Biomedical subjects

G R Wiggans

Publications and source records attributed to G R Wiggans.

At least 19 recordsLinked to original sources

PubMed2006

Genetic parameters and evaluation of rear legs (rear view) for Brown Swiss and Guernseys.

Genetic parameters were estimated for rear legs (rear view; RLRV) and 15 current linear type traits of Brown Swiss and Guernsey dairy cattle. The Brown Swiss Cattle Breeders' Association of the USA and the American Guernsey Association began scoring RLRV in 2004. For Brown Swiss, 8,502 records were available for 7,676 cows in 417 herds; Guernsey data included 5,437 records for 4,749 cows in 229 herds. Nine unknown-parent groups were defined for each breed, each with 2 birth years. The model included fixed effects for the interaction of herd, appraisal date, and parity; appraisal age within parity; and lactation stage within parity and random effects for animal, permanent environment, and residual error. The multitrait analysis for RLRV and the 15 linear type traits used canonical transformation, multiple diagonalization, and a decelerated expectation-maximization REML algorithm. For Brown Swiss, heritability was 0.102 for RLRV and ranged from 0.099 for rear legs (side view) to 0.453 for stature. For Guernseys, heritability ranged from 0.078 for RLRV to 0.428 for stature. For Brown Swiss, the highest genetic correlation with RLRV was 0.71 for rear udder width; the most negative correlation was -0.19 with rump angle. For Guernseys, the highest genetic correlations with RLRV were 0.43 for rear udder width and 0.42 for body depth; the most negative correlation was -0.46 with rear legs (side view). With heritability near 0.10, RLRV should be useful in selection for improved locomotion. Release of genetic evaluations for RLRV began in May 2006 for Brown Swiss and Guernseys.

Animals↗

PubMed2006

Characterization of Holstein heifer fertility in the United States.

The overall object of this research was to characterize US Holstein (virgin) heifer fertility. This included investigation of factors influencing heifer fertility and estimation of heritability, as well as correlations with cow fertility and first-lactation milk yield. A secondary objective was to compare linear and logistic model estimates of fixed effects and linear and threshold model estimates of heritability. Data consisted of Holstein heifers, which were artificially inseminated, with their first breeding between March 2003 and August 2005. Herds were required to have at least 60 breedings across the 3 yr of data and an overall mean conception rate (CR) between 20 and 80%. After edits there were 537,938 breedings of 362,512 heifers in 2,668 herds from 41 states used for analysis. After edits, the overall mean CR for US Holstein heifers was 57%. Linear and logistic model estimates for all factors were nearly identical. Year of breeding accounted for the most variation in heifer CR, with heifer age and month of breeding being the next most important factors. Conception rate in heifers is maximal at an intermediate age of 15 to 16 mo. Heifers at 26 mo of age and older have roughly a 10% lower CR than heifers bred at younger ages. Although month of breeding affected heifer CR, effects are less than for cows. In contrast to cow fertility, heifer CR is nearly as good in the hotter summer months as in cooler months. Approximately 88% of US herds had a 40 to 70% heifer CR. Heritability estimates of heifer CR on first service were 0.5% from the linear model and 1.0% from the threshold model. Genetic correlation estimates of heifer CR on first service with cow CR on first service and with first-lactation milk yield were 0.39 and -0.19, respectively. Results indicated that selection on either the currently available US daughter pregnancy rate evaluations for cow fertility or on cow CR will also improve heifer fertility. Furthermore, heritability of heifer CR is lower than for cow CR and reporting of heifer breedings is currently less complete than for cow breedings. Thus, there are currently no immediate plans to implement a US genetic evaluation for heifer CR.

Animals↗

PubMed2006

Accounting for heterogeneous variances in multitrait evaluation of Jersey type traits.

The multitrait genetic evaluation system for type traits was modified to estimate adjustments for heterogeneous variance (HV) simultaneously with estimated breeding values (EBV) for final score and 14 linear traits. Each variance within herd, year, and parity was regressed toward a predicted variance, which was determined by fitting a model with fixed effects of the mean final score for herd, size of the contemporary group, appraisal month, and year-season and a random effect for herd-appraisal date. Herd-appraisal date was included as a random effect to regress the observed heterogeneity for a given herd-appraisal date toward the fixed effects. Method R was used to estimate variances for the heterogeneity model in each EBV iteration. To evaluate the effect of the adjustment, parent averages were calculated from evaluations with recent appraisals removed. The adjustment slightly improved correlations within birth year between those parent averages and EBV from current data on bulls for most traits, but did not improve correlations for final score, strength, dairy form, teat length, or foot angle. Annual trends for EBV were lower with HV adjustment than for unadjusted EBV for all traits except final score and rump angle for cows and rump width for bulls, which were essentially unchanged. Standard deviations of Mendelian sampling (evaluation minus mean of parent evaluations) declined less over time for HV-adjusted than for unadjusted evaluations. The slope at year 2000 of Mendelian-sampling standard deviations from HV-adjusted evaluations ranged from 10.0% for udder depth to 42.7% for teat length compared with the slope for unadjusted evaluations. This HV adjustment, which was implemented for USDA evaluations in May 2001 for Jerseys and in 2002 for other breeds, improves the accuracy of evaluations, particularly comparisons over time, by accounting for the change in variation.

Animals↗

PubMed2005

Genetic evaluation of calving ease for Brown Swiss and Jersey bulls from purebred and crossbred calvings.

The objective of this study was to examine the feasibility of implementing routine national calving ease (CE) genetic evaluations of Brown Swiss (BS) and Jersey (JE) sires that include records of crossbred calvings. Records were available for 11,793 BS calvings, 3431 BS-sired crosses, 65,293 JE calvings, and 7090 JE-sired crosses. Evaluations were performed for each breed using only purebred calvings and using both purebred and crossbred calvings. In the latter evaluations, the sire-maternal grandsire model used for the routine evaluation of Holstein (HO) CE was modified to include a fixed breed composition effect to account for differences between purebred and crossbred calvings. Jersey cows had very little calving difficulty (0.5 to 0.7%) and JE bulls had a very small range of evaluations, suggesting that a routine JE evaluation would be of little value. Results from the BS evaluations suggest a routine evaluation would provide BS breeders with a useful tool for genetic improvement. Further examination of data showed that many BS calvings were in mixed herds with HO calvings. As a result, a joint evaluation for BS and HO bulls was developed. The BS data showed that there is similar genetic variability as found in the HO population, which suggests implementation of a routine evaluation including BS CE would be of value. It appears BS bulls may produce daughters with superior maternal calving ability compared with HO. Validation of the joint evaluation was performed by comparing results with the routine HO evaluation. Holstein solutions from the joint evaluation were comparable to results from the routine HO-only evaluation. Correlations among solutions and evaluations showed HO evaluations were not adversely affected by BS data and BS sires were reranked as compared with the BS-only evaluation.

Animals↗

PubMed2005

Accounting for pregnancy diagnosis in predicting days open.

The system for estimating days open for cows with no subsequent lactation was examined to determine if estimates should vary depending on pregnancy diagnosis. Pregnancy diagnosis information was unavailable when the original prediction system was developed, but collection was begun in 2002. New prediction equations were estimated from nearly 1.1 million Holstein lactations for 20-d intervals from 110 to 250 days in milk (DIM). Use of pregnancy diagnosis improved accuracy compared with the original system. The improvement was particularly evident for lactations of cows confirmed to be open in the 130-to-149 DIM interval, where predicted days open increased by > 96 d. For lactations of cows with a confirmed pregnancy, predicted days open decreased by 18 d for the same interval. Prediction errors decreased with increasing DIM. Jersey lactations averaged fewer days open, but in most cases Holstein solutions provided adequate predictions. Specific adjustments were generated for Jersey lactations with no breedings reported. Those adjustments reduced the predicted days open averaged across parity by an amount that increased from 9 to 27 d with DIM interval. The new prediction equations were implemented for November 2004 evaluations for daughter pregnancy rate.

Animals↗

PubMed2005

Adjustment for heterogeneous covariance due to herd milk yield by transformation of test-day random regressions.

A method of accounting for differences in covariance components of test-day milk records was developed based on transformation of regressions for random effects. Preliminary analysis indicated that genetic and nongenetic covariance structures differed by herd milk yield. Differences were found for phenotypic covariances and also for genetic, permanent environmental, and herd-time covariances. Heritabilities for test-day milk yield tended to be lower at the end and especially at the start of lactation; they also were higher (maximum of approximately 25%) for high-yield herds and lower (maximum of 15%) for low-yield herds. Permanent environmental variances were on average 10% lower in high-yield herds. Relative herd-time variances were approximately 10% at start of lactation and then began to decrease regardless of herd yield; high-yield herds increased in midlactation followed by another decrease, and medium-yield herds increased at the end of lactation. Regressors for random regression effects were transformed to adjust for heterogeneity of test-day yield covariances. Some animal reranking occurred because of this transformation of genetic and permanent environmental effects. When genetic correlations between environments were allowed to differ from 1, some additional animal re-ranking occurred. Correlations of variances of genetic and permanent-environmental regression solutions within herd, test-day, and milking frequency class with class mean milk yields were reduced with adjustment for heterogeneous covariance. The method suggests a number of innovative solutions to issues related to heterogeneous covariance structures, such as adjusted estimates in multibreed evaluation.

Aging↗

PubMed2004

Development of a national genetic evaluation for cow fertility.

A national fertility evaluation was developed based on pregnancy rate, which measures the percentage of nonpregnant cows becoming pregnant within each 21-d opportunity period. Data for evaluation are days open, which are calculated as date pregnant minus previous calving date. Date pregnant is determined from last reported breeding or from subsequent calving minus expected gestation length. Success or failure of last breeding can be confirmed by veterinary diagnosis or a report that the cow was sold because of infertility. Data are adjusted for parity and calving season within geographic region and time period and evaluated. Fertility records are considered complete at 250 d in milk, and lower and upper limits of 50 and 250 d are applied to days open. For calculation of genetic evaluations, days open are converted to pregnancy rate by the linear formula pregnancy rate = 0.25 (233 - days open). Evaluations are expressed as predicted transmitting ability for daughter pregnancy rate, and calculation is done with an animal model. Genetic correlations among several fertility measures and other evaluated traits were estimated from 3 large data sets. Correlation with days open was less for nonreturn rate than for days to first breeding, probably because nonreturn rate had lower heritability. Cow fertility was negatively correlated with yield but is a major component of longevity. Thus, recent selection for longevity may have slowed the long-term decline in fertility. Direct selection for fertility could halt or reverse the decline.

Agriculture↗

PubMed2004

Relationship of test-day somatic cell score with test-day and lactation milk yields.

To determine the relationship of test-day (TD) somatic cell score (SCS) to TD and lactation milk yields, 1,320,590 records from Holstein first and second calvings from 1995 through 2002 were examined. All lactations had recorded yield and SCS for at least the first 4 TD. Least square analyses were conducted for yields on TD 2 through 10 within herd and cow. The model included regressions on current TD SCS and mean SCS of all previous TD with separate estimates by parity; effects for parity and calving year were included as well as regression on days in milk on TD 1. Corresponding analyses were conducted without regression on current SCS. An analysis of lactation yield was performed with a similar model and regression on all TD SCS. The SCS was highest most often on TD 1 for parity 1 (22.5%) and on TD 10 for parity 2 (18.5%). Regression of TD milk yield on mean of previous TD SCS was highest during the latter half of lactation (maximum of -0.346 kg/SCS unit on TD 9) for parity 1 and during TD through 7 (maximum of -0.366 kg/SCS unit on TD 4) for parity 2. Regression of TD yield on current TD SCS tended to be larger for later lactation. Regression of lactation yield on TD SCS was negative and important for TD 1 through 6 for parity 1 and for all TD for parity 2. To minimize milk loss, mastitis control is most important immediately pre- and postcalving for parity 1 and throughout lactation for parity 2.

Animals↗

PubMed2004

Type trait (co)variance components for five dairy breeds.

(Co)variance components were estimated for final score and 14 or 15 linear type traits for the Ayrshire, Brown Swiss, Guernsey, Jersey, and Milking Shorthorn breeds. Appraisals from 1995 or later were used. New estimates were calculated to accommodate changes in scoring of traits and because of a change from multiplicative to additive adjustment for age and lactation stage. The adjustment method was changed for better support of the adjustment for heterogeneous variance within iteration, which was implemented in 2002. The largest changes in heritability were an increase of 0.10 for rump angle for Milking Shorthorns and a decrease of 0.11 for udder depth for Jerseys. The new estimates of (co)variance components should provide improved accuracy of type evaluations, particularly for traits that have had variance changes over time.

Aging↗

PubMed2004

Estimated heterogeneity of phenotypic variance of test-day yield with a structural variance model.

First-lactation test-day milk, fat, and protein yields from New York, Wisconsin, and California herds from 1990 through 2000 were adjusted additively for age and lactation stage. A random regression model with third-order Legendre polynomials for permanent environmental and genetic effects was used. The model included a random effect with the same polynomial regressions for 2 yr of calvings within herd (herd-time effect) to provide herd-specific lactation curves that can change every 2 yr. (Co)variance components were estimated using expectation-maximization REML simultaneously with phenotypic variances that were modeled using a structural variance model. Maximum heritability for test-day milk yield was estimated to be approximately 20% around 200 to 250 d in milk; heritabilities were slightly lower for test-day fat and protein yields. Herd-time effects explained 12 to 20% of phenotypic variance and had the greatest impact at start of lactation. Variances of test-day yields increased with time, subclass size, and milking frequency. Test month had limited influence on variance. Variance increased for cows in herds with low and high milk yields and for early and late lactation stages. Repeatabilities of variances observed for a given class of herd, test-day, and milking frequency were 14 to 17% across nested variance subclasses based on lactation stage.

Age Factors↗

PubMed2003

Calving ease (Co)variance components for a sire-maternal grandsire threshold model.

Variance components for a sire-maternal grandsire (MGS) threshold model were estimated from subsets of the US calving ease (CE) database, which includes over 10 million calving records with CE scored 1 (no problem) to 5 (extreme difficulty). Selected records included sire and MGS among the 2601 most frequently appearing bulls. The data were further restricted by requiring at least 20 records in each herd year. Five mutually exclusive sample datasets of approximately 200,000 records each were created based on herd code. The model included random herd-year, sire, MGS, and residual effects and fixed year-season, parity-sex, and birth year of sire and MGS effects. Fewer than 50 iterations were required to reach convergence. The (co)variance component estimates from the five replicates were quite similar. The set of estimates (0.438, herd-year; 0.022, sire; 0.016, MGS; 0.009, sire-MGS) that yielded among the highest heritabilities (0.086, direct; 0.048, maternal) and a correlation of direct and maternal effects near the mean (-0.12) was selected for use in the implementation of a sire-MGS model for CE.

Analysis of Variance↗

PubMed2003

Technical note: detection and adjustment of abnormal test-day yields.

A method to detect and to adjust or exclude abnormally low or high milk, fat, and protein yields on test-day (TD) was developed. Predicted TD yield is calculated based on preceding and subsequent (if available) TD yields. Observed TD yields that are < 60% or > 150% of predicted TD yield are defined as abnormal. Most abnormal yields are adjusted to this floor or ceiling, but some are excluded. Yields of < 4.5 kg that are identified as from a cow that was sick or that are less than half the mean of adjacent tests are excluded as are yields of > 59 kg above predicted yield. Lactation yields are calculated from the restricted TD yields. When this procedure was applied to 2002 data, 1.8% of milk, 2.4% of fat, and 1.6% of protein yields on TD were below the acceptance range and 0.1% of milk and protein and 0.8% of fat were above. Predicted TD yield was calculated as preceding TD yield plus preceding test interval multiplied by daily yield change (slope) based on days in milk (DIM), DIM2, previous normal TD yield, and interaction between DIM and previous TD yield. To accommodate changes in slope at peak yield, separate coefficients were estimated for < 50 and > or = 50 DIM. Herd mean was used when only one TD was recorded for a cow (or when two were recorded and the second was designated as abnormal based on the first) and to determine an acceptable range for component percentages. Predicted TD yield for first TD was based on subsequent rather than previous normal TD. To test the adjustments, lactation records with one abnormal TD yield or more were matched with subsequent lactation records. Correlation between consecutive lactations increased from 0.692 to 0.693 for milk (561,063 lactation pairs), from 0.653 to 0.660 for fat (951,387 lactation pairs), and from 0.686 to 0.694 for protein (488,653 lactation pairs). Outlier adjustment improved the correlation between consecutive lactation yields and is applied routinely to TD records of cows for calvings since 1997.

Animals↗

PubMed2003

Implementation of a sire-maternal grandsire model for evaluation of calving ease in the United States.

The objective of this study was to add a maternal grandsire (MGS) effect to the existing sire model for national calving ease genetic evaluations. The Animal Improvement Programs Laboratory (AIPL) of USDA assumed responsibility for conducting the national genetic evaluation for calving ease and maintaining the associated database in 1999. Existing evaluations used a sire threshold model. Adding an MGS effect to the model was expected to improve accuracy by partially accounting for merit of mates and differences in maternal ability of the dams. Dystocia data were migrated to a relational database integrated with the AIPL production database. This database design allowed more rigorous data edits by comparison with the production data and improved MGS identification (ID) rate by utilizing pedigrees from the production records. Integration of dystocia data with production data increased MGS ID rate from 58 to 73%. In addition, nearly 200,000 duplicate records were identified using the new edit system. Sire and sire-MGS models were compared using over 10 million observations available for the August 2002 national genetic evaluation. The sire model included herd-year, season, sex of calf, parity of dam, birth year group of sire, and sire. For the sire-MGS model, MGS and birth year group of MGS were added, year-seasons rather than seasons were used, and sex of calf and parity of dam were combined into a single interaction effect. Herd-year, sire, and MGS were random effects. Variance components used for the sire model were those previously used in the national evaluation and for the sire-MGS model were estimated in a separate study. Correlations between predicted genetic merits for service sire calving ease from the two models was 85%, indicating general agreement, but with some significant differences in evaluations. A sire-MGS model was implemented in August 2002 for the national calving ease genetic evaluation system.

Animals↗

PubMed2003

Within-herd effects of age at test day and lactation stage on test-day yields.

Variance ratios were estimated for random within-herd effects of age at test day and lactation stage, on test-day yield and somatic cell score to determine whether including these effects would improve the accuracy of estimation. Test-day data starting with 1990 calvings for the entire US Jersey population and Holsteins from California, Pennsylvania, Wisconsin, and Texas were analyzed. Test-day yields were adjusted for across-herd effects using solutions from a regional analysis. Estimates of the relative variance (fraction of total variance) due to within-herd age effects were small, indicating that regional adjustments for age were adequate. The relative variances for within-herd lactation stage were large enough to indicate that accuracy of genetic evaluations could be improved by including herd stage effects in the model for milk, fat, and protein, but not for somatic cell score. Because the within-herd lactation stage effect is assumed to be random, the effect is regressed toward the regional effects for small herds, but in large herds, lactation curves become herd specific. Model comparisons demonstrated the greater explanatory power of the model with a within-herd-stage effect as prediction error standard deviations were greater for the model without this effect. The benefit of the within-herd-stage effects was confirmed in a random regression model by comparing variance components from models with and without random within-herd regressions and through log-likelihood ratio tests.

Age Factors↗

PubMed2001

Impact of paternity errors in cow identification on genetic evaluations and international comparisons.

The impact of paternity identification errors on US genetic evaluations and international comparisons of Holstein dairy bulls for milk, fat, and protein yields was investigated. Sire identification was replaced for 11% of Holstein cows that were sired by AI bulls and had records in the US database for national genetic evaluations; US evaluations were computed based on those modified pedigrees and compared with official national evaluations. Estimated breeding values from the data with introduced paternity errors were biased, especially for later generations. Estimated genetic trends decreased by 11 to 15%. Estimates of standard deviations of sire transmitting ability also decreased by 8 to 9%. International multitrait across-country comparisons of bulls were computed based on national evaluations from the United States, Canada, New Zealand, and The Netherlands. Estimates of genetic correlations between the United States and other countries decreased by 0.04 to 0.06 when US evaluations were based on modified pedigree. The resulting bias toward selection of domestic bulls and the inability to identify truly superior animals that are available internationally could decrease potential selection differentials by 0.07 to 0.09 standard deviation units on the US scale, which corresponds to sire breeding values of approximately 50 kg for milk, 3 kg for fat, and 1.7 kg for protein. Losses for the other countries were lower and ranged from 0.02 to 0.05 standard deviation units, because a correlation of less than unity with the United States decreased the impact of US cow paternity errors on the scales of other countries. Although paternity verification is desirable and technically feasible, commercial implementation would require low testing costs.

Animals↗

PubMed2000

Herd and state means for somatic cell count from dairy herd improvement.

To determine the impact of reducing the current legal limit of 750,000 cells/ml for somatic cell count (SCC) in US market milk, data were examined from 539,577 herd test days for Dairy Herd Improvement herds on test during 1996 and 1997. Somatic cell scores for individual cows were converted to SCC. The SCC for each cow was weighted by milk yield and used to compute herd mean on test day. The mean for each state was derived by weighting herd test-day SCC by herd test-day milk yield. State means were lowest in the West and highest in the Southeast. The percentage of herd test days with an SCC of >750,000 cells/ml ranged from 0 to 14% across states; the mean was 4%. Only 1% of the herd tests were >750,000 cells/ml on 2 consecutive test days. Mean SCC in the United States was 307,100 cells/ml for 1996 and 313,500 cells/ml for 1997. Mean SCC was lower during October through January (280,000 to 300,000 cells/ml) than during July and August (340,000 cells/ml). Herd size and SCC were negatively related; larger herds had lower SCC. Because records of some cows treated with antibiotics were included in the data, herd SCC means likely were higher than corresponding bulk tank SCC. Most herds had test-day SCC that were substantially below legal bulk tank limits and could have met lower limits (e.g., 500,000 cells/ml).

Animals↗

PubMed1999

A genome scan for QTL influencing milk production and health traits in dairy cattle.

A genome scan was conducted in the North American Holstein-Friesian population for quantitative trait loci (QTL) affecting production and health traits using the granddaughter design. Resource families consisted of 1,068 sons of eight elite sires. Genome coverage was estimated to be 2,551 cM (85%) for 174 genotyped markers. Each marker was tested for effects on milk yield, fat yield, protein yield, fat percentage, protein percentage, somatic cell score, and productive herd life using analysis of variance. Joint analysis of all families identified marker effects on 11 chromosomes that exceeded the genomewide, suggestive, or nominal significance threshold for QTL effects. Large marker effects on fat percentage were found on chromosomes 3 and 14, and multimarker regression analysis was used to refine the position of these QTL. Half-sibling families from Israeli Holstein dairy herds were used in a daughter design to confirm the presence of the QTL for fat percentage on chromosome 14. The QTL identified in this study may be useful for marker-assisted selection and for selection of a refined set of candidate genes affecting these traits.

Animals↗

PubMed1999

Standardization and conversion of marker polymorphism measures.

Large scale gene mapping efforts in domestic animals have generated and mapped a large number of genetic markers that are useful for mapping quantitative trait and disease loci and for DNA diagnostic purposes such as parentage testing. Marker polymorphism is an important criterion for selecting genetic markers in planning experiment for mapping quantitative trait loci or for DNA diagnostic purposes. Current formulations of marker polymorphism measures are functions of marker allele frequencies. In this study, two measures of marker polymorphism that are available from gene mapping studies and do not require allele frequencies were proposed and analyzed: the observed polymorphic information content (PIC) and the observed family information content (FIC). The observed FIC was more stable than the observed PIC because the observed FIC is unaffected by the variation in the frequency of heterozygous parents. However, both FIC and PIC are dependent on the gene mapping design. The effective number of alleles is recommended as a tool to standardize marker polymorphism measures so that polymorphism of different markers can be compared on an equal basis, and to obtain a new polymorphism measure (such an exclusion probability) from an existing measure (such as FIC). The usage of the effective number of alleles to standardize FIC, PIC and exclusion probabilities is illustrated using genetic markers in a published linkage map.

Animals↗