Biomedical subjects

L D Van Vleck

Publications and source records attributed to L D Van Vleck.

At least 19 recordsLinked to original sources

PubMed2000

Prediction of crude fat content of longissimus muscle of beef using the ratio of fat area calculated from computer image analysis: comparison of regression equations for prediction using different input devices at different stations.

Crude fat content of longissimus (ribeye) muscle of beef cattle was predicted from a ratio of fat area (RFA) to area of ribeye muscle calculated from computer image analysis (CIA). Cross sections of 64 ribeyes taken from the 6-7th rib from cattle at experiment station A and cross sections of 94 ribeyes taken from the 6-7th rib from cattle at Experiment Station B were used in this study. Slices (1 to 1.5 cm in thickness) of just the Longissimus dorsi were homogenized and sampled for chemical estimation of crude fat content using petroleum ether. Crude fat content as determined from chemical analysis was used as the true estimate of fat content. A CCD (charge-coupled device) camera was used as the input device at Experiment Station A, and a single-lens reflex camera was used at Experiment Station B to photograph ribeyes for CIA. The contour comparison method, which assigns a threshold value for each marbling particle, was used to obtain accurate binarization in this study. Minimum and maximum of chemical measurements of crude fat were 2.1 and 39.8%, and for CIA calculation of the RFA were 6.1 and 56.8%, respectively. This range covered almost the complete range of the beef marbling standard used in carcass grading in Japan. The equation for the regression of the crude fat content (Y) on RFA (X) calculated from CIA for all of the data was Y = .793X-3.04 with r2 = .96. Regression equations for prediction of crude fat percentage from RFA taking into consideration the effect of experiment station were Y = .741X-2.22 with r2 = .91 for Experiment Station A, and Y = .782X-2.54 with r2 = .91 for Experiment Station B. Analysis of covariance showed that the effects of experiment stations on intercepts and slopes were not significant (P > .10). The ranges of differences between actual and predicted crude fat content from the prediction equation that was calculated without consideration of the effect of station were -6.4 to 4.0%. CIA of cross sections of the ribeye muscle seems to have potential for prediction of crude fat content.

Adipose Tissue↗

PubMed2000

Genetic parameters among weight, prolificacy, and wool traits of Columbia, Polypay, Rambouillet, and Targhee sheep.

Genetic parameters for Columbia, Polypay, Rambouillet, and Targhee sheep were estimated using REML with animal models for prolificacy, weight, and wool traits. All bivariate analyses included a covariance between additive genetic effects for the two traits plus appropriate additional covariances. Number of observations by breed ranged from 5,140 to 7,095 for prolificacy traits, from 7,750 to 9,530 for weight traits, and from 4,603 to 34,746 for wool traits. Heritability estimates ranged from .03 to .11 for prolificacy traits (litter size at birth and litter size at weaning), from .09 to .26 for weight traits (birth weight and average daily gain), and from .25 to .53 for wool traits (fleece weight, fleece grade and staple length). Estimates of direct genetic correlations among prolificacy and among weight traits were positive and ranged from .58 to 1.00 and .18 to 1.00, respectively. Estimates of direct genetic correlation between fleece weight and staple length were positive (.50 to .70) but were negative between fleece weight and fleece grade (-.60 to -.34) and between staple length and fleece grade (-.72 and -.40). Prolificacy and wool traits were essentially uncorrelated. Weight and prolificacy traits were slightly positively correlated. Weight traits had a moderate positive direct genetic correlation with fleece weight and staple length, but were uncorrelated with fleece grade. These estimates of genetic parameters between prolificacy, weight, and wool traits can be used to construct multiple-trait selection indexes for dual-purpose sheep.

Age Factors↗

PubMed2000

Genetic correlations for daily gain between ram and ewe lambs fed in feedlot conditions and ram lambs fed in Pinpointer units.

When performance is recorded in automated facilities that measure feed intake of individual lambs that are penned in a group, such as Pinpointer units, a legitimate question is the degree to which daily gain is genetically correlated with daily gain achieved under feedlot conditions. Lambs were from a composite population (1/2 Columbia, 1/4 Suffolk, and 1/4 Hampshire germplasm) and of the F2 or more advanced generations. Data were daily gains of 1,101 rams (PR) fed in Pinpointer units (11 to 17 wk of age) and 2,021 rams (FR) and 3,513 ewes (FE) fed under feedlot conditions (9- or 10-wk period starting at 9 wk of age). The FR and FE lambs were born from 1983 through 1995, whereas the PR lambs were born from 1986 through 1995. Measurements of daily gain in PR, FR, and FE lambs were considered to represent three correlated traits. Unadjusted means were .411, .406, and .326 kg/d for PR, FR, and FE, respectively. Random effects in the model were animal direct genetic, maternal genetic, and maternal permanent environmental. Fixed effects were associated with age of dam (1 to 6 yr), type of rearing (1 to 4), and contemporary group (test date). Variances due to maternal genetic effects with single-trait analyses were near zero, so those effects were eliminated from the three-trait analysis although a random uncorrelated effect due to dam was included in the model. Estimates of heritability were .22, .14, and .23 for PR, FR, and FE, respectively, with fractions of variance due to dam effects ranging from .02 to .05. Estimates of genetic correlations were .86 for PR with FR, .83 for PR with FE, and 1.00 for FR with FE. Estimated phenotypic variances were similar for PR and FR, but one-third less for FE. The similarity of heritability estimates and estimates of genetic correlations all exceeding .83 suggest that daily gain of rams fed in Pinpointer units will reflect genetic expression for daily gain in both ram and ewe lambs fed under feedlot conditions.

Animal Feed↗

PubMed2000

Parameter estimates for genetic effects on carcass traits of Korean native cattle.

Data (n = 1,746) collected from 1985 through 1995 on Korean Native Cattle by the National Livestock Research Institute of Korea were used to estimate genetic parameters for marbling score, dressing percentage, and longissimus muscle area, with backfat thickness, slaughter age, or slaughter weight as covariates. Estimates were obtained with REML. Model 1 included animal genetic and residual random effects. Model 2 was extended to include an uncorrelated random effect of the dam. Model 3 was based on Model 1 but also included sire x region x year-season interaction effects. Model 4 combined Models 2 and 3. All models included fixed effects for region x year-season and age of dam x sex combinations. From single-trait analyses, estimates of heritability with covariates to adjust for backfat thickness, slaughter age, and slaughter weight from Model 4 were, respectively, .10, .08, and .01 for marbling score; .09, .12, and .16 for dressing percentage; and .18, .17, and .24 for longissimus muscle area. From three-trait analyses, estimates of genetic correlations between marbling score and dressing percentage, marbling score and longissimus muscle area, and dressing percentage and longissimus muscle area were, respectively, -.99, .20, and -.11 with backfat thickness as covariate; -.88, .47, and .01 with slaughter age as covariate; and -.03, .39, and .91 with slaughter weight as covariate. Results of this study suggest that choice of covariate (backfat thickness, slaughter age, or slaughter weight) for the model seems to be important for carcass traits for Korean Native Cattle. Including sire x region x year-season interaction effects in the model for marbling score and dressing percentage may be important because whether sire x region x year-season interaction effects were in the model affected estimates of other variance components for the three carcass traits. Whether the maternal effect was in the model had little effect on estimates of other parameters. With backfat thickness and slaughter age end points, selection for increasing marbling score would be expected to result in decreasing dressing percentage for Korean Native Cattle. With slaughter weight as a covariate for end point, increased longissimus muscle area would be associated with increased dressing percentage, and increased marbling score would be related to increased longissimus muscle area. The differences in estimates associated with choice of end point, however, need further study.

Animals↗

PubMed2000

Parameter estimates for direct and maternal genetic effects on yearling, eighteen-month, and slaughter weights of Korean native cattle.

Data collected by the National Livestock Research Institute of the Rural Development Administration of Korea were used to estimate genetic parameters for yearling (YWT, n = 5,848), 18-mo (W18, n = 4,585), and slaughter (SWT, n = 2,279) weights for Korean Native cattle. Nine animal models were used to obtain REML estimates of genetic parameters: DP-2 included genetic, uncorrelated dam, and residual random effects; DQ-2 included genetic, sire x region x year-season interaction, and residual random effects; DPQ-2 was based on DQ-2 but included both interaction and dam effects; DMP-2 was based on DP-2 but with dam effect partitioned to include maternal genetic and permanent environmental effects; and DMPQ-2 was based on DMP-2 but also included sire interaction effects. Those five models included two fixed factors: region x year-season and age of dam x sex effects. Models DP-3, DQ-3, DPQ-3, and DMPQ-3 were based on DP-2, DQ-2, DPQ-2, and DMPQ-2 but included as a third fixed factor whether or not identification of the sire was known. Estimates of heritability with DMPQ-3 for YWT, with DPQ-3 for W18 and SWT when analyzed with single-trait analyses were .14, .11, and .17, respectively, and were nearly the same with bivariate analyses. Estimate of maternal heritability for YWT from single-trait analysis was .04, with estimates for other traits near zero. For bivariate analyses, the estimate for YWT was .01. With single trait analysis, estimate of the direct-maternal genetic correlation for YWT was negative (-.81). Estimates of direct genetic correlations between YWT and W18, YWT and SWT, and W18 and SWT were .99, 1.00, and .97, respectively. Estimates of environmental correlations varied from .60 to .81; the largest was between W18 and SWT. Including a fixed factor for whether sire identification was missing or not missing reduced the estimate of heritability for slaughter weight. The results suggest that the sire x region x year-season interaction is important for yearling weight and may be needed in a model for slaughter weight. Maternal effects may be of slight importance for yearling weight but of no importance for W18 and SWT. Models for national cattle evaluations for Korean Native cattle for YWT should be considered that include maternal genetic and permanent environmental as well as sire x region x year-season interaction effects, but those effects seem not to be needed for models for W18 and SWT. Not much reranking of sires occurred when ranked was based on the different models for W18 and SWT.

Animals↗

PubMed2000

Parameter estimates for number of lambs born at different ages and for 18-month body weight of Rambouillet sheep.

Genetic parameters were estimated using REML with animal models for number of lambs born and 18-mo body weight in Rambouillet sheep. Number of lambs born was modeled either as repeated measurements on the same trait or as different traits at different ages. The original data for number of lambs born were separated according to age of the ewe into two classes: 2 and 3 yr, and older than 3 yr. Numbers of ewes with lambing records for the age classes were 653 and 466 with 1,106 and 1,118 records, respectively. For the data set that included all ages, the number of ewes was 684 with 2,224 records, and for 18-mo body weight the number of ewes measured was 557. For number of lambs born, the animal model included random genetic, permanent environmental, and residual environmental effects and fixed effects for age of ewe, year of lambing, and month of year of lambing. Lambing day within season was used as a covariate. For 18-mo body weight, year of birth of ewe was used as a fixed effect. Actual age in days when the ewe was weighed was used as a covariate. Estimates of heritability for number of lambs born by age group were .04, for 2- and 3-yr old ewes, and .06, for ewes greater than 3 yr old, from the two-trait (two age of ewe classes) analyses and .06 when all ages were included. Estimates of heritability for number of lambs born from the single-trait analyses were somewhat less than estimates from two-trait analyses. Estimate of genetic correlation between number of lambs born for the 2 and 3 yr and the >3 yr classes was near unity (1.00), which suggests that a repeated measures model for number of lambs born is adequate for making selection decisions. Estimate of genetic correlation between number of lambs born and 18-mo body weight was .35 with a heritability estimate of .48 for 18-mo body weight. The estimate of genetic correlation suggests that selection for increased number of lambs born would result in increased 18-mo body weight.

Age Factors↗

PubMed2000

Parameter estimates for greasy fleece weight of Rambouillet sheep at different ages.

Variance components for greasy fleece weight in Rambouillet sheep were estimated. Greasy fleece weight was modeled either as repeated measurements on the same trait or as different traits at different ages. The original data were separated according to the age of the ewe at shearing into three classes; 1 yr, 2 and 3 yr, and older than 3 yr. An animal model was used to obtain estimates of genetic parameters with a REML algorithm. Total numbers of animals in pedigrees for the different age classes were 696, 729, and 573, respectively, and 822 for the repeated measures model across ages. The animal model included direct genetic, permanent environmental, and residual environmental random effects and fixed effects for age of ewe, shearing date as contemporary group, and number of lambs born. Days between shearings was used as a covariate. Single-trait analyses were initially done to obtain starting values for multiple-trait analyses. A repeated measures model across ages was also used. Estimates of heritability by age group were .42, .50, and .58 from three-trait (age class) analyses and for the repeated measures model the estimate was .57. Estimates of genetic correlations between fleece yields for 1 yr and 2 and 3 yr, 1 yr and >3 yr, and 2 and 3 yr and >3 yr classes were .88, .89, and .97, respectively. These estimates of genetic correlations suggest that a repeated measures model for greasy fleece weight is adequate for making selection decisions.

Aging↗

PubMed2000

Bias in genetic evaluations by records of cows treated with bovine somatotropin.

Records from Dairy Records Management Systems in Raleigh were used to estimate effects of bovine somatotropin (bST) treatment and to predict breeding values for milk production traits. The data comprised 5245 test-day records of bST-treated cows and 126,223 test-day records of untreated cows in first lactation for milk, fat, and protein yields. Fixed effects of bST treatment were estimated from test-day animal models with herd-test-date as another fixed factor. Percentage increases due to bST treatment ranged from 7 to 8% for test-day milk, fat, and protein yields. Random regression coefficients for additive genetic and permanent environmental effects were included in the model. To assess the potential for bias in genetic evaluations when some and not all cows are treated with bST, breeding values predicted by the test-day model with and without effects of bST treatment were compared for cows and sires. Correlations between breeding values predicted from models with and without effects of bST treatment were 0.99. However, relatively large bias was found for individual animals. This result suggests that bias in genetic evaluation caused by ignoring bST treatment may be significant.

Animals↗

PubMed1999

Identification of quantitative trait loci influencing traits related to energy balance in selection and inbred lines of mice.

Energy balance is a complex trait with relevance to the study of human obesity and maintenance energy requirements of livestock. The objective of this study was to identify, using unique mouse models, quantitative trait loci (QTL) influencing traits that contribute to variation in energy balance. Two F2 resource populations were created from lines of mice differing in heat loss measured by direct calorimetry as an indicator of energy expenditure. The HB F2 resource population originated from a cross between a noninbred line selected for high heat loss and an inbred line with low heat loss. Evidence for significant QTL influencing heat loss was found on chromosomes 1, 2, 3, and 7. Significant QTL influencing body weight and percentage gonadal fat, brown fat, liver, and heart were also identified. The LH F2 resource population originated from noninbred lines of mice that had undergone divergent selection for heat loss. Chromosomes 1 and 3 were evaluated. The QTL for heat loss identified on chromosome 1 in the HB population was confirmed in the LH population, although the effect was smaller. The presence of a QTL influencing 6-wk weight was also confirmed. Suggestive evidence for additional QTL influencing heat loss, percentage subcutaneous fat, and percentage heart was found for chromosome 1.

Adipose Tissue↗

PubMed1999

Variance components and breeding values for growth traits from different statistical models.

Estimates of genetic parameters resulting from various analytical models for birth weight (BWT, n = 4,155), 205-d weight (WWT, n = 3,884), and 365-d weight (YWT, n = 3,476) were compared. Data consisted of records for Line 1 Hereford cattle selected for postweaning growth from 1934 to 1989 at ARS-USDA, Miles City, MT. Twelve models were compared. Model 1 included fixed effects of year, sex, age of dam; covariates for birth day and inbreeding coefficients of animal and of dam; and random animal genetic and residual effects. Model 2 was the same as Model 1 but ignored inbreeding coefficients. Model 3 was the same as Model 1 and included random maternal genetic effects with covariance between direct and maternal genetic effects, and maternal permanent environmental effects. Model 4 was the same as Model 3 but ignored inbreeding. Model 5 was the same as Model 1 but with a random sire effect instead of animal genetic effect. Model 6 was the same as Model 5 but ignored inbreeding. Model 7 was a sire model that considered relationships among males. Model 8 was a sire model, assuming sires to be unrelated, but with dam effects as uncorrelated random effects to account for maternal effects. Model 9 was a sire and dam model but with relationships to account for direct and maternal genetic effects; dams also were included as uncorrelated random effects to account for maternal permanent environmental effects. Model 10 was a sire model with maternal grandsire and dam effects all as uncorrelated random effects. Model 11 was a sire and maternal grandsire model, with dams as uncorrelated random effects but with sires and maternal grandsires assumed to be related using male relationships. Model 12 was the same as Model 11 but with all pedigree relationships from the full animal model for sires and maternal grandsires. Rankings on predictions of breeding values were the same regardless of whether inbreeding coefficients for animal and dam were included in the models. Heritability estimates were similar regardless of whether inbreeding effects were in the model. Models 3 and 9 best fit the data for estimation of variances and covariances for direct, maternal genetic, and permanent environmental effects. Other models resulted in changes in ranking for predicted breeding values and for estimates of direct and maternal heritability. Heritability estimates of direct effects were smallest with sire and sire-maternal grandsire models.

Animals↗

PubMed1999

Comparison of models to estimate genetic effects of weaning weight of Angus cattle.

Weaning weights from nine sets of Angus field data from three regions of the United States were analyzed. Six animal models were used to compare two approaches to account for an environmental dam-offspring covariance and to investigate the effects of sire x herd-year interaction on the genetic parameters. Model 1 included random direct and maternal genetic, maternal permanent environmental, and residual effects. Age at weaning was a covariate. Other fixed effects were age of dam and a herd-year-management-sex combination. Possible influence of a dam's phenotype on her daughter's maternal ability was modeled by including a regression on maternal phenotype (fm) (Model 3) or by fitting grandmaternal genetic and grandmaternal permanent environmental effects (Model 5). Models 2, 4, and 6 were based on Models 1, 3, and 5, respectively, and additionally included sire x herd-year (SH) interaction effects. With Model 3, estimates of fm ranged from -.003 to .014, and (co)variance estimates were similar to those from Model 1. With Model 5, grandmaternal heritability estimates ranged from .02 to .07. Estimates of maternal heritability and direct-maternal correlation (r(am)) increased compared with Model 1. With models including SH, estimates of the fraction of phenotypic variance due to SH interaction effects were from .02 to .10. Estimates of direct and maternal heritability were smaller and estimates of r(am) were greater than with models without SH interaction effects. Likelihood values showed that SH interaction effects were more important than fm and grandmaternal effects. The comparisons of models suggest that r(am) may be biased downward if SH interaction and(or) grandmaternal effects are not included in models for weaning weight.

Animals↗

PubMed1999

Estimation of direct, maternal, and grandmaternal genetic effects for weaning weight in several breeds of beef cattle.

Weaning weights from nine parental breeds and three composites were analyzed to estimate variance due to grandmaternal genetic effects and to compare estimates for variance due to maternal genetic effects from two different models. Number of observations ranged from 794 to 3,465 per population. Number of animals in the pedigree file ranged from 1,244 to 4,326 per population. Two single-trait animal models were used to obtain estimates of covariance components by REML using an average information method. Model 1 included random direct and maternal genetic, permanent maternal environmental, and residual environmental effects as well as fixed sex x year and age of dam effects. Model 2 in addition included random grandmaternal genetic and permanent grandmaternal environmental effects to account for maternal effects of a cow on her daughter's maternal ability. Non-zero estimates of proportion of variance due to grandmaternal effects were obtained for 7 of the 12 populations and ranged from .03 to .06. Direct heritability estimates in these populations were similar with both models. Existence of variance due to grandmaternal effects did not affect the estimates of maternal heritability (m2) or the correlation between direct and maternal genetic effects (r(am)) for Angus and Gelbvieh. For the other five populations, magnitude of estimates increased for both m2 and r(am) when estimates of variance due to grandmaternal effects were not zero. Estimates of the correlation between maternal and grandmaternal genetic effects were large and negative. These results suggest that grand-maternal effects exist in some populations, that when such effects are ignored in analyses maternal heritability may be underestimated, and that the correlation between direct and maternal genetic effects may be biased downward if grandmaternal effects are not included in the model for weaning weight of beef cattle.

Animals↗

PubMed1999

Genetic parameters for growth traits for a composite terminal sire breed of sheep.

Records of 9,055 lambs from a composite population originating from crossing Columbia rams to Hampshire x Suffolk ewes at the U.S. Meat Animal Research Center were used to estimate genetic parameters among growth traits. Traits analyzed were weights at birth (BWT), weaning (7 wk, WWT), 19 mo (W19), and 31 mo (W31) and postweaning ADG from 9 to 18 or 19 wk of age. The ADG was also divided into daily gain of males (DGM) and daily gain of females (DGF). These two traits were analyzed with W19 and with W31 in three-trait analyses. (Co)variance components were estimated with REML for an animal model that included fixed effects of sex, age of dam, type of birth or rearing, and contemporary group. Random effects were direct and maternal genetic of animal and dam with genetic covariance, maternal permanent environmental, and random residual. Estimates of direct heritability were .09, .09, .35, .44, .19, .16, and .23 for BWT, WWT, W19, W31, ADG, DGM, and DGF, respectively. Estimates of maternal permanent environmental variance as a proportion of phenotypic variance were .09, .12, .03, .03, .03, .06, and .02, respectively. Estimates of maternal heritability were .17 and .09 for BWT and WWT and .01 to .03 for other traits. Estimates of genetic correlations were large among W19, W31, and ADG (.69 to .97), small between BWT and W31 or ADG, and moderate for other pairs of traits (.32 to .45). The estimate of genetic correlation between DGM and DGF was .94, and the correlation between maternal permanent environmental effects for these traits was .56. For the three-trait analyses, the genetic correlations of DGM and DGF with W19 were .69 and .82 and with W31 were .67 and .67, respectively. Results show that models for genetic evaluation for BWT and WWT should include maternal genetic effects. Estimates of genetic correlations show that selection for ADG in either sex can be from records of either sex (DGM or DGF) and that selection for daily gain will result in increases in mature weight but that BWT is not correlated with weight at 31 mo.

Animals↗

PubMed1999

Genotypic expression at different ages: I. Prolificacy traits of sheep.

Genetic parameters for prolificacy traits for Columbia (COLU), Polypay (POLY), Rambouillet (RAMB), and Targhee (TARG) breeds of sheep were estimated with REML using animal models. Traits were number of live births (LAB), litter size at birth (LSB) and weaning (LSW), and litter weight weaned (LWW). Numbers of observations ranged from 5,140 to 7,095 for prolificacy traits and from 5,101 to 8,973 for litter weight weaned for the four breeds. For single-trait analyses, ewes were classified as young (1 yr old), middle-aged (2 and 3 yr old), or older (> 3 yr old). After single-trait analyses, three-trait analyses were done for each characteristic with traits defined by age class. Generally, heritability estimates from single-trait analyses were low and ranged from .01 to .17 for LAB and LSB and from .00 to .10 for LSW. Heritability estimates obtained for LWW ranged from low to moderate (.00 to .25) and were less for older ewes. Heritability estimates from the three-trait analyses were generally similar to estimates from single-trait analyses. Heritabilities for LAB and LSB were similar, and, for three-trait analyses, they ranged across age groups from .07 to .13 for COLU, .13 to .16 for POLY, .10 to .16 for RAMB, and .01 to .16 for TARG. Estimates for LSW from three-trait analyses ranged from .07 to .12 for COLU, .04 to .09 for POLY, .01 to .11 for RAMB, and .03 to .11 for TARG. For LWW, heritabilities ranged from .00 to .21 for COLU, .05 to .08 for POLY, .12 to .15 for RAMB, and .18 to .29 for TARG. Genetic correlations for LAB, LSB and LSW among age-defined traits ranged from .25 to 1.00. Genetic correlations for LAB and LSB between young and middle and between young and older age classes were less than .80 in COLU, POLY, and RAMB breeds. Only genetic correlations between middle and older age classes for these breeds were greater than .80. For TARG, genetic correlations among all age classes were greater than .80 (.88 to 1.00) for those traits. All genetic correlations among ages for LSW were greater than .80 for POLY and TARG. For RAMB, only the correlation between young and older age classes for LSW was less than .80 (.45). None was greater than .80 for COLU. For LWW, genetic correlations among all age classes in POLY and RAMB were greater than .80 (.82 to 1.00). For COLU, genetic correlation between young and middle was low (.07), between young and older was high (.88), and between middle and older classes was moderately high (.54). For TARG, genetic correlations were .49, .65, and .98 for young-middle, young-older, and middle-older age classes, respectively. Results indicate that more progress could be made in selection programs for prolificacy traits in some sheep breeds by considering age of ewe as a part of the trait rather than by simply adjusting for ages of ewes.

Aging↗

PubMed1999

Genotypic expression at different ages: II. Wool traits of sheep.

Genetic parameters for wool traits for Columbia, Polypay, Rambouillet, and Targhee breeds of sheep were estimated with single- and multiple-trait analyses using REML with animal models. Traits considered were fleece grade, fleece weight, and staple length. Total number of observations ranged from 11,673 to 34,746 for fleece grade and fleece weight and from 3,500 to 11,641 for staple length for the four breeds. For single-trait analyses, data were divided by age of ewe: young ages (age of 1 yr), middle ages (ages of 2 and 3 yr), and older ages (age greater than 3 yr). Heritability estimates averaged over breeds for fleece grade decreased from .42 at a young age to .37 for older ages. For fleece weight, heritability estimates averaged .52, .57, and .55 within the successively older groups. Heritability estimates for staple length averaged .54 for young and middle age classes. Few older ewes had staple length measurements. After single-trait analyses, new data sets were created for three-trait analyses with traits defined by three age classes when animals were measured. Heritability estimates with three-trait analyses, except for a few cases, were somewhat greater than those from single-trait analyses. For fleece grade, the genetic correlations averaged over breeds were .72 for young with middle, .42 for young with older, and .86 for middle with older age classes. For fleece weight, the average genetic correlations were .81, .83, and .98. For staple length, the average genetic correlation for young with middle age classes was .82. Estimates of genetic correlations across ages varied considerably among breeds. The average estimates of correlations suggest that fleece grade may need to be defined by age, especially for the Columbia and Rambouillet breeds. For fleece weight and staple length, however, the average correlations suggest no need to define those traits by age.

Aging↗

PubMed1999

Genotypic expression with different ages of dams: III. Weight traits of sheep.

Correlations between genetic expression in lambs when dams were young (1 yr), middle-aged (2 and 3 yr), or older (older than 3 yr) were estimated with three-trait analyses for weight traits. Weights at birth (BWT) and weaning (WWT) and ADG from birth to weaning were used. Numbers of observations were 7,731, 9,518, 9,512, and 9,201 for Columbia (COLU), Polypay (POLY), Rambouillet (RAMB), and Targhee (TARG) breeds of sheep, respectively. When averaged, relative estimates for WWT and ADG were similar across breeds. Estimates were variable across breeds. On average, direct heritability was greater when environment was young dams (.44 for BWT and .34 for WWT) than when environment was dams of middle age or older (.24 and .28 for BWT and .20 and .16 for WWT, respectively). Maternal heritability was greater when dams were middle-aged or older (.28 and .22 vs .18) for BWT but was greater when dams were younger (.10 vs .05 and .04) for WWT. The estimates of genetic correlations for direct effects across age of dam environments averaged .32 for birth weight and averaged .70 for weaning weight. Average estimates of maternal genetic correlations across age of dam classes were .36 or less for both BWT and WWT. Average estimates of correlations among maternal permanent environmental effects were .49 or less across age of dam classes. Total maternal effects accounted for .33 to .42 of phenotypic variance for BWT and for .09 to .26 of phenotypic variance for WWT. The average estimates of genetic correlations between expressions of the same genotypes with different ages of dams suggest that measurements of BWT of lambs with dams in young, middle, and older age classes should be considered to be separate traits for genetic evaluation and that for WWT measurements with young age of dam class and combined middle and older age of dam classes should be considered to be separate traits for genetic evaluation.

Aging↗

PubMed1999

Variance caused by cytoplasmic line and sire by herd interaction effects for milk yield considering estimation bias.

A total of 138,869 lactation milk yields (305 d, milked twice daily, mature equivalent) from the first three parities of 68,063 New York Holstein cows were used to estimate variance components that were due to additive direct genetic effects, cow permanent environmental effects (cow within sire for sire model), sire by herd interaction effects, and cytoplasmic line effects. The original data were assigned to 10 random samples, which were each analyzed using an animal model and a sire model. From each sample of original data, 20 other samples were analyzed with levels assigned randomly to cytoplasmic and interaction effects (data with randomly simulated levels). Ten of those samples were analyzed with an animal model and 10 with a sire model. The models also included fixed effects of herd-year-seasons. For the animal model and sire model, average fractions of phenotypic variance and average standard errors were, respectively, for additive direct genetic effects 0.300 (0.029) and 0.228 (0.040) for original data and 0.325 (0.025) and 0.262 (0.039) for data with randomly simulated levels. For cow permanent environmental effects the respective averages were 0.242 (0.024) and 0.444 (0.014) for original data and 0.235 (0.025) and 0.492 (0.016) for data with randomly simulated levels. The averages for sire by herd interaction effects were 0.015 (0.008) and 0.018 (0.007) for original data and 0.003 (0.007) and 0.004 (0.009) for data with randomly simulated levels. For cytoplasmic line effects, the respective averages were 0.011 (0.007) and 0.043 (0.008) for original data and 0.003 (0.006) and 0.003 (0.007) for data with randomly simulated levels. The differences between estimates of variance components for original data and data with randomly simulated levels suggest that estimates of fractions of total variance caused by sire by herd interaction and cytoplasmic effects estimated with REML may be biased upward by 0.003 to 0.004.

Analysis of Variance↗

PubMed1998

Parameter estimates for direct, maternal, and grandmaternal genetic effects for birth weight and weaning weight in Hereford cattle.

Birth and weaning weights adjusted for age of dam from four lines of Hereford cattle were analyzed to determine the relationships among grandmaternal, maternal, and direct genetic effects. Three lines were selected for 1) weaning weight (WWL), 2) yearling weight (YWL), and 3) an index of yearling weight and muscle score (IXL). The fourth line was an unselected control line (CTL). Numbers of observations ranged from 1,699 (CTL) to 2,811 (WWL), and number of animals in the pedigree file ranged from 2,266 to 3,192. Two animal models were used to obtain estimates by REML using an average information method. Model 1 included random direct and maternal genetic, permanent maternal environmental, and residual environmental effects, and fixed sex x year effects. Model 2 additionally included random grandmaternal genetic and permanent grandmaternal environmental effects. For birth weight, Models 1 and 2 gave almost identical estimates for direct and maternal heritability, and for the fraction of variance that was due to maternal permanent environmental effects. Estimates for grandmaternal heritability could be obtained only for IXL (.03) and CTL (.01). For weaning weight, estimates for direct heritability were similar from both models. Estimates for maternal heritability from Model 1 were .18, .20, .13, and .20, and corresponding estimates from Model 2 were .34, .31, .13, and .34 for WWL, YWL, IXL, and CTL, respectively. For IXL, estimates for variances that were due to grandmaternal genetic and grandmaternal permanent environmental variances could not be obtained and were set to zero. Grandmaternal heritability estimates for WWL, YWL, and CTL were .05, .09, and .12. Estimates of correlations between direct and maternal genetic effects were -.13, -.44, -.11, and -.26 for WWL, YWL, IXL, and CTL. Estimates of correlations between direct and grandmaternal genetic effects were .21, .83, and .55, and those between maternal and grandmaternal genetic effects were -.99, -.84, and -.76 for WWL, YWL, and CTL, respectively. These results indicate that grandmaternal effects may be important for weaning weight and that maternal heritability may be underestimated if grandmaternal effects are not included in the model.

Animals↗