Evaluation of genotyping concordance for commercial bovine SNP arrays using quality-assurance samples.

SNP arrays are widely used in genetic research and agricultural genomics applications, and the quality of SNP genotyping data is of paramount importance. In the present study, SNP genotyping concordance and discordance were evaluated for commercial bovine SNP arrays based on two types of quality assurance (QA) samples provided by Neogen GeneSeek. The genotyping discordance rates (GDRs) between chips were on average between 0.06% and 0.37% based on the QA type I data and between 0.05% and 0.15% based on the QA type II data. The average genotyping error rate (GER) pertaining to single SNP chips, based on the QA type II data, varied between 0.02% and 0.08% per SNP and between 0.01% and 0.06% per sample. These results indicate that genotyping concordance rate was high (i.e. from 99.63% to 99.99%). Nevertheless, mitochondrial and Y chromosome SNPs had considerably elevated GDRs and GERs compared to the SNPs on the 29 autosomes and X chromosome. The majority of genotyping errors resulted from single allotyping errors, which also included the opposite instances for allele 'dropout' (i.e. from AB to AA or BB). Simultaneous allotyping errors on both alleles (e.g. mistaking AA for BB or vice versa) were relatively rare. Finally, a list of SNPs with a GER greater than 1% is provided. Interpretation of association effects of these SNPs, for example in genome-wide association studies, needs to be taken with caution. The genotyping concordance information needs to be considered in the optimal design of future bovine SNP arrays.

GENOMICS SYMPOSIUM: Using genomic approaches to uncover sources of variation in age at puberty and reproductive longevity in sows.

Genetic variants associated with traits such as age at puberty and litter size could provide insight into the underlying genetic sources of variation impacting sow reproductive longevity and productivity. Genomewide characterization and gene expression profiling were used using gilts from the University of Nebraska-Lincoln swine resource population ( = 1,644) to identify genetic variants associated with age at puberty and litter size traits. From all reproductive traits studied, the largest fraction of phenotypic variation explained by the Porcine SNP60 BeadArray was for age at puberty (27.3%). In an evaluation data set, the predictive ability of all SNP from high-ranked 1-Mb windows (1 to 50%), based on genetic variance explained in training, was greater (12.3 to 36.8%) compared with the most informative SNP from these windows (6.5 to 23.7%). In the integrated data set ( = 1,644), the top 1% of the 1-Mb windows explained 6.7% of the genetic variation of age at puberty. One of the high-ranked windows detected (SSC2, 12-12.9 Mb) showed pleiotropic features, affecting both age at puberty and litter size traits. The RNA sequencing of the hypothalami arcuate nucleus uncovered 17 differentially expressed genes (adjusted < 0.05) between gilts that became pubertal early (<155 d of age) and late (>180 d of age). Twelve of the differentially expressed genes are upregulated in the late pubertal gilts. One of these genes is involved in energy homeostasis (), a function in which the arcuate nucleus plays an important contribution, linking nutrition with reproductive development. Energy restriction during the gilt development period delayed age at puberty by 7 d but increased the probability of a sow to produce up to 3 parities ( < 0.05). Identification of pleotropic functional polymorphisms may improve accuracy of genomic prediction while facilitating a reduction in sow replacement rates and addressing welfare concerns.

The impact of training strategies on the accuracy of genomic predictors in United States Red Angus cattle.

Genomic selection (GS) has become an integral part of genetic evaluation methodology and has been applied to all major livestock species, including beef and dairy cattle, pigs, and chickens. Significant contributions in increased accuracy of selection decisions have been clearly illustrated in dairy cattle after practical application of GS. In the majority of U.S. beef cattle breeds, similar efforts have also been made to increase the accuracy of genetic merit estimates through the inclusion of genomic information into routine genetic evaluations using a variety of methods. However, prediction accuracies can vary relative to panel density, the number of folds used for folds cross-validation, and the choice of dependent variables (e.g., EBV, deregressed EBV, adjusted phenotypes). The aim of this study was to evaluate the accuracy of genomic predictors for Red Angus beef cattle with different strategies used in training and evaluation. The reference population consisted of 9,776 Red Angus animals whose genotypes were imputed to 2 medium-density panels consisting of over 50,000 (50K) and approximately 80,000 (80K) SNP. Using the imputed panels, we determined the influence of marker density, exclusion (deregressed EPD adjusting for parental information [DEPD-PA]) or inclusion (deregressed EPD without adjusting for parental information [DEPD]) of parental information in the deregressed EPD used as the dependent variable, and the number of clusters used to partition training animals (3, 5, or 10). A BayesC model with π set to 0.99 was used to predict molecular breeding values (MBV) for 13 traits for which EPD existed. The prediction accuracies were measured as genetic correlations between MBV and weighted deregressed EPD. The average accuracies across all traits were 0.540 and 0.552 when using the 50K and 80K SNP panels, respectively, and 0.538, 0.541, and 0.561 when using 3, 5, and 10 folds, respectively, for cross-validation. Using DEPD-PA as the response variable resulted in higher accuracies of MBV than those obtained by DEPD for growth and carcass traits. When DEPD were used as the response variable, accuracies were greater for threshold traits and those that are sex limited, likely due to the fact that these traits suffer from a lack of information content and excluding animals in training with only parental information substantially decreases the training population size. It is recommended that the contribution of parental average to deregressed EPD should be removed in the construction of genomic prediction equations. The difference in terms of prediction accuracies between the 2 SNP panels or the number of folds compared herein was negligible.

Breed effects and genetic parameter estimates for calving difficulty and birth weight in a multibreed population.

Birth weight (BWT) and calving difficulty (CD) were recorded on 4,579 first-parity females from the Germplasm Evaluation Program at the U.S. Meat Animal Research Center (USMARC). Both traits were analyzed using a bivariate animal model with direct and maternal effects. Calving difficulty was transformed from the USMARC scores to corresponding -scores from the standard normal distribution based on the incidence rate of the USMARC scores. Breed fraction covariates were included to estimate breed differences. Heritability estimates (SE) for BWT direct, CD direct, BWT maternal, and CD maternal were 0.34 (0.10), 0.29 (0.10), 0.15 (0.08), and 0.13 (0.08), respectively. Calving difficulty direct breed effects deviated from Angus ranged from -0.13 to 0.77 and maternal breed effects deviated from Angus ranged from -0.27 to 0.36. Hereford-, Angus-, Gelbvieh-, and Brangus-sired calves would be the least likely to require assistance at birth, whereas Chiangus-, Charolais-, and Limousin-sired calves would be the most likely to require assistance at birth. Maternal breed effects for CD were least for Simmental and Charolais and greatest for Red Angus and Chiangus. Results showed that the diverse biological types of cattle have different effects on both BWT and CD. Furthermore, results provide a mechanism whereby beef cattle producers can compare EBV for CD direct and maternal arising from disjoined and breed-specific genetic evaluations.

Long-term selection for litter size in swine results in shifts in allelic frequency in regions involved in reproductive processes.

High-density genotype data were analyzed in three lines of swine that express substantial variation in sow fertility to uncover regions of the genome potentially influenced during selection for litter size traits. The experimental lines examined include the Nebraska Index Line (NIL), which has been subjected to long-term selection for litter size; a control line derived from the same population that founded NIL; and a commercial Duroc × Hampshire (D × H) population, in which no selection for litter size was practiced. Regions of the genome potentially affected by selection for litter size traits in NIL were determined by multiple lines of evidence, including altered allelic frequency compared to the other lines, loss of heterozygosity and relative extended haplotype homozygosity. Additionally, a genome-wide association study for litter size traits was conducted in a population based on NIL and commercial maternal line genetics. Several genomic regions identified as putative signatures of selection overlapped with QTL for litter size traits. One of these regions, located on SSC2 (13-14 Mb), includes the candidate gene P2X3R, which plays a role in implantation and sustained release of hormones associated with reproductive processes. Sequencing identified synonymous SNPs in P2X3R that are fixed in NIL but polymorphic with nearly equal frequencies in the D × H line, indicating a potential role of P2X3R in sow fertility. These results suggest that data derived from these lines can help to uncover and understand a portion of the genetic variance associated with fertility traits in swine.

Quantitative trait locus mapping and functional genomics of an organophosphate resistance trait in the western corn rootworm, Diabrotica virgifera virgifera.

The western corn rootworm, Diabrotica virgifera virgifera, is an insect pest of corn and population suppression with chemical insecticides is an important management tool. Traits conferring organophosphate insecticide resistance have increased in frequency amongst D. v. virgifera populations, resulting in the reduced efficacy in many corn-growing regions of the USA. We used comparative functional genomic and quantitative trait locus (QTL) mapping approaches to investigate the genetic basis of D. v. virgifera resistance to the organophosphate methyl-parathion. RNA from adult methyl-parathion resistant and susceptible adults was hybridized to 8331 microarray probes. The results predicted that 11 transcripts were significantly up-regulated in resistant phenotypes, with the most significant (fold increases ≥ 2.43) being an α-esterase-like transcript. Differential expression was validated only for the α-esterase (ST020027A20C03), with 11- to 13-fold greater expression in methyl-parathion resistant adults (P < 0.05). Progeny with a segregating methyl-parathion resistance trait were obtained from a reciprocal backcross design. QTL analyses of high-throughput single nucleotide polymorphism genotype data predicted involvement of a single genome interval. These data suggest that a specific carboyxesterase may function in field-evolved corn rootworm resistance to organophosphates, even though direct linkage between the QTL and this locus could not be established.

Evaluation of reduced subsets of single nucleotide polymorphisms for the prediction of age at puberty in sows.

Genomic information could be used efficiently to improve traits that are expensive to measure, sex limited or expressed late in life. This study analyzed the phenotypic variation explained by major SNPs and windows for age at puberty in gilts, an indicator of reproductive longevity. A genome-wide association study using 56, 424 SNPs explained 25.2% of the phenotypic variation in age at puberty in a training set (n = 820). All SNPs from the top 10% of 1-Mb windows explained 33.5% of the phenotypic variance compared to 47.1% explained by the most informative markers (n = 261). In an evaluation population, consisting of subsequent batches (n = 412), the predictive ability of all SNPs from the major 1-Mb windows was higher compared to the variance captured by the most informative SNP from each of these windows. The phenotypic variance explained in the evaluation population varied from 12.3% to 36.8% when all SNPs from major windows were used compared to 6.5-23.7% explained by most informative SNPs. The correlation between phenotype and genomic prediction values based on SNP effects estimated in the training population was marginal compared to their effects retrained in the evaluation population for all (0.46-0.81) or most informative SNPs (0.30-0.65) from major windows. An increase in genetic gain of 20.5% could be obtained if genomic selection included both sexes compared to females alone. The pleiotropic role of major genes such as AVPR1A could be exploited in selection of both age at puberty and reproductive longevity.

Genome-wide analysis of TNF-alpha response in pigs challenged with porcine circovirus 2b.

Tumor necrosis factor alpha (TNF-α) is a pro-inflammatory cytokine with a role in activating adaptive immunity to viral infections. By inhibiting the capacity of plasmacytoid dendritic cells to produce interferon-α and TNF-α, porcine circovirus 2 (PCV2) limits the maturation of myeloid dendritic cells and impairs their ability to recognize viral and bacterial antigens. Previously, we reported QTL for viremia and immune response in PCV2-infected pigs. In this study, we analyzed phenotypic and genetic relationships between TNF-α protein levels, a potential indicator of predisposition to PCV2 co-infection, and PCV2 susceptibility. Following experimental challenge with PCV2b, TNF-α reached the peak at 21 days post-infection (dpi), at which time a difference was observed between pigs that expressed extreme variation in viremia and growth (P < 0.10). A genome-wide association study (n = 297) revealed that genotypes of 56,433 SNPs explained 73.9% of the variation in TNF-α at 21 dpi. Major SNPs were identified on SSC8, SSC10 and SSC14. Haplotypes based on SNPs from a SSC8 (9 Mb) 1-Mb window were associated with variation in TNF-α (P < 0.02), IgG (P = 0.05) and IgM (P < 0.13) levels at 21 dpi. Potential overlap of regulatory mechanisms was supported by the correlations between genomic prediction values of TNF-α and PCV2 antibodies (21 dpi, r > 0.22), viremia (14-21 dpi, P > 0.29) and viral load (r = 0.31, P < 0.0001). Characterization of the QTL regions uncovered genes that could influence variation in TNF-α levels as well as T- and B-cell development, which can affect disease susceptibility.

Estimation of breed-specific heterosis effects for birth, weaning, and yearling weight in cattle.

Heterosis, assumed proportional to expected breed heterozygosity, was calculated for 6834 individuals with birth, weaning and yearling weight records from Cycle VII and advanced generations of the U.S. Meat Animal Research Center (USMARC) Germplasm Evaluation (GPE) project. Breeds represented in these data included: Angus, Hereford, Red Angus, Charolais, Gelbvieh, Simmental, Limousin and Composite MARC III. Heterosis was further estimated by proportions of British × British (B × B), British × Continental (B × C) and Continental × Continental (C × C) crosses and by breed-specific combinations. Model 1 fitted fixed covariates for heterosis within biological types while Model 2 fitted random breed-specific combinations nested within the fixed biological type covariates. Direct heritability estimates (SE) for birth, weaning ,and yearling weight for Model 1 were 0.42 (0.04), 0.22 (0.03), and 0.39 (0.05), respectively. The direct heritability estimates (SE) of birth, weaning, and yearling weight for Model 2 were the same as Model 1, except yearling weight heritability was 0.38 (0.05). The B × B, B × C, and C × C heterosis estimates for birth weight were 0.47 (0.37), 0.75 (0.32), and 0.73 (0.54) kg, respectively. The B × B, B × C, and C × C heterosis estimates for weaning weight were 6.43 (1.80), 8.65 (1.54), and 5.86 (2.57) kg, respectively. Yearling weight estimates for B × B, B × C, and C × C heterosis were 17.59(3.06), 13.88 (2.63), and 9.12 (4.34) kg, respectively. Differences did exist among estimates of breed-specific heterosis for weaning and yearling weight, although the variance component associated with breed-specific heterosis was not significant. These results illustrate that there are differences in breed-specific heterosis and exploiting these differences can lead to varying levels of heterosis among mating plans.

Genomic analysis of the differential response to experimental infection with porcine circovirus 2b.

Porcine circovirus type 2 (PCV2) is the etiological agent of a group of associated diseases (PCVAD) that affect production efficiency and can lead to mortality. Using different crossbred lines of pigs, we analyzed host genetic variation of viral load, immune response and weight change following experimental infection with a PCV2b strain (n = 386). Pigs expressed variation in the magnitude and initiation of viremia and immune response recorded weekly until 28 days post-infection. A higher viral load was correlated with weight gain (r = -0.26, P < 0.0001) and presence of PCV2-specific antibodies (IgM, r = 0.26-0.34, P < 0.0001; IgG, r = 0.17-0.20, P < 0.01). In genome-wide association analyses of the responses at different time points, the proportions of phenotypic variation explained by combined effects of 56 433 SNPs were 34.8-59.4% for viremia, 10.1-59.5% for antibody response and 5.6-14.9% for weight change. Relationships between genomic prediction of overall viral load and weight gain during the first weeks of challenge were negative (-0.21 and -0.24 respectively, P < 0.0001). Individuals that carried more favorable alleles across three SNPs on SSC9 (0.60 Mb) and SSC12 (6.8 and 18.2 Mb) partially explained this relationship, having lower viral load (P < 0.0001); lower viremia at day 14 (P < 0.0001), day 21 (P < 0.01) and day 28 (P < 0.05) and greater overall average daily gain during infection (ADGi ; P < 0.01), ADGi at week 3 (P < 0.001) and week 4 (P < 0.01). These additive genetic relationships could lead to molecular solutions to improve animal health and reduce production costs.

The change in differing leukocyte populations during vaccination to bovine respiratory disease and their correlations with lung scores, health records, and average daily gain.

Bovine respiratory disease (BRD) is the most economically important disease in U.S. feedlots. Infection can result in morbidity, mortality, and reduced average daily gain. Cheap and reliable genetic methods of prediction and protection from BRD would be highly advantageous to the industry. The immune response may correlate with BRD incidence. Cattle (n = 2,182) were vaccinated against common viral and bacterial pathogens of BRD. Two blood samples were collected, one during booster vaccination and one 21d later, enabling 3 phenotypes for each trait [prebooster (pre), postbooster (post), and delta (post minus pre)]. From the blood samples innate and adaptive responses [counts of white blood cells (WBC), neutrophils, lymphocytes, monocytes, eosinophils, and basophils] were measured. In addition, feedlot ADG and binary traits [health records (HR; 0 = healthy, 1 = ill) and lung scores (LS; collected at harvest; 0 = no lesions, 1 = lesions)] were also recorded. Traits ADG, HR, and LS have all been significantly correlated with infection to BRD. In this investigation we aimed to find correlations between the immune response and ADG, HR, and LS to find an easily measurable trait that would be a good predictor of BRD resistance after vaccination. The results showed an average positive delta for the innate immune response (eosinophils, basophils, neutrophils), whereas the adaptive immune response had an average negative delta (lymphocytes). Overall, we discovered that the immune responses had moderately high heritabilities (h(2); lowest: delta monocytes, 0.21 ± 0.05; greatest: pre lymphocytes: 0.5 ± 0.05), with lymphocytes having the greatest h(2) throughout the study (h(2) ≥ 0.41). All genetic correlations were calculated using bivariate REML models. Although LS did not significantly correlate with any of the immune phenotypes, both ADG (post lymphocytes, -0.24 ± 0.12) and HR (pre eosinophils, -0.67 ± 0.29; delta WBC, -0.5 ± 0.24, and delta lymphocytes, -0.67 ± 0.21) did. All the significant genetic correlations with HR were negative; resistance to BRD appears to be a function of greater delta lymphocytes and WBC. The increase in eosinophils may potentially link its role in decreasing lymphocytes. These results may enable producers to predict if revaccination, quarantine, and breeding of animals is required to reduce the incidence of BRD postvaccination. In addition, immunological phenotypes maybe used to aid genomic selection indices to select animals with greater rates of protection after BRD vaccination.

The effect of myostatin genotype on body temperature during extreme temperature events.

Extreme heat and cold events can create deleterious physiological changes in cattle as they attempt to cope. The genetic background of animals can influence their response to these events. The objective of the current study was to determine the impact of myostatin genotype (MG) on body temperature during periods of heat and cold stress. Two groups of crossbred steers and heifers of unknown pedigree and breed fraction with varying percentages of Angus, Simmental, and Piedmontese were placed in a feedlot over 2 summers and 2 winters. Before arrival, animals were genotyped for the Piedmontese-derived myostatin mutation (C313Y) to determine their MG as either homozygous normal (0 copy; n = 84), heterozygous (1 copy; n = 96), or homozygous for inactive myostatin (2 copy; n = 59). Hourly tympanic and vaginal temperature measurements were collected for steers and heifers, respectively, for 5 d during times of anticipated heat and cold stress. Mean (±SD) ambient temperature for summer and winter stress events were 24.4 (±4.64) and -1.80 (±11.71), respectively. A trigonometric function (sine + cosine) with periods of 12 and 24 h was used to describe the diurnal cyclical pattern. Hourly body temperature was analyzed within a season, and fixed effects included MG, group, trigonometric functions nested within group, and interaction of MG with trigonometric functions nested within group; random effects were animal and residual (Model [I]). A combined analysis of season and group was also investigated with the inclusion of season as a main effect and the nesting of effects within both group and season (Model [C]). In both models, the residual was fitted using an autoregressive covariance structure. A 3-way interaction of MG, season, and trigonometric function periodicities of 24 h (P < 0.001) and 12 h (P < 0.02) for Model [C] indicate that a genotype × environment interaction exists for MG. For MG during summer stress events the additive estimate was 0.10°C (P < 0.01) and dominance estimate was -0.12°C (P < 0.001). During winter stress events the additive estimate was 0.10°C (P < 0.001) and dominance estimate was 0.054°C (P > 0.05). The current study illustrated that a genotype × environment interaction exists for MG and 1-copy animals were more robust to environmental extremes in comparison with 0- or 2-copy animals.

Genome-wide prediction of age at puberty and reproductive longevity in sows.

Traditional selection for sow reproductive longevity is ineffective due to low heritability and late expression of the trait. Incorporation of DNA markers into selection programs is potentially a more practical approach for improving sow lifetime productivity. Using a resource population of crossbred gilts, we explored pleiotropic sources of variation that influence age at puberty and reproductive longevity. Of the traits recorded before breeding, only age at puberty significantly affected the probability that females would produce a first parity litter. The genetic variance explained by 1-Mb windows of the sow genome, compared across traits, uncovered regions that influence both age at puberty and lifetime number of parities. Allelic variants of SNPs located on SSC5 (27-28 Mb), SSC8 (36-37 Mb) and SSC12 (1.2-2 Mb) exhibited additive effects and were associated with both early expression of puberty and a greater than average number of lifetime parities. Combined analysis of these SNPs showed that an increase in the number of favorable alleles had positive impact on reproductive longevity, increasing number of parities by up to 1.36. The region located on SSC5 harbors non-synonymous alleles in the arginine vasopressin receptor 1A (AVPR1A) gene, a G-protein-coupled receptor associated with social and reproductive behaviors in voles and humans and a candidate for the observed effects. This region is characterized by high levels of linkage disequilibrium in different lines and could be exploited in marker-assisted selection programs across populations to increase sow reproductive longevity.

Evolution of starvation resistance in Drosophila melanogaster: measurement of direct and correlated responses to artificial selection.

Laboratory selection for resistance to starvation has been conducted under relatively controlled conditions to investigate direct and correlated responses to artificial selection. With regard to starvation resistance, there are three physiological routes by which the trait can evolve: resource accumulation, energy conservation and starvation tolerance. A majority of energetic compounds and macromolecules including triglycerides, trehalose and other sugars, and soluble protein increased in abundance as a result of selection. Movement was additionally investigated with selected males moving less than control males and selected females exhibiting a similar response to selection. Results obtained from this study supported two of the possible evolutionary mechanisms for adaptation to starvation: energy compound storage and conservation. If the response to selection is based on an evolutionarily conserved pattern of genetic correlations (elevated lipid, elevated sugars and reduced movement), then the response to selection is medically relevant and the genetic architecture should be investigated in depth.

Transcriptional profiling of the sperm storage organs of Drosophila melanogaster.

The occurrence of female sperm storage across taxa indicates the importance of this complex and dynamic process. Organs responsible for sperm storage (SSOs) and proteins expressed therein, are important in fundamental aspects of reproduction and could play a major role in evolutionary processes such as post-mating sexual selection. Given the essential role of SSOs, it is surprising that the process of sperm storage is so poorly understood. This study investigated the transcriptome of female Drosophila melanogaster SSOs (seminal receptacle and spermathecae). Spermathecae were enriched for proteases and metabolic enzymes while the seminal receptacle was enriched for genes involved in localization, signaling and ion transport. Differences in functional gene categories indicate that these organs play unique roles in sperm storage.

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

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

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

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

Estimates of genetic parameters for Holstein cows for test-day yield traits with a random regression cubic spline model.

Genetic parameters were estimated with restricted maximum likelihood for individual test-day milk, fat, and protein yields and somatic cell scores with a random regression cubic spline model. Test-day records of Holstein cows that calved from 1994 through early 1999 were obtained from Dairy Records Management Systems in Raleigh, North Carolina, for the analysis. Estimates of heritability for individual test-days and estimates of genetic and phenotypic correlations between test-days were obtained from estimates of variances and covariances from the cubic spline analysis. Estimates were calculated of genetic parameters for the averages of the test days within each of the ten 30-day test intervals. The model included herd test-day, age at first calving, and bovine somatropin treatment as fixed factors. Cubic splines were fitted for the overall lactation curve and for random additive genetic and permanent environmental effects, with five predetermined knots or four intervals between days 0, 50, 135, 220, and 305. Estimates of heritability for lactation one ranged from 0.10 to 0.15, 0.06 to 0.10, 0.09 to 0.15, and 0.02 to 0.06 for test-day one to test-day 10 for milk, fat, and protein yields and somatic cell scores, respectively. Estimates of heritability were greater in lactations two and three. Estimates of heritability increased over the course of the lactation. Estimates of genetic and phenotypic correlations were smaller for test-days further apart.

Technical note: Calculation of standard errors of estimates of genetic parameters with the multiple-trait derivative-free restricted maximal likelihood programs.

The multiple-trait derivative-free REML set of programs was written to handle partially missing data for multiple-trait analyses as well as single-trait models. Standard errors of genetic parameters were reported for univariate models and for multiple-trait analyses only when all traits were measured on animals with records. In addition to estimating (co)variance components for multiple-trait models with partially missing data, this paper shows how the multiple-trait derivative-free REML set of programs can also estimate SE by augmenting the data file when not all animals have all traits measured. Although the standard practice has been to eliminate records with partially missing data, that practice uses only a subset of the available data. In some situations, the elimination of partial records can result in elimination of all the records, such as one trait measured in one environment and a second trait measured in a different environment. An alternative approach requiring minor modifications of the original data and model was developed that provides estimates of the SE using an augmented data set that gives the same residual log likelihood as the original data for multiple-trait analyses when not all traits are measured. Because the same residual vector is used for the original data and the augmented data, the resulting REML estimators along with their sampling properties are identical for the original and augmented data, so that SE for estimates of genetic parameters can be calculated.

Estimates of genetic parameters for Holstein cows for test-day yield traits with a random regression cubic spline model

Genetic parameters were estimated with restricted maximum likelihood for individual test-day milk, fat, and protein yields and somatic cell scores with a random regression cubic spline model. Test-day records of Holstein cows that calved from 1994 through early 1999 were obtained from Dairy Records Management Systems in Raleigh, North Carolina, for the analysis. Estimates of heritability for individual test-days and estimates of genetic and phenotypic correlations between test-days were obtained from estimates of variances and covariances from the cubic spline analysis. Estimates were calculated of genetic parameters for the averages of the test days within each of the ten 30-day test intervals. The model included herd test-day, age at first calving, and bovine somatropin treatment as fixed factors. Cubic splines were fitted for the overall lactation curve and for random additive genetic and permanent environmental effects, with five predetermined knots or four intervals between days 0, 50, 135, 220, and 305. Estimates of heritability for lactation one ranged from 0.10 to 0.15, 0.06 to 0.10, 0.09 to 0.15, and 0.02 to 0.06 for test-day one to test-day 10 for milk, fat, and protein yields and somatic cell scores, respectively. Estimates of heritability were greater in lactations two and three. Estimates of heritability increased over the course of the lactation. Estimates of genetic and phenotypic correlations were smaller for test-days further apart.