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The HH1 haplotype on chromosome 5 is associated with a reduced conception rate and a deficit of homozygotes at the population level in Holstein cattle. The source HH1 haplotype was traced to the bull Pawnee Farm Arlinda Chief (Chief), who was born in 1962 and has sired more than 16,000 daughters. We identified a nonsense mutation in APAF1 (apoptotic protease activating factor 1;APAF1 p.Q579X) within HH1 using whole-genome resequencing of Chief and 3 of his sons. This mutation is predicted to truncate 670 AA (53.7%) of the encoded APAF1 protein that contains a WD40 domain critical to protein-protein interactions. Initial screening revealed no homozygous individuals for the mutation in 758 animals previously genotyped, whereas all 497 HH1 carriers possessed 1 copy of the mutant allele. Subsequent commercial genotyping of 246,773 Holsteins revealed 5,299 APAF1 heterozygotes and zero homozygotes for the mutation. The causative role of this mutation is also supported by functional data in mice that have demonstrated Apaf1 to be an essential molecule in the cytochrome-c-mediated apoptotic cascade and directly implicated in developmental and neurodegenerative disorders. In addition, most Apaf1 homozygous knockouts die by day 16.5 of development. We thus propose that the APAF1 p.Q579X nonsense mutation is the functional equivalent of the Apaf1 knockout. This mutation has caused an estimated 525,000 spontaneous abortions worldwide over the past 35 years, accounting for approximately $420 million in losses. With the mutation identified, selection against the deleterious allele in breeding schemes has aided in eliminating this defect from the population, reducing carrier frequency from 8% in past decades to 2% in 2015.

The GeneSeek Genomic Profiler (GGP) BeadChip (GeneSeek, Lincoln, NE), which became available commercially in February 2012, is based on the Illumina BovineLD Genotyping BeadChip (Illumina Inc., San Diego, CA), with 1,745 additional single nucleotide polymorphisms (SNP) for genomic evaluation and SNP for proprietary single-gene tests. The BovineLD chip with 6,909 SNP, which replaced the Illumina GoldenGate Bovine3K Genotyping BeadChip, has been available since October 2011. The GGP's additional SNP for genomic evaluation were selected to improve imputation by filling SNP gaps on chromosomes and including more Bovine3K SNP than were on the BovineLD chip and to impute microsatellite alleles to facilitate parentage validation. The SNP for single-gene tests were included to minimize the number of separate tests required for those genes, particularly for bulls. The September 2012 US national genomic evaluation included genotypes from BovineLD and GGP chips for 82,510 animals. For those data, BovineLD and GGP performance was similar. The call rate for SNP on these chips that were used in genomic evaluation was 99.6%. The 9 Y-chromosome SNP in common on the BovineLD and GGP chips were highly effective in sex validation (call rate of 99% for males and 0.01% for females). For both chips, the rate of parent–progeny conflicts on a SNP basis (≤0.004%) was similar to that for SNP on the Illumina BovineSNP50 Genotyping BeadChip. Imputation accuracy for 45,187 BovineSNP50 SNP averaged 99.4% for Holsteins. Imputation accuracy was slightly higher for the GGP chip compared with the BovineLD chip because of its additional SNP. Reliability for genomic evaluations using BovineLD and GGP genotypes was 3 percentage points higher than that for Bovine3K 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 (50 K) markers, 1,797 animals with 8,031 (8 K) markers, 20,177 animals with 6,836 (6 K) markers, 52,270 animals with 2,683 (3 K) markers, and 3,229 nongenotyped dams (0 K) 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 8 K 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 50 K, 94.6% from 6 K, 90.5% from 3 K, and 93.5% from 0 K. With FImpute, 99.96% were correct from HD, 99.3% from 50 K, 94.7% from 6 K, 91.1% from 3 K, and 95.1% from 0 K genotypes. Accuracy for the 3 K and 6 K genotypes further improved by approximately 2 percentage points if imputed first to 50 K 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 50 K 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 50 K 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.

To facilitate routine genomic evaluation, a database was constructed to store genotypes for 50,972 single nucleotide polymorphisms (SNP) from the Illumina BovineSNP50 BeadChip (Illumina Inc., San Diego, CA). Multiple samples per animal are allowed. All SNP genotypes for a sample are stored in a single row. An indicator specifies whether the genotype for a sample was selected for use in genomic evaluation. Samples with low call rates or pedigree conflicts are designated as unusable. Among multiple samples that qualify for use in genomic evaluation, the one with the highest call rate is designated as usable. When multiple samples are stored for an animal, a composite is formed during extraction by using SNP genotypes from other samples to replace missing genotypes. To increase the number of SNP available, scanner output for approximately 19,000 samples was reprocessed. Any SNP with a minor allele frequency ofor = 1% for Holsteins, Jerseys, or Brown Swiss was selected, which was the primary reason that the number of SNP used for USDA genomic evaluations increased. Few parent-progeny conflicts (or = 1%) and a high call rate (or = 90%) were additional requirements that eliminated 2,378 SNP. Because monomorphic SNP did not degrade convergence during estimation of SNP effects, a single set of 43,385 SNP was adopted for all breeds. The use of a database for genotypes, detection of conflicts as genotypes are stored, online access for problem resolution, and use of a single set of SNP for genomic evaluations have simplified tracking of genotypes and genomic evaluation as a routine and official process.

Nearly 57,000 single-nucleotide polymorphisms (SNP) genotyped with the Illumina BovineSNP50 BeadChip (Illumina Inc., San Diego, CA) were investigated to determine usefulness of the associated SNP for genomic prediction. Genotypes were obtained for 12,591 bulls and cows, and SNP were selected based on 5,503 bulls with genotypes from a larger set of SNP. The following SNP were deleted: 6,572 that were monomorphic, 3,213 with scoring problems (primarily because of poor definition of clusters and excess number of clusters), and 3,649 with a minor allele frequency of2%. Number of SNP for each minor allele frequency class (or =2%) was fairly uniform (777 to 1,004). For 5 contiguous SNP assigned to chromosome 7, no bulls were heterozygous, which indicated that those SNP are actually on the nonpseudoautosomal portion of the X chromosome. Another 178 SNP that were not assigned to a chromosome but that had many fewer heterozygotes than expected were also assigned to the X chromosome. Existence of Hardy-Weinberg equilibrium was investigated by comparing observed with expected heterozygosity. For 11 SNP, the observed percentage of heterozygous individuals differed from the expected by15%; therefore, those SNP were deleted. For 2,628 SNP, the genotype at another SNP was highly correlated (i.e., genotypes were identical for99.5% of bulls), and those were deleted. After edits, 40,874 SNP remained. A parent-progeny conflict was declared when the genotypes were alternate homozygotes. Mean number of conflicts was 2.3 when pedigree was correct and 2,411 when it was incorrect. The sire was genotyped for93% of animals. Maternal grandsire genotype was similarly checked; however, because alternate homozygotes could be valid, a conflict threshold of 16% was used to indicate a need for further investigation. Genotyping consistency was investigated for 21 bulls genotyped twice with differences primarily from SNP that were not scored in one of the genotypes. Concordance for readable SNP was extremely high (99.96-100%). Thousands of SNP that were polymorphic in Holsteins were monomorphic in Jerseys or Brown Swiss, which indicated that breed-specific SNP sets are required or that all breeds need to be considered in the SNP selection process. Genotypes from the Illumina BovineSNP50 BeadChip are of high accuracy and provide the basis for genomic evaluations in the United States and Canada.

Genetic effects for many dairy traits and for total economic merit are evenly distributed across all chromosomes. A high-density scan using 38,416 single nucleotide polymorphism markers for 5,285 bulls confirmed 2 previously known major genes on Bos taurus autosomes (BTA) 6 and 14 but revealed few other large effects. Markers on BTA18 had the largest effects on calving ease, several conformation traits, longevity, and total merit. Prediction accuracy was highest using a heavy-tailed prior assuming that each marker had an effect on each trait, rather than assuming a normal distribution of effects as in a linear model, or that only some loci have nonzero effects. A prior model combining heavy tails with finite alleles produced results that were intermediate compared with the individual models. Differences between models were small (1 to 2%) for traits with no major genes and larger for heavy tails with traits having known quantitative trait loci (QTL; 6 to 8%). Analysis of bull recessive codes suggested that marker effects from genomic selection may be used to identify regions of chromosomes to search in detail for candidate genes, but individual single nucleotide polymorphisms were not tracking causative mutations with the exception of diacylglycerol O-acyltransferase 1. Additive genetic merits were constructed for each chromosome, and the distribution of BTA14-specific estimated breeding value (EBV) showed that selection primarily for milk yield has not changed the distribution of EBV for fat percentage even in the presence of a known QTL. Such chromosomal EBV also may be useful for identifying complementary mates in breeding programs. The QTL affecting dystocia, conformation, and economic merit on BTA18 appear to be related to calf size or birth weight and may be the result of longer gestation lengths. Results validate quantitative genetic assumptions that most traits are due to the contributions of a large number of genes of small additive effect, rather than support the finite locus model.

Quantitative trait loci affecting economically important traits were studied for eight large US Holstein grandsire families by using the granddaughter design. A total of 155 microsatellite markers located throughout the bovine genome were selected for the scan. The data analyzed include genotypes for 50 markers not previously reported. Results analyses of 105 marker genotypes reported previously were updated. Effects of marker alleles were analyzed for 38 traits including traits for milk production, somatic cell score, productive life, conformation, calving ease, and 16 canonical traits derived from conformation and production traits. Permutation tests were used to calculate empirical traitwise error rates. A traitwise critical value of P = 0.1 was used to determine significance. Ten putative quantitative trait loci associated with seven of the new markers were identified within specific families. One marker on chromosome 14 was associated with differences in fat yield, fat percentage, and a canonical production trait in two families. Markers on chromosomes 18 and 22 were associated with differences in rump angle in the same family. Markers were associated with differences in udder depth and fore udder attachment on chromosomes 16 and 20, respectively. One marker on chromosome 27 was associated with a difference in the dairy capacity composite index, and another marker on chromosome 13 was associated with a difference in a canonical conformation trait. These additional markers complete our genome scan to identify quantitative trait loci affecting economically important traits in a selected commercial Holstein population. The quantitative trait loci identified in this genome scan may be useful for marker-assisted selection to increase the rate of genetic improvement on traits such as disease resistance and conformation traits associated with fitness while accelerating genetic improvement for production.