Literature DB >> 32331884

Symposium review: How to implement genomic selection.

P M VanRaden1.   

Abstract

Genomic selection was adopted very quickly in the 10 yr after first implementation, and breeders continue to find new uses for genomic testing. Breeding values with higher reliability earlier in life are estimated by combining DNA genotypes for many thousands of loci using existing identification, pedigree, and phenotype databases for millions of animals. Quality control for both new and previous data is greatly improved by comparing genomic and pedigree relationships to correct parent-progeny conflicts and discover many additional ancestors. Many quantitative trait loci and gene tests have been added to previous assays that used only evenly spaced, highly polymorphic markers. Imputation now combines genotypes from many assays of differing marker densities. Prediction models have gradually advanced from normal or Bayesian distributions within trait and breed to single-step, multitrait, or other more complex models, such as multibreed models that may be needed for crossbred prediction. Genomic selection was initially applied to males to predict progeny performance but is now widely applied to females or even embryos to predict their own later performance. The initial focus on additive merit has expanded to include mating programs, genomic inbreeding, and recessive alleles. Many producers now use DNA testing to decide which heifers should be inseminated with elite dairy, beef, or sex-sorted semen, which should be embryo donors or recipients, or which should be sold or kept for breeding. Because some of these decisions are expensive to delay, predictions are now provided weekly instead of every few months. Predictions from international genomic databases are often more accurate and cost-effective than those from within-country databases that were previously designed for progeny testing unless local breeds, conditions, or traits differ greatly from the larger database. Selection indexes include many new traits, often with lower heritability or requiring large initial investments to obtain phenotypes, which provide further incentive to cooperate internationally. The genomic prediction methods developed for dairy cattle are now applied widely to many animal, human, and plant populations and could be applied to many more.
Copyright © 2020 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  DNA testing; dairy cattle; genomic prediction; genomic selection

Mesh:

Year:  2020        PMID: 32331884     DOI: 10.3168/jds.2019-17684

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


  13 in total

Review 1.  Application of Genetic, Genomic and Biological Pathways in Improvement of Swine Feed Efficiency.

Authors:  Pourya Davoudi; Duy Ngoc Do; Stefanie M Colombo; Bruce Rathgeber; Younes Miar
Journal:  Front Genet       Date:  2022-06-09       Impact factor: 4.772

Review 2.  Which field of research would Gregor Mendel choose in the 21st century?

Authors:  Frédéric Berger
Journal:  Plant Cell       Date:  2022-07-04       Impact factor: 12.085

3.  Genomic Prediction of Complex Traits in Perennial Plants: A Case for Forest Trees.

Authors:  Fikret Isik
Journal:  Methods Mol Biol       Date:  2022

4.  Single-step genomic evaluation of Russian dairy cattle using internal and external information.

Authors:  Andrei A Kudinov; Esa A Mäntysaari; Timo J Pitkänen; Ekaterina I Saksa; Gert P Aamand; Pekka Uimari; Ismo Strandén
Journal:  J Anim Breed Genet       Date:  2021-11-28       Impact factor: 3.271

Review 5.  Plant Breeding for Intercropping in Temperate Field Crop Systems: A Review.

Authors:  Virginia M Moore; Brandon Schlautman; Shui-Zhang Fei; Lucas M Roberts; Marnin Wolfe; Matthew R Ryan; Samantha Wells; Aaron J Lorenz
Journal:  Front Plant Sci       Date:  2022-03-31       Impact factor: 5.753

Review 6.  Genomic Analysis, Progress and Future Perspectives in Dairy Cattle Selection: A Review.

Authors:  Miguel A Gutierrez-Reinoso; Pedro M Aponte; Manuel Garcia-Herreros
Journal:  Animals (Basel)       Date:  2021-02-25       Impact factor: 3.231

7.  Transcriptome Analysis Identifies Candidate Genes and Signaling Pathways Associated With Feed Efficiency in Xiayan Chicken.

Authors:  Cong Xiao; Jixian Deng; Linghu Zeng; Tiantian Sun; Zhuliang Yang; Xiurong Yang
Journal:  Front Genet       Date:  2021-03-17       Impact factor: 4.599

8.  Potential of preimplantation genomic selection using the blastomere separation technique in bovine in vitro fertilized embryos.

Authors:  Takashi Fujii; Akira Naito; Satoru Moriyasu; Soichi Kageyama
Journal:  J Reprod Dev       Date:  2021-02-28       Impact factor: 2.214

9.  Toward genomic selection in Pinus taeda: Integrating resources to support array design in a complex conifer genome.

Authors:  Madison Caballero; Edwin Lauer; Jeremy Bennett; Sumaira Zaman; Susan McEvoy; Juan Acosta; Colin Jackson; Laura Townsend; Andrew Eckert; Ross W Whetten; Carol Loopstra; Jason Holliday; Mihir Mandal; Jill L Wegrzyn; Fikret Isik
Journal:  Appl Plant Sci       Date:  2021-07-02       Impact factor: 1.936

Review 10.  Historical Evolution of Cattle Management and Herd Health of Dairy Farms in OECD Countries.

Authors:  Ivo Medeiros; Aitor Fernandez-Novo; Susana Astiz; João Simões
Journal:  Vet Sci       Date:  2022-03-09
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