Abstract

BackgroundAlthough genome-wide association and genomic selection studies have primarily focused on additive effects, dominance and imprinting effects play an important role in mammalian biology and development. The degree to which these non-additive genetic effects contribute to phenotypic variation and whether QTL acting in a non-additive manner can be detected in genetic association studies remain controversial.ResultsTo empirically answer these questions, we analyzed a large cattle dataset that consisted of 42,701 genotyped Holstein cows with genotyped parents and phenotypic records for eight production and reproduction traits. SNP genotypes were phased in pedigree to determine the parent-of-origin of alleles, and a three-component GREML was applied to obtain variance decomposition for additive, dominance, and imprinting effects. The results showed a significant non-zero contribution from dominance to production traits but not to reproduction traits. Imprinting effects significantly contributed to both production and reproduction traits. Interestingly, imprinting effects contributed more to reproduction traits than to production traits. Using GWAS and imputation-based fine-mapping analyses, we identified and validated a dominance association signal with milk yield near RUNX2, a candidate gene that has been associated with milk production in mice. When adding non-additive effects into the prediction models, however, we observed little or no increase in prediction accuracy for the eight traits analyzed.ConclusionsCollectively, our results suggested that non-additive effects contributed a non-negligible amount (more for reproduction traits) to the total genetic variance of complex traits in cattle, and detection of QTLs with non-additive effect is possible in GWAS using a large dataset.

Highlights

  • Genome-wide association and genomic selection studies have primarily focused on additive effects, dominance and imprinting effects play an important role in mammalian biology and development

  • Though one may naturally assume that dominance and imprinting effects affect economically important traits in plants and animals, it remains controversial how much phenotypic variation can be attributed to these non-additive effects, how many quantitative trait loci (QTL) follow non-additive inheritance, and whether incorporating non-additive genetic effects will benefit genomic prediction [2,3,4]

  • This study provided a systematic view of dominance and imprinting effects through a comprehensive analysis of a large cattle data set, including variance decomposition, Genome-wide association study (GWAS), and genomic prediction

Read more

Summary

Introduction

Genome-wide association and genomic selection studies have primarily focused on additive effects, dominance and imprinting effects play an important role in mammalian biology and development. The degree to which these non-additive genetic effects contribute to phenotypic variation and whether QTL acting in a non-additive manner can be detected in genetic association studies remain controversial. Both dominance and imprinting play an important role in mammalian biology and development [1]. A few recent studies have tried to add imprinting effects into the decomposition of total genetic variation [13,14,15,16]. It was shown that mating programs increased rates of genetic gain when non-additive genetic

Objectives
Methods
Results
Discussion
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call