Literature DB >> 10531605

Prediction of parental dominance combinations for planned matings, methodology, and simulation results.

L Varona1, I Misztal.   

Abstract

Optimal use of dominance information requires a mating system and predictions of specific combining abilities for each set of prospective parents. Current evaluation procedures provide such predictions only for a limited number of parents. A procedure is described that predicts the specific combining ability for any parents. In this procedure, for each set of parents and their ancestors, the additive relationship matrix is created as a dense matrix. This matrix is then used to create a parental dominance matrix in a sparse matrix form, in which the rows of the matrix correspond to all parental combinations for which predictions are already available. Each new prediction requires a solution of the system of equations with the parental dominance matrix as the left-hand side. The efficiency of the mating system that accounts for dominance was evaluated in a simulation study. The simulated data files varied with respect to proportion of males and females selected, proportion of cattle born through embryo transfer, and additive and dominance variance. Sires and dams were preselected based on the additive merits only, but specific matings were arranged based on the combined additive plus dominance merit. The response to selection with consideration of dominance increased from 3.8 to 16.6% of the response from one generation of additive selection. The response was greater when the additive variance was smaller, the dominance variance was larger, the intensity of additive selection was lower, and the proportion of full sibs was greater. Use of dominance in the mating system is feasible and results in an additional genetic response to selection.

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Year:  1999        PMID: 10531605     DOI: 10.3168/jds.S0022-0302(99)75463-9

Source DB:  PubMed          Journal:  J Dairy Sci        ISSN: 0022-0302            Impact factor:   4.034


  7 in total

1.  On the additive and dominant variance and covariance of individuals within the genomic selection scope.

Authors:  Zulma G Vitezica; Luis Varona; Andres Legarra
Journal:  Genetics       Date:  2013-10-11       Impact factor: 4.562

2.  Marker-assisted prediction of non-additive genetic values.

Authors:  Nanye Long; Daniel Gianola; Guilherme J M Rosa; Kent A Weigel
Journal:  Genetica       Date:  2011-06-15       Impact factor: 1.082

3.  A note on mate allocation for dominance handling in genomic selection.

Authors:  Miguel A Toro; Luis Varona
Journal:  Genet Sel Evol       Date:  2010-08-11       Impact factor: 4.297

4.  Efficient Markov chain Monte Carlo implementation of Bayesian analysis of additive and dominance genetic variances in noninbred pedigrees.

Authors:  Patrik Waldmann; Jon Hallander; Fabian Hoti; Mikko J Sillanpää
Journal:  Genetics       Date:  2008-06       Impact factor: 4.562

5.  Estimating additive and non-additive genetic variances and predicting genetic merits using genome-wide dense single nucleotide polymorphism markers.

Authors:  Guosheng Su; Ole F Christensen; Tage Ostersen; Mark Henryon; Mogens S Lund
Journal:  PLoS One       Date:  2012-09-13       Impact factor: 3.240

6.  Genomic analysis of dominance effects on milk production and conformation traits in Fleckvieh cattle.

Authors:  Johann Ertl; Andrés Legarra; Zulma G Vitezica; Luis Varona; Christian Edel; Reiner Emmerling; Kay-Uwe Götz
Journal:  Genet Sel Evol       Date:  2014-06-24       Impact factor: 4.297

7.  An assessment of genomic connectedness measures in Nellore cattle.

Authors:  Sabrina T Amorim; Haipeng Yu; Mehdi Momen; Lúcia Galvão de Albuquerque; Angélica S Cravo Pereira; Fernando Baldi; Gota Morota
Journal:  J Anim Sci       Date:  2020-11-01       Impact factor: 3.159

  7 in total

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