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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 #359290
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: Variance of gametic diversity and its use in selection programs

Author
item SANTOS, DANIEL - University Of Maryland
item Cole, John
item LAWLOR, THOMAS - Holstein Association Usa, Inc
item Vanraden, Paul
item TONHATI, HUMBERTO - Universidade Estadual Paulista (UNESP)
item MA, LI - University Of Maryland

Submitted to: Journal of Dairy Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/27/2019
Publication Date: 6/1/2019
Citation: Santos, D.J., Cole, J.B., Lawlor, T.J., Van Raden, P.M., Tonhati, H., Ma, L. 2019. Variance of gametic diversity and its use in selection programs. Journal of Dairy Science. 102(6):5279-5294. https://doi.org/10.3168/jds.2018-15971.
DOI: https://doi.org/10.3168/jds.2018-15971

Interpretive Summary: The variance of gametic diversity depends on the Mendelian transmission of all QTL from an individual to its gametes. To date, due to lack of information, this source of variation has not typically been considered in livestock breeding programs. Methods for estimating gametic variance and its applications to existing genomic selection programs are described in this study. Results show that the variance of gametic diversity can be an important parameter for controlling genetic diversity and for improving genetic selection in breeding programs.

Technical Abstract: The variance of gametic diversity can be a useful tool to find individuals that are more likely to produce progeny with extreme breeding values. The aim of this study is to show how to obtain this variance for individuals in routine genomic evaluations, as well as to use this variance as a selection criterion in conjunction with breeding values to improve genetic gains. An analytical approach was employed to obtain the gametic variance from the sum of binomial variances of individual QTL across the genome. Simulation was then used to verify the predictability of the variance of gametic diversity in many scenarios. For genomic evaluation, genomic BLUP (GBLUP) and Bayesian least absolute shrinkage and selection operator (BLASSO) models were compared, with BLASSO having better performance for estimating variance of gametic diversity. Results suggested that markers with low minor allele frequency (MAF), as well as the covariance between markers, should be included in the estimation. Compared to sequence data, SNP data are sufficient for estimating variance of gametic diversity. To incorporate variance of gametic diversity into selective breeding, we proposed a new index, the relative predicted transmitting ability (RPTA), which allows a better use of the genetic potential of individuals than traditional PTA. The RPTA is easy to obtain and apply in existing genomic evaluations. In addition, the confidence levels of this index can be adjusted by the number of progeny per parent, making it suitable for dairy cattle breeding. We also applied variance of gametic diversity to the U.S. genomic evaluations for Holstein and Jersey. The DGAT1 gene had a strong effect on the prediction of variance of gametic diversity for several dairy traits, biasing the distributions of this parameter in both cattle breeds. Population-level inbreeding had a small impact on gametic variability, with greater effects for traits affected by many genes. In conclusion, variance of gametic diversity, a potentially important parameter in selective breeding programs, is easy to compute and useful for both improving genetic gains and control of genetic diversity.