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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Animal Genomics and Improvement Laboratory » Research » Publications at this Location » Publication #361359

Research Project: Improving Dairy Animals by Increasing Accuracy of Genomic Prediction, Evaluating New Traits, and Redefining Selection Goals

Location: Animal Genomics and Improvement Laboratory

Title: Genomic prediction and marker selection using high-density genotypes from 5 dairy breeds

item Vanraden, Paul
item Null, Daniel
item O'CONNELL, JEFFREY - University Of Maryland School Of Medicine
item Cole, John
item LI, BINGJIE - Oak Ridge Institute For Science And Education (ORISE)

Submitted to: Journal of Dairy Science
Publication Type: Abstract Only
Publication Acceptance Date: 3/10/2019
Publication Date: 6/23/2019
Citation: Van Raden, P.M., Null, D.J., O'Connell, J.R., Cole, J.B., Li, B. 2019. Genomic prediction and marker selection using high-density genotypes from 5 dairy breeds . Journal of Dairy Science. 102(Suppl. 1):400(abstr. 471).

Interpretive Summary:

Technical Abstract: Genotypes for 314,765 Jerseys (JE), 9,077 Ayrshires (AY; including Scandinavian Red), 39,191 Brown Swiss, 4,440 Guernsey, and 351,666 Holsteins (HO) were imputed to high density (HD). The separate HD reference populations included Illumina BovineHD genotypes for 410 JE, 527 AY, 181 BS, 147 GU, and 4,015 HO. The 641,459 variants included the HD SNPs and all 79,276 (80K) genetic markers and QTLs used in routine evaluations. The variants were not pruned for high linkage disequilibrium as in previous HD studies of only HO. Chromosome locations used the ARS-UCD1 map after removing some incorrectly placed regions. Imputation using findhap version 3 with 24 processors took < 2 days for each breed. Before imputation, 90-97% of genotypes in each breed were unknown, and after imputation, 2.1% of JE, 3.6% of AY, 4.7% of BS, 2.8% of GU, and 0.7% of HO alleles remained unknown. Segments in chromosomes 1 and 2 had the most haplotypes in each breed, indicating possible map issues not discovered in earlier tests with fewer SNPs. Prediction and SNP selection results focus only on JE as an example. Allele effects for 26 traits were estimated using phenotypic reference populations that included up to 6,121 JE males and 99,426 JE females. Convergence took 4-8 days using 1 processor per trait and up to 800 iterations. Correlations of HD with 80K genomic predictions for young animals averaged 0.988; yield traits were highest with correlations of about 0.995; cow conception rate and dairy form were lowest at 0.982. Some HD effects were more than twice as large as the largest 80K SNP. On chromosome 11 at 104 Mbase, HD SNPs had the largest effects for fore udder attachment, front teat placement, rump width, and rump angle. For udder cleft and teat length, HD SNPs had higher effects than the highest SNP already in the 80K list. Large new effects were also discovered from HD for daughter pregnancy rate and cow conception rate. Surprisingly for protein, the Beta-Lactoglobulin gene test had smaller effects than three nearby HD SNPs. Previous studies selected and included markers with large effects for HO traits; adding these newly selected HD markers should also improve JE, AY, BS, GU, and crossbred genomic predictions.