B.J. Van Doormaal

Genomic imputation and evaluation using high-density Holstein genotypes

Genomic evaluations for 161,341 Holsteins were computed by using 311,725 of 777,962 markers on the Illumina BovineHD Genotyping BeadChip (HD). Initial edits with 1,741 HD genotypes from 5 breeds revealed that 636,967 markers were usable but that half were redundant. Holstein genotypes were from 1,510 animals with HD markers, 82,358 animals with 45,187 (50K) markers, 1,797 animals with 8,031 (8K) markers, 20,177 animals with 6,836 (6K) markers, 52,270 animals with 2,683 (3K) markers, and 3,229 nongenotyped dams (0K) with >90% of haplotypes imputable because they had 4 or more genotyped progeny. The Holstein HD genotypes were from 1,142 US, Canadian, British, and Italian sires, 196 other sires, 138 cows in a US Department of Agriculture research herd (Beltsville, MD), and 34 other females. Percentages of correctly imputed genotypes were tested by applying the programs findhap and FImpute to a simulated chromosome for an earlier population that had only 1,112 animals with HD genotypes and none with 8K genotypes. For each chip, 1% of the genotypes were missing and 0.02% were incorrect initially. After imputation of missing markers with findhap, percentages of genotypes correct were 99.9% from HD, 99.0% from 50K, 94.6% from 6K, 90.5% from 3K, and 93.5% from 0K. With FImpute, 99.96% were correct from HD, 99.3% from 50K, 94.7% from 6K, 91.1% from 3K, and 95.1% from 0K genotypes. Accuracy for the 3K and 6K genotypes further improved by approximately 2 percentage points if imputed first to 50K and then to HD instead of imputing all genotypes directly to HD. Evaluations were tested by using imputed actual genotypes and August 2008 phenotypes to predict deregressed evaluations of US bulls proven after August 2008. For 28 traits tested, the estimated genomic reliability averaged 61.1% when using 311,725 markers vs. 60.7% when using 45,187 markers vs. 29.6% from the traditional parent average. Squared correlations with future data were slightly greater for 16 traits and slightly less for 12 with HD than with 50K evaluations. The observed 0.4 percentage point average increase in reliability was less favorable than the 0.9 expected from simulation but was similar to actual gains from other HD studies. The largest HD and 50K marker effects were often located at very similar positions. The single-breed evaluation tested here and previous single-breed or multibreed evaluations have not produced large gains. Increasing the number of HD genotypes used for imputation above 1,074 did not improve the reliability of Holstein genomic evaluations.

Relationship Between Reproduction Traits and Functional Longevity in Canadian Dairy Cattle

The aim of this study was to use survival analysis to assess the relationship between reproduction traits and functional longevity of Canadian dairy cattle. Data consisted of 1,702,857; 67,470; and 33,190 Holstein, Ayrshire, and Jersey cows, respectively. Functional longevity was defined as the number of days from first calving to culling, death, or censoring; adjusted for the effect of milk yield. The reproduction traits included calving traits (calving ease, calf size, and calf survival) and female fertility traits (number of services, days from calving to first service, days from first service to conception, and days open). The statistical model was a Weibull proportional hazards model and included the fixed effects of stage of lactation, season of production, the annual change in herd size, and type of milk recording supervision, age at first calving, effects of milk, fat, and protein yields calculated as within herd-year-parity deviations for each reproduction trait. Herd-year-season of calving and sire were included as random effects. Analysis was performed separately for each reproductive trait. Significant associations between reproduction traits and longevity were observed in all breeds. Increased risk of culling was observed for cows that required hard pull, calved small calves, or dead calves. Moreover, cows that require more services per conception, a longer interval between first service to conception, an interval between calving to first service greater than 90 d, and increased days open were at greater risk of being culled.

Genetic analysis of return over feed in Canadian Holsteins.

The objective of this study was to investigate genetic merit of return over feed (ROF), which is a herd profit index defined by CanWest Dairy Herd Improvement as a difference between milk income and feed cost. A multiple-trait (MT) model and random regression model (RRM) were used. The traits analyzed in MT were rearing cost and ROF of the first three lactations. In RRM, a cumulative ROF was fitted as function of age and rearing cost was treated as a correlated trait. Variance components were estimated within a Bayesian framework by Gibbs sampling using a subsample of data. Breeding values were then estimated for 3 041 078 animals using records of 1 951 893 cows. Estimates of heritability for rearing cost from MT and RRM were 0.23 and 0.22, respectively. ROF per lactation and cumulative ROF were negatively correlated with rearing cost. Estimates of heritability of ROF through the first, second and third lactation from MT were 0.27, 0.10 and 0.08, respectively. Estimates of heritability of ROF from RRM increased with age and ranged from 0.08 through 0.31. Estimated breeding values (EBVs) for ROF from MT and RRM were moderately correlated with official EBV for production traits and the Canadian selection index (Lifetime Profit Index). Herd life EBV had -0.07 and 0.19 correlations with EBVs for ROF from MT and RRM, respectively. From both MT and RRM, small favorable correlations were reported between EBVs for ROF and for bone quality and angularity, whereas low unfavorable correlations were reported with EBV for udder depth, front end and chest width. Majority of correlations between EBVs for ROF and for reproduction traits were near 0, with the exception of EBV for gestation length, calf size and calving ease, where small favorable correlations were reported. The ROF is a good indicator of cow profitability despite the fact that it is a simplified profit index that does not account for animal-specific health and reproductive cost. However, because ROF does not account for differences in heritabilities between components of profit, ROF is not recommended to be used for direct selection for profit.