Literature DB >> 22859761

Efficiency of genomic selection in a purebred pig male line.

T Tribout1, C Larzul, F Phocas.   

Abstract

Stochastic simulation was used to compare the efficiency of 3 pig breeding schemes based on either traditional genetic evaluation or genomic evaluation. The simulated population contained 1,050 female and 50 male breeding animals. It was selected for 10 yr for a synthetic breeding goal that included 2 traits with equal economic weights and heritabilities of 0.2 or 0.4. The reference breeding scheme, named BLUP-AM, was based on the phenotyping of all candidates (13,770 animals/yr) for Trait 1 and of relatives from 10% of the litters (270 animals/yr) for Trait 2 and on BLUP-Animal Model genetic evaluations. Under the first alternative scenario, named GE-1TP, selection was based on genomic breeding values (GBV) estimated with one training population (TP) made up of candidate relatives phenotyped for both traits, with a size increasing from 1,000 to 3,430 over time. Under the second alternative scenario, named GE-2TP, the GBV for Trait 2 were estimated using a TP identical to that of GE-1TP, but the GBV for Trait 1 were estimated using a large TP made up of candidates that increased in number from 13,770 to 55,080 over time. Over the simulated period, both genomic breeding schemes generated 39 to 58% more accurate EBV for Trait 2 than the reference scheme, resulting in 78 to 128% (GE-1TP) and 63 to 84% (GE-2TP) greater average annual genetic trends for this trait. For Trait 1, GE-1TP was 18 to 24% less accurate than BLUP-AM, reducing average annual genetic trends by 27 to 44%. By contrast, GE-2TP generated 35 to 43% more accurate EBV and 8 to 22% greater average annual genetic trends for Trait 1 than the reference scheme. Consequently, GE-2TP was 27 to 33% more efficient in improving the global breeding goal than BLUP-AM whereas GE-1TP was globally as efficient as the reference scheme. Both genomic schemes reduced the inbreeding rate, the greatest decrease being observed for GE-2TP (-49 to -60% compared with BLUP-AM). In conclusion, genomic selection could substantially and durably improve the efficiency of pig breeding schemes in terms of reliability, genetic trends, and inbreeding rate without any need to modify their current structure. Even though it only generates a small TP, limited annual phenotyping capacity for traits currently only recorded on relatives would not be prohibitive. A large TP is, however, required to outperform the current schemes for traits recorded on the candidates in the latter.

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Year:  2012        PMID: 22859761     DOI: 10.2527/jas.2012-5107

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


  18 in total

1.  The impact of selective genotyping on the response to selection using single-step genomic best linear unbiased prediction.

Authors:  Jeremy T Howard; Tom A Rathje; Caitlyn E Bruns; Danielle F Wilson-Wells; Stephen D Kachman; Matthew L Spangler
Journal:  J Anim Sci       Date:  2018-11-21       Impact factor: 3.159

2.  Genomic selection for wheat traits and trait stability.

Authors:  Mao Huang; Antonio Cabrera; Amber Hoffstetter; Carl Griffey; David Van Sanford; José Costa; Anne McKendry; Shiaoman Chao; Clay Sneller
Journal:  Theor Appl Genet       Date:  2016-06-04       Impact factor: 5.699

3.  Economic aspects of implementing genomic evaluations in a pig sire line breeding scheme.

Authors:  Thierry Tribout; Catherine Larzul; Florence Phocas
Journal:  Genet Sel Evol       Date:  2013-10-15       Impact factor: 4.297

4.  Evaluation of genome based estimated breeding values for meat quality in a berkshire population using high density single nucleotide polymorphism chips.

Authors:  S Baby; K-E Hyeong; Y-M Lee; J-H Jung; D-Y Oh; K-C Nam; T H Kim; H-K Lee; J-J Kim
Journal:  Asian-Australas J Anim Sci       Date:  2014-11       Impact factor: 2.509

5.  Genomic selection needs to be carefully assessed to meet specific requirements in livestock breeding programs.

Authors:  Elisabeth Jonas; Dirk-Jan de Koning
Journal:  Front Genet       Date:  2015-02-20       Impact factor: 4.599

Review 6.  Methods to address poultry robustness and welfare issues through breeding and associated ethical considerations.

Authors:  William M Muir; Heng-Wei Cheng; Candace Croney
Journal:  Front Genet       Date:  2014-11-26       Impact factor: 4.599

7.  Application of Genomic Data for Reliability Improvement of Pig Breeding Value Estimates.

Authors:  Ekaterina Melnikova; Artem Kabanov; Sergey Nikitin; Maria Somova; Sergey Kharitonov; Petr Otradnov; Olga Kostyunina; Tatiana Karpushkina; Elena Martynova; Aleksander Sermyagin; Natalia Zinovieva
Journal:  Animals (Basel)       Date:  2021-05-27       Impact factor: 2.752

8.  Total cost estimation for implementing genome-enabled selection in a multi-level swine production system.

Authors:  Caitlyn E Abell; Jack C M Dekkers; Max F Rothschild; John W Mabry; Kenneth J Stalder
Journal:  Genet Sel Evol       Date:  2014-05-19       Impact factor: 4.297

9.  Accuracy of estimation of genomic breeding values in pigs using low-density genotypes and imputation.

Authors:  Yvonne M Badke; Ronald O Bates; Catherine W Ernst; Justin Fix; Juan P Steibel
Journal:  G3 (Bethesda)       Date:  2014-04-16       Impact factor: 3.154

10.  Accuracy of genomic prediction for growth and carcass traits in Chinese triple-yellow chickens.

Authors:  Tianfei Liu; Hao Qu; Chenglong Luo; Dingming Shu; Jie Wang; Mogens Sandø Lund; Guosheng Su
Journal:  BMC Genet       Date:  2014-10-15       Impact factor: 2.797

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