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Sun C.,National Association of Animal Breeders | VanRaden P.M.,U.S. Department of Agriculture | O'Connell J.R.,University of Maryland, Baltimore | Weigel K.A.,University of Wisconsin - Madison | Gianola D.,University of Wisconsin - Madison
Journal of Dairy Science | Year: 2013

Computerized mating programs using genomic information are needed by breed associations, artificial-insemination organizations, and on-farm software providers, but such software is already challenged by the size of the relationship matrix. As of October 2012, over 230,000 Holsteins obtained genomic predictions in North America. Efficient methods of storing, computing, and transferring genomic relationships from a central database to customers via a web query were developed for approximately 165,000 genotyped cows and the subset of 1,518 bulls whose semen was available for purchase at that time. This study, utilizing 3 breeds, investigated differences in sire selection, methods of assigning mates, the use of genomic or pedigree relationships, and the effect of including dominance effects in a mating program. For both Jerseys and Holsteins, selection and mating programs were tested using the top 50 marketed bulls for genomic and traditional lifetime net merit as well as 50 randomly selected bulls. The 500 youngest genotyped cows in the largest herd in each breed were assigned mates of the same breed with limits of 10 cows per bull and 1 bull per cow (only 79 cows and 8 bulls for Brown Swiss). A dominance variance of 4.1 and 3.7% was estimated for Holsteins and Jerseys using 45,187 markers and management group deviation for milk yield. Sire selection was identified as the most important component of improving expected progeny value, followed by managing inbreeding and then inclusion of dominance. The respective percentage gains for milk yield in this study were 64, 27, and 9, for Holsteins and 73, 20, and 7 for Jerseys. The linear programming method of assigning a mate outperformed sequential selection by reducing genomic or pedigree inbreeding by 0.86 to 1.06 and 0.93 to 1.41, respectively. Use of genomic over pedigree relationship information provided a larger decrease in expected progeny inbreeding and thus greater expected progeny value. Based on lifetime net merit, the economic value of using genomic relationships was >$3 million per year for Holsteins when applied to all genotyped females, assuming that each will provide 1 replacement. Previous mating programs required transferring only a pedigree file to customers, but better service is possible by incorporating genomic relationships, more precise mate allocation, and dominance effects. Economic benefits will continue to grow as more females are genotyped. © 2013 American Dairy Science Association.


VanRaden P.M.,U.S. Department of Agriculture | Olson K.M.,National Association of Animal Breeders | Wiggans G.R.,U.S. Department of Agriculture | Cole J.B.,U.S. Department of Agriculture | Tooker M.E.,U.S. Department of Agriculture
Journal of Dairy Science | Year: 2011

Genomic measures of relationship and inbreeding within and across breeds were compared with pedigree measures using genotypes for 43,385 loci of 25,219 Holsteins, 3,068 Jerseys, and 872 Brown Swiss. Adjustment factors allow genomic and pedigree relationships to match more closely within breeds and in multibreed populations and were estimated using means and regressions of genomic on pedigree relationships and allele frequencies in base populations. Correlations of genomic relationships with pedigree inbreeding were higher within each breed when an allele frequency of 0.5, rather than base population frequencies, was used, whereas correlations of average genomic relationships with average pedigree relationships and also reliabilities of genomic evaluations were higher using base population frequencies. Allele frequencies differed in the 3 breeds and were correlated by 0.65 to 0.67 when estimated from genotyped animals compared with 0.72 to 0.74 when estimated from breed base populations. The largest difference in allele frequency was between Holstein and the other breeds on chromosome Bos taurus autosome 4 near a gene affecting appearance of white skin patches (vitiligo) in humans. Each animal's breed composition was predicted very accurately with a standard deviation of <3% using regressions on genotypes at all loci or less accurately with a standard deviation of <6% using subsets of loci. Genomic future inbreeding (half an animal's mean genomic relationship to current animals of the same breed) was correlated by 0.75 to 0.94 with expected future inbreeding (half the average pedigree relationship). Correlations of both were slightly higher with parent averages than with genomic evaluations for net merit of young Holstein bulls. Thus, rates of increase in genomic and pedigree inbreeding per generation should be slightly reduced with genomic selection, in agreement with previous simulations. Genomic inbreeding and future inbreeding have been provided with individual genomic predictions since 2008. New methods to adjust pedigree and genomic relationship matrices so that they match may provide an improved basis for multibreed genomic evaluation. Positive definite matrices can be obtained by adjusting pedigree relationships for covariances among base animals within breed, whereas adjusting genomic relationships to match pedigree relationships can introduce negative eigenvalues. Pedigree relationship matrices ignore common ancestry shared by base animals within breed and may not approximate genomic relationships well in multibreed populations. © 2011 American Dairy Science Association.


VanRaden P.M.,U.S. Department of Agriculture | Olson K.M.,National Association of Animal Breeders | Null D.J.,U.S. Department of Agriculture | Hutchison J.L.,U.S. Department of Agriculture
Journal of Dairy Science | Year: 2011

Five new recessive defects were discovered in Holsteins, Jerseys, and Brown Swiss by examining haplotypes that had a high population frequency but were never homozygous. The method required genotypes only from apparently normal individuals and not from affected embryos. Genotypes from the BovineSNP50 BeadChip (Illumina, San Diego, CA) were examined for 58,453 Holsteins, 5,288 Jerseys, and 1,991 Brown Swiss with genotypes in the North American database. Haplotypes with a length of ≤75 markers were obtained. Eleven candidate haplotypes were identified, with the earliest carrier born before 1980; 7 to 90 homozygous haplotypes were expected, but none were observed in the genomic data. Expected numbers were calculated using either the actual mating pattern or assuming random mating. Probability of observing no homozygotes ranged from 0.0002 for 7 to 10 -45 for 90 expected homozygotes. Phenotypic effects were confirmed for 5 of the 11 candidate haplotypes using 14,911,387 Holstein, 830,391 Jersey, and 68,443 Brown Swiss records for conception rate. Estimated effect for interaction of carrier service sire with carrier maternal grandsire ranged from -3.0 to -3.7 percentage points, which was slightly smaller than the -3.9 to -4.6 percentage points expected for lethal recessives but slightly larger than estimated effects for previously known lethal alleles of -2.5 percentage points for brachyspina and -2.9 percentage points for complex vertebral malformation. Conception rate was coded as a success only if the gestation went to term or the cow was confirmed to be pregnant. Estimated effect of carrier interaction for stillbirth rate based on 10,876,597 Holstein and 25,456 Jersey records was small. Thus, lethal effects may include conception, gestation, and stillbirth losses. Carrier frequency has been >20% for many years for the confirmed defect in Jerseys and is currently 16% for the defect in Brown Swiss. The 3 defects discovered in Holsteins have carrier frequencies of 2.7 to 6.4% in the current population. For previously known defects, map locations and lack of homozygotes were consistent with the literature and lethal recessive inheritance, but numbers of expected homozygotes for some were small because of low frequency. Very large genotypic and phenotypic data sets allow efficient detection of smaller and less frequent effects. Haplotype tests can help breeders avoid carrier matings for such defects and reduce future frequencies. © 2011 American Dairy Science Association.


Norman H.D.,U.S. Department of Agriculture | Miller R.H.,U.S. Department of Agriculture | Wright J.R.,U.S. Department of Agriculture | Hutchison J.L.,U.S. Department of Agriculture | And 2 more authors.
Journal of Dairy Science | Year: 2012

Frequency of abortions recorded through Dairy Herd Improvement (DHI) testing was summarized for cows with lactations completed from 2001 through 2009. For 8.5. million DHI lactations of cows that had recorded breeding dates and were >151. d pregnant at lactation termination, the frequency of recorded abortions was 1.31%. Effects of year, herd-year, month, and pregnancy stage at lactation termination; parity; breed; milk yield; herd size; geographic region; and state within region associated with DHI-recorded abortion were examined. Abortions recorded through DHI (minimum gestation of 152. d required) were more frequent during early gestation; least squares means (LSM) were 4.38, 3.27, 1.19, and 0.59% for 152 to 175, 176 to 200, 201 to 225, and 226 to 250. d pregnant, respectively. Frequency of DHI-recorded abortions was 1.40% for parity 1 and 1.01% for parity ≥8. Abortion frequency was highest from May through August (1.42 to 1.53%) and lowest from October through February (1.09 to 1.21%). Frequency of DHI-recorded abortions was higher for Holsteins (1.32%) than for Jerseys (1.10%) and other breeds (1.27%). Little relationship was found between DHI-recorded abortions and herd size. Abortion frequencies for effects should be considered to be underestimated because many abortions, especially those caused by genetic recessives, go undetected. Therefore, various nonreturn rates (NRR; 60, 80, ..., 200. d) were calculated to document pregnancy loss confirmed by the absence of homozygotes in the population. Breeding records for April 2011 US Department of Agriculture sire conception rate evaluations were analyzed with the model used for official evaluations with the addition of an interaction between carrier status of the service sire (embryo's sire) and cow sire (embryo's maternal grandsire). Over 13. million matings were examined using various NRR for Holstein lethal recessive traits (brachyspina and complex vertebral malformation) and undesirable recessive haplotypes (HH1, HH2, and HH3) as well as >61,000 matings for a Brown Swiss haplotype (BH1), and 670,000 matings for a Jersey haplotype (JH1). Over 80% of fertility loss occurred by 60. d after breeding for BH1, HH3, and JH1, by 80. d for HH2, by 100. d for BY, and by 180. d for HH1. For complex vertebral malformation, fertility loss increased from 40 to 74% across gestation. Association of undesirable recessives with DHI-recorded abortions ranged from 0.0% for Jerseys to 2.4% for Holsteins. © 2012 American Dairy Science Association.


Connor E.E.,U.S. Department of Agriculture | Hutchison J.L.,U.S. Department of Agriculture | Olson K.M.,National Association of Animal Breeders | Norman H.D.,U.S. Department of Agriculture
Journal of Animal Science | Year: 2012

Increasing feed costs and the desire to improve environmental stewardship have stimulated renewed interest in improving feed efficiency of livestock, including that of US dairy herds. For instance, USDA cost projections for corn and soybean meal suggest a 20% increase over 2010 pricing for a 16% protein mixed dairy cow ration in 2011, which may lead to a reduction in cow numbers to maintain profitability of dairy production. Furthermore, an October 2010 study by The Innovation Center for US Dairy to assess the carbon footprint of fluid milk found that the efficiency of feed conversion is the single greatest factor contributing to variation in the carbon footprint because of its effects on methane release during enteric fermentation and from manure. Thus, we are conducting research in contemporary US Holsteins to identify cows most efficient at converting feed to milk in temperate climates using residual feed intake (RFI), a measure used successfully to identify the beef cattle most efficient at converting feed to gain. Residual feed intake is calculated as the difference between predicted and actual feed intake to support maintenance and production (e.g., growth in beef cattle, or milk in dairy cattle). Heritability estimates for RFI in dairy cattle reported in the literature range from 0.01 to 0.38. Selection for a decreased RFI phenotype can reduce feed intake, methane production, nutrient losses in manure, and visceral organ weights substantially in beef cattle. We have estimated RFI during early lactation (i.e., to 90 d in milk) in the Beltsville Agricultural Research Center Holstein herd and observed a mean difference of 3.7 kg/d (P < 0.0001) in actual DMI between the efficient and inefficient groups (±0.5 SD from the mean RFI of 0), with no evidence of differences (P > 0.20) in mean BW, ADG, or energy-corrected milk exhibited between the 2 groups. These results indicate promise for using RFI in dairy cattle to improve feed conversion to milk. Previous and current research on the use of RFI in lactating dairy cattle are discussed, as well as opportunities to improve production efficiency of dairy cattle using RFI for milk production. © American Society of Animal Science.


Olson K.M.,National Association of Animal Breeders | VanRaden P.M.,U.S. Department of Agriculture | Tooker M.E.,U.S. Department of Agriculture | Cooper T.A.,U.S. Department of Agriculture
Journal of Dairy Science | Year: 2011

Two methods of testing predictions from genomic evaluations were investigated. Data used were from the August 2006 and April 2010 official USDA genetic evaluations of dairy cattle. The training data set consisted of both cows and bulls that were proven (had own or daughter information) as of August 2006 and included 8,022, 1,959, and 1,056 Holsteins, Jerseys, and Brown Swiss, respectively. The validation data set consisted of bulls that were unproven as of August 2006 and were proven by April 2010 with 2,653, 411, and 132 Holsteins, Jerseys, and Brown Swiss for the production traits. Method 1 used the training animal's predicted transmitting ability (PTA) from August of 2006. Method 2 used the training animal's April 2010 PTA to estimate single nucleotide polymorphism effects. Both methods were tested using several regressions with the same validation animals. In both cases, the validation animals were tested using the deregressed April 2010 PTA. All traits that had genomic evaluations from the official USDA April 2010 genetic evaluations were tested. Results included bias, differences from expected regressions (calculated using selection intensities), and the coefficients of determination. The genomic information increased the predictive ability for most of the traits in all of the breeds. The 2 methods of testing resulted in some differences that would affect interpretation of results. The coefficient of determination was higher for all traits using method 2. This was the expected result as the data were not independent because evaluations of the validation bulls contributed to their sires' evaluations. The regression coefficients from method 2 were often higher than the regression coefficients from method 1. Many traits had regression coefficients that were higher than 2 standard deviations from the expected regressions when using method 2. This was partially due to the lack of independence of the training and validation data sets. Most traits did have some level of bias in the prediction equations, regardless of breed. The use of method 1 made it possible to evaluate the increased accuracy in proven first-crop bull evaluations by using genomic information. Proven first-crop bulls had an increase in accuracy from the addition of genomic information. It is advised to use method 1 for validation of genomic evaluations. © 2011 American Dairy Science Association.


Olson K.M.,National Association of Animal Breeders | VanRaden P.M.,U.S. Department of Agriculture | Tooker M.E.,U.S. Department of Agriculture
Journal of Dairy Science | Year: 2012

Multibreed models are currently used in traditional US Department of Agriculture (USDA) dairy cattle genetic evaluations of yield and health traits, but within-breed models are used in genomic evaluations. Multibreed genomic models were developed and tested using the 19,686 genotyped bulls and cows included in the official August 2009 USDA genomic evaluation. The data were divided into training and validation sets. The training data set comprised bulls that were daughter proven and cows that had records as of November 2004, totaling 5,331Holstein, 1,361 Jersey, and 506 Brown Swiss. The validation data set had 2,508Holstein, 413 Jersey, and 185 Brown Swiss bulls that were unproven (no daughter information) in November 2004 and proven by August 2009. A common set of 43,385 single nucleotide polymorphisms (SNP) was used for all breeds. Three methods of multibreed evaluation were investigated. Method 1 estimated SNP effects separately within breed and then applied those breed-specific SNP estimates to the other breeds. Method 2 estimated a common set of SNP effects from combined genotypes and phenotypes of all breeds. Method 3 solved for correlated SNP effects within each breed estimated jointly using a multitrait model where breeds were treated as different traits. Across-breed genomic predicted transmitting ability (GPTA) and within-breed GPTA were compared using regressions to predict the deregressed validation data. Method 1 worked poorly, and coefficients of determination (R2) were much lower using training data from a different breed to estimate SNP effects. Correlations between direct genomic values computed using training data from different breeds were less than 30% and sometimes negative. Across-breed GPTA from method 2had higher R2 values than parent average alone but typically produced lower R2 values than the within-breed GPTA. The across-breed R2 exceeded the within-breed R2 for a few traits in the Brown Swiss breed, probably because information from the other breeds compensated for the small numbers of Brown Swiss training animals. Correlations between within-breed GPTA and across-breed GPTA ranged from 0.91 to 0.93. The multibreed GPTA from method 3 were significantly better than the current within-breed GPTA, and adjusted R2 for protein yield (the only trait tested for method 3) were highest of all methods for all breeds. However, method 3 increased the adjusted R2 by only 0.01 for Holsteins, ≤0.01 for Jerseys, and 0.01 for Brown Swiss compared with within-breed predictions. © 2012 American Dairy Science Association.


Wiggans G.R.,U.S. Department of Agriculture | Cooper T.A.,U.S. Department of Agriculture | VanRaden P.M.,U.S. Department of Agriculture | Olson K.M.,National Association of Animal Breeders | Tooker M.E.,U.S. Department of Agriculture
Journal of Dairy Science | Year: 2012

Genomic evaluations using genotypes from the Illumina Bovine3K BeadChip (3K) became available in September 2010 and were made official in December 2010. The majority of 3K-genotyped animals have been Holstein females. Approximately 5% of male 3K genotypes and between 3.7 and 13.9%, depending on registry status, of female genotypes had sire conflicts. The chemistry used for the 3K is different from that of the Illumina BovineSNP50 BeadChip (50K) and causes greater variability in the accuracy of the genotypes. Approximately 2% of genotypes were rejected due to this inaccuracy. A single nucleotide polymorphism (SNP) was determined to be not usable for genomic evaluation based on percentage missing, percentage of parent-progeny conflicts, and Hardy-Weinberg equilibrium discrepancies. Those edits left 2,683 of the 2,900 3K SNP for use in genomic evaluations. The mean minor allele frequencies (MAF) for Holstein, Jersey, and Brown Swiss were 0.32, 0.28, and 0.29, respectively. Eighty-one SNP had both a large number of missing genotypes and a large number of parent-progeny conflicts, suggesting a correlation between call rate and accuracy. To calculate a genomic predicted transmitting ability (GPTA) the genotype of an animal tested on a 3K is imputed to the 45,187 SNP included in the current genomic evaluation based on the 50K. The accuracy of imputation increases as the number of genotyped parents increases from none to 1 to both. The average percentage of imputed genotypes that matched the corresponding actual 50K genotypes was 96.3%. The correlation of a GPTA calculated from a 3K genotype that had been imputed to 50K and GPTA from its actual 50K genotype averaged 0.959 across traits for Holsteins and was slightly higher for Jerseys at 0.963. The average difference in GPTA from the 50K- and 3K-based genotypes across trait was close to 0. The evaluation system has been modified to accommodate the characteristics of the 3K. The low cost of the 3K has greatly increased genotyping of females. Prior to the availability of the 3K (August 2010), female genotyping accounted for 38.7% of the genotyped animals. In the past year, the portion of total genotypes from females across all chip types rose to 59.0%. © 2012 American Dairy Science Association.


Sun C.,National Association of Animal Breeders | VanRaden P.M.,U.S. Department of Agriculture | Cole J.B.,U.S. Department of Agriculture | O'Connell J.R.,University of Maryland Baltimore County
PLoS ONE | Year: 2014

Dominance may be an important source of non-additive genetic variance for many traits of dairy cattle. However, nearly all prediction models for dairy cattle have included only additive effects because of the limited number of cows with both genotypes and phenotypes. The role of dominance in the Holstein and Jersey breeds was investigated for eight traits: milk, fat, and protein yields; productive life; daughter pregnancy rate; somatic cell score; fat percent and protein percent. Additive and dominance variance components were estimated and then used to estimate additive and dominance effects of single nucleotide polymorphisms (SNPs). The predictive abilities of three models with both additive and dominance effects and a model with additive effects only were assessed using ten-fold cross-validation. One procedure estimated dominance values, and another estimated dominance deviations; calculation of the dominance relationship matrix was different for the two methods. The third approach enlarged the dataset by including cows with genotype probabilities derived using genotyped ancestors. For yield traits, dominance variance accounted for 5 and 7% of total variance for Holsteins and Jerseys, respectively; using dominance deviations resulted in smaller dominance and larger additive variance estimates. For nonyield traits, dominance variances were very small for both breeds. For yield traits, including additive and dominance effects fit the data better than including only additive effects; average correlations between estimated genetic effects and phenotypes showed that prediction accuracy increased when both effects rather than just additive effects were included. No corresponding gains in prediction ability were found for non-yield traits. Including cows with derived genotype probabilities from genotyped ancestors did not improve prediction accuracy. The largest additive effects were located on chromosome 14 near DGAT1 for yield traits for both breeds; those SNPs also showed the largest dominance effects for fat yield (both breeds) as well as for Holstein milk yield.


Sun C.,National Association of Animal Breeders | VanRaden P.M.,U.S. Department of Agriculture
PLoS ONE | Year: 2014

Long-term response of genomic selection can be improved by considering allele frequencies of selected markers or quantitative trait loci (QTLs). A previous formula to weight allele frequency of favorable minor alleles was tested, and 2 new formulas were developed. The previous formula used nonlinear weights based on square root of frequency of the favorable allele. The new formulas included a parameter δ to balance long- and short-term progress; one used square root and the other used simple linear weights. The formulas were tested by simulation of 20 generations (population size of 3,000 for each generation) with direct selection on 3,000 QTLs (100 per chromosome). A QTL distribution with normally distributed allele effects and a heavy-tailed distribution were tested. Optimum δ from simulation was applied to data from Holstein, Jersey and Brown Swiss dairy cattle to compare differences of adjusted and official genomic evaluations. From simulation, optimum δ was 0.4 for the heavy-tailed QTL distribution but only 0.1 or 0.2 for a normal distribution. The previous formula had slower response than unweighted selection in early generations and did not recover by generation 20. Long-term response was slightly greater with the new formulas than with unweighted selection; the linear formula may be best for routine use because of more progress in early generations compared to nonlinear formula. Official and adjusted U.S. evaluations based on actual genotypes and estimated marker effects were correlated by 0.994 for Holsteins and Jerseys and 0.989 for Brown Swiss using linear weighting of allele frequency, which was higher than nonlinear weighting. The difference between adjusted and official evaluations was highly correlated negatively with an animal's average genomic relationship to the population. Thus, strategies to reduce genomic inbreeding may achieve almost as much long-term progress as selection of favorable minor alleles.

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