Student Research

Maternal lineage effects on milk production traits, considered indicative of cytoplasmic inheritance, were evaluated with animal models. Cattle were from a selection experiment begun in 1968. Maternal pedigrees were traced to the first female member in the Holstein-Friesian Herd Book, and foundation females were assigned to maternal lineage groups. All models accounted for year-season of calving, parity, and selection lines. Maternal lineage effects were included in a repeated records model with cow effects and preadjustment for sire and maternal grandsire transmitting abilities. Maternal lineage accounted for 5.2, 4.1, and 10.5 percent of phenotypic variation in milk yield, fat yield, and fat percentage, respectively. Maternal lineage was evaluated as a fixed effect in an animal model including random animal and permanent environmental effects. Ranges of maternal lineage estimates were 2934 kg milk, 154 kg fat, and.907 percent fat. Maternal lineage significantly affected fat percentage. Maternal genetic (nuclear) effects and their covariance with additive animal effects did not significantly account for additional variation nor did they influence maternal lineage estimates. Maternal lineage also affected calculated net energy of milk;Mitochondrial DNA (mtDNA) displacement-loop (D-loop) sequence polymorphism information from 36 maternal lineages was evaluated. Of 17 base pair substitutions evaluated, several were significantly associated with milk, fat, and solids-not-fat production. Another marked a large impact on fat percentage and net energy concentration. Positive and negative effects on all production traits were observed. One base pair substitution was related to a large favorable decrease in days open, number of breedings, and reproductive costs;Maternal lineage groups defined by several methods of classification using mtDNA sequence characteristics were evaluated with animal models. Groups defined as those maternal lineages with or without base pair substitution at nucleotide 169 accounted for increased milk fat and estimated milk energy production. Clustering the 36 maternal lineages using 17 mtDNA D-loop sequence differences produced groups with significant effect on fat percentage and energy concentration.

First lactation milk, fat, protein, and lactose yields and percentage yields were analyzed using a multiple-trait sire model including herd-year-season, sire group, and age of cow as fixed effects. Variance components were estimated using restricted maximum likelihood with an expectation-maximization algorithm, and included sire relationships. Somatic cell score (SCS) was fit both as a fixed effect in the model and as an additional dependent variable in two analyses. The results were almost identical for both analyses. Lactose percentage means ranged from 4.84 to 4.97% across three dairy breeds. Data used to estimate variance components were first lactation Holstein records from 5246 daughters of 392 AI sires, collected from 1986 to 1988. Heritability estimates were.30,.29,.27, and.26 for milk, fat, protein, and lactose yields,.45,.47, and.53 for percentage yields, and.16 for SCS, respectively. Genetic correlations of lactose percentage with milk, fat, protein, fat and protein percentages, and SCS were -.30, -.16, -.21,.16,.29, and -.11, respectively, while phenotypic correlations were -.08, -.02,.01,.11,.29, and -.15;A gene flow algorithm developed by Harris and Freeman (1991), which accounted for multiple stage selection with overlapping generations, and the previous estimates of variance components were used to estimate response to selection. Progress could be made in any single trait through single-trait selection for that trait. Desirable genetic gains in all economically important traits, however, could not be achieved simultaneously by single-trait selection for any one trait. Multiple-trait selection indexes involving milk and protein yields would be expected to result in genetic gains similar to single-trait selection for milk and protein yields. In addition to the increase in milk and protein yields, lactose percentage would decrease and fat percentage would increase minimally, but somatic cell score would increase.

Immunological assays were evaluated in 137 Holstein cows during the periparturient period. Results for all immune assays were altered around calving time. Heritability estimates were obtained before, at, and after immunosuppression. Significant genetic variability was found in the periparturient changes for neutrophil chemokinesis, assays measuring neutrophil respiratory burst (cytochrome C reduction, chemiluminescence, and iodination), serum concentration in IgG[subscript]1, IgG[subscript]2, and IGM, and serum hemolytic complement activity;Genetic factors affecting mastitis indicators (somatic cell score, clinical cases, bacteriological status) and retroviral infections (bovine leukosis virus, bovine immunodeficiency virus) were studied. Heritabilities for all mastitis indicators averaged 0.10, but differences were seen among mastitis indicators. Heritability estimates for retroviral infections were close to zero. The genetic correlation between the number of quarters infected with minor and major pathogens was negative;We examined the genetic effects on the disease indicators of our immunological assays and of the alleles at the BoLA-DRB3 locus, at the IgG[subscript] 2a locus, and at the locus for the mutation responsible for the bovine leukocyte adhesion deficiency syndrome. Negative genetic associations were found between all mastitis indicators and the presence of BoLA-DRB3 alleles b12 and b11, various neutrophil assays, the number of blood mononuclear cells, and the presence of IgG[subscript] 2a allele A1. BoLA-DRB3 allele b3 was negatively associated with infection with bovine immunodeficiency virus. No genetic effect of any of the immunological parameters on infection with bovine leukosis virus could be demonstrated.

Additive genetic, permanent environmental, and residual components of variance were estimated at three herd production levels by restricted maximum likelihood for all lactation milk and fat yields and natural logarithm of yields. Data consisted of 121,136 mature equivalent, 2x, 305 day first and later lactation yields for 91,206 artificially sired Holstein cows calving between 1979 and 1984 throughout the United States. A total of 485 of 526 sires represented had first crop daughters in the data. Three production levels were defined by mean mature equivalent milk yield of all cows freshening in the same herd-year. The univariate model of analysis included fixed herd-year-season and sire genetic group and random sire nested within group, cow nested within sire, and residual effects;The analyses of untransformed records resulted in components of variance that in general increased as the level of production increased. For both milk and fat yield, genetic variance increased at the greatest relative rate, resulting in the largest estimates of heritability at the high level of production. Correlations of sire solutions across production levels were close to expected values, indicating the absence of genotype environment interaction. Variance components remained heterogeneous after log transformation of yields. Estimates of residual components on the log scale decreased as production level increased. Estimates of heritability were not changed by log transformation of yields;After variance component estimation, cows and sires were evaluated for milk yield using three mixed models. In two models, variances estimated at the medium production level were used for all records and the analysis used either untransformed or log transformed yields. In the third model, untransformed yields were used and heterogeneous variances at the three production levels were considered. Rank correlations of sire and cow evaluations from the three models were close to unity. Ranks of top sires were similar, but differences in ranks of top cows were large across the three models. A model accounting for heterogeneous variances at several production levels is feasible if variance estimates are available. If heterogeneity of variances are ignored, untransformed yields should be used instead of log transformed yields.

Genetic and phenotypic parameters of immune response traits were investigated for Holstein bulls. Aspects of general immune response were evaluated in 60 post-pubertal bulls. Assessment of neutrophil function was emphasized and was based on laboratory measures of migration, phagocytosis, oxidative metabolism, and cytotoxicity. Lymphocyte blastogenesis due to mitogens and leukograms were included in the battery of laboratory assays. Data were collected from bulls before, during, and after glucocorticoid-induced immunosuppression in a biological model that mimicked periparturient immunosuppression. Derivative-free maximum likelihood was used to estimate genetic and phenotypic (co)variances for immune response traits. Traits were defined as immune function measured by a specific laboratory assay on several days within a particular time period. Single- and multiple-trait animal models were used in the data analyses. Prior to immunosuppression, heritabilities for 14 immune response traits ranged from .27 to .56. Heritabilities in weeks 2 and 3 tended to be lower than week 1, although heritabilities for spontaneous lymphocyte blastogenesis, neutrophil iodination, directed migration, and cytotoxicity assays varied little across weeks. Genetic and phenotypic correlations between traits described by data from the same assay across different weeks generally ranged from .30 to .75 and .25 to .60, respectively. Genetic correlations among measures of neutrophil oxidative metabolism and between phagocytic capacity and neutrophil cytotoxicity were high and positive. Immune responses during stressed and non-stressed periods can be generally characterized as separate but overlapping traits. Estimated parameters for immune response could potentially be used for construction of selection indices for greater disease resistance.

The importance of effects of cytoplasmic inheritance on milk production traits of dairy cattle was examined. Three approaches were taken;Effects of cows' maternal lineages on production were estimated by using animal models. Maternal lineages were established on the basis of cows' earliest recorded female ancestors. Data were 6054 records from 2264 cows from North Carolina and Iowa research herds. First parity records from North Carolina, all records from North Carolina, and all records pooled from Iowa and North Carolina were analyzed by separate procedures. Both yield and milk composition traits were studied. Significant associations with maternal lineages were detected for milk fat percentage and milk energy concentration. Variance components for maternal lineages were also estimated. Maternal lineages accounted for 2.9% of phenotypic variance in fat percentage found in the pooled records. Otherwise, 1% or less of the variance in any trait was associated with maternal lineages;The sequences of the displacement-loop and ribosomal RNA genes of mitochondrial DNA were determined for cows from North Carolina and Iowa herds. Effects of polymorphism in these regions of DNA on production traits were estimated by using animal models that included regression coefficients for sites of polymorphism. Significant associations between phenotype and mitochondrial DNA polymorphism were detected at several sites for most traits. Without exception, when a significant effect existed, the wild-type sequence was favorable to the mutant (less common) type;Simulation was used to determine impacts of ignoring cytoplasmic effects on estimation of variance components, accuracy of genetic evaluations, genetic response, and selection of bull dams. Three levels of maternal lineage variance were considered: 2.5, 5, and 10% of total variance. Failure to account for cytoplasmic effects caused reduced selection accuracy and genetic response. Sizes of progeny test programs can be reduced without sacrificing response if cytoplasmic effects are correctly considered. Impacts increase linearly as size of cytoplasmic effects increase. Including maternal lineage effects in a genetic evaluation model when true effects are zero causes reduced accuracy and genetic response. No practical differences were observed whether maternal lineage effects were considered fixed versus random.

Two BLUP models were used to evaluate young Holstein bulls for production with and without adjusting records for days open. Model I included the mean, HYS, groups, sires of herdmates (fixed) and young bulls within groups (random). In model II, the same effects were used considering all bulls and sires random with adding the relationship among bulls. Data were 24,997 progenies of 484 young bulls and 119,013 herdmates progenies of 291 sires. The maximum differences among adjusted and unadjusted young bulls' predictors were 674 pounds of milk and 21 pounds of fat, model I, and 622 pounds of milk and 19 pounds of fat, model II. The rank correlations among all bulls' adjusted and unadjusted predictors were ≥0.98. However, the rank correlations for the best 5% young bulls were 0.84 for milk and 0.92 for fat, model I, and 0.75 for milk and 0.82 for fat, model II. For the poorest 5% young bulls, the rank correlations were 0.76 for milk and 0.91 for fat, model I, and 0.82 for milk and 0.91 for fat, model II;Third BLUP model was used to evaluate sires and cows for production using multiple lactation data with and without adjusting records for present days open, previous days open, and previous days dry. This model included the mean, HYS, groups, sires within groups, and cows nested within sires. The relationship among sires was used. Data were 315,502 cows with 678,502 lactations, daughters of 522 sires. The maximum differences among adjusted and unadjusted predictors were 507 pounds of milk and 16 pounds of fat for sires, and 2485 pounds of milk and 91 pounds of fat for dams. The rank correlations among adjusted and unadjusted predictors were ≥ 0.97 for sires and dams. But, the rank correlations for the best 5% of sires were 0.77 for milk and 0.91 for fat; they were 0.94 for milk and 0.95 for fat, for the poorest 5% of sires. Rank correlations were 0.7 for milk and 0.59 for fat of the top 20 dams and 0.85 for milk and 0.72 for fat of the bottom 20 dams;Adjusting pedigree information for past reproductive performance improved the regression coefficients for sires and maternal grandsires in predicting young bulls' proofs. However, the regression coefficients for dams were very small (0.02 to 0.03) with or without adjustment.

Paper 1 outlines a generalization to Hill's equations for predicting response to selection. Equations are developed that account for multiple stage selection in either or both sexes and the flow of genes for animals selected at later stages. The asymptotic response to a single cycle of selection is shown to agree with classical selection theory. The equations applied to a dairy progeny testing scheme representative of an artificial insemination organization in the USA. The predicted asymptotic rates to a single cycle of selection were overestimated by 6% and the cumulative response to continuous selection over 20 years was overestimated by 8% when single stage male selection model was compared to two stage selection model;A linear programming model that accounts for the economic consequences of response to selection to the producer enterprise over a given planning horizon is described in Paper 2. A procedure is given in detail for defining upper lower bound constraints on variables that are correlated in the linear programming model. The optimal response to selection per year for the production traits was closest to their maximums achievable from a gene-flow model. Of all the non-production traits, days open had the greatest proportion of its maximum achievable from a gene-flow model. The linear programming model was used to compute relative economic weights (REV). The REVs for milk, fat, and protein production were considerably larger than the REVs for the non-production traits for all planning horizons. Somatic cell score had the largest REVs of the non-production traits in all planning horizons;In the third paper multiple-trait REML was used to estimate the heritabilities and the genetic and phenotypic correlations for 48- and 72-mo herd life from sire models incorporating sire relationships. Two traits were defined for 48- and 72-mo herd life, true herd life (THL) and functional herd life (FHL), which were adjusted for milk production prior to culling. The genetic correlations were used to compute weights for indirect prediction of true and functional herd-life PTA from linear-type traits PTA. (Abstract shortened by UMI.)