Literature DB >> 17504955

Marker-assisted selection for commercial crossbred performance.

J C M Dekkers1.   

Abstract

Several studies have shown that selection of purebreds for increased performance of their crossbred descendants under field conditions is hampered by low genetic correlations between purebred and commercial crossbred (CC) performance. Although this can be addressed by including phenotypic data from CC relatives for selection of purebreds through combined crossbred and purebred selection (CCPS), this also increases rates of inbreeding and requires comprehensive systems for collection of phenotypic data and pedigrees at the CC level. This study shows that both these limitations can be overcome with marker-assisted selection (MAS) by using estimates of the effects of markers on CC performance. To evaluate the potential benefits of CC-MAS, a model to incorporate marker information in selection strategies was developed based on selection index theory, which allows prediction of responses and rates of inbreeding by using standard deterministic selection theory. Assuming a genetic correlation between purebred and CC performance of 0.7 for a breeding program representing a terminal sire line in pigs, CC-MAS was shown to substantially increase rates of response and reduce rates of inbreeding compared with purebred selection and CCPS, with 60 CC half sibs available for each purebred selection candidate. When the accuracy of marker-based EBV was 0.6, CC-MAS resulted in 34 and 10% greater responses in CC performance than purebred selection and CCPS. Corresponding rates of inbreeding were 1.4% per generation for CC-MAS, compared with 2.1% for purebred selection and 3.0% for CCPS. For marker-based EBV with an accuracy of 0.9, CC-MAS resulted in 75 and 43% greater responses than purebred selection and CCPS, and further reduced rates of inbreeding to 1.0% per generation. Selection on marker-based EBV derived from purebred phenotypes resulted in substantially less response in CC performance than in CC-MAS. In conclusion, effective use of MAS requires estimates of the effect on CC performance, and MAS based on such estimates enables more effective selection for CC performance without the need for extensive pedigree recording and while reducing rates of inbreeding.

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Year:  2007        PMID: 17504955     DOI: 10.2527/jas.2006-683

Source DB:  PubMed          Journal:  J Anim Sci        ISSN: 0021-8812            Impact factor:   3.159


  47 in total

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Journal:  Genetics       Date:  2014-09       Impact factor: 4.562

4.  Assessment of sire contribution and breed-of-origin of alleles in a three-way crossbred broiler dataset.

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5.  Genomic selection of purebreds for crossbred performance.

Authors:  Noelia Ibánez-Escriche; Rohan L Fernando; Ali Toosi; Jack C M Dekkers
Journal:  Genet Sel Evol       Date:  2009-01-15       Impact factor: 4.297

6.  Genomic evaluation for a three-way crossbreeding system considering breed-of-origin of alleles.

Authors:  Claudia A Sevillano; Jeremie Vandenplas; John W M Bastiaansen; Rob Bergsma; Mario P L Calus
Journal:  Genet Sel Evol       Date:  2017-10-23       Impact factor: 4.297

7.  Diversity analysis and genomic prediction of Sclerotinia resistance in sunflower using a new 25 K SNP genotyping array.

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Journal:  Theor Appl Genet       Date:  2015-11-04       Impact factor: 5.699

8.  Performance of genomic selection in mice.

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9.  Genomic prediction with multiple biparental families.

Authors:  Pedro C Brauner; Dominik Müller; Willem S Molenaar; Albrecht E Melchinger
Journal:  Theor Appl Genet       Date:  2019-10-08       Impact factor: 5.699

10.  Haplotype inference in crossbred populations without pedigree information.

Authors:  Albart Coster; Henri C M Heuven; Rohan L Fernando; Jack C M Dekkers
Journal:  Genet Sel Evol       Date:  2009-08-11       Impact factor: 4.297

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