Changes in genetic trends in US dairy cattle since the implementation of genomic selection.

Genomic selection increases accuracy and decreases generation interval, accelerating genetic changes in populations. Assumptions of genetic improvement must be addressed to quantify the magnitude and direction of change. Genetic trends of US dairy cattle breeds were examined to determine the genetic gain since the implementation of genomic evaluations in 2009. Inbreeding levels and generation intervals were also investigated. Breeds included Ayrshire, Brown Swiss, Guernsey, Holstein (HO), and Jersey (JE), which were characterized by the evaluation breed the animal received. Mean genomic predicted breeding values (PBV¯) were analyzed per year to calculate genetic trends for bulls and cows. The data set contained 154,008 bulls and 33,022,242 cows born since 1975. Breakpoints were estimated using linear regression, and nonlinear regression was used to fit the piecewise model for the small sample number in some years. Generation intervals and inbreeding levels were also investigated since 1975. Milk, fat, and protein yields, somatic cell score, productive life, daughter pregnancy rate, and livability PBV¯ were documented. In 2017, 100% of bulls in this data set were genotyped. The percentage of genotyped cows has increased 23 percentage points since 2010. Overall, production traits have increased steadily over time, as expected. The HO and JE breeds have benefited most from genomics, with up to 192% increase in genetic gain since 2009. Due to the low number of observations, trends for Ayrshire, Brown Swiss, and Guernsey are difficult to infer from. Trends in fertility are most substantial; particularly, most breeds are trending downwards and daughter pregnancy rate for JE has been decreasing steadily since 1975 for bulls and cows. Levels of genomic inbreeding are increasing in HO bulls and cows. In 2017, genomic inbreeding levels were 12.7% for bulls and 7.9% for cows. A suggestion to control this is to include the genomic inbreeding coefficient with a negative weight to the selection index of bulls with high future genomic inbreeding levels. For sires of bulls, the current generation intervals are 2.2 yr in HO, 3.2 in JE, 4.4 in Brown Swiss, 5.1 in Ayrshire, and 4.3 in Guernsey. The number of colored breed bulls in the United States is currently at an extremely low level, and this number will only increase with a market incentive or additional breed association involvement. Increased education and extension could be beneficial to increase knowledge about inbreeding levels, use of genomics and genetic improvement, and genetic diversity in the genomic selection era.

Genetic effects of heat stress on milk fatty acids in Brazilian Holstein cattle.

The present study aimed to estimate covariance components of milk fatty acids (FA) and to compare the genomic estimated breeding values under general and heat-stress effects. Data consisted of 38,762 test-day records from 6,344 Holstein cows obtained from May 2012 through January 2018 on 4 dairy herds from Brazil. Single-trait repeatability test-day models with random regressions as a function of temperature-humidity index values were used for genetic analyses. The models included contemporary groups, parity order (1-6), and days in milk classes as fixed effects, and general and thermotolerance additive genetic and permanent environmental as random effects. Notably, differences in heritability estimates between environments (general and heat stress) increased (0.03 to 0.06) for unsaturated FA traits, such as unsaturated, monounsaturated, and polyunsaturated, at higher heat-stress levels. In contrast, heritability estimated between environments for saturated FA traits, including saturated FA, palmitic acid (C16:0), and stearic acid (C18:0) did not observe significant differences between environments. In addition, our study revealed negative genetic correlations between general and heat-stress additive genetic effects (antagonistic effect) for the saturated FA, C16:0, C18:0, and C18:1, which ranged from -0.007 to -0.32. Spearman's ranking correlation between genomic estimated breeding values ranged from -0.27 to 0.99. Results indicated a moderate to strong interaction of genotype by the environment for most FA traits comparing a heat-stress environment with thermoneutral conditions. Our findings point out novel opportunities to explore the use of FA milk profile and heat-stress models.

Genomic predictions for crossbred dairy cattle.

Genomic evaluations are useful for crossbred as well as purebred populations when selection is applied to commercial herds. Dairy farmers had already spent more than $1 million to genotype over 32,000 crossbred animals before US genomic evaluations became available for those animals. Thus, new tools were needed to provide accurate genomic predictions for crossbreds. Genotypes for crossbreds are imputed more accurately when the imputation reference population includes purebreds. Therefore, genotypes of 6,296 crossbred animals were imputed from lower-density chips by including either 3,119 ancestors or 834,367 genotyped animals in the reference population. Crossbreds in the imputation study included 733 Jersey × Holstein F1 animals, 55 Brown Swiss × Holstein F1 animals, 2,300 Holstein backcrosses, 2,026 Jersey backcrosses, 27 Brown Swiss backcrosses, and 502 other crossbreds of various breed combinations. Another 653 animals appeared to be purebreds that owners had miscoded as a different breed. Genomic breed composition was estimated from 60,671 markers using the known breed identities for purebred, progeny-tested Holstein, Jersey, Brown Swiss, Ayrshire, and Guernsey bulls as the 5 traits (breed fractions) to be predicted. Estimates of breed composition were adjusted so that no percentages were negative or exceeded 100%, and breed percentages summed to 100%. Another adjustment set percentages above 93.5% equal to 100%, and the resulting value was termed breed base representation (BBR). Larger percentages of missing alleles were imputed by using a crossbred reference population rather than only the closest purebred reference population. Crossbred predictions were averages of genomic predictions computed using marker effects for each pure breed, which were weighted by the animal's BBR. Marker and polygenic effects were estimated separately for each breed on the all-breed scale instead of within-breed scales. For crossbreds, genomic predictions weighted by BBR were more accurate than the average of parents' breeding values and slightly more accurate than predictions using only the predominant breed. For purebreds, single-trait predictions using only within-breed data were as accurate as multi-trait predictions with allele effects in different breeds treated as correlated effects. Crossbred genomic predicted transmitting abilities were implemented by the Council on Dairy Cattle Breeding in April 2019 and will aid producers in managing their breeding programs and selecting replacement heifers.

Genome-wide association study for milk production traits in a Brazilian Holstein population.

Advances in the molecular area of selection have expanded knowledge of the genetic architecture of complex traits through genome-wide association studies (GWAS). Several GWAS have been performed so far, but confirming these results is not always possible due to several factors, including environmental conditions. Thus, our objective was to identify genomic regions associated with traditional milk production traits, including milk yield, somatic cell score, fat, protein and lactose percentages, and fatty acid composition in a Holstein cattle population producing under tropical conditions. For this, 75,228 phenotypic records from 5,981 cows and genotypic data of 56,256 SNP from 1,067 cows were used in a weighted single-step GWAS. A total of 46 windows of 10 SNP explaining more than 1% of the genetic variance across 10 Bos taurus autosomes (BTA) harbored well-known and novel genes. The MGST1 (BTA5), ABCG2 (BTA6), DGAT1 (BTA14), and PAEP (BTA11) genes were confirmed within some of the regions identified in our study. Potential novel genes involved in tissue damage and repair of the mammary gland (COL18A1), immune response (LTTC19), glucose homeostasis (SLC37A1), synthesis of unsaturated fatty acids (LTBP1), and sugar transport (SLC37A1 and MFSD4A) were found for milk yield, somatic cell score, fat percentage, and fatty acid composition. Our findings may assist genomic selection by using these regions to design a customized SNP array to improve milk production traits on farms with similar environmental conditions.

Pedigree verification and parentage assignment using genomic information in the Mexican Holstein population.

Genealogical information is an essential tool for carrying out any genetic improvement program. The objective of this study was to determine the accuracy of pedigree information in the Mexican registered Holstein population using genomic data available in Mexico and for the US Holstein population. The study included 7,508 animals (158 sires and 7,350 cows) that were born from 2002 through 2014, registered with Holstein de México, and genotyped with single nucleotide polymorphism arrays of different densities. Parentage could not be validated for 17% of sires of cows and 12% of sires of bulls. Most (79%) of the dams of cows and the dams of bulls had no genotype available and could not be validated. A parentage test was possible for only 6,104 sires of cows, 139 sires of bulls, 1,519 dams of cows, and 33 dams of bulls. Of the animals with a parentage test, parent assignment was confirmed for 89% of sires of cows, 92% of dams of cows, 95% of sires of bulls, and 97% of dams of bulls. Parent discovery was possible for some animals without confirmed parents: 17% for sires of cows, 2.5% for dams of cows, 43% for sires of bulls, and 0% for dams of bulls. Of the 7,795 progeny tests, 777 had parent conflicts, which is an error rate of 9.97% for parental recording in the population, a rate that is similar to those recently reported for other populations. True parents for some progeny conflicts (15%) were discovered for the Mexican population, and the remaining parents were assigned as unknown. Expected effects of misidentification on rate of genetic gain could be decreased by half if genealogical errors were decreased to 5%. This study indicates that genotyping and genealogy recovery may help in increasing rates of genetic improvement in the Mexican registered Holstein population.

Determination of quantitative trait nucleotides by concordance analysis between quantitative trait loci and marker genotypes of US Holsteins.

Experimental designs that exploit family information can provide substantial predictive power in quantitative trait nucleotide discovery projects. Concordance between quantitative trait locus genotype as determined by the a posteriori granddaughter design and marker genotype was determined for 30 trait-by-chromosomal segment effects segregating in the US Holstein population with probabilities of <10-20 to accept the null hypotheses of no segregating gene affecting the trait within the chromosomal segment. Genotypes for 83 grandsires and 17,217 sons were determined by either complete sequence or imputation for 3,148,506 polymorphisms across the entire genome; 471 Holstein bulls had a complete genome sequence, including 64 of the grandsires. Complete concordance was obtained only for stature on chromosome 14 and daughter pregnancy rate on chromosome 18. For each quantitative trait locus, effects of the 30 polymorphisms with highest concordance scores for the analyzed trait were computed by stepwise regression for predicted transmitting abilities of 26,750 bulls with progeny test and imputed genotypes. Effects for stature on chromosome 11, daughter pregnancy rate on chromosome 18, and protein percentage on chromosome 20 met 3 criteria: complete or almost complete concordance, nominal significance of the polymorphism effect after correction for all other polymorphisms, and marker coefficient of determination >40% of total multiple-regression coefficient of determination for the 30 polymorphisms with highest concordance. An intronic variant marker on chromosome 5 at 93,945,738 bp explained 7% of variance for fat percentage and 74% of total multiple-marker regression variance but was concordant for only 24 of 30 families. The missense polymorphism Phe279Tyr in GHR at 31,909,478 bp on chromosome 20 was confirmed as the causative mutation for fat and protein concentration. For effect on fat percentage on chromosome 14, 12 additional missense polymorphisms were found that had almost complete concordance with the suggested causative polymorphism (missense mutation Ala232Glu in DGAT1). The only polymorphism found likely to improve predictive power for genomic evaluation of dairy cattle was on chromosome 15; that polymorphism had a frequency of 0.45 for the allele with economically positive effects on all production traits.

The genetic and biological basis of feed efficiency in mid-lactation Holstein dairy cows.

The objective of this study was to identify genomic regions and candidate genes associated with feed efficiency in lactating Holstein cows. In total, 4,916 cows with actual or imputed genotypes for 60,671 single nucleotide polymorphisms having individual feed intake, milk yield, milk composition, and body weight records were used in this study. Cows were from research herds located in the United States, Canada, the Netherlands, and the United Kingdom. Feed efficiency, defined as residual feed intake (RFI), was calculated within location as the residual of the regression of dry matter intake (DMI) on milk energy (MilkE), metabolic body weight (MBW), change in body weight, and systematic effects. For RFI, DMI, MilkE, and MBW, bivariate analyses were performed considering each trait as a separate trait within parity group to estimate variance components and genetic correlations between them. Animal relationships were established using a genomic relationship matrix. Genome-wide association studies were performed separately by parity group for RFI, DMI, MilkE, and MBW using the Bayes B method with a prior assumption that 1% of single nucleotide polymorphisms have a nonzero effect. One-megabase windows with greatest percentage of the total genetic variation explained by the markers (TGVM) were identified, and adjacent windows with large proportion of the TGVM were combined and reanalyzed. Heritability estimates for RFI were 0.14 (±0.03; ±SE) in primiparous cows and 0.13 (±0.03) in multiparous cows. Genetic correlations between primiparous and multiparous cows were 0.76 for RFI, 0.78 for DMI, 0.92 for MBW, and 0.61 for MilkE. No single 1-Mb window explained a significant proportion of the TGVM for RFI; however, after combining windows, significance was met on Bos taurus autosome 27 in primiparous cows, and nearly reached on Bos taurus autosome 4 in multiparous cows. Among other genes, these regions contain ß-3 adrenergic receptor and the physiological candidate gene, leptin, respectively. Between the 2 parity groups, 3 of the 10 windows with the largest effects on DMI neighbored windows affecting RFI, but were not in the top 10 regions for MilkE or MBW. This result suggests a genetic basis for feed intake that is unrelated to energy consumption required for milk production or expected maintenance as determined by MBW. In conclusion, feed efficiency measured as RFI is a polygenic trait exhibiting a dynamic genetic basis and genetic variation distinct from that underlying expected maintenance requirements and milk energy output.

Cow genotyping strategies for genomic selection in a small dairy cattle population.

This study compares how different cow genotyping strategies increase the accuracy of genomic estimated breeding values (EBV) in dairy cattle breeds with low numbers. In these breeds, few sires have progeny records, and genotyping cows can improve the accuracy of genomic EBV. The Guernsey breed is a small dairy cattle breed with approximately 14,000 recorded individuals worldwide. Predictions of phenotypes of milk yield, fat yield, protein yield, and calving interval were made for Guernsey cows from England and Guernsey Island using genomic EBV, with training sets including 197 de-regressed proofs of genotyped bulls, with cows selected from among 1,440 genotyped cows using different genotyping strategies. Accuracies of predictions were tested using 10-fold cross-validation among the cows. Genomic EBV were predicted using 4 different methods: (1) pedigree BLUP, (2) genomic BLUP using only bulls, (3) univariate genomic BLUP using bulls and cows, and (4) bivariate genomic BLUP. Genotyping cows with phenotypes and using their data for the prediction of single nucleotide polymorphism effects increased the correlation between genomic EBV and phenotypes compared with using only bulls by 0.163±0.022 for milk yield, 0.111±0.021 for fat yield, and 0.113±0.018 for protein yield; a decrease of 0.014±0.010 for calving interval from a low base was the only exception. Genetic correlation between phenotypes from bulls and cows were approximately 0.6 for all yield traits and significantly different from 1. Only a very small change occurred in correlation between genomic EBV and phenotypes when using the bivariate model. It was always better to genotype all the cows, but when only half of the cows were genotyped, a divergent selection strategy was better compared with the random or directional selection approach. Divergent selection of 30% of the cows remained superior for the yield traits in 8 of 10 folds.

Genomic evaluation, breed identification, and population structure of Guernsey cattle in North America, Great Britain, and the Isle of Guernsey.

As of December 2015, 2,376 Guernsey bulls and cows had genotypes from collaboration between the United States, Canada, the United Kingdom, and the Isle of Guernsey. Of those, 439 bulls and 504 cows had traditional US evaluations, which provided sufficient data to justify investigation of the possible benefits of genomic evaluation for the Guernsey breed. Evaluation accuracy was assessed using a traditional 4-yr cutoff study. Twenty-two traits were analyzed (5 yield traits, 3 functional traits, and 14 conformation traits). Mean reliability gain over that for parent average was 16.8 percentage points across traits, which compares with 8.2, 18.5, 20.0, and 32.6 percentage points reported for Ayrshires, Brown Swiss, Jerseys, and Holsteins, respectively. Highest Guernsey reliability gains were for rump width (44.5 percentage points) and dairy form (40.5 percentage points); lowest gains were for teat length (1.9 percentage points) and rear legs (side view) (2.3 percentage points). Slight reliability losses (1.5 to 4.5 percentage points) were found for udder cleft, final score, and udder depth as well as a larger loss (13.6 percentage points) for fore udder attachment. Twenty-one single nucleotide polymorphisms were identified for Guernsey breed determination and can be used in routine genotype quality control to confirm breed and identify crossbreds. No haplotypes that affect fertility were identified from the current data set. Principal component analysis showed some divergence of US and Isle of Guernsey subpopulations. However, the overlap of US, Canadian, UK, and Isle of Guernsey subpopulations indicated the presence of gene flow, and the similarities in the subpopulations supports a common genomic evaluation system across the regions.

Increasing the number of single nucleotide polymorphisms used in genomic evaluation of dairy cattle.

GeneSeek (Neogen Corp., Lexington, KY) designed a new version of the GeneSeek Genomic Profiler HD BeadChip for Dairy Cattle, which originally had >77,000 single nucleotide polymorphisms (SNP). A set of >140,000 SNP was selected that included all SNP on the existing GeneSeek chip, all SNP used in US national genomic evaluations, SNP that were possible functional mutations, and other informative SNP. Because SNP with a lower minor allele frequency might track causative variants better, 30,000 more SNP were selected from the Illumina BovineHD Genotyping BeadChip (Illumina Inc., San Diego, CA) by choosing SNP to maximize differences in minor allele frequency between a SNP being considered for the new chip and the 2 SNP that flanked it. Single-gene tests were included if their location was known and bioinformatics indicated relevance for dairy cattle. To determine which SNP from the new chip should be included in genomic evaluations, genotypes available from chips already in use were used to impute and evaluate the SNP set. Effects for 134,511 usable SNP were estimated for all breed-trait combinations; SNP with the largest absolute values for effects were selected (5,000 for Holsteins, 1,000 for Jerseys, and 500 each for Brown Swiss and Ayrshires for each trait). To increase overlap with the 60,671 SNP currently used for genomic evaluation, 12,094 more SNP with the largest effects were added. After removing SNP with many parent-progeny conflicts, 84,937 SNP remained. Three cutoff studies were conducted with 3 SNP sets to determine reliability gain over that for parent average when evaluations based on August 2011 data were used to predict December 2014 performance. Across all traits, mean Holstein reliability gains were 32.5, 33.4, and 32.0 percentage points for 60,671, 84,937, and 134,511 SNP, respectively. After genotypes from the new chip became available, the proposed set was reduced from 84,937 to 77,321 SNP to remove SNP that were not included during manufacture, reduce computing time, and improve imputation performance. The set of 77,321 SNP was evaluated using August 2011 data to predict April 2015 performance. Reliability gain over 60,671 SNP was 1.4 percentage points across traits for Holsteins. Improvement over 84,937 SNP was partially the result of 4mo of additional data and genotypes from the new chip. Revision of the SNP set used for genomic evaluation is expected to be an ongoing process to increase evaluation accuracy.

Genetic parameters for milk fatty acids, milk yield and quality traits of a Holstein cattle population reared under tropical conditions.

Information about genetic parameters is essential for selection decisions and genetic evaluation. These estimates are population specific; however, there are few studies with dairy cattle populations reared under tropical and sub-tropical conditions. Thus, the aim was to obtain estimates of heritability and genetic correlations for milk yield and quality traits using pedigree and genomic information from a Holstein population maintained in a tropical environment. Phenotypic records (n = 36 457) of 4203 cows as well as the genotypes for 57 368 single nucleotide polymorphisms from 755 of these cows were used. Covariance components were estimated using the restricted maximum likelihood method under a mixed animal model, considering a pedigree-based relationship matrix or a combined pedigree-genomic matrix. High heritabilities (around 0.30) were estimated for lactose and protein content in milk whereas moderate values (between 0.19 and 0.26) were obtained for percentages of fat, saturated fatty acids and palmitic acid in milk. Genetic correlations ranging from -0.38 to -0.13 were determined between milk yield and composition traits. The smaller estimates compared to other similar studies can be due to poor environmental conditions, which may reduce genetic variability. These results highlight the importance in using genetic parameters estimated in the population under evaluation for selection decisions.

Using genomics to enhance selection of novel traits in North American dairy cattle.

The objectives of this paper were to briefly review progress in the genetic evaluation of novel traits in Canada and the United States, assess methods to predict selection accuracy based on cow reference populations, and illustrate how the use of indicator traits could increase genomic selection accuracy. Traits reviewed are grouped into the following categories: udder health, hoof health, other health traits, feed efficiency and methane emissions, and other novel traits. The status of activities expected to lead to national genetic evaluations is indicated for each group of traits. For traits that are more difficult to measure or expensive to collect, such as individual feed intake or immune response, the development of a cow reference population is the most effective approach. Several deterministic methods can be used to predict the reliability of genomic evaluations based on cow reference population size, trait heritability, and other population parameters. To provide an empirical validation of those methods, predicted accuracies were compared with observed accuracies for several cow reference populations and traits. Reference populations of 2,000 to 20,000 cows were created through random sampling of genotyped Holstein cows in Canada and the United States. The effects of single nucleotide polymorphisms (SNP) were estimated from those cow records, after excluding the dams of validation bulls. Bulls that were first progeny tested in 2013 and 2014 were then used to carry out a validation and estimate the observed accuracy of genomic selection based on those SNP effects. Over the various cow population sizes and traits considered in the study, even the best prediction methods were found, on average, to either under-evaluate observed accuracy by 0.20 or over-evaluate it by 0.22, depending on the approach used to estimate the number of independently segregating chromosome segments. In some instances, differences between observed and predicted accuracies were as large as 0.47. Indicator traits can be very useful for the selection of novel traits. To illustrate this, protein yield, body weight, and mid-infrared data were used as indicator traits for feed efficiency. Using those traits in conjunction with 5,000 cow records for dry matter intake increased the reliability of genomic predictions for young animals from 0.20 to 0.50.

Short communication: Improving accuracy of Jersey genomic evaluations in the United States and Denmark by sharing reference population bulls.

The effect on prediction accuracy for Jersey genomic evaluations of Danish and US bulls from using a larger reference population was assessed. Each country contributed genotypes from 1,157 Jersey bulls to the reference population of the other. Data were separated into reference (US only, Danish only, and combined US-Danish) and validation (US only and Danish only) populations. Depending on trait (milk, fat, and protein yields and component percentages; productive life; somatic cell score; daughter pregnancy rate; 14 conformation traits; and net merit), the US reference population included 2,720 to 4,772 bulls and cows with traditional evaluations as of August 2009; the Danish reference population included 635 to 996 bulls. The US validation population included 442 to 712 bulls that gained a traditional evaluation between August 2009 and December 2013; the Danish validation population included 105 to 196 bulls with multitrait across-country evaluations on the US scale by December 2013. Genomic predicted transmitting abilities (GPTA) were calculated on the US scale using a selection index that combined direct genomic predictions with either traditional predicted transmitting ability for the reference population or traditional parent averages (PA) for the validation population and a traditional evaluation based only on genotyped animals. Reliability for GPTA was estimated from the reference population and August 2009 traditional PA and PA reliability. For prediction of December 2013 deregressed daughter deviations on the US scale, mean August 2009 GPTA reliability for Danish validation bulls was 0.10 higher when based on the combined US-Danish reference population than when the reference population included only Danish bulls; for US validation bulls, mean reliability increased by 0.02 when Danish bulls were added to the US reference population. Exchanging genotype data to increase the size of the reference population is an efficient approach to increasing the accuracy of genomic prediction when the reference population is small.

Effect of reference population size and available ancestor genotypes on imputation of Mexican Holstein genotypes.

The effects of reference population size and the availability of information from genotyped ancestors on the accuracy of imputation of single nucleotide polymorphisms (SNP) were investigated for Mexican Holstein cattle. Three scenarios for reference population size were examined: (1) a local population of 2,011 genotyped Mexican Holsteins, (2) animals in scenario 1 plus 866 Holsteins in the US genotype database (GDB) with genotyped Mexican daughters, and (3) animals in scenario 1 and all US GDB Holsteins (338,073). Genotypes from 4 chip densities (2 low density, 1 mid density, and 1 high density) were imputed using findhap (version 3) to the 45,195 markers on the mid-density chip. Imputation success was determined by comparing the numbers of SNP with 1 or 2 alleles missing and the numbers of differently predicted SNP (conflicts) among the 3 scenarios. Imputation accuracy improved as chip density and numbers of genotyped ancestors increased, and the percentage of SNP with 1 missing allele was greater than that for 2 missing alleles for all scenarios. The largest numbers of conflicts were found between scenarios 1 and 3. The inclusion of information from direct ancestors (dam or sire) with US GDB genotypes in the imputation of Mexican Holstein genotypes increased imputation accuracy by 1 percentage point for low-density genotypes and by 0.5 percentage points for high-density genotypes, which was about half the gain found with information from all US GDB Holsteins. A larger reference population and the availability of genotyped ancestors improved imputation; animals with genotyped parents in a large reference population had higher imputation accuracy than those with no or few genotyped relatives in a small reference population. For small local populations, including genotypes from other related populations can aid in improving imputation accuracy.

Short communication: Analysis of genomic predictor population for Holstein dairy cattle in the United States--Effects of sex and age.

Increased computing time for the ever-growing predictor population and linkage decay between the ancestral population and current animals have become concerns for genomic evaluation systems. The effects on reliability of US genomic evaluations from including cows and bulls in the Holstein predictor population and also from excluding older bulls from the predictor population were examined. Holstein data collected for December 2013 US genomic evaluations were used in cutoff studies to determine reliability gains, regression coefficients, and bias for 5 yield, 3 fitness, 2 fertility, and 18 conformation traits. Three predictor populations were examined based on animal sex: 30,852 cows with traditional evaluations as of August 2012, 21,883 bulls with traditional evaluations as of August 2012, and a combined group of all bulls and cows. Three subsets of the bull predictor population were examined to determine effect of age: bulls born before 1996 excluded (25% of bulls excluded), bulls born before 2001 excluded (50%), and bulls born before 2005 excluded (75%). The validation set for all predictor populations was either bulls or cows first receiving a traditional evaluation between August 2012 and December 2013. Across all traits, the addition of cows to the bull predictor population increased reliability gains by 0.4 percentage points for validation bulls and 4.4 points for validation cows. Across all traits, excluding bulls born before 1996 from the bull-only predictor population decreased gains in genomic reliability by 1.8 percentage points. For 19 of 28 traits, excluding bulls born before 2005 from the predictor population resulted in lower bias in genomic evaluations of validation bulls. Although the contribution of cows and older bulls to improved accuracy of US genomic evaluations is small, a plateau of achievable gain has not yet been reached.

Technical note: Rapid calculation of genomic evaluations for new animals.

A method was developed to calculate preliminary genomic evaluations daily or weekly before the release of official monthly evaluations by processing only newly genotyped animals using estimates of single nucleotide polymorphism effects from the previous official evaluation. To minimize computing time, reliabilities and genomic inbreeding are not calculated, and fixed weights are used to combine genomic and traditional information. Correlations of preliminary and September official monthly evaluations for animals with genotypes that became usable after the extraction of genotypes for August 2014 evaluations were >0.99 for most Holstein traits. Correlations were lower for breeds with smaller population size. Earlier access to genomic evaluations benefits producers by enabling earlier culling decisions and genotyping laboratories by making workloads more uniform across the month.

Genomic evaluation, breed identification, and discovery of a haplotype affecting fertility for Ayrshire dairy cattle.

Genomic evaluations of dairy cattle in the United States have been available for Brown Swiss, Holsteins, and Jerseys since 2009. As of January 2013, 1,023 Ayrshires had genotypes in the North American database. Evaluation accuracy was assessed using genomic evaluations based on 646 bulls with 2008 traditional evaluations to predict daughter performance of up to 180 bulls in 2012. Mean gain in reliability over parent average for all traits was 8.2 percentage points. The highest gains were for protein yield (16.9 percentage points), milk yield (16.6 percentage points), and stature (16.2 percentage points). Twelve single nucleotide polymorphisms were useful for Ayrshire breed determination. Fewer breed-determining SNP were available for Ayrshires than for Holsteins, Jerseys, and Brown Swiss because of the similarity of Ayrshires and Holsteins. A haplotype that affects fertility was identified on chromosome 17 and traces back in the genotyped population to the bull Selwood Betty's Commander (born in 1953). The haplotype carrier frequency for genotyped Ayrshires was 26.1%. Sire conception rate was decreased by 4.3 ± 2.5 percentage points for carriers of the haplotype as determined by 618 matings of carrier sire by carrier maternal grandsire. Genomic evaluations for Ayrshires were officially implemented in the United States in April 2013.

Application of the a posteriori granddaughter design to the Holstein genome.

An a posteriori granddaughter design was applied to estimate quantitative trait loci genotypes of sires with many sons in the US Holstein population. The results of this analysis can be used to determine concordance between specific polymorphisms and segregating quantitative trait loci. Determination of the actual polymorphisms responsible for observed genetic variation should increase the accuracy of genomic evaluations and rates of genetic gain. A total of 52 grandsire families, each with ⩾100 genotyped sons with genetic evaluations based on progeny tests, were analyzed for 33 traits (milk, fat and protein yields; fat and protein percentages; somatic cell score (SCS); productive life; daughter pregnancy rate; heifer and cow conception rates; service-sire and daughter calving ease; service-sire and daughter stillbirth rates; 18 conformation traits; and net merit). Of 617 haplotype segments spanning the entire bovine genome and each including ~5×106 bp, 5 cM and 50 genes, 608 autosomal segments were analyzed. A total of 19 335 unique haplotypes were found among the 52 grandsires. There were a total of 133 chromosomal segment-by-trait combinations, for which the nominal probability of significance for the haplotype effect was <10-8, which corresponds to genome-wide significance of <10-4. The number of chromosomal regions that met this criterion by trait ranged from one for rear legs (rear view) to seven for net merit. For each of the putative quantitative trait loci, at least one grandsire family had a within-family contrast with a t-value of >3. Confidence intervals (CIs) were estimated by the nonparametric bootstrap for the largest effect for each of nine traits. The bootstrap distribution generated by 100 samples was bimodal only for net merit, which had the widest 90% CI (eight haplotype segments). This may be due to the fact that net merit is a composite trait. For all other chromosomes, the CI spanned less than a third of the chromosome. The narrowest CI (a single haplotype segment) was found for SCS. It is likely that analysis by more advanced methods could further reduce CIs at least by half. These results can be used as a first step to determine the actual polymorphisms responsible for observed quantitative variation in dairy cattle.