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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 #323636

Title: Dissecting non-additive genetic effects for production and reproductive traits in dairy cattle

item JIANG, JICAI - University Of Maryland
item O'CONNELL, JEFFREY - University Of Maryland
item Vanraden, Paul
item MA, LI - University Of Maryland

Submitted to: Plant and Animal Genome Conference Proceedings
Publication Type: Abstract Only
Publication Acceptance Date: 1/8/2016
Publication Date: 1/8/2016
Citation: Jiang, J., O'Connell, J.R., Van Raden, P.M., Ma, L. 2016. Dissecting non-additive genetic effects for production and reproductive traits in dairy cattle. Plant and Animal Genome Conference Proceedings. San Diego, CA, Jan. 9–13, P0528.

Interpretive Summary:

Technical Abstract: Genomic imprinting is an epigenetic mechanism by which a parent-of-origin-specific allele is silenced and only the other allele is expressed. Both dominance and imprinting play an important role in mammalian biology and development. Though one may naturally assume that dominance and imprinting effects contribute to economically important traits in plants and animals, it remains controversy how much these non-additive effects contribute to phenotypic variation and how many QTLs act in such a non-additive manner. To empirically answer these questions, we analyzed a large cattle dataset from USDA that consists of ~42,000 Holstein cows with both SNP genotype data and yield deviation phenotype data. The SNP genotypes were phased to determine the parent-of-origin of an allele and genetic values were decomposed into three components (i.e., additive, dominance and imprinting effects). For each of the three types of effects, corresponding genomic relationship matrix was built based on phased 60k SNP data. A three-component GREML was used to model the three components simultaneously and to obtain variance decomposition estimates. The results showed that the variance explained by imprinting effect was negligible for all three production traits, less than 2.0% of the total genetic variance. For reproductive traits that have a low heritability, however, imprinting effect explained a relatively large portion of the total genetic variance (17.9% for daughter pregnancy rate, 24.8% for cow conception rate, and 36.9% for heifer conception rate). Additionally, we performed a whole-genome single-marker scan for additive, dominance and imprinting effects on all eight traits. Using a genome-wide significance level of 1x10^-6, we found no imprinting effect at single-SNP level. However, we identified a novel dominance signal around Chr23:18Mb that associates with milk yield. Collectively, our results show that non-additive effects contribute a non-negligible amount (more for reproduction traits) to the total genetic variance of complex traits in cattle, and detection of individual associations for non-additive effect is possible using a large dataset.