Discovering ancestors and connecting relatives in large genomic databases.

Genomic evaluation has improved both plant and animal breeding by allowing more accurate estimation of an individual's genetic potential. Because often only a small proportion of the population to be evaluated has been genotyped, genomic estimations rely heavily on complete pedigree information. Confirmation, discovery, and correction of parentage and connected relatives allow the creation of more complete pedigrees, which in turn increase the number of usable phenotypic records and prediction accuracy. Previous methods accounted for parent-progeny conflicts using SNP. More recently haplotype methods allowed discovery of distant relationships such as maternal grandsire (MGS) and maternal great-grandsire (MGGS) with improved accuracy. However, discovered MGS and MGGS often were not used, because no dam information was available to link them to the calf. An automated procedure to discover and fill missing maternal identification information was developed, allowing discovered MGS and MGGS to be used in imputation as well as in calculating breeding values for animals in the US dairy cattle database. An MGS was discovered for 295,136 animals with unknown dam, and the MGGS was discovered for 153,909 of these animals. A virtual maternal identification was added for animals with missing information. The effect of pedigree completion on progeny inbreeding, breeding values, and reliabilities was examined. Mean inbreeding of animals with missing maternal pedigree information was 6.69% before and 6.87% after pedigree assignment; expected future inbreeding was 7.24% before and 7.20% after assignment. Reliabilities for traditional breeding values increased from 26.6 to 32.6% for milk yield, 25.9 to 32.0% for fat yield, and 26.9 to 32.9% for protein yield; genomic reliabilities also increased slightly from 76.2 to 77.1% for milk, 76.0 to 76.9% for fat, and 76.3 to 77.3% for protein. The procedure developed for pedigree completion is a useful tool for improving accuracy of national and international evaluations and aiding producers in making better mating decisions.

Confirmation and discovery of maternal grandsires and great-grandsires in dairy cattle.

Selection, mating, and improvement of dairy animals have required accurate pedigrees. Genomic tools allow paternal ancestors to be easily confirmed or discovered because most sires are genotyped for many markers, but maternal ancestors are more difficult to discover because most female ancestors are not genotyped. Three methods to discover maternal grandsires (MGS) were developed and compared. Conflicts were counted one single nucleotide polymorphism (SNP) at a time between genotypes of the animal and potential MGS (duo method) or also using the sire's genotype (trio method). Alternatively, haplotypes of a potential MGS were matched to the animal's maternal haplotype, obtained by using linkage across loci (HAP method). The duo and trio methods can be performed as soon as a genotype is received because no imputation is required. The HAP method improved accuracy because genotypes with 2,683 (3 K) SNP were imputed to the 45,187 (50K) SNP used for genomic evaluation. The HAP method was tested using modified pedigrees with 5% of true MGS replaced by a random genotyped bull from the same birth year and 5% of MGS set to missing for 4,134 Holsteins, 552 Jerseys, and 142 Brown Swiss that had confirmed, genotyped sires. Those same animals were used to test the duo and trio methods, except that some animals had multiple genotypes and imputed dams were excluded. Accuracy measured how often the correct MGS was selected from among 12,152 genotyped Holstein, 2,265 Jersey, and 1,605 Brown Swiss potential MGS. Accuracies were 61, 60, and 65%, respectively, with the duo method; 95, 91, and 94% with the trio method; and 97, 95, and 97% with the HAP method. Accuracy of the duo method was poor (only 52% for animals genotyped with 3 K and 65% with 50K) because additional information from the paternal genotype is not used. Accuracy of the trio method was 97% with 50K but only 78% with 3K because the missing SNP were not imputed. Accuracy of the HAP method was 94% with 3 K genotypes, 98% with 50K, and 92% with nongenotyped, imputed dams. When the HAP method was extended to great-grandsires, the accuracy of maternal great-grandsire discovery was 92% for 652 Holsteins, 95% for 33 Jerseys, and 85% for 20 Brown Swiss. Accuracy was even higher using simulated genotypes. Because most dairy bulls over several generations have been genotyped, percentages of haplotypes shared with candidate males can accurately confirm, correct, or discover the sires, MGS, and even more distant ancestors of most animals.

Selection and management of DNA markers for use in genomic evaluation.

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 of > or = 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.