L. D. Van Vleck

Estimates of genetic parameters and genetic change for reproduction, weight, and wool characteristics of Targhee sheep

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.

Estimation of genetic parameters for milk, fat, protein and mozzarella cheese production for the Italian river buffalo Bubalus bubalis population

The objective of this work was to estimate genetic parameters for the Italian population of river buffaloes. Lactation records (10,663) for milk, fat, protein and mozzarella cheese production of river buffalo cows were analyzed by fitting a multiple trait animal model using restricted maximum likelihood. The number of cows with records was 3873 with 6842 animals in the relationship matrix. mozzarella cheese production per lactation was computed by considering milk yield, and fat and protein percentages. The average lactational yields of milk, fat, protein and calculated mozzarella (kg) and fat and protein percentages were 2286.86492.1, 196.9645.6, 104.7621.7, 589.16125.4, 8.5960.85 and 4.5560.28, respectively. Heritability estimates for milk, fat, protein and mozzarella yields and fat and protein percentages were 0.14, 0.11, 0.14, 0.13, 0.17 and 0.10, respectively. Though estimates of heritability are lower than for the same traits in dairy cattle, estimates of phenotypic and genetic correlations between all traits show the possibility of developing a selection scheme to improve characteristics of milk for production of mozzarella cheese, the most important product of Italian buffaloes.

Genetic parameters of reproductive traits in sheep

Reproductive traits from 7642 ewes were recorded from 1975 to 1983. The ewes were of five breeds (Dorset (D), Finnsheep (F), Rambouillet (R), Suffolk (S) and Targhee (T)) and two composite lines [C1 (1=2F þ 1=4R þ 1=4D) and C2 (1=2F þ 1=4S þ 1=4T)]. Genetic parameters were estimated for six basic and seven composite traits. The basic traits were conception rate (CR), total number of lamb born (NLB), number of lambs born alive (NLBA), number of lambs alive at weaning (NLAW), litter mean weight per lamb born (LMWLB) and litter mean weight per lamb weaned (LMWLW). The composite traits were ratio of lambs surviving to weaning relative to NLB (LSW ¼ NLAW=NLB), number of lambs born

Estimation of genetic parameters for average daily gain using models with competition effects.

Components of variance for ADG with models including competition effects were estimated from data provided by the Pig Improvement Company on 11,235 pigs from 4 selected lines of swine. Fifteen pigs with average age of 71 d were randomly assigned to a pen by line and sex and taken off test after approximately 89 d (off-test BW ranged from 61 to 158 kg). Models included fixed effects of line, sex, and contemporary group and initial test age as a covariate, with random direct genetic, competition (genetic and environmental), pen, litter, and residual effects. With the full model, variances attributable to direct, direct-competition, genetic competition, and litter (co)variance components could be partitioned; genetic competition variance was small but statistically significantly different from zero. Variances attributable to environmental competition, pen, and residual effects could not be partitioned, but combinations of these environmental variances were estimable. Variances could be partitioned with either pen effects or environmental competition effects in the model. Environmental competition effects seemed to be the source of variance associated with pens. With pen as a fixed effect and without environmental competition effects in the model, genetic components of variance could not be partitioned, but combinations of genetic (co)variances were estimable. With both pen and environmental competition effects ignored, estimates of direct-competition and genetic competition (co)variance components were greatly inflated. With competition (genetic and environmental) effects ignored, the estimate of pen variance increased by 39%, with little change in estimates of direct genetic or residual variance. When both pen and competition (genetic and environmental) effects were dropped from the model, variance attributable to direct genetic effects was inflated. Estimates of variance attributable to competition effects were small in this study. Including environmental competition effects as permanent environmental effects in the model did not change estimates of genetic (co)variances. We concluded that including either pen effects or environmental competition effects as random effects in the model avoids bias in estimates of genetic variances but that including pen effects is much easier.

ESTIMATES OF GENETIC PARAMETERS FOR GROWTH TRAITS OF GOBRA CATTLE

Estimates of (co)variance componenfs and genefic paramefers wcre obtained for birth (no. = 3909), weaning (no. = Important materna1 effecfs were found for a11 traits. Estimates of direct heritabilities zoere substantially higher when materna1 efiects were ignored. Estimates of direct ami materna1 heritabilities with mode1 4 were 0.07 (s.e. 0.03) and 0.04 (se. @02), 0.20 (se. 0.05) and 0.21 (se. 0.05), 0.24 (s.e. 0.07) and 0.21 (se. 0.06), and 0.14 (s.e. O

Effects of social interactions on empirical responses to selection for average daily gain of boars

I6) and 0.26 (se. 0.06) for birfh, weaning, yearling and final weights, respectively. Correlations between direct and materna1 genetic effects were negative for a11 traits, and large for weaning and yearling weights witlz estimates of -0.61 (se. 0~33) and -0.50 (se. 0.31), respectively. There was a signifcant positive linear phenotypic trend for weaning and yearling weights. Linear trends for additive direct and materna1 breeding values were net signifcant for any trait except maternal breeding value for yearling weight.

Effect of pen mates on growth, backfat depth, and longissimus muscle area of swine

Effects of social interactions on responses to selection for ADG were examined with records of 9,720 boars from dam lines (1 and 2) and sire lines (3 and 4) provided by Pig Improvement Company. Each line was analyzed separately. Pens contained 15 boars. Average daily gains were measured from about 71 to 161 d of age and BW from 31 to 120 kg. Models included fixed effects of contemporary groups and initial test age as a covariate and random direct genetic (a), social genetic (c), social environmental (ce), and litter (lt) effects. Estimates of direct heritability with model 1 (the full model with a, c, ce, and lt) were 0.21, 0.28, 0.13, and 0.15 for lines 1 to 4. Estimates of heritability of social effects were near zero. Estimates of total heritable variance were 55, 52, 38, and 96% of phenotypic variance for lines 1 through 4. Empirical responses to selection with model 1 were calculated using the parameter estimates from model 1. For response of 1 genetic SD for both components (a and c), the proportions of expected total gain due to social effects (with economic weights of 1 and pen size-1 = 14) were 54, 28, 65, and 65% for the 4 lines. Genetic superiorities of the top 10% of boars were calculated for boars ranked using reduced models, but with EBV calculated using the full model (model 1). Average total breeding values (ETBV = EBV(a)+14EBV(c)) for the top 10% of boars selected with model 1 were 74.08, 94.26, 31.79, and 92.88 g for lines 1 through 4, respectively. For rankings based on model 2 (a, ce, and lt), but EBV calculated with model 1, average total breeding values for the top 10% were 68.15, 94.03, 7.33, and 84.72 g with empirical correlated responses for genetic social effects from selection for direct effects of 0.93, 1.89, -2.19, and 3.52 g for lines 1 to 4.

Prediction of genetic values for feed intake from individual body weight gain and total feed intake of the pen.

Records on final BW (kg), backfat depth (cm), and LM area (cm(2)) of pigs from a University of Nebraska Large White/Landrace composite population were analyzed to estimate the effects of pen mates. Measurements were at approximately 180 d of age for 3,524 pigs in 351 pens (9 to 11 pigs per pen) farrowed from 1999 to 2005. The area of each pen was 8.13 m(2). The full model (M1) included the fixed effects of contemporary group, sex, line, and the covariates of age and inbreeding coefficient, and included random direct genetic, genetic pen-mate, permanent environmental, pen, litter, and residual effects. A derivative-free algorithm was used to obtain REML estimates of variance components for final BW adjusted to 180 d of age with M1 and 7 reduced models, and with 4 reduced models for the carcass traits. For final BW, likelihood ratio tests showed that M1 did not fit the data better than model 2 (permanent environmental effect omitted from M1) or model 3 (pen omitted from M1). Model 2 was not significantly (P > 0.05) better than model 3, which shows that variance attributable to pen effects and permanent environmental effects cannot be separated. Large sampling variances of estimates of the pen component of variance for models with pen-mate effects also indicate an inability to separate pen effects from the effects of pen mates. When pen-mate genetic effects were not in the model, estimates of components of variance and the fit of the data were the same for models 4 (included both permanent environmental and pen effects), 6 (included pen effects), and 7 (included permanent environmental effects), which shows that including both pen and permanent environmental effects was no better than including one or the other. Models 4, 6, and 7 were significantly better than model 8, which did not include pen-mate effects and pen effects, implying that pen effects are important. The estimate of pen variance with model 2 was approximately (number of pen mates - 1) times the estimate of variance of pen-mate permanent environmental effects with model 3. Patterns of estimates of variance components with models 2, 5, 6, and 8 for backfat depth and LM area were similar to those for final BW. Estimates of direct genetic variance and phenotypic variance were similar for all models. Estimates of heritability for direct genetic effects were approximately 0.40 for final BW, 0.45 for backfat depth, and 0.27 for LM area. Estimates of heritability for pen-mate genetic effects were 0.001 for the 3 traits for models including either pen or permanent environmental effects. Under the management conditions for this experiment, the conclusion is that the model for genetic evaluation should include litter effects and either pen effects or pen-mate permanent environmental effects and possibly genetic pen-mate effects, in general agreement with the results of studies of different populations at other locations.

Genetic Relationships Between Male and Female Reproductive Traits in Beef Cattle1

Records of individual feed intake (FI) and BW gain (GN) were obtained from the Germ Plasm Evaluation (GPE) program at US Meat Animal Research Center (USMARC). Animals were randomly assigned to pens. Only pens with 6 to 9 steers (n = 289) were used for this study (data set 1). Variance components and genetic parameters were estimated using data set 1. Estimated genetic values (EGV) for FI were calculated by 5 methods using single and 2-trait analyses: 1) individual FI and individual GN, 2) individual FI alone, 3) 2-trait with individual GN but with FI missing, 4) individual GN and pen total FI, and 5) pen total FI alone. Analyses were repeated but with some of the same records assigned artificially to 36 pens of 5 and 4 paternal half sibs per pen (data sets 2 and 3). Models included year as a fixed factor and birth and weaning weights, age on test, and days fed as covariates. Estimates of heritability were 0.42 +/- 0.16 and 0.34 +/- 0.17 for FI and GN. The estimate of the genetic correlation was 0.57 +/- 0.23. Empirical responses to selection were calculated as the average EGV for the top and bottom 10% based on rank for each method but with EGV from method 1 substituted for the EGV on which ranking was based. With data set 1, rank correlations between EGV from method 1 and EGV from methods 2, 3, 4, and 5 were 0.99, 0.53, 0.32, and 0.15, respectively. Empirical responses relative to method 1 agreed with the rank correlations. Accuracy of EGV for method 4 (0.44) was greater than for method 3 (0.35) and for method 5 (0.29). Accuracies for methods 4 and 5 were greater than indicated by empirical responses and correlations with EGV from method 1. Comparisons of the 5 methods were similar for data sets 2 and 3. With data set 2, rank correlations between EGV from method 1 and EGV from methods 3, 4, and 5 were 0.47, 0.64, and 0.62. Average accuracies of 56, 75, and 75% relative to method 1 (0.67) generally agreed with the empirical responses to selection. As expected, accuracy using pen total FI and GN to obtain EGV for FI was greater than using GN alone. With data set 1, empirical response to selection with method 4 was one-third of that for method 1, although average accuracy was 65% of that for method 1. With assignment of 5 paternal half sibs to artificial pens, using pen total FI and individual GN was about 81% as effective for selection as using individual FI and GN to obtain EGV for FI and was substantially more effective than use of GN alone.

Effect of including inbreeding coefficients for animal and dam on estimates of genetic parameters and prediction of breeding values for reproductive and growth traits of Piedmontese cattle

Reproductive traits were measured for 234 bulls and 1184 heifers from matings of three dam breeds (Angus, Hereford, and MARC III) with six sire breeds (Angus, Hereford, Brahman, Boran, Tuli, and Belgian Blue) from the Germ Plasm Evaluation (GPE) Program at Roman L. Hruska US Meat Animal Research Center. Male traits were yearling scrotal circumference (YSC), height (YH), and yearling BW; age at puberty (AP1; production of 50 million sperm with ≥10% progressive motility); age, scrotal circumference, average testis length, and testicular volume when 500 million sperm were produced with ≥50% progressive motility (AP3, SC3, L3 and V3, respec