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Distribution and location of genetic effects for dairy traits

J. B. Cole^*,1, P. M. VanRaden^*, J. R. O’Connell, C. P. Van Tassell^*,, T. S. Sonstegard, R. D. Schnabel, J. F. Taylor and G. R. Wiggans^*

^* Animal Improvement Programs Laboratory, ARS, USDA, Beltsville, MD 20705-2350
University of Maryland School of Medicine, Baltimore 21201
Bovine Functional Genomics Laboratory, ARS, USDA, Beltsville, MD 20705-2350
Division of Animal Sciences, University of Missouri, Columbia 65201

¹ Corresponding author: john.cole{at}ars.usda.gov

Genetic effects for many dairy traits and for total economic merit are evenly distributed across all chromosomes. A high-density scan using 38,416 single nucleotide polymorphism markers for 5,285 bulls confirmed 2 previously known major genes on Bos taurus autosomes (BTA) 6 and 14 but revealed few other large effects. Markers on BTA18 had the largest effects on calving ease, several conformation traits, longevity, and total merit. Prediction accuracy was highest using a heavy-tailed prior assuming that each marker had an effect on each trait, rather than assuming a normal distribution of effects as in a linear model, or that only some loci have nonzero effects. A prior model combining heavy tails with finite alleles produced results that were intermediate compared with the individual models. Differences between models were small (1 to 2%) for traits with no major genes and larger for heavy tails with traits having known quantitative trait loci (QTL; 6 to 8%). Analysis of bull recessive codes suggested that marker effects from genomic selection may be used to identify regions of chromosomes to search in detail for candidate genes, but individual single nucleotide polymorphisms were not tracking causative mutations with the exception of diacylglycerol O-acyltransferase 1. Additive genetic merits were constructed for each chromosome, and the distribution of BTA14-specific estimated breeding value (EBV) showed that selection primarily for milk yield has not changed the distribution of EBV for fat percentage even in the presence of a known QTL. Such chromosomal EBV also may be useful for identifying complementary mates in breeding programs. The QTL affecting dystocia, conformation, and economic merit on BTA18 appear to be related to calf size or birth weight and may be the result of longer gestation lengths. Results validate quantitative genetic assumptions that most traits are due to the contributions of a large number of genes of small additive effect, rather than support the finite locus model.

Key Words: calving trait • genomic selection • single nucleotide polymorphism • quantitative trait loci