Literature DB >> 18076474

Inbreeding in genome-wide selection.

H D Daetwyler1, B Villanueva, P Bijma, J A Woolliams.   

Abstract

Traditional selection methods, such as sib and best linear unbiased prediction (BLUP) selection, which increased genetic gain by increasing accuracy of evaluation have also led to an increased rate of inbreeding per generation (DeltaFG). This is not necessarily the case with genome-wide selection, which also increases genetic gain by increasing accuracy. This paper explains why genome-wide selection reduces DeltaFG when compared with sib and BLUP selection. Genome-wide selection achieves high accuracies of estimated breeding values through better prediction of the Mendelian sampling term component of breeding values. This increases differentiation between sibs and reduces coselection of sibs and DeltaFG. The high accuracy of genome-wide selection is expected to reduce the between family variance and reweigh the emphasis of estimated breeding values of individuals towards the Mendelian sampling term. Moreover, estimation induced intraclass correlations of sibs are expected to be lower in genome-wide selection leading to a further decrease of coselection of sibs when compared with BLUP. Genome-wide prediction of breeding values, therefore, enables increased genetic gain while at the same time reducing DeltaFG when compared with sib and BLUP selection.

Mesh:

Year:  2007        PMID: 18076474     DOI: 10.1111/j.1439-0388.2007.00693.x

Source DB:  PubMed          Journal:  J Anim Breed Genet        ISSN: 0931-2668            Impact factor:   2.380


  68 in total

1.  The impact of genetic architecture on genome-wide evaluation methods.

Authors:  Hans D Daetwyler; Ricardo Pong-Wong; Beatriz Villanueva; John A Woolliams
Journal:  Genetics       Date:  2010-04-20       Impact factor: 4.562

2.  Incorporating desirable genetic characteristics from an inferior into a superior population using genomic selection.

Authors:  J Odegård; M H Yazdi; A K Sonesson; T H E Meuwissen
Journal:  Genetics       Date:  2008-12-01       Impact factor: 4.562

3.  The Impact of Genomic and Traditional Selection on the Contribution of Mutational Variance to Long-Term Selection Response and Genetic Variance.

Authors:  Herman A Mulder; Sang Hong Lee; Sam Clark; Ben J Hayes; Julius H J van der Werf
Journal:  Genetics       Date:  2019-08-20       Impact factor: 4.562

Review 4.  Genomic prediction in animals and plants: simulation of data, validation, reporting, and benchmarking.

Authors:  Hans D Daetwyler; Mario P L Calus; Ricardo Pong-Wong; Gustavo de Los Campos; John M Hickey
Journal:  Genetics       Date:  2012-12-05       Impact factor: 4.562

5.  Genomic selection prediction accuracy in a perennial crop: case study of oil palm (Elaeis guineensis Jacq.).

Authors:  David Cros; Marie Denis; Leopoldo Sánchez; Benoit Cochard; Albert Flori; Tristan Durand-Gasselin; Bruno Nouy; Alphonse Omoré; Virginie Pomiès; Virginie Riou; Edyana Suryana; Jean-Marc Bouvet
Journal:  Theor Appl Genet       Date:  2014-12-07       Impact factor: 5.699

6.  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

7.  The impact of genetic relationship information on genomic breeding values in German Holstein cattle.

Authors:  David Habier; Jens Tetens; Franz-Reinhold Seefried; Peter Lichtner; Georg Thaller
Journal:  Genet Sel Evol       Date:  2010-02-19       Impact factor: 4.297

8.  Testing strategies for genomic selection in aquaculture breeding programs.

Authors:  Anna K Sonesson; Theo H E Meuwissen
Journal:  Genet Sel Evol       Date:  2009-06-30       Impact factor: 4.297

9.  Accuracy of direct genomic values in Holstein bulls and cows using subsets of SNP markers.

Authors:  Gerhard Moser; Mehar S Khatkar; Ben J Hayes; Herman W Raadsma
Journal:  Genet Sel Evol       Date:  2010-10-16       Impact factor: 4.297

10.  Dynamics of long-term genomic selection.

Authors:  Jean-Luc Jannink
Journal:  Genet Sel Evol       Date:  2010-08-16       Impact factor: 4.297

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.