Literature DB >> 24119810

Mating programs including genomic relationships and dominance effects.

C Sun1, P M VanRaden, J R O'Connell, K A Weigel, D Gianola.   

Abstract

Computerized mating programs using genomic information are needed by breed associations, artificial-insemination organizations, and on-farm software providers, but such software is already challenged by the size of the relationship matrix. As of October 2012, over 230,000 Holsteins obtained genomic predictions in North America. Efficient methods of storing, computing, and transferring genomic relationships from a central database to customers via a web query were developed for approximately 165,000 genotyped cows and the subset of 1,518 bulls whose semen was available for purchase at that time. This study, utilizing 3 breeds, investigated differences in sire selection, methods of assigning mates, the use of genomic or pedigree relationships, and the effect of including dominance effects in a mating program. For both Jerseys and Holsteins, selection and mating programs were tested using the top 50 marketed bulls for genomic and traditional lifetime net merit as well as 50 randomly selected bulls. The 500 youngest genotyped cows in the largest herd in each breed were assigned mates of the same breed with limits of 10 cows per bull and 1 bull per cow (only 79 cows and 8 bulls for Brown Swiss). A dominance variance of 4.1 and 3.7% was estimated for Holsteins and Jerseys using 45,187 markers and management group deviation for milk yield. Sire selection was identified as the most important component of improving expected progeny value, followed by managing inbreeding and then inclusion of dominance. The respective percentage gains for milk yield in this study were 64, 27, and 9, for Holsteins and 73, 20, and 7 for Jerseys. The linear programming method of assigning a mate outperformed sequential selection by reducing genomic or pedigree inbreeding by 0.86 to 1.06 and 0.93 to 1.41, respectively. Use of genomic over pedigree relationship information provided a larger decrease in expected progeny inbreeding and thus greater expected progeny value. Based on lifetime net merit, the economic value of using genomic relationships was >$3 million per year for Holsteins when applied to all genotyped females, assuming that each will provide 1 replacement. Previous mating programs required transferring only a pedigree file to customers, but better service is possible by incorporating genomic relationships, more precise mate allocation, and dominance effects. Economic benefits will continue to grow as more females are genotyped.
Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  dominance; genomic relationship; genotype; mating program

Mesh:

Substances:

Year:  2013        PMID: 24119810     DOI: 10.3168/jds.2013-6969

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


  22 in total

1.  Identification of genomic regions associated with inbreeding depression in Holstein and Jersey dairy cattle.

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Journal:  Genet Sel Evol       Date:  2014-11-18       Impact factor: 4.297

2.  Genomic Prediction Methods Accounting for Nonadditive Genetic Effects.

Authors:  Luis Varona; Andres Legarra; Miguel A Toro; Zulma G Vitezica
Journal:  Methods Mol Biol       Date:  2022

3.  Genome-wide estimates of coancestry, inbreeding and effective population size in the Spanish Holstein population.

Authors:  Silvia Teresa Rodríguez-Ramilo; Jesús Fernández; Miguel Angel Toro; Delfino Hernández; Beatriz Villanueva
Journal:  PLoS One       Date:  2015-04-16       Impact factor: 3.240

4.  Including dominance effects in the genomic BLUP method for genomic evaluation.

Authors:  Motohide Nishio; Masahiro Satoh
Journal:  PLoS One       Date:  2014-01-08       Impact factor: 3.240

5.  Increasing long-term response by selecting for favorable minor alleles.

Authors:  Chuanyu Sun; Paul M VanRaden
Journal:  PLoS One       Date:  2014-02-05       Impact factor: 3.240

6.  A simple strategy for managing many recessive disorders in a dairy cattle breeding program.

Authors:  John B Cole
Journal:  Genet Sel Evol       Date:  2015-11-30       Impact factor: 4.297

7.  Mixed model methods for genomic prediction and variance component estimation of additive and dominance effects using SNP markers.

Authors:  Yang Da; Chunkao Wang; Shengwen Wang; Guo Hu
Journal:  PLoS One       Date:  2014-01-30       Impact factor: 3.240

8.  GVCBLUP: a computer package for genomic prediction and variance component estimation of additive and dominance effects.

Authors:  Chunkao Wang; Dzianis Prakapenka; Shengwen Wang; Sujata Pulugurta; Hakizumwami Birali Runesha; Yang Da
Journal:  BMC Bioinformatics       Date:  2014-08-09       Impact factor: 3.169

9.  Improvement of prediction ability for genomic selection of dairy cattle by including dominance effects.

Authors:  Chuanyu Sun; Paul M VanRaden; John B Cole; Jeffrey R O'Connell
Journal:  PLoS One       Date:  2014-08-01       Impact factor: 3.240

10.  The contribution of dominance to phenotype prediction in a pine breeding and simulated population.

Authors:  J E de Almeida Filho; J F R Guimarães; F F E Silva; M D V de Resende; P Muñoz; M Kirst; M F R Resende
Journal:  Heredity (Edinb)       Date:  2016-04-27       Impact factor: 3.821

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