Computing numerator relationships between any pair of animals

We describe a simple method to compute the numerator relationship between any or all pairs of animals in the numerator relationship matrix. The method depends on output of the MTDFNRM program from the MTDFREML set of programs. An option of the MTDFNRM program creates a file that includes the inbreeding coefficient for each animal. The method also makes use of how the inbreeding coefficient is traditionally calculated: one-half of the relationship between the animal’s parents. To obtain the numerator relationship between any pair of animals, the original pedigree file is augmented with a dummy animal with an identification number (ID) greater than for any animal in the original pedigree file. The ID of the pair of animals for which the relationship is wanted is included as parents. MTDFNRM is then run with the option to create a file of ordered and original IDs for animals and their parents along with the inbreeding coefficients. We then multiply the inbreeding coefficient for a dummy animal by two to obtain the numerator relationship between the two animals designated as parents.

A general review of competition genetic effects with an emphasis on swine breeding

A review of previous studies is presented on estimates of genetic parameters and responses to selection with traditional breeding approaches, on correlations between agonistic behavior and growth performance, and on theoretical frameworks for selection incorporating interactions among individuals and on practical methods for incorporating competition effects in breeding programs.

Estimates of correlations among yield traits and somatic cell score with different models to adjust for bovine somatotropin effects on Holstein dairy cows

Records of Holstein cows from the Dairy Records Processing Center at Raleigh, NC were edited to obtain three data sets: 65,720 first, 50,694 second, and 65,445 later lactations. Correlations among yield traits and somatic cell score were estimated with three different models: 1) bovine somatotropin (bST) administration ignored, 2) bST administration as a fixed effect and 3) administration of bST as part of the contemporary group (herd-year-month-bST). Heritability estimates ranged from 0.13 to 0.17 for milk, 0.12 to 0.20 for fat, 0.14 to 0.16 for protein yields, and 0.08 to 0.09 for somatic cell score. Estimates were less for later than first lactations. Estimates of genetic correlations among yields ranged from 0.35 to 0.85 with no important differences between estimates with the 3 models. Estimates for lactation 2 agreed with estimates for lactation 1. Estimates of genetic correlations for later lactations were generally greater than for lactations 1 and 2 except between milk and protein yields. Estimates of genetic correlations between yields and somatic cell score were mostly negative or small (-0.45 to 0.11). Estimates of environmental correlations among yield traits were similar with all models (0.77 to 0.97). Estimates of environmental correlations between yields and somatic cell score were negative (-0.22 to -0.14). Estimates of phenotypic correlations among yield traits ranged from 0.70 to 0.95. Estimates of phenotypic correlations between yields and somatic cell score were small and negative. For all three data sets and all traits, no important differences in estimates of genetic parameters were found for the two models that adjusted for bST and the model that did not

Impact of bovine somatotropin on ranking for genetic value of dairy sires for milk yield traits and somatic cell score

Records of Holstein cows were used to examine how different models account for the effect of bovine somatotropin (bST) treatment on genetic evaluation of dairy sires for yield traits and somatic cell score. Data set 1 included 65,720 first-lactation records. Set 2 included 50,644 second-lactation records. Set 3 included 45,505 records for lactations three, four and five. Estimated breeding values (EBV) of sires were with three different animal models. With Model 1, bST administration was ignored. With Model 2, bST administration was used as a fixed effect. With Model 3, administration of bST was used to define the contemporary group (herd-year-month of calving-bST). Correlations for EBV of 1,366 sires with treated daughters between pairs of the three models were calculated for milk, fat and protein yields and somatic cell score for the three data sets. Correlations for EBV of sires between pairs of models for all traits ranged from 0.971 to 0.999. Fractions of sires with bST-treated progeny selected in common (top 10 to 15%) were 0.94 and usually greater for all pairs of models for all traits and parities. For this study, the method of statistical adjustment for bST treatment resulted in a negligible effect on genetic evaluations of sires when some daughters were treated with bST and suggests that selection of sires to produce the next generation of sires and cows might not be significantly affected by how the effect of bST is modeled for prediction of breeding values for milk, fat and protein yields and somatic cell score

Estimates of genetic parameters for Holstein cows for test-day yield traits with a random regression cubic spline model

Genetic parameters were estimated with restricted maximum likelihood for individual test-day milk, fat, and protein yields and somatic cell scores with a random regression cubic spline model. Test-day records of Holstein cows that calved from 1994 through early 1999 were obtained from Dairy Records Management Systems in Raleigh, North Carolina, for the analysis. Estimates of heritability for individual test-days and estimates of genetic and phenotypic correlations between test-days were obtained from estimates of variances and covariances from the cubic spline analysis. Estimates were calculated of genetic parameters for the averages of the test days within each of the ten 30-day test intervals. The model included herd test-day, age at first calving, and bovine somatropin treatment as fixed factors. Cubic splines were fitted for the overall lactation curve and for random additive genetic and permanent environmental effects, with five predetermined knots or four intervals between days 0, 50, 135, 220, and 305. Estimates of heritability for lactation one ranged from 0.10 to 0.15, 0.06 to 0.10, 0.09 to 0.15, and 0.02 to 0.06 for test-day one to test-day 10 for milk, fat, and protein yields and somatic cell scores, respectively. Estimates of heritability were greater in lactations two and three. Estimates of heritability increased over the course of the lactation. Estimates of genetic and phenotypic correlations were smaller for test-days further apart.

Age-of-dam adjustment factors for birth and weaning weight records of beef cattle: a review

Age-of-dam adjustment factors are used to preadjust birth and weaning weight data for national beef cattle genetic evaluations. Adjustments are used in order to make the means of the different age-of-dam subclasses similar so that a fair comparison of animals can be performed. A review was made of various research studies that have estimated age-of-dam adjustment factors for birth weight and weaning weight of beef cattle. In general, birth weight age-of-dam adjustment factors are the same across the sexes, but weaning weight age-of-dam adjustment factors differ across the sexes, with heifer calves receiving smaller adjustments than their male counterparts. Additionally, adjustment factors vary greatly across breeds. Preadjustment of records is difficult to do because a perfect estimate of adjustments is not possible. A more appropriate method for adjusting for age-of-dam is to simultaneously adjust during national genetic evaluations

Heritability estimates for carcass traits of cattle: a review

We present estimates of heritability for carcass traits of cattle published in the scientific literature. Seventy-two papers published from 1962 to 2004, which reported estimates of heritability for carcass traits, were reviewed. The unweighted means of estimates of heritability for 14 carcass traits by slaughter end point (age, weight, and fat depth) were calculated. Among the three end points, carcass weight, backfat thickness, longissimus muscle area, and marbling score were the carcass traits with the most estimates of heritability (56 is less than or equal to "n", and "n" is less than or equal to 66). The averages for these traits indicate that they are similarly and moderately heritable (0.40, 0.36, 0.40, and 0.37, respectively). However, heritability estimates for most traits varied greatly, which could be due to differences in breed groups, methods of estimation, effects in the model, number of records, measurement errors, sex, and management. Few studies have compared heritability estimates for carcass traits adjusted to different end points. Results from such studies have been inconsistent, although some studies revealed that heritability estimates for several carcass traits are sensitive to the covariate included in the model for the end point, implying that direct response to selection would be different for some traits depending on slaughter end point. The effect of different end points on estimates of heritability for many carcass traits has not been studied.