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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 #402358
Research Project: Increasing Accuracy of Genomic Prediction, Developing Algorithms, Selecting Markers, and Evaluating New Traits to Improve Dairy Cattle

Location: Animal Genomics and Improvement Laboratory

Title: Quality and value of imputing gene tests for all animals

Author
item O'CONNELL, JEFFREY - University Of Maryland School Of Medicine
item Vanraden, Paul
item Ogwo, Emmanuella

Submitted to: Journal of Dairy Science
Publication Type: Abstract Only
Publication Acceptance Date: 3/21/2023
Publication Date: 6/25/2023
Citation: O'Connell, J., Van Raden, P.M., Ogwo, E.O. 2023. Quality and value of imputing gene tests for all animals [abstract]. Journal of Dairy Science. 106(Suppl. 1):189(abstr. 2715).

Interpretive Summary:

Technical Abstract: Genomic selection is driven by genotyping arrays designed for uniform coverage of the genome because most quantitative trait loci (QTLs) underlying the heritability of the trait are unknown. Laboratories have improved the arrays since 2014 with custom content by adding selected QTLs discovered from whole-genome sequencing (WGS) and high-effect markers from higher-density arrays. Which years and arrays include QTLs affects the number of animals genotyped and accuracy of imputing QTL for other genotyped animals. Breed differences, missing data rates, and error rates were investigated for 8 QTL gene tests currently imputed for all genotyped animals of 5 breeds plus crossbreds. Gene content for each gene test was predicted for non-genotyped relatives using mixed model methods like those used in single-step genomic evaluations, allowing potential direct selection across all animals. Some QTL have economic merit not yet included in national selection indexes such as 1) polled mutations near 1:2578598 (chr:position on ARS-UCD1 map) that suppress horn growth, improve animal welfare, and reduce farm labor, 2) Beta-casein allele (a2) at 6:84451299 in a milk protein gene that may improve digestibility, and 3) K-casein alleles near 6:84451299 that can increase cheese yield. Other QTLs mainly affect traits already in selection such as 4) DGAT1 QTL at 14:611019 affecting fatty acid metabolism, percentages, and yields of fat and protein, 5) BGHR QTL at 20:31888449 with large effect on protein percentage, and 6) the ABCG2 QTL at 6:36599640 with largest effect for Net Merit in Holsteins, but the favorable allele is now nearly fixed. Many other QTL have recessive lethal effects. For the 8 QTL studied, Mendel error rates were low except for polled in Jerseys and DGAT1 in most breeds. Imputation errors resulted in smaller effects for DGAT1 than the nearby flanking SNPs that are present on most arrays. Because some valuable gene tests are sold by laboratories rather than delivered with array genotypes, freely imputed QTLs could benefit breeders and progress. Decreasing costs of WGS data will increase power of QTL discovery, and more QTL genotypes should increase imputation accuracy, prediction accuracy, and economic gain.