. Estimates of repeatability of maternal preweaning gain, milk production, and udder score were 0.43 +/- 0.03, 0.39 +/- 0.05, and 0.34 +/- 0.03, respectively. Breeding value for maternal gain from birth to weaning was highly predictive of breeding value for milk production. Direct measurement of milk production to use in genetic improvement may not be justified because it is difficult to measure, and selection based on the breeding value for maternal preweaning gain may be nearly as effective in changing milk production as direct selection. A potentially undesirable consequence of selection to increase milk production is the degradation of udder quality. However, this correlation is not so strong as to preclude simultaneous improvement of milk production and udder quality using appropriate predicted breeding values for each trait.

Animals↗