Literature DB >> 25384137

Applied animal genomics: results from the field.

Alison L Van Eenennaam1, Kent A Weigel, Amy E Young, Matthew A Cleveland, Jack C M Dekkers.   

Abstract

Genomic selection (GS) is the use of statistical methods to estimate the genetic merit of a genotyped animal based on prediction equations derived from large ancestral populations with both phenotypes and genotypes. It has revolutionized the dairy cattle breeding industry and has been implemented with varying degrees of success in other animal breeding programs, including swine, poultry, and beef cattle. The findings of empirical field studies applying GS to the breeding sectors of these main animal protein industries are reviewed. Several translational considerations must be addressed before implementing GS in genetic improvement programs. These include determining and obtaining economically relevant phenotypes and determining the optimal size of the training population, cost-effective genotyping strategies, the practicality of field implementation, and the relative costs versus the benefits of the realized rate of genetic gain. GS may additionally change the optimal breeding scheme design, and studies that address this consideration are also reviewed briefly.

Entities:  

Keywords:  animal breeding; genetic prediction; genomic selection; translational genomics

Mesh:

Year:  2013        PMID: 25384137     DOI: 10.1146/annurev-animal-022513-114119

Source DB:  PubMed          Journal:  Annu Rev Anim Biosci        ISSN: 2165-8102            Impact factor:   8.923


  27 in total

1.  Efficiency of genomic prediction of non-assessed single crosses.

Authors:  José Marcelo Soriano Viana; Helcio Duarte Pereira; Gabriel Borges Mundim; Hans-Peter Piepho; Fabyano Fonseca E Silva
Journal:  Heredity (Edinb)       Date:  2017-11-28       Impact factor: 3.821

2.  In silico mapping of quantitative trait loci (QTL) regulating the milk ionome in mice identifies a milk iron locus on chromosome 1.

Authors:  Darryl L Hadsell; Louise A Hadsell; Monique Rijnkels; Yareli Carcamo-Bahena; Jerry Wei; Peter Williamson; Michael A Grusak
Journal:  Mamm Genome       Date:  2018-08-02       Impact factor: 2.957

3.  Assessing the expected response to genomic selection of individuals and families in Eucalyptus breeding with an additive-dominant model.

Authors:  R T Resende; M D V Resende; F F Silva; C F Azevedo; E K Takahashi; O B Silva-Junior; D Grattapaglia
Journal:  Heredity (Edinb)       Date:  2017-07-05       Impact factor: 3.821

4.  Design of reference populations for genomic selection in crossbreeding programs.

Authors:  Ilse E M van Grevenhof; Julius H J van der Werf
Journal:  Genet Sel Evol       Date:  2015-03-07       Impact factor: 4.297

5.  Artificial selection with traditional or genomic relationships: consequences in coancestry and genetic diversity.

Authors:  Silvia Teresa Rodríguez-Ramilo; Luis Alberto García-Cortés; María Ángeles Rodríguez de Cara
Journal:  Front Genet       Date:  2015-04-07       Impact factor: 4.599

6.  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

7.  Genomic prediction in contrast to a genome-wide association study in explaining heritable variation of complex growth traits in breeding populations of Eucalyptus.

Authors:  Bárbara S F Müller; Leandro G Neves; Janeo E de Almeida Filho; Márcio F R Resende; Patricio R Muñoz; Paulo E T Dos Santos; Estefano Paludzyszyn Filho; Matias Kirst; Dario Grattapaglia
Journal:  BMC Genomics       Date:  2017-07-11       Impact factor: 3.969

8.  Evaluating the accuracy of genomic prediction of growth and wood traits in two Eucalyptus species and their F1 hybrids.

Authors:  Biyue Tan; Dario Grattapaglia; Gustavo Salgado Martins; Karina Zamprogno Ferreira; Björn Sundberg; Pär K Ingvarsson
Journal:  BMC Plant Biol       Date:  2017-06-29       Impact factor: 4.215

Review 9.  Gene targeting, genome editing: from Dolly to editors.

Authors:  Wenfang Tan; Chris Proudfoot; Simon G Lillico; C Bruce A Whitelaw
Journal:  Transgenic Res       Date:  2016-02-03       Impact factor: 2.788

10.  Genomic prediction of breeding values for carcass traits in Nellore cattle.

Authors:  Gerardo A Fernandes Júnior; Guilherme J M Rosa; Bruno D Valente; Roberto Carvalheiro; Fernando Baldi; Diogo A Garcia; Daniel G M Gordo; Rafael Espigolan; Luciana Takada; Rafael L Tonussi; Willian B F de Andrade; Ana F B Magalhães; Luis A L Chardulo; Humberto Tonhati; Lucia G de Albuquerque
Journal:  Genet Sel Evol       Date:  2016-01-29       Impact factor: 4.297

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.