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Biomedical subjects

I Misztal

Publications and source records attributed to I Misztal.

65 records · Page 4Linked to original sources

Genetic parameters for first and second lactation milk yields of Polish black and white cattle with random regression test-day models.

Single- and two-trait random regression models were applied to estimate variance components of test-day records of milk, fat, and protein yields in the first and second lactation of Polish Black and White cattle. The model included fixed herd test-day effect, three covariates to describe lactation curve nested within age-season classes, and random regressions for additive genetic and permanent environmental effects. In two-parity models, each parity was treated as a separate trait. For milk and the two-parity model, heritabilities were in the range of 0.14 to 0.19 throughout first lactation and 0.10 to 0.16 throughout second lactation. For fat, heritabilities were within 0.11 to 0.16 and 0.11 to 0.22 throughout first and second lactations, respectively. For protein in the two-parity model, heritabilities were within 0.10 to 0.15 throughout most of first lactation and within 0.06 to 0.15 throughout the most of second lactation. For milk, genetic correlations between the first and second parities were 0.6 at the beginning of the lactation, rising to 0.9 in the middle, and 0.8 at the end of the lactation. For fat, the corresponding correlations were 0.6, 0.8, and 0.7, respectively, and for protein were 0.6, 0.8, and 0.8, respectively. Heritability estimates for all traits were flatter for the two-parity model. Relatively smooth genetic and permanent environmental variances with the two-parity model indicated that large swings of heritabilities could be artifacts of single-trait random regression models. High correlations between most of test day records across lactations suggested that a repeatability model could be considered as an alternative to a multiple-trait model to analyze multiple parities.

Algorithms↗

Estimation of the dominance variance for postweaning gain in the U.S. Limousin population.

The objective of this study was to estimate the dominance variance for postweaning gain in Limousin cattle. Data included 215,326 records of postweaning gain from 205 to 365 d, provided by the North American Limousin Foundation. Parental dominance subclasses were formed and related using the method of Hoeschele and VanRaden. Variance components were estimated using Method R based on six samples of 50%. Fixed effects in the model included contemporary group and covariates for inbreeding and breed composition (percentage Limousin). Heterozygosity was negatively correlated with breed composition (< -.99) and was therefore not included in the model. Two types of contemporary groups used as original groups from the National Cattle Evaluation were partially based on breed composition. Original contemporary groups that were too homogeneous for breed composition were replaced by herd-year-sex classes. Two models were used with the two data sets. Model 1 contained the fixed effects described above and an additive genetic effect. Model 2 included a dominance effect in addition to the effects contained in Model 1. In total, four combinations of contemporary group x model were used. Dominance variance was computed as being four times the estimated parental subclass variance. Estimates for inbreeding depression and breed composition (percentage Limousin) were all small and not greatly affected by inclusion of dominance effects or changes in contemporary groups. Estimates of the additive variance (expressed as percentage of the phenotypic variance) were only slightly affected, with values between 20 and 21%. Dominance estimates were highly affected when passing from original (10%) and to alternative contemporary groups (18%). Such large values may indicate that dominance is important for postweaning gain. Results showed the advantage of an individual dominance approach based on sire-dam combinations; therefore, expected gains through the use of specific combination ability as a part of the mating selection criteria for growth might be high.

Animals↗

Genetic parameter estimates for carcass and yearling ultrasound measurements in Brangus cattle.

Carcass measurements of 12th-rib fat thickness (CARCFAT), longissimus muscle area (CARCLMA), and weight (CARCWT) on 2,028 Brangus and Brangus-sired fed steers and heifers, as well as yearling weights (YWT) and ultrasound measures of 12th-rib fat thickness (USFAT) and longissimus muscle area (USLMA) on 3,583 Brangus bulls and heifers were analyzed to estimate genetic parameters. Data were analyzed using a six-trait animal model and an average information REML algorithm. The model included fixed effects for contemporary group and breed of dam, covariates for age at slaughter or measurement, and random animal and residual effects. Heritabilities for CARCFAT, CARCLMA, CARCWT, USFAT, USLMA, and YWT were .27+/-.05, .39+/-.05, .59+/-.06, .11+/-.03, .29+/-.04, and .40+/-.04, respectively. Genetic correlations between CARCFAT and USFAT, CARCLMA and USLMA, and CARCWT and YWT were .69+/-.18, .66+/-.14, and .61+/-.11, respectively. The favorable and moderately strong genetic correlations between carcass measurements and similar yearling breeding-animal ultrasound measurements indicate that such measurements of 12th-rib fat and longissimus muscle area are useful in predicting genetic values for carcass leanness and longissimus muscle area. Selection using yearling ultrasound measurements of breeding cattle should result in predictable genetic improvement for carcass characteristics. Inclusion of yearling ultrasound measurements for fat thickness and longissimus muscle area should enhance national cattle evaluation programs.

Adipose Tissue↗

Estimation of dominance variance in purebred Yorkshire swine.

We used 179,485 Yorkshire reproductive and 239,354 Yorkshire growth records to estimate additive and dominance variances by Method Fraktur R. Estimates were obtained for number born alive (NBA), 21-d litter weight (LWT), days to 104.5 kg (DAYS), and backfat at 104.5 kg (BF). The single-trait models for NBA and LWT included the fixed effects of contemporary group and regression on inbreeding percentage and the random effects mate within contemporary group, animal permanent environment, animal additive, and parental dominance. The single-trait models for DAYS and BF included the fixed effects of contemporary group, sex, and regression on inbreeding percentage and the random effects litter of birth, dam permanent environment, animal additive, and parental dominance. Final estimates were obtained from six samples for each trait. Regression coefficients for 10% inbreeding were found to be -.23 for NBA, -.52 kg for LWT, 2.1 d for DAYS, and 0 mm for BF. Estimates of additive and dominance variances expressed as a percentage of phenotypic variances were, respectively, 8.8 +/- .5 and 2.2 +/- .7 for NBA, 8.1 +/- 1.1 and 6.3 +/- .9 for LWT, 33.2 +/- .4 and 10.3 +/- 1.5 for DAYS, and 43.6 +/- .9 and 4.8 +/- .7 for BF. The ratio of dominance to additive variances ranged from .78 to .11.

Adipose Tissue↗

Effect of full sibs on additive breeding values under the dominance model for stature in United States Holsteins.

Differences in breeding values between dominance and additive models were examined theoretically and with field data. Data included 5.2 million records on stature from 3.0 million US Holsteins. The largest full-sib family had 29 animals, and 7% of all animals had at least one full sib. The dominance model, which accounted for dominance covariances, included the following effects: management, age, stage of lactation, permanent environment, animal additive, and parental dominance (one-quarter of dominance variance) as well as a regression coefficient for inbreeding percentage. Two reduced models were also assumed; in the first, the parental dominance effect was removed, and, in the second, the inbreeding regression coefficient was also removed. The correlations between breeding values in the three models were > 0.999, but breeding values of some animals from full-sib families changed > 5 standard deviations of parental dominance. The largest changes were observed for parents with large numbers of full-sib progeny, with limited information from parents, and without individual performance records. On average, the differences were up to four times larger for cows than for bulls and up to five times larger for dams than for sires. The greatest differences in breeding values between the dominance and the additive models were observed for dams with full-sib progeny, female full sibs, and low reliability bulls with full sibs in the extended family. Animals with large amounts of additive information as progeny-tested bulls were influenced little by the inclusion of dominance. Animals with a large proportion of information coming from animals with dominance relationships, such as cows originating via embryo transfer changed the most.

Animals↗

Influence of dominance relationships on the estimation of dominance variance with sire-dam subclass effects.

Two data sets from the USDA Livestock and Range Research Laboratory were analyzed to study dominance variance and the influence of dominance relationships. The first consisted of 4,155 birth weight (3,884 weaning weight) records of inbred USDA Line 1 Herefords. The second consisted of 8,065 birth weight (7,380 weaning weight) records from a line-cross experiment with five lines. Two models were used. Both included fixed effects of year-sex of calf and age of dam, and covariates for calving date, inbreeding of animal, and inbreeding of dam. For the second set, additional covariates were line composition and heterozygosity coefficients. Random effects were direct and maternal additive genetic, maternal permanent environment, sire-dam subclass, and residual. Model 1 considered sire-dam subclasses unrelated. Model 2 related sire-dam subclasses with a parental dominance relationship matrix. Variance components were estimated using REML. Differences between estimates with Model 1 and 2 were unimportant except for dominance variance. For the first data set, estimates with Model 2 of relative genetic direct and maternal variances, direct-maternal correlation, permanent environment, and dominance variances for birth weight were .35, .13, -.02, .03, and .25, respectively, and they were .39, .11, .04, .06 and .14 for the second data set. For weaning weight, the first data set estimates were .20, .15, -.37, .19, and .11, respectively, and they were .16, .20, -.07, .18, and .18 for the second data set. Changes, decreases and increases, in estimates of dominance variances may be due to increased information from relationships and family types other than full-sibs. The assumption of unrelated sire-dam subclasses might not be appropriate for estimation of dominance variance in populations with many dominance relationships among sire-dam classes.

Animals↗

Dominance models with method R for stature of Holsteins.

Estimates of variance components were obtained with method R for several additive and dominance models. The data included 301,960 records for first parity and 280,040 records for later parities of Holsteins. The single-record model included effects of management, regression on inbreeding percentage, age at calving, stage of lactation, and additive and dominance effects. The repeatability model included these effects in addition to permanent environment. For the single-record model, estimates were 46% of the total variance for additive variance, 12% of total variance for dominance variance, and -0.06 for the regression coefficient on inbreeding. In the repeatability model, the variance for permanent environment was estimated at 5%; other estimates were similar. When the dominance effect was eliminated, the estimate of the variance for permanent environment increased to 17% for the repeatability model. Elimination of stage of lactation increased regression on inbreeding to 0.09 and the estimate of dominance variance to 17% in the single-record model. The same change increased the estimate of additive variance to 64% for the repeatability model. Elimination of regression on inbreeding or stage of lactation had a small effect on the estimates. The presence or absence of the dominance effect had little influence on additive variance. In the absence of dominance, the estimate of the permanent environment effect included the dominance effect. Estimates of variances with method R are very sensitive to age adjustments. With the adjustments, the estimates of the dominance and additive variances are consistent.

Aging↗

Estimation of genetic parameters for somatic cell score in Holsteins.

Genetic parameters of somatic cell scores for Holstein cows were estimated using an animal model and REML for two data sets. Set 1, with 13,017 records from 5278 cows, was used to obtain variance components, heritability, and repeatability for two lactation measures: the simple average and the weighted average of test day data. Set 2, with 14,418 records from 4806 cows, was used to obtain genetic correlations for the simple average between lactations 1 and 2, between lactations 1 and 3, and between lactations 2 and 3. Simple and weighted average of test day somatic cell scores had the same heritabilities (.12) and repeatabilities (.35). Phenotypic variances were about 1.2, and herd-sire interaction variances were small (.002). Genetic correlation for somatic cell score was about .55 between lactations 1 and 2 and between lactations 1 and 3 and .65 between lactations 2 and 3. Phenotypic correlation was .20 between lactations 1 and 2, .16 between lactations 1 and 3, and .31 between lactations 2 and 3.

Animals↗

Prediction error variance and restricted maximum likelihood estimation for animal model with relationship grouping.

Genetic evaluation using animal model with relationship grouping has been shown to be feasible. However, algorithms were unavailable for prediction error variance and REML estimation of variance components. This paper shows that prediction error variance of an estimable function of the total merit of additive genetic and group effects is a simple function of a generalized inverse of the coefficient matrix for a transformed mixed model equation or of the inverse of the coefficient matrix when it is restricted to full rank. The REML algorithms, using the transformed equation, having slightly more complicated expressions than usual but could be more feasible computationally. Formulae for prediction error variance apply in general. The REML algorithms are extended to an animal model with an arbitrary number of random factors and can be extended to estimate covariance components.

Algorithms↗

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↗

Genetic analysis of dystocia and calf mortality in Israeli-Holsteins by threshold and linear models.

Calvings of 106,751 Israeli Holstein heifers were analyzed for dystocia and calf mortality, scored dichotomously, and a composite trait, scored trichotomously. Dystocia was also studied with 146,973 second and third parity records. Models fitted included herd-year-season, sex of calf, calving age, calving month, sire of cow, sire of calf, and groups of sire of cow and of calf. Herd-year-season, sire of cow and calf, and residuals were random with diagonal variance-covariance matrices. Herd-year-season variance was assume to be 10% of the residual component. Other variance components were estimated by REML for linear models and by the counterpart of REML for threshold models. Heritability estimates were two to five times greater in threshold than in linear models, but correlations between corresponding sire evaluations were all greater than .9. Linear model sire evaluations were skewed positively, whereas threshold model evaluations had symmetrical distributions. Heritability for dystocia was greater in first than in later parities. Correlations between first and later parity sire evaluations were less than .5. Thus, the genetic control of dystocia seems to be different for heifers and cows. Correlations between sire of cow and calf evaluations were less than .3. Correlations between dystocia and calf mortality evaluations were about .7.

Animals↗