Meteorological data (1993 to 2004) from 2 public weather stations in Phoenix, Arizona, and Athens, Georgia, were analyzed with test day milk yield data from herds near weather stations to identify the most appropriate temperature-humidity index (THI) to measure losses in milk production due to heat stress in the semiarid climate of Arizona and the humid climate of Georgia. Seven THI with different weightings of dry bulb temperature and humidity were compared. Test-day data were analyzed using 2 models to determine threshold of heat stress and rate of decline of milk production associated with a specific THI. Differences in thresholds of heat stress were found among indices and between regions. Indices with higher weights on humidity were best in the humid climate, whereas indices with larger weights on temperature were the best indicators of heat stress in the semiarid climate. Humidity was the limiting factor of heat stress in humid climates, whereas dry bulb temperature was the limiting factor of heat stress in dry climates.

The objective of this research was to estimate heritabilities of milk urea nitrogen (MUN) and lactose in the first 3 parities and their genetic relationships with milk, fat, protein, and SCS in Canadian Holsteins. Data were a random sample of complete herds (60,645 test day records of 5,022 cows from 91 herds) extracted from the edited data set, which included 892,039 test-day records of 144,622 Holstein cows from 4,570 herds. A test-day animal model with multiple-trait random regression and the Gibbs sampling method were used for parameter estimation. Regression curves were modeled using Legendre polynomials of order 4. A total of 6 separate 4-trait analyses, which included MUN, lactose, or both (yield or percentage) with different combinations of production traits (milk, fat and protein yield, fat and protein percentages, and somatic cell score) were performed. Average daily heritabilities were moderately high for MUN (from 0.384 to 0.414), lactose kilograms (from 0.466 to 0.539), and lactose percentage (from 0.478 to 0.508). Lactose yield was highly correlated with milk yield (0.979). Lactose percentage and MUN were not genetically correlated with milk yield. However, lactose percentage was significantly correlated with somatic cell score (-0.202). The MUN was correlated with fat (0.425) and protein percentages (0.20). Genetic correlations among parities were high for MUN, lactose percentage, and yield. Estimated breeding values (EBV) of bulls for MUN were correlated with fat percentage EBV (0.287) and EBV of lactose percentage were correlated with lactation persistency EBV (0.329). Correlations between lactose percentage and MUN with fertility traits were close to zero, thus diminishing the potential of using those traits as possible indicators of fertility.

BackgroundEffectiveness of genomic selection and fine mapping is determined by the level of linkage disequilibrium (LD) across the genome. Knowledge of the range of genome-wide LD, defined as a non-random association of alleles at different loci, can provide an insight into the optimal density and location of single-nucleotide polymorphisms (SNPs) for genome-wide association studies and can be a keystone for interpretation of results from QTL mapping.ResultsLinkage disequilibrium was measured by |D'| and r2 between 38,590 SNPs (spaced across 29 bovine autosomes and the X chromosome) using genotypes of 887 Holstein bulls. The average level of |D'| and r2 for markers 40-60 kb apart was 0.72 and 0.20, respectively in Holstein cattle. However, a high degree of heterogeneity of LD was observed across the genome. The sample size and minor allele frequency had an effect on |D'| estimates, however, r2 was not noticeably affected by these two factors. Syntenic LD was shown to be useful for verifying the physical location of SNPs. No differences in the extent of LD and decline of LD with distance were found between the intragenic and intergenic regions.ConclusionsA minimal sample size of 444 and 55 animals is required for an accurate estimation of LD by |D'| and r2, respectively. The use of only maternally inherited haplotypes is recommended for analyses of LD in populations consisting of large paternal half-sib families. Large heterogeneity in the pattern and the extent of LD in Holstein cattle was observed on both autosomes and the X chromosome. The extent of LD was higher on the X chromosome compared to the autosomes.

A random regression model with both random and fixed regressions fitted by Legendre polynomials of order 4 was compared with 3 alternative models fitting linear splines with 4, 5, or 6 knots. The effects common for all models were a herd-test-date effect, fixed regressions on days in milk (DIM) nested within region-age-season of calving class, and random regressions for additive genetic and permanent environmental effects. Data were test-day milk, fat and protein yields, and SCS recorded from 5 to 365 DIM during the first 3 lactations of Canadian Holstein cows. A random sample of 50 herds consisting of 96,756 test-day records was generated to estimate variance components within a Bayesian framework via Gibbs sampling. Two sets of genetic evaluations were subsequently carried out to investigate performance of the 4 models. Models were compared by graphical inspection of variance functions, goodness of fit, error of prediction of breeding values, and stability of estimated breeding values. Models with splines gave lower estimates of variances at extremes of lactations than the model with Legendre polynomials. Differences among models in goodness of fit measured by percentages of squared bias, correlations between predicted and observed records, and residual variances were small. The deviance information criterion favored the spline model with 6 knots. Smaller error of prediction and higher stability of estimated breeding values were achieved by using spline models with 5 and 6 knots compared with the model with Legendre polynomials. In general, the spline model with 6 knots had the best overall performance based upon the considered model comparison criteria.

Heat stress was evaluated as a factor in differences between regional evaluations for milk yield in the United States. The national data set (NA) consisted of 56 million first-parity, test-day milk yields on 6 million Holsteins. The Northeastern subset (NE) included 12.5 million records on 1.3 million first-calved heifers from 8 states, and the Southeastern subset (SE) included 3.5 million records on 0.4 million heifers from 11 states. Climatic data were available from 202 public weather stations. Each herd was assigned to the nearest weather station. Average daily temperature-humidity index (mean THI) 3 d before test date was used as an indicator of heat stress. Two test-day repeatability models were implemented. Effects included in both models were herd-test date, age at calving class, frequency of milking, days in milk x season class, additive genetic (regular breeding value) and permanent environmental effects. Additionally, the second model included random regressions on degrees of heat stress (t = max[0, mean THI - 72]) for additive genetic (breeding value for heat tolerance) and permanent environmental effects. Both models were fitted with the national and regional data sets. Correlations involved estimated breeding values (EBV) from SE and NE for sires with >or=100 and >or=300 daughters in each region. When heat stress was ignored (first model) the correlations of regular EBV between SE and NE for sires with >or=100 (>or=300) daughters were 0.85 (0.87). When heat stress was considered (second model), the correlation increased by up to 0.01. The correlations of heat stress EBV between NE and SE for sires with >or=100 (>or=300, >or=700) daughters were 0.58 (0.72, 0.81). Evaluations for heat tolerance were similar in cooler and hotter regions for high-reliability sires. Heat stress as modeled explains only a small amount of regional differences, partly because test-day records depict only snapshots of heat stress.