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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 us- ing 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) in- dividual 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 ge- netic 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 cor- relations 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. Compari- sons 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, empiri- cal 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 pater- nal 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.

Birth weight (BW), weaning weight (WW), 6-month weight (W6), 9-month weight (W9) and yearling weight (YW) of Kermani lambs were used to estimate genetic parameters. The data were collected from Shahrbabak Sheep Breeding Research Station in Iran during the period of 1993-1998. The fixed effects in the model were lambing year, sex, type of birth and age of dam. Number of days between birth date and the date of obtaining measurement of each record was used as a covariate. Estimates of (co)variance components and genetic parameters were obtained by restricted maximum likelihood, using single and two-trait animal models. Based on the most appropriate fitted model, direct and maternal heritabilities of BW, WW, W6, W9 and YW were estimated to be 0.10 +/- 0.06 and 0.27 +/- 0.04, 0.22 +/- 0.09 and 0.19 +/- 0.05, 0.09 +/- 0.06 and 0.25 +/- 0.04, 0.13 +/- 0.08 and 0.18 +/- 0.05, and 0.14 +/- 0.08 and 0.14 +/- 0.06 respectively. Direct and maternal genetic correlations between the lamb weights varied between 0.66 and 0.99, and 0.11 and 0.99. The results showed that the maternal influence on lamb weights decreased with age at measurement. Ignoring maternal effects in the model caused overestimation of direct heritability. Maternal effects are significant sources of variation for growth traits and ignoring maternal effects in the model would cause inaccurate genetic evaluation of lambs.

This study examined competition effects on ADG in the feedlot of 1,882 Hereford bulls representing 8 birth years from a selection experiment. Each year, 8 feedlot pens were used to feed bulls in groups, with 2 pens nested within each of the 4 selection lines. Gains were recorded for up to 8 periods of 28 d. Models for analyses included pen effects (fixed or random), fixed effects such as year and line, and random direct genetic, competition genetic (and in some analyses competition environmental), and environmental effects. Each pen mate as a competitor affected the records of all others in the pen. All lines traced to common foundation animals, so the numerator relationships among and within pens were the bases for separating direct and competition genetic effects and pen effects. For this population and pen conditions (average of 30 bulls per pen), the major results were 1) competition genetic effects seemed present for the first 28-d period but not for the following 7 periods; 2) models with pens considered as fixed effects could not separate variances and covariance due to direct and competition genetic effects; 3) models without competition effects had large estimates of the variance component due to pen effects for gain through 8 periods; and 4) models with genetic and environmental competition effects accounted for nearly all of the variance traditionally attributed to pen effects (even though estimates of the competition variance component were small, the estimates of pen variance were near zero).

Adjustment factors to allow comparison of EPD from several breed associations for birth, weaning, and yearling weights have been available for more than 10 yr. This paper describes steps to calculate adjustment factors for EPD for 4 carcass traits: marbling score, fat thickness, ribeye area, and retail product percentage. The required information is the same as for the weight traits: 1) breed of sire solutions based on measurements on progeny at the US Meat Animal Research Center (USMARC) that have sires with breed association EPD, 2) mean EPD of sires weighted by number of progeny at USMARC (USMARC progeny not included in breed association EPD), and 3) mean EPD of nonparents from breed associations (defined as animals born 2 yr prior to calculation of EPD). Records at USM-ARC are adjusted to 100% heterozygosity because the purpose of the adjustment factors is to allow prediction of performance of progeny of sires mated to other breeds of dam. A critical step is to adjust breed of sire solutions, which are based on an earlier sample of sires, to the equivalent of a sample from a more recent nonparent group using the difference between mean EPD from information sources 2) and 3). The difference is multiplied by the coefficient of regression of USMARC progeny on EPD of their sires. With weight traits, these coefficients are not greatly different from unity. With the carcass traits, 2 sets of coefficients can be used depending on whether the EPD are based on carcass or ultrasound measurements. The regression coefficients also reflect differences in conditions for USMARC progeny (all steers) and factors associated with breed association EPD. Only for marbling score and ribeye area were any estimates of the regression coefficients near unity. For other traits, the coefficients ranged from 1.65 to 2.82. The solutions for breed of sire, differences in mean EPD, and regression coefficients are then used to calculate adjustment factors for EPD of 11 breeds including the arbitrary base breed, Angus.

The widespread use of the set of multiple-trait derivative-free REML programs for prediction of breeding values and estimation of variance components has led to significant improvement in traits of economic importance. The initial version of this software package, however, was generally limited to pedigree-based relationships. With continued advances in genomic research and the increased availability of genotyping, relationships based on molecular markers are obtainable and desirable. The addition of a new program to the set of multiple-trait derivative-free REML programs is described that allows users the flexibility to calculate relationships using standard pedigree files or an arbitrary relationship matrix based on genetic marker information. The strategy behind this modification and its design is described. An application is illustrated in a QTL association study for canine hip dysplasia.

The objective was to describe genetic parameters and genetic changes in litter sizes at birth and weaning (LB and LW, n = 9081), birth weight (BW, n = 11,896), weaning weight (WW, n = 11,104), fleece weight and grade (FW and FG, n = 8872), and staple length (SL, n = 1805) of Polypay sheep. Direct heritability estimates from single-trait analyses were 0.11 for LB, 0.02 for LW, 0.17 for BW, 0.18 for WW, 0.68 for FW, 0.36 for FG, and 0.76 for SL. Estimates of direct genetic correlation were 0.40 between LB and LW, 0.57 between BW and WW, 0.65 between FW and SL, − 0.37 between FW and FG and − 0.70 between SL and FG. Breeding values (BV) from both single-trait and seven-trait analyses calculated using the parameters estimated from single-trait and two-trait analyses were compared across years of birth with respect to genetic trends. Estimated BV from both analyses for LB, LW, BW, WW and FW increased over time, while those for FG and SL were unchanged. Estimated changes in BV over time did not differ substantially for single-trait and seven-trait analyses, except for traits highly correlated with another trait that was responding to selection (i.e., LB, which was highly correlated to both LW and WW).

This study compared genetic evaluations from 3 test-day (TD) models with different assumptions about the environmental covariance structure for TD records and genetic evaluations from 305-d lactation records for dairy cows. Estimates of genetic values of 12,071 first-lactation Holstein cows were obtained with the 3 TD models using 106,472 TD records. The compound symmetry (CS) model was a simple test-day repeatability animal model with compound symmetry covariance structure for TD environmental effects. The ARs and ARe models also used TD records but with a first-order autoregressive covariance structure among short-term environmental effects or residuals, respectively. Estimates of genetic values with the TD models were also compared with those from a model using 305-d lactation records. Animals were genetically evaluated for milk, fat, and protein yields, and somatic cell score (SCS). The largest average estimates of accuracy of predicted breeding values were obtained with the ARs model and the smallest were with the 305-d model. The 305-d model resulted in smaller estimates of correlations between average predicted breeding values of the parents and lactation records of their daughters for milk and protein yields and SCS than did the CS and ARe models. Predicted breeding values with the 3 TD models were highly correlated (0.98 to 1.00). Predicted breeding values with 305-d lactation records were moderately correlated with those with TD models (0.71 to 0.87 for sires and 0.80 to 0.87 for cows). More genetic improvement can be achieved by using TD models to select for animals for higher milk, fat, and protein yields, and lower SCS than by using models with 305-d lactation records.

The objective of this study was to compare test-day (TD) models with autoregressive covariance structures for the estimation of genetic and environmental components of variance for milk, fat and protein yields, and somatic cell score (SCS) in Holstein cows. Four models were compared: model I (CS model) was a simple TD repeatability animal model with compound symmetry covariance structure for environmental effects, model II (ARpe model) and model III (ARe model) had first-order autoregressive covariance structures for TD permanent or residual environmental effects, respectively, and model IV (305-d model) was a simple animal model using 305-d records. Data were 106,472 first-lactation TD records of 12,071 Holstein cows calving from 1996 through 2001. Likelihood ratio tests indicated that ARpe and ARe models fit the data significantly better than the CS model. The ARe model resulted in slightly smaller estimates of genetic variance and heritability than did the CS model. Estimates of residual variance were always smaller with the CS model than with the ARe model with the autoregressive covariance structure among TD residual effects. Estimates of heritability with different TD models were in the range of 0.06 to 0.11. The 305-d model resulted in estimates of heritability in the range of 0.11 to 0.36. The autoregressive covariance structure among TD residual effects may help to prevent bias in heritability estimates for milk, fat and protein yields, and SCS.

The objective was to determine appropriate analytical models considering cytoplasmic inheritance for birth weight (BWT, n=35,604), weaning weight (WWT, n=34,114), fleece weight (FWT, n=38,113) and number born (NB, n=39,029) for Rambouillet sheep. For BWT, models that included dam by year, dam by number born, and sire by dam effects, in addition to direct and maternal effects, were significantly better than the basic maternal effects model. For WWT, variances due to direct, maternal, and maternal permanent environmental effects (0.05 of variance) were not zero. For FWT, heritability was 0.55 for all models, but models with dam by year (0.02), sire by dam (0.05), and sire by cytoplasmic line (0.02) were jointly significantly better than models with permanent environmental effects. For NB, only direct heritability (0.08) and relative permanent environmental variance (0.04) were not zero. No trait showed evidence of variation due to cytoplasmic effects. Adding seldom considered effects to the model did not change estimates of variance due to direct and maternal genetic effects. Variance due to dominance effects may be important for BWT and FWT. The basic direct-maternal effects model seems sufficient for genetic evaluations for WWT and FWT but models for BWT and NB may need to include other effects.

Rams express differences in sexual performance during the breeding season. Breeding rams with high sexual performance scores as measured during a sexual performance test can improve flock fertility. Whether selecting rams for high sexual performance score will indirectly improve ewe reproductive performance is not known. The objective of this study was to estimate the genetic correlation between sexual performance scores of rams and reproduction of ewes. Sexual performance scores of rams and reproductive performance (number of lambs born per ewe exposed and number of lambs weaned per ewe exposed) from four breeds were analyzed with univariate and bivariate animal models using REML. A total of 4685 records for sexual performance scores of rams were obtained from the US Sheep Experiment Station (Columbia, n = 807; Polypay, n = 1668; Rambouillet, n = 1208; and Targhee, n = 1002). Reproductive performance of ewes was based on 35,154 records (Columbia, n = 7693; Polypay, n = 9229; Rambouillet, n = 10,954; and Targhee, n = 7278). Estimates of heritability for sexual performance score of rams were larger for the Columbia (0.31 ± 0.09) and Polypay (0.30 ± 0.08) than that for Rambouillet (0.14 ± 0.07) and Targhee breeds (0.17 ± 0.08). Overall breed heritability estimate was 0.22 ± 0.04. Heritability estimates for number of lambs born were larger (0.05–0.11) than for number of lambs weaned (0.02–0.05). Estimates of genetic correlation between sexual performance score and number of lambs born were near zero (−0.09 to 0.02) except for the Columbia breed (0.24 ± 0.20). Estimates of genetic correlation between sexual performance score of the ram and number of lambs weaned varied by breed (Columbia, 0.28 ± 0.26; Polypay, 0.00 ± 0.25; Rambouillet, −0.17 ± 0.25; and Targhee, 0.32 ± 0.28). Overall breed genetic correlations of sexual performance of rams with number of lambs born and weaned were 0.00 ± 0.10 and 0.00 ± 0.12, respectively. Because of the low heritability of ewe reproductive traits and their apparently nil to low genetic correlation with sexual performance scores of rams, selection and use of rams with high

Calving difficulty, survival from birth to weaning, birth weight, and weaning weight of 167 calves and carcass traits of 88 cattle (63 for adjusted fat thickness) were compared for progeny of Red Poll and Longhorn bulls mated to crossbred cows that calved at 2 or 3 yr of age. Results indicated that Longhornsired calves required 28% less assistance at calving than Red Poll-sired calves when dams calved at 2 yr of age (P≤0.05), but there was no difference between Red Poll- and Longhorn-sired calves for calving difficulty with 3-yr-old cows. Red Poll-sired calves had significantly greater birth and weaning BW than did Longhorn-sired calves for 2-yr-old dams. Significant differences attributable to sire breed were found only for bone percentage of progeny of 3-yr-old dams, but not for carcass weight, fat thickness, longissimus area, USDA quality grades, and percentages retail product, fat trim, or bone. There was a significant interaction between sire breed and age of dam only for calving difficulty. Within sire breed, calving difficulty of 2-yr-old dams was greater than that for 3-yr-old dams, and calves from 2-yr-old dams also were significantly lighter at weaning than were calves from 3-yr-old dams (P

Birth weights (4,155) and weaning weights (3,884) of Line 1 Herefords collected at the Fort Keogh Livestock and Range Research Laboratory in Miles City, MT, between the years of 1935 to 1989 were available. To study the effect of misidentification on esti- mates of genetic parameters, the sire identification of calf was randomly replaced by the identification of an- other sire based on the fraction of progeny each sire contributed to a yearly calf crop. Misidentification rates ranged from 5 to 50% with increments of 5%. For each rate of misidentification, 100 replicates were obtained and analyzed with single-trait and two-trait analyses with a restricted maximum likelihood (REML) algo- rithm. Two different models were used. Both models contained year × sex combinations and ages of dam as fixed effects, calendar birth date as a fixed covariate, and random animal and maternal genetic effects and maternal permanent environment effects. Model 2 also included sire × year combinations as random effects. As the rate of misidentification increased, estimates of the

Genetic parameters for lifetime production for cows with the opportunity to produce from 2 through 7 yr of age, as measured by the number of calves born (NB2, ..., NB7), the number of calves weaned (NW2, ..., NW7), and cumulative weaning weight (CW2, ..., CW7), were estimated using data from 3,064 Hereford cows from a selection experiment with a control line (CTL) and three lines selected for weaning weight (WWL), yearling weight (YWL), and an index of yearling weight and muscle score (IXL). Weaning weights were adjusted to 200 d of age and for sex and age of dam. Estimates of heritability and genetic and environmental correlations were obtained by restricted maximum likelihood with bivariate animal models, with year of birth of the cow as a fixed effect and direct genetic and residual as random effects. Genetic trends were estimated by regressing means of estimated breeding values by year of birth and line on birth year. Estimates of heritability (SE) for opportunity groups of 2 to 7 yr of age ranged from 0.08 (0.03) to 0.16 (0.05) for NB; from 0.05 (0.02) to 0.16 (0.05) for NW; and from 0.06 (0.02) to 0.16 (0.05) for CW. Estimates of genetic correlations (SE) among NB traits ranged from 0.60 (0.14) to 1.00 (0.00), and estimates of environmental correlations (SE) ranged from 0.67 (0.02) to 0.99 (0.00). For NW, estimates of genetic and environmental correlations ranged from 0.98 (0.11) to 1.00 (0.00) and from 0.65 (0.02) to 0.99 (0.00), respectively. Estimates of genetic correlations (SE) among CW traits ranged from 0.94 (0.08) to 1.00 (0.00). Estimates of environmental correlations (SE) ranged from 0.66 (0.02) to 0.99 (0.00). Estimates of genetic correlations for NB2 with all definitions of NW ranged from 0.47 (0.18) to 0.71 (0.12), and with all definitions of CW ranged from 0.55 (0.16) to 0.80 (0.11). Estimates of genetic correlations between NW2 and all definitions for CW ranged from 0.95 (0.02) to 0.99 (0.06). Estimates of annual genetic (SE) change were negligible for NB2, NB6, NW2, and NW6 for all lines. Estimates of annual genetic (SE) change for CW2 were 0.85 (0.11), 0.79 (0.14), 0.51 (0.10), and 0.52 (0.18) kg/yr, and for CW6 were 5.01 (1.25), 2.64 (1.75), 3.67 (1.16), and 3.33 (2.37) kg/yr for WWL, YWL, IXL, and CTL, respectively. Selection for lifetime production as measured by NB, NW, or CW could be effective but would be relatively slow due to low estimates of heritability and to increased generation intervals.

Genetic parameters for length of productive life given the opportunity (LPL/O), measured as days between first calving and disposal conditioned on one of six opportunity groups, L1 through L6 (e.g., L2 is length of productive life in days given the opportunity to live 2 yr after first calving), and lifetime production (LP), measured as the number of calves born (NB), number of calves weaned (NW), and cumulative weaning weight (CW) by 6 yr after first calving, were estimated using records of 1,886 Hereford cows from a selection experiment with three selected lines and a control line. Weaning weights were adjusted to 200 d of age and for sex and age of dam. Estimates of heritability and genetic and environmental correlations were obtained by restricted maximum likelihood with bivariate animal models, with year of birth of cow as a fixed effect and direct genetic and residual as random effects. Genetic trends were estimated by regressing means of estimated breeding values by year of birth and line on birth year. Estimates of heritability (SE) for LPL/O ranged from 0.05 (0.01) to 0.15 (0.03). Estimates of genetic correlations (SE) among LPL/O ranged from 0.74 (0.14) to 1.00 (0.00), and estimates of environmental correlations ranged from 0.67 (0.05) to 0.98 (0.01). Estimates of heritability (SE) for NB, NW, and CW were 0.17 (0.05), 0.21 (0.06), and 0.18 (0.01). Estimates of genetic correlations (SE) among NB, NW, and CW ranged from 0.96 (0.02) to 0.99 (0.01). Estimates of environmental correlations (SE) ranged from 0.93 (0.01) to 0.99 (0.01). Estimates of genetic correlations for L6 with NB, NW, and CW were near 1.00 (0.09). Estimates of environmental correlations (SE) ranged from 0.57 (0.03) to 0.60 (0.03). Estimates of genetic change per year (SE) for L6 were low for all lines and ranged from -3.53 (2.09) to 4.63 (2.11) d/yr. Genetic trends for NB and NW were negligible for all lines. Genetic trends for CW were low and ranged from -2.81 (1.67) to 3.29 (1.76) kg/yr. Differences in genetic trends between selected lines and control were not significant (P > 0.05). Estimates of environmental trends (SE) over all lines were -104.00 (25.48) d/yr, -0.26 (0.02) calves/yr, -0.25 (0.02) calves/yr, and -55.10 (15.63) kg/yr, for L6, NB, NW, and CW, respectively. Selection for LPLIO or LP could be successful in a breeding program, but may be relatively slow due to the low magnitude of heritability and extended generation interval.

Data from the first four cycles of the Germplasm Evaluation Program at the U.S. Meat Animal Research Center (USMARC) were used to investigate genetic relationships between mature weight (MW, n = 37,710), mature weight adjusted for body condition score (AMW, n = 37,676), mature height (HT, n = 37,123), and BCS (n = 37,676) from 4- to 8-yr old cows (n = 1,800) and carcass traits (n = 4,027) measured on their crossbred paternal half-sib steers. Covariance components among traits were estimated using REML. Carcass traits were adjusted for age at slaughter. Estimates of heritability for hot carcass weight (HCWT); percentage of retail product; percentage of fat; percentage of bone; longissimus muscle area; fat thickness adjusted visually; estimated kidney, pelvic, and heart fat percentage; marbling score; Warner-Bratzler shear force; and taste panel tenderness measured on steers were moderate to high (0.26 to 0.65), suggesting that selection for carcass and meat traits could be effective. Estimates of heritability for taste panel flavor and taste panel juiciness were low and negligible (0.05 and 0.01, respectively). Estimates of heritability from cow data over all ages and seasons were high for MW, AMW, and HT (0.52, 0.57, 0.71; respectively) and relatively low for BCS (0.16). Pairwise analyses for each female mature trait with each carcass trait were done with bivariate animal models. Estimates of genetic correlations between cow mature size and carcass composition or meat quality traits, with the exception of HCWT, were relatively low. Selection for cow mature size (weight and/or height) could be effective and would not be expected to result in much, if any, correlated changes in carcass and meat composition traits. However, genetic correlations of cow traits, with the possible exception of BCS, with HCWT may be too large to ignore. Selection for steers with greater HCWT would lead to larger cows.

Breeds were compared for differences in BW (n = 56,731), heights (n = 51,407) and body condition scores (BCS, n = 56,371) of 2- to 8-yr-old cows from four cycles of the Germplasm Evaluation (GPE) Program at the U. S. Meat Animal Research Center (MARC). Angus, Hereford, and topcross cows from 22 breeds of sires were produced. The mixed model for repeated measures of BW, height, and BCS included random additive genetic and permanent environmental effects of the cow. Differences among crosses were significant for all traits. In general, BW, within cycle, was greater for cows sired by breeds of large size and low milk production (Chianina and Charolais) than for those of large size and moderate milk production (Maine Anjou, Salers, and Shorthorn), moderate size and moderate milk production (Angus and South Devon), moderate size and low milk production (Hereford), and small size and low milk production (Galloway and Longhorn). Breeds of moderate size and moderately high milk production (Pinzgauer, Red Poll, and Tarentaise) were even lighter. Cows with Jersey sires were separated from all other breed groups because of light BW. Cows with sires of British origin tended to be lighter than those of continental European origin. Cows with Bos indicus sires (Brahman and Nellore) ranked between other breeds of large and moderate size for BW or for BW adjusted for BCS. In general, adjustment for BCS did not alter rankings of breed groups for differences in cow BW. Differences among breed groups for height closely followed differences for BW.

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 F 1 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.

Breed differences for weight (CW), height (CH), and condition score (CS) were estimated from records (n = 12,188) of 2- to 6-yr-old cows (n = 744) from Cycle IV of the U.S. Meat Animal Research Center's Germplasm Evaluation (GPE) Program. Cows were produced from mating Angus and Hereford dams to Angus, Hereford, Charolais, Shorthorn, Galloway, Longhorn, Nellore, Piedmontese, and Salers sires. Samples of Angus and Hereford sires were 1) reference sires born from 1962 through 1970 and 2) 1980s sires born in 1980 through 1987. The mixed model included cow age, season of measurement and their interactions, year of birth, pregnancy-lactation code (PL), and breed-group as fixed effects for CW and CS. Analyses of weight adjusted for condition score included CS as a linear covariate. The model for CH excluded PL. Random effects were additive genetic and permanent environmental effects associated with the cow. Differences among breed groups were significant (P < 0.05) for all traits and were maintained through maturity with few interchanges in ranking. The order of F 1 cows for weight was as follows: Charolais (506 to 635 kg for different ages), Shorthorn and Salers, reciprocal Hereford-Angus (HA) with 1980s sires, Nellore, HA with reference sires, Galloway, Piedmontese, and Longhorn (412 to 525 kg for different ages). Order for height was as follows: Nellore (136 to 140 cm), Charolais, Shorthorn, Salers, HA with 1980s sires, Piedmontese, Longhorn, Galloway and HA with reference sires (126 to 128 cm). Hereford and Angus cows with reference sires were generally lighter than those with 1980s sires. In general, breed differences for height followed those for weight except that F 1 Nellore cows were tallest, which may in part be due to Bos taurus-Bos indicus heterosis for size.

The objectives of this study were to estimate (co)variance components for growth and feed efficiency measures, and to compare selection strategies to improve economic efficiency of gain. Variance components for pre- and postweaning growth, body weight, and measures of feed efficiency were estimated from data collected on 1,047 Targhee lambs over 7 yr. Approximately 21 d after weaning, lambs were group-fed for 4 wk, with ad libitum access to a diet of 37% whole barley grain and 63% pelleted alfalfa hay. Lambs were then individually fed for 6 wk. Lambs were then returned to group feeding for another 4-wk period. The mean feed conversion ratio (gain/intake) for the individual feeding period was 0.11. Mean postweaning ADG for the total 14-wk feeding period was 0.26 kg. (Co)variance components were estimated from single- and two-trait animal models using REML. The selection strategies compared included direct selection, index selection, and restricted index selection. Estimates of (co)variances derived from single- and two-trait models were similar, except for mid-test body weight. Preweaning growth had a low heritability estimate (0.03 +/- 0.04) compared with postweaning growth measures (0.25 to 0.39), but all measures of growth were highly correlated (r2 > 0.98). Heritability estimates of measures of gain efficiency were variable (total feed intake = 0.39; feed conversion ratio = 0.26; residual feed intake = 0.26). Total feed intake was strongly correlated genetically with feed conversion ratio (0.79) and residual feed intake (0.77). The estimate of genetic correlation between feed conversion ratio and residual feed intake was low (0.23). Comparison of selection strategies showed the superiority of index selection (ADG, total feed, body weight) for economic improvement compared with other strategies. Economic response to direct selection for ADG was at least twice that for direct selection for feed conversion ratio or against total feed intake, and that for restricted indices (selecting against residual feed, while holding body weight and/or gain constant). Selection for ADG may be a practical approach for indirectly improving efficiency of gain in lambs.

Statistical models (16) were compared for birth weight of 24,741 Columbia lambs recorded at the U.S. Sheep Experiment Station (USSES; 1950 to 1998). The goal was to estimate fractions of variance due to cytoplasmic line (c2; n = 590) and sire x cytoplasmic line interaction (sc2; n = 12,831) with other nuclear and environmental effects included in the model. The basic model included direct genetic (fractional variance, a2; n = 26,623), maternal genetic (m2, with direct-maternal correlation ram), and maternal permanent environmental (p2m; n = 6,385) effects. The model with sc2 was significantly (P < 0.05) better than the basic model with c2, but with other random effects added, sc2 became zero. Significant (P < 0.05) variance components were associated with random dam x year (dy2) and dam x number born (dn2) interaction effects. Estimates with all effects in the model were: a2, 0.26; m2, 0.24; ram, -0.05; p2m, 0.02; c2, 0.00; dn2, 0.04; dy2, 0.08; sd2, 0.04; sc2, 0.00. Estimates for a2, m2, and ram were the same for all models. Estimate of p2 changed when other effects were added to the model. The largest estimates for nongenetic effects were: p2m, 0.06; c2, 0.00; dy2, 0.14; sd2, 0.13; and sc2, 0.04. Parameter estimates were similar regardless of whether fixed genetic groups (n = 84) were in the model. For weaning weight (120 d, n = 23,903), estimates of variances of effects added to the basic model were all near zero (a2, 0.14; m2, 0.09; ram, 0.23; p2m, 0.04). For fleece weight (FW, n = 29,024) and number born (NB, n = 29,688), animal permanent environmental effects were added to the model (p2a; n = 7,741 and 7,840) and ram was dropped. For these traits, effects not in the basic model had small variances. For FW, estimates with the full model were: a2, 0.52; m2, 0.01; p2m, 0.00; p2a, 0.06; c2, 0.00; dy2, 0.00; sd2, 0.02; and sc2, 0.06, and for NB they were: a2, 0.08; m2, 0.00; p2m, 0.00; p2a, 0.02; c2, 0.00; dy2, 0.00; sd2, 0.00; and sc2, 0.01. Cytoplasmic effects were not important. Unusual random effects in the model did not change estimates for basic parameters. Although some effects were significant, especially for BW, effects on genetic evaluations are likely to be small.

The objective was to describe genetic parameters and genetic changes in litter sizes at birth and weaning (LB and LW, n=9081), birth weight (BW, n=11,896), weaning weight (WW, n=11,104), fleece weight and grade (FW and FG, n=8872), and staple length (SL, n=1805) of Polypay sheep. Direct heritability estimates from single-trait analyses were 0.11 for LB, 0.02 for LW, 0.17 for BW, 0.18 for WW, 0.68 for FW, 0.36 for FG, and 0.76 for SL. Estimates of direct genetic correlation were 0.40 between LB and LW, 0.57 between BW and WW, 0.65 between FW and SL, 0.37 between FW and FG and 0.70 between SL and FG. Breeding values (BV) from both single-trait and seven-trait analyses calculated using the parameters estimated from single-trait and two-trait analyses were compared across years of birth with respect to genetic trends. Estimated BV from both analyses for LB, LW, BW, WWand FW increased over time, while those for FG and SL were unchanged. Estimated changes in BVover time did not differ substantially for single-trait and seven-trait analyses, except for traits highly correlated with another trait that was responding to selection (i.e., LB, which was highly correlated to both LW and WW). D 2005 Elsevier B.V. All rights reserved.

Records for yearling scrotal circumference (SC; n = 7,580), age at puberty in heifers (AP; n = 5,292), age at first calving (AFC; n = 4,835), and pregnancy, calving, or weaning status following the first breeding season (PR1, CR1, or WR1, respectively; n = 7,003) from 12 Bos taurus breeds collected at the Meat Animal Research Center (USDA) between 1978 and 1991 were used to estimate genetic parameters. Age at puberty (AP) was defined as age in days at first detected ovulatory estrus. Pregnancy (calving or weaning) status was scored as one for females conceiving (calving or weaning) given exposure during the breeding season and as zero otherwise. The final model for SC included fixed effects of age of dam at breeding (AD), year of breeding (Y), and breed (B) and age in days at measurement as a covariate. Fixed effects in models for AP and AFC were AD, Y, B, and month of birth. Fixed effects in models for PR1, CR1, and WR1 included AD, Y, and B. For all traits, random effects in the model were direct genetic, maternal genetic, maternal permanent environmental, and residual. Analyses for a three-trait animal model were carried out with SC, AP, and a third trait (the third trait was AFC, PR1, CR1, or WR1). A derivative-free restricted maximum likelihood algorithm was used to estimate the (co)variance components. Direct and maternal heritability estimates were 0.41 and 0.05 for SC; 0.16 and 0.03 for AP; 0.08 and 0.00 for AFC; 0.14 and 0.02 for PR1; 0.14 and 0.03 for CR1; and 0.12 and 0.01 for WR1. Genetic correlations between direct and maternal genetic effects within trait were -0.26, -0.63, -0.91, -0.79, -0.66, and -0.85 for SC, AP, AFC, PR1, CR1, and WR1, respectively. Direct genetic correlations between SC and AP and between those traits and AFC, PR1, CR1, and WR1 ranged from -0.15 (between SC and AP) to 0.23 (between AP and WR1). Estimates of heritability indicate that yearling SC should respond to direct selection better than AP, AFC, PR1, CR1, and WR1. Variation due to maternal genetic effects was small for all traits. No strong genetic correlations were detected between SC and female reproductive traits or between AP and the other female traits. These results suggest that genetic response in female reproductive traits through sire selection on yearling SC is not expected to be effective.

Fifteen models were compared for the birth weight of 33,994 lambs recorded at the U.S. Sheep Experimental Station (1950 to 1998). The initial intent was to estimate fractions of variance due to cytoplasmic line (c2; n = 892) and sire by cytoplasmic line interaction (sc2; n = 17,557). The basic model included direct genetic (fractional variance, a2; n = 35,684), maternal genetic (m2, with correlation r-am), and maternal permanent environmental (p2; n = 8,418) effects. The model with sc2 was significantly better than the basic model with and without c2. When other random effects were added, sc2 became zero. Significant effects were associated with random dam x year (dy2; n = 24,801), sire x dam (sd2; n = 23,924), and dam x number born (dn2; n = 12,944) interaction effects. Estimates with all effects in the model were a2, 0.24; m2, 0.19; r-am, 0.11; p2, 0.05; c2, 0.00; dn2, 0.04; dy2, 0.06; sd2, 0.05; sc2, 0.00. Estimates for a2, m2, and r-am were the same for all models. Estimate of p2 changed when other effects were added to the model. Largest estimates for nongenetic effects were: p2, 0.08; c2, 0.00; dy2, 0.13; sd2, 0.11; and sc2, 0.04. Regardless of whether Westell groups (n = 91) were in the model, estimates were similar. For weaning weight (120-d, n = 32,715), estimates of variances of effects added to the basic model were all near zero (a2, 0.18; m2, 0.12; r-am, -0.01; p2, 0.06). For number born (NB, n = 37,020) and fleece weight (FW, n = 36,197), animal permanent environmental effects were added to the model (ap2; n = 9,871 and 9,760) and r-am was dropped. For these traits, effects not in the basic model had small variances. Nonzero estimates with full model were a2, 0.10; ap2, 0.01; dy2, 0.02; and sc2, 0.01 for NB, and a2, 0.54; m2, 0.02; ap2, 0.02; dy2, 0.04; and sc2, 0.02 for FW. Cytoplasmic effects were not important. The addition of unusual random effects to the model did not change estimates for the basic parameters. Although some of these effects were significant, especially for BW, the effects on genetic evaluations are likely to be small.

Estimates of heritabilities and genetic correlations were obtained for weaning weight records of 23,681 crossbred steers and heifers and carcass re- cords from 4,094 crossbred steers using animal models. Carcass traits included hot carcass weight; retail prod- uct percentage; fat percentage; bone percentage; ribeye area; adjusted fat thickness; marbling score, Warner- Bratzler shear force and kidney, pelvic and heart fat percentage. Weaning weight was modeled with fixed effects of age of dam, sex, breed combination, and birth year, with calendar birth day as a covariate and random direct and maternal genetic and maternal permanent environmental effects. The models for carcass traits included fixed effects of age of dam, line, and birth year, with covariates for weaning and slaughter ages and random direct and maternal effects. Direct and mater

The objective was to examine the direct and correlated responses of linear type, yield traits, and somatic cell scores (SCS) to divergent selection for predicted transmitting ability for type (PTAT) in Holsteins, while maintaining selection for yield traits across lines. For four generations, one-half of the University of Nebraska research Holstein herd was bred to Holstein sires with PTAT1.50 and the other half to sires with PTAT1.25, with nearly equal predicted transmitting abilities for yield traits for both groups. Estimates of genetic and residual correlations and heritabilities were obtained from REML estimates of (co)variance components. Model for type traits included fixed effect of date cows were classified, effects of age in days at freshening, and stage of lactation at classification. Year-season when cows freshened was fixed effect in model for yield and SCS. Animal genetic and residual effects were random. Final score, milk, fat, and protein yields, and SCS had heritability estimates of 0.38, 0.13,0.22, 0.09, and 0.38, respectively. Heritability estimates for type traits ranged from 0.04 to 0.52. Estimates of genetic correlations of final score with SCS and milk, fat, and protein yields were -0.64, 0.01, -0.18, and 0.06, respectively. Estimates of genetic correlations among linear type traits ranged from -0.77 to 1.00. Means of estimated breeding values for final score, stature, strength, body depth, fore udder attachment, rear udder height and width, udder cleft, udder depth, and front teat placement were significantly different between lines in the third generation. Milk, fat, and protein yields were not significantly different between lines in third generation, whereas SCS was significantly different. Estimate of genetic correlation between final score and SCS suggest that selection on PTAT would result in a change for SCS. In this study, divergent selection on PTAT of sires had a significant effect on udder and body traits, but little or no effect on feet and leg traits.

Genetic parameters of mature weight are needed for effective selection and genetic evalua- tion. Data for estimating these parameters were col- lected from 1963 to 1985 and consisted of 32,018 mature weight records of 4,175 Hereford cows that were in one control and three selection lines that had been selected for weaning weight, for yearling weight, or for an index combining yearling weight and muscle score for 22 yr. Several models and subsets of the data were considered. The mature weight records consisted of a maximum of three seasonal weights taken each year, at brand clipping (February and March), before breeding (May and June), and at palpation (August and September). Heritability estimates were high (0.49 to 0.86) for all models considered, which suggests that selection to change mature weight could be effective. The model that best fit the data included maternal genetic and maternal permanent environmental effects in addition to direct genetic and direct permanent environmental effects. Estimates of direct heritability with this model ranged from 0.53 to 0.79, estimates of maternal herita- bility ranged from 0.09 to 0.21, and estimates of the genetic correlation between direct and maternal effects ranged from −0.16 to −0.67 for subsets of the data based on time of year that mature weight was measured. For the same subsets, estimates of the proportions of vari- ance due to direct permanent environment and mater- nal permanent environment ranged from 0.00 to 0.09 and 0.00 to 0.06, respectively. Using a similar model that combined all records and included an added fixed effect of season of measurement of mature weight, di- rect heritability, maternal heritability, genetic correla- tion between direct and maternal effects, proportion of variance due to direct permanent environmental ef- fects, and proportion of variance due to maternal per- manent environmental effects were estimated to be 0.69, 0.13, −0.65, 0.00, and 0.04, respectively. Mature weight is a highly heritable trait that could be included in selection programs and maternal effects should not be ignored when analyzing mature weight data.

Estimates of genetic parameters for birth (N = 3909), weaning (N = 3425), yearling (N = 2764) and final (N = 2144) weights were obtained from the records of Gobra cattle collected at the Centre de Recherches Zootechniques de Dahra, Senegal. Three animal models were fitted to obtain estimates by REML using an average information (AI) approach. Model 1 considered random direct, maternal genetic and maternal permanent environmental effects. In model 2, a general grandmaternal effect was added to the random effects considered in model 1, and in model 3, the general grandmaternal effect was divided into grandmaternal genetic and grandmaternal permanent environmental effects. All models allowed covariances among genetic effects. The inclusion of grandmaternal effects in models 2 and 3 did not change the estimates of the genetic parameters compared to model 1. Variances attributable to grandmaternal effects became negative and were set close to zero, except for yearling weight for which grandmaternal heritability was 0.03 ± 0.03. The estimates for direct and maternal heritabilities were, respectively, 0.08 ± 0.03 and 0.03 ± 0.02 for birth, 0.20 ± 0.05 and 0.21 ± 0.05 for weaning, 0.26 ± 0.07 and 0.16 ± 0.07 for yearling and 0.14 ± 0.06 and 0.16 ± 0.06 for final weights. The estimates of the genetic correlation between direct and maternal effects for birth, weaning, yearling and final weights were -0.17 ± 0.40, -0.58 ± 0.32, -0.52 ± 0.34 and -0.34 ± 0.37, respectively. For yearling weight with grandmaternal heritability estimated to be only 0.03, model 3 gave estimates of the genetic correlation between direct and grandmaternal effects and between maternal and grandmaternal effects of 0.28 ± 0.48 and -0.33 ± 0.67, respectively. Estimates of direct and maternal heritabilities were unchanged when grandmaternal effects were not included in the model.Foram obtidas as estimativas dos pesos ao nascimento (N = 3909), ao desmame (N = 3425), com 1 ano de idade (N = 2764) e final (N = 2144) a partir dos registros de gado Gobra coletados no Centro de Pesquisas em Zootecnia de Dahra, Senegal. Três modelos animais foram adaptados para obter estimativas por REML usando uma abordagem de informação média (AI). O modelo 1 considerou os efeitos ambientais aleatórios direto, genético maternal e maternal permanente. No modelo 2, um efeito geral relativo às avós foi adicionado aos efeitos aleatórios considerados no modelo 1, e no modelo 3 o efeito geral relativo às avós foi dividido em efeitos ambientais genético e permanente. Todos os modelos admitiram covariâncias entre os efeitos genéticos. A inclusão dos efeitos relativos às avós nos modelos 2 e 3 não alterou as estimativas dos parâmetros genéticos comparados com o modelo 1. As variâncias atribuíveis aos efeitos relativos às avós tornaram-se negativas e foram posicionadas próximas a zero, exceto para o peso com 1 ano, para o qual a herdabilidade relativa à avo foi 0,03 ± 0,03. As estimativas para as herdabilidades direta e maternal foram, respectivamente, 0,08 ± 0,03 e 0,03 ± 0,02 para peso ao nascimento, 0,20 ± 0,05 e 0,21 ± 0,05 para peso ao desmame, 0,26 ± 0,07 e 0,16 ± 0,07 para peso com 1 ano e 0,14 ± 0,06 e 0,16 ± 0,06 para o peso final. As estimativas da correlação genética entre os efeitos direto e maternal para os pesos ao nascimento, ao desmame, com 1 ano e final foram -0,17 ± 0,40, -0,58 ± 0,32, -0,52 ± 0,34 e -0,34 ± 0,37, respectivamente. Para o peso com 1 ano com herdabilidade relativa à avó estimada como sendo apenas 0,03, o modelo 3 deu estimativas da correlação genética entre os efeitos direto e relativo à avó e entre os efeitos maternal e relativo à avó de 0,28 ± 0,48 e -0,33 ± 0,67, respectivamente. As estimativas de herdabilidade direta e maternal não se alteraram quando os efeitos relativos à avó não foram incluídos no modelo.

Estimates of (co)variance components and genetic parameters were obtained for birth (no. = 3909), weaning (no. = 3425), yearling (no. = 2763), and final weight (no. = 2142) for Gobra cattle at the Centre de Recherches Zootechniques de Dahra (Senegal), using single trait animal models. Data were analysed by restricted maximum likelihood. Four different animal models were fitted for each trait. Model 1 considered the animal as the only random effect. Model 2 included in addition to the additive direct effect of the animal, the environmental effect due to the dam. Model 3 added the maternal additive genetic effects and allowed a covariance between the direct and maternal genetic effects. Model 4 fitted both maternal genetic and permanent environmental effects. Inclusion of both types of maternal effects (genetic and environmental) provided a better fit for birth and weaning weights than models with one maternal effect only. For yearling and final weights, the improvement was not significant. Important maternal effects werefound for all traits. Estimates of direct heritabilities were substantially higher when maternal effects were ignored. Estimates of direct and maternal heritabilities with model 4 were 0·07 (s.e. 0·03) and 0·04 (s.e. 0·02), 0·20 (s.e. 0·05) and 0·21 (s.e. 0.05), 0·24 (s.e. 0·07) and 0·21 (s.e. 0·06), and 0·14 (s.e. 0·06) and 0.16 (s.e. 0·06) for birth, weaning, yearling and final weights, respectively. Correlations between direct and maternal genetic effects were negative for all traits, and large for weaning and yearling weights with estimates of -0·61 (s.e. 0·33) and -0·50 (s.e. 0·31), respectively. There was a significant positive linear phenotypic trend for weaning and yearling weights. Linear trends for additive direct and maternal breeding values were not significant for any trait except maternal breeding value for yearling weight.

theoretical response of yield in self-pollinated crops. Other researchers have addressed this relationship with Determining the appropriate number of lines to retain across generrespect to maize (Baker and Curnow, 1969; Rawlings, ations during inbred line development in maize (Zea mays L.) is interest during line development is performance of testcross progeny, Using a specific genetic model assuming additivity genetic information on lines per se adds to basic understanding of the within and among loci (no dominance, no epistasis) and genetic response of maize to inbreeding and selection. The objective of no linkage, Baker and Curnow (1969) simulated effects this research was to compare genetic responses of families per se to of population size on progress from selection in maize. varying selection intensities across early generations of selfing in In this simulation study, selection was aimed at improvmaize. A FORTRAN program simulating a stochastic genetic model ing the composite population as a source of inbred lines. with 30, 40, and 30% additive, dominant, and over-dominant loci, Rawlings (1979) discussed choices of effective popularespectively, and a random environmental effect was used to compare tion size considering short- and long-term objectives in varying combinations of selection intensities across generations. In the recurrent selection programs from the standpoint of simulation, individual plants were evaluated on the basis of testcross progeny performance using multiple testers and environments. Indi- gene fixation, maintenance of genetic variation, and vidual plants corresponding to top performing testcross progenies linkage equilibrium, and gave formulas for calculating were selected as parents for successive generations. Within each gener- appropriate population sizes and selection intensities. ation, phenotypic and genetic means of families per se increased with From a survey of U.S. maize breeders, Bauman (1981) increased selection intensities. Response to selection in any given found that, on average, U.S. maize breeders started with generation was not dependent on selection intensity used in the previ- approximately 500 S1 families and by the S4 generation, ous generation. Percent homozygosity and frequency of superior al- only 40 were retained. Bauman pointed out that breedleles increased as selection pressure intensified. Few original plants ers discarded 64% of the families in S1 generation based contributed to retained families with only approximately 5% of S0 on visual selection, indicating that both visual selection plants appearing in pedigrees of selected S4 families. Retaining few but larger families resulted in increased genetic values of families per and the breeder’s experience were important in selecse, compared with saving a large number of smaller families, even tion. Using procedures outlined by Robson et al. (1967), though selection was based on testcross performance. Johnson (1989) calculated the probability of correctly identifying S3 progenies on the basis of S2 testcross performance and found that critical decisions on allocation

Milk yield, fat yield, and fat percentage during the first three lactations were studied using New York Holsteins that were milked twice daily over a 305-d, mature equivalent lactation. Those data were used to estimate variances from direct and maternal genetic effects, cytoplasmic effects, sire by herd interaction, and cow permanent environmental effects. Cytoplasmic line was traced to the last female ancestor using DHI records from 1950 through 1991. Records were 138,869 lactations of 68,063 cows calving from 1980 through 1991. Ten random samples were based on herd code. Samples averaged 4926 dams and 2026 cytoplasmic lines. Model also included herd-year-seasons as fixed effects and genetic covariance for direct-maternal effects. Mean estimates of the effects of maternal genetic variances and direct-maternal covariances, as fractions of phenotypic variances, were 0.008 and 0.007 for milk yield, 0.010 and 0.010 for fat yield, and 0.006 and 0.025 for fat percentage, respectively. Average fractions of variance from cytoplasmic line were 0.011, 0.008, and 0.009 for milk yield, fat yield, and fat percentage. Removal of maternal genetic effects and covariance for maternal direct effects from the model increased the fraction of direct genetic variance by 0.014, 0.021, and 0.046 for milk yield, fat yield, and fat percentage; little change in the fraction was due to cytoplasmic line. Exclusion of cytoplasmic effects from the model increased the ratio of additive direct genetic variance to phenotypic variance by less than 2%. Similarly, when sire by herd interaction was excluded, the ratio of direct genetic variance to phenotypic variance increased 1% or less.

Mixed model methodology based on a multi-trait animal model was used to estimate genetic trends for lamb weights in three synthetic Arcott (Canadian Outaouais and Rideau) breeds and two random bred control (Suffolk and Finnish Landrace) breeds. Selection in the Canadian Arcott was primarily on lamb weight at 91 d with a lesser emphasis on litter size. Outaouais and Rideau Arcotts were selected primarily for litter size with a lesser emphasis on lamb weight at 91 d. All lambs were housed indoors year-round in a controlled environment under conditions of artificial rearing and 8-mo breeding cycles. Genetic improvement over 20 yr based on predicted breeding values for lamb weights at birth, 21, 70 and 91 d of age were 0.3, 0.9, 2.1 and 2.8 kg, respectively in the Canadian, 0.2, 0.6, 1.2 and 1.5 kg in the Outaouais, and 0.3, 0.5, 0.9 and 1.4 kg in the Rideau breeds. Corresponding values for the unselected Suffolk were 0.3, 0.4, 0.4 and 0.5 kg, respectively, and for the Finnsheep were 0.2, 0.2, 0.3 and 0.5 kg. Alternative methods of estimating genetic trends using control populations were based on deviation of the predicted mean year-season phenotype in the selected breeds from that in the corresponding random bred control breeds (Suffolk for Canadian, and Finnsheep for Outaouais and Rideau) and also as a deviation from the year-season estimate in the corresponding random bred control breeds. Genetic trends estimated from the alternative methods, which took into account the contribution of drift, were larger than those based on predicted breeding values. These values were reflected in the realized heritabilities estimated from regression of cumulative selection differential on the genetic trends. In the Arcott breeds, annual genetic trend for lamb weights varied according to breed and the estimation procedure which amounted to 0.25–0.81% of the mean. It is evident selection offers one of the most practical means for rapid and permanent improvement of early lamb growth in multi-breed synthetic populations under conditions of artificial rearing, 8-mo breeding cycle and a controlled environment. Key words: Sheep breeds, genetic trends, multi-trait animal model and growth traits

The animal model for genetic evaluations of dairy cattle by the USDA currently includes a term for interaction effects of sire and herd. The relative magnitude of the variance of that effect was established in the 1960s as 14% of the total variance, but recent research has shown that the proportion is 2% or less. This report compared EBV using either the 14% or the actual estimate from 20 samples of records from herds in California, New York, and Pennsylvania. From 6 to 22% of bulls or cows selected for milk and fat yields based on evaluation with 14% of the total variance would not be selected using the sample estimates, depending on selection intensity, region, and whether only first or up to three lactations were used in the evaluations. Nevertheless, the average EBV of the bulls and cows selected based on 14% of the total variance were only slightly less than for those selected on 2%. This pilot research suggests that further study of the national data be done to establish the appropriate proportion of variance from interaction effects of sire and herd to use with national evaluations. Kinds of evaluations of bulls and ages of cows and bulls should be considered.

Days open, days dry, and season of calving were examined to maximize Income Over Feed Cost (IOFC) and 305-d mature equivalent milk production for three different production levels. Models with all fixed effects were analyzed using SAS® PROC GLM for 50,743 Holstein cows from 4687 herds calving in yr 1990 and 1991. Production level of cow was not important to determine optimum days open to maximize 305-d milk yield, but was important for days open to maximize IOFC. For 305-d milk yield, days open of 91 to 105 d, 76 to 90 d, and 61 to 75 d were optimum for cows calving in season 2 (February through April), season 3 (May through July), and season 4 (August through October) respectively. For IOFC, optimum days open was 15 d higher for average and above average production levels for seasons 2 and 3 than for below average production level. Optimum days open to maximize IOFC for calving season 4 was 15 d higher for above average production level than for below average and average levels. Cows calving in season 2 had highest optimum days open. Conclusive results could not be obtained for season 1 as less than 10% of records in the data set belonged to that season and of those only 10% had an open period shorter than 150 d. On average, cows calving in season 3 yielded highest IOFC, which was $667, $482, and $276 more than cows calving in season 1 (November to January), season 2, and season 4 respectively. The 305-d milk yield was not different for the four seasons of calving.

Estimates of (co)variance components and genetic parameters were obtained for birth, 205-d, and 365-d weight for Nelore cattle in Brazil, using single and multiple-trait animal models. Data were from the Brazilian Zebu Breeders Association (ABCZ). Records of 27,549 calves sired by 587 bulls and raised on pasture in 57 herds were analyzed by restricted maximum likelihood fitting an animal model including direct and maternal genetic and permanent environmental effects. Single and multiple-trait analyses were carried out. Heritability estimates for direct effects were lower than previous values reported for the Nelore breed. The estimates for maternal genetic effects showed that the contribution of this component to the phenotypic variance of birth and weaning weight is not very high but is still present at yearling weight. Correlations between direct and maternal additive genetic effects were negative for all traits analyzed except for yearling weight in the single-trait analysis where the sign was positive but the magnitude was small (+.09). Genetic correlations between weaning and yearling weights were .74 (direct effect) and .84 (maternal effect). Permanent environmental and residual correlations among traits were also obtained.

For 1,442 Belgian Blue bulls performance-tested at the Centre de Sélection de la Race Blanc-Bleue Belge, nine traits were observed: height at withers at 7 mo, height at withers at 13 mo, weight at 7 mo, weight at 13 mo, average feed consumption of concentrates, average daily gain, average feed consumption of concentrates per average daily gain, average feed consumption of concentrates per mean metabolic weight, and price per kilogram of live weight. This price is based on muscle conformation and is therefore used as muscle conformation score. Restricted maximum likelihood with a derivative-free algorithm was used to estimate (co)variance components because there were different models and missing values per trait. Estimates of heritabilities were above .50 except for average feed consumption per average daily gain (.16) and average feed consumption per mean metabolic weight (.33). Estimates of genetic and phenotypic correlations between height at withers and weight traits were positive and moderate to high. Average daily gain showed a negative genetic correlation with weight at 7 mo (-.68) but had positive correlations with height at withers at 13 mo and weight at 13 mo (.22 and .43). Muscle conformation expressed as price per kilogram of live weight was related to low average feed consumption per average daily gain. Average feed consumption showed high correlations with weight at 7 mo and weight at 13 mo. Average feed consumption per average daily gain had a high negative genetic correlation with average daily gain (-.89).

Dominance and additive x additive genetic variances were estimated for birth and weaning traits of calves from three synthetic lines of beef cattle differing in mature size. Data consisted of 3,992 and 2,877 records from lines of small-, medium-, and large-framed calves in each of two research herds located at Rhodes and McNay, IA, respectively. Variance components were estimated separately by herd and line for birth weight (BWT), birth hip height (BH), 205-d weight (WW), and 205-d hip height (WH) by derivative-free REML with an animal model. Model 1 included fixed effects of year, sex, and age of dam. Random effects were additive direct (a) and additive maternal (m) genetic with covariance (a,m), maternal permanent environmental, and residual. Model 2 also included dominance (d) and model 3 included dominance plus additive x additive (a:a) effects. In general, only slight changes occurred in other variance components estimates when day was included in Model 2. However, large estimates of additive x additive genetic variances obtained with Model 3 for 4 out of 24 analyses were associated with reductions in estimates of direct additive variances. Direct (maternal) heritability estimates averaged across herd-line combinations with Model 2 were .53(.11), .42(.04), .27(.12), and .35(.04) for BWT, BH, WW, and WH, respectively. Corresponding covariance (a,m) estimates as fractions of phenotypic variance (sigma p2) were .00, .01, .01, and .06, respectively. For maternal permanent environmental effects in Model 2, average estimates of variances as fractions of sigma p2 across herd-line combinations were .03, .00, .05, and .02, for BW, BH, WW, and WH, respectively. Dominance effects explained, on average, 18, 26, 28, and 11% of total variance for BWT, BH, WW, and WH, respectively. Most of the estimates for additive x additive variances were negligible, except for one data set for BWT, two for BH, and one for WH, where the relative estimates of this component were high (.21 to .45). These results suggest that most of the non-additive genetic variance in the traits studied is accounted for by dominance genetic effects.

The objective of this study was to evaluate the effect of parentage misidentification on estimation of genetic parameters for the Italian buffalo population for milk yield from 45,194 lactation records of 23,104 Italian buffalo cows. Animals were grouped into 10 data sets in which sires and dams were DNA identified, or reported from the pedigree, or unknown. A derivative-free restricted maximum likelihood method was used to estimate components of variance with a repeatability model. The model contained age at calving nested within parity and days from calving to conception as linear covariates, herd-year-seasons as fixed effects, and additive genetic, permanent environmental, and temporary environmental effects as random effects. Estimates of heritability (±SE) ranged from 0.00 ± 0.099 (sires and dams as reported in the pedigree) to 0.39 ± 0.094 (sires DNA identified and dams as reported in the pedigree). When identification of sires was as reported in the pedigree, estimates of heritability were close to zero. These small estimates indicate that a large proportion of reported paternity is incorrect. When sires are unknown and dams are DNA identified, the proportion of variance due to sires seems to be captured in the estimate of permanent environmental variance as a fraction of phenotypic variance. Therefore, as heritability decreased, permanent environmental variance increased about the same amount. Data sets with dams identified from pedigree and sires DNA identified showed the largest estimate of heritability (0.39), which was essentially the same as when dams were DNA identified (0.38). This result supports that most dams are correctly reported from the pedigree. Genetic progress should be much greater with bulls DNA identified because of greater heritability, but without artificial insemination and progeny testing, progress would be slow and would depend mostly on selection of sires based on dam estimated breeding values. Implementation of artificial insemination programs and DNA testing to identify sires are the keys for increasing genetic progress in the Italian buffalo population.

The purpose of this study was to estimate the correlation between the expression of genes from sires in purebred and crossbred progeny (rPC) and in Hereford and Angus F1 calves (rHA). Performance traits were weights at birth, 200 d, and 365 d. Progeny from Hereford, Polled Hereford, and Angus bulls mated to Hereford or Angus cows were used to estimate rPC. Progeny from Charolais, Shorthorn, Simmental, Limousin, Maine-Anjou, Chianina, Gelbvieh, Tarentaise, and Salers bulls mated to Hereford or Angus cows were used to estimate rHA. Performances in purebreds (P) and crosses (C) or in Hereford (H) and Angus (A) F1 calves were treated as separate traits. A multivariate animal model with birth year-cow age-sex subclasses, random correlated direct and maternal additive genetic effects, and maternal permanent environmental effects was used. Separate analyses were done by breed of sire. A derivative-free algorithm was used to obtain REML estimates of (co)variance components. Weighted averages across breeds of estimates of heritability for P, C, H, and A were, respectively, .61, .51, .47, and .40 for birth weight, .41, .46, .37, and .34 for weaning weight, and .50, .49, .42, and .46 for yearling weight. Estimates of rPC ranged from .88 to .97, .55 to .94, and .68 to .86 for weights at birth, 200 d, and 365 d, respectively. Estimates of rHA ranged from .43 to .99, .56 to .95, and .50 to .98 for weights at birth, 200 d, and 365 d, respectively. Weighted averages of estimates of rPC and rHA across sire breeds were, respectively, .93 and .85 for birth weight, .77 and .73 for weaning weight, and .76 and .86 for yearling weight. These results indicate that ranking of sires producing purebreds or crosses, or crossbred calves from different breeds of dams, is approximately the same for birth and yearling weights, but some reranking might occur for weaning weight.

Genetic and environmental (co)variance components were estimated for carcass trait records from 219 rabbits using univariate, restricted maximum likelihood (REML) with derivative and derivativefree REML (DFREML) methods. Derivative REML estimates of variance components using the GLMM (General Linear Mixed Models) package were for independent sire within sire breed, dam within sire, litter within dam, and residual random effects. Animal models used with DFREML included direct and maternal genetic effects with numerator additive genetic relationships, litter effects, and residual effects. Carcass trait heritabilities for direct genetic effects were generally consistent between corresponding REML methods. In animal models using DFREML that accounted for relationships, direct genetic variances were inflated when maternal genetic effects were ignored. Inclusion or exclusion of the litter effect had little impact on other variance components. Inclusion of covariance between direct and maternal genetic effects with numerator relationships resulted in relative shifts in direct and maternal genetic variances, but not in litter variances. Estimates of genetic correlations suggest antagonisms between direct and maternal genetic effects particularly for preslaughter, carcass, and total lean weight traits.

Formulas are presented to illustrate the calculation of correct variances of prediction error (PEV) and the correlation between true and predicted values (rTI) when the incorrect variance-covariance matrix for the random effects is used in mixed-model equations (MME). The example with progeny records of highly related and inbred sires showed that PEV were underestimated from the diagonals of the inverse of the coefficient matrix of the MME when sires were assumed unrelated and not inbred and were overestimated when relationships among sires were calculated with Henderson's simple rules for the inverse of the numerator relationship matrix, A(-1), which do not consider inbreeding. When Quaas' rules for A(-1), which do consider inbreeding, are used, the correct PEV are obtained. In the example, calculations of rTI from the diagonals of the inverse of the coefficient matrix were too large when relationships and inbreeding were ignored and were obviously wrong when the approximation to the numerator relationship matrix, A, was based on the simple rules for calculating A(-1). If the correct A is used in the MME, the calculation of rTI may be incorrect if inbreeding of the evaluated individual is not considered. If inbreeding is known, adjustment for inbreeding is easy for calculation of rTI.

This study examined the effect of genetic grouping on REML estimates of additive genetic variance with an animal model with selected base populations. A simulated population of 40 animals (20 males and 20 females) was followed under selection or random mating conditions for 10 generations. Each population was replicated 20 or 50 times. Genetic grouping reduced estimates of additive genetic variance in populations with selected base animals, whereas grouping had little effect on the estimate in unselected populations. The effect of genetic grouping varied according to the quantity and kind of information that was missing (percentage of deleted data and pattern of deletion). When genetic grouping was completely random, the estimates were unaffected. Because including genetic groups in the model for analysis affected the estimates of additive genetic variance, the question should be considered of what value or values for heritability should be used for genetic evaluation when grouping is used to account for prior selection.

Milk yield was regressed on sire PD for 28,755, 65,990, and 30,279 sire identified records from Colombia, Mexico, and Puerto Rico. Milk yields were expressed as daughter herd-year deviations for projected or actual 305-d milk yield after adjustments for age and season of calving. Herd-year means and standard deviations were determined using all cows in a herd-year including those with unknown sires. Average herd-year mean and SD were less for Colombia and Puerto Rico than for Mexico. Average herd-year SD within same herd-year mean classification also were smaller for Colombia and Puerto Rico compared to Mexico. Coefficients for daughter milk response regressed on sire PD were similar in Colombia (.31 ± .02) and Puerto Rico (.32 ± .02) and greater in Mexico (.54 ± .02). Daughter responses increased similarly and approximately linearly with increasing herd-year SD in each country but not with increasing herd-year mean. Daughter milk response to sire selection was less than reported responses in US herds with similar herd-year means and SD. Therefore, using sire PTA estimated from US daughters will overestimate milk responses of daughters in Latin American dairy herd environments.

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 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.

Bovine respiratory disease (BRD) is the most costly feedlot disease in the United States. Selection for disease resistance is one of several possible interventions to prevent or reduce the economic loss associated with animal disease and to improve animal welfare. Undesirable genetic relationships, however, may exist between production and disease resistance traits. The objectives of this study were to estimate the phenotypic, environmental, and genetic correlations of BRD with growth, carcass, and LM palatability traits. Health records on 18,112 feedlot cattle over a 15-yr period and slaughter data on 1,627 steers over a 4-yr period were analyzed with bivariate animal models. Traits included ADG, adjusted carcass fat thickness at the 12th rib, marbling score, LM area, weight of retail cuts, weight of fat trim, bone weight, Warner-Bratzler shear force, tenderness score, and juiciness score. The estimated heritability of BRD incidence was 0.08 +/- 0.01. Phenotypic, environmental, and genetic correlations of the observed traits with BRD ranged from -0.35 to 0.40, -0.36 to 0.55, and -0.42 to 0.20, respectively. Most correlations were low or negligible. The percentage of carcass bone had moderate genetic, phenotypic, and environmental correlations with BRD (-0.42, -0.35, and -0.36, respectively). Hot carcass weight and weight of retail cuts had moderate, undesirable phenotypic correlations with BRD (0.37 and 0.40, respectively). Correlations of BRD with LM palatability and ADG were not detected. Low or near zero estimates of genetic correlations infer that selection to reduce BRD in feedlot cattle would have negligible correlated responses on growth, carcass, and meat palatability traits or that selection for those traits will have little effect on BRD susceptibility or resistance.

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.

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.

This study examined competition effects on ADG in the feedlot of 1,882 Hereford bulls representing 8 birth years from a selection experiment. Each year, 8 feedlot pens were used to feed bulls in groups, with 2 pens nested within each of the 4 selection lines. Gains were recorded for up to 8 periods of 28 d. Models for analyses included pen effects (fixed or random), fixed effects such as year and line, and random direct genetic, competition genetic (and in some analyses competition environmental), and environmental effects. Each pen mate as a competitor affected the records of all others in the pen. All lines traced to common foundation animals, so the numerator relationships among and within pens were the bases for separating direct and competition genetic effects and pen effects. For this population and pen conditions (average of 30 bulls per pen), the major results were 1) competition genetic effects seemed present for the first 28-d period but not for the following 7 periods; 2) models with pens considered as fixed effects could not separate variances and covariance due to direct and competition genetic effects; 3) models without competition effects had large estimates of the variance component due to pen effects for gain through 8 periods; and 4) models with genetic and environmental competition effects accounted for nearly all of the variance traditionally attributed to pen effects (even though estimates of the competition variance component were small, the estimates of pen variance were near zero).