Literature DB >> 24395822

Applications of population genetics to animal breeding, from wright, fisher and lush to genomic prediction.

William G Hill1.   

Abstract

Although animal breeding was practiced long before the science of genetics and the relevant disciplines of population and quantitative genetics were known, breeding programs have mainly relied on simply selecting and mating the best individuals on their own or relatives' performance. This is based on sound quantitative genetic principles, developed and expounded by Lush, who attributed much of his understanding to Wright, and formalized in Fisher's infinitesimal model. Analysis at the level of individual loci and gene frequency distributions has had relatively little impact. Now with access to genomic data, a revolution in which molecular information is being used to enhance response with "genomic selection" is occurring. The predictions of breeding value still utilize multiple loci throughout the genome and, indeed, are largely compatible with additive and specifically infinitesimal model assumptions. I discuss some of the history and genetic issues as applied to the science of livestock improvement, which has had and continues to have major spin-offs into ideas and applications in other areas.

Mesh:

Year:  2014        PMID: 24395822      PMCID: PMC3872177          DOI: 10.1534/genetics.112.147850

Source DB:  PubMed          Journal:  Genetics        ISSN: 0016-6731            Impact factor:   4.562


  83 in total

1.  Accurate prediction of genetic values for complex traits by whole-genome resequencing.

Authors:  Theo Meuwissen; Mike Goddard
Journal:  Genetics       Date:  2010-03-22       Impact factor: 4.562

Review 2.  Up hill, down dale: quantitative genetics of curvaceous traits.

Authors:  Karin Meyer; Mark Kirkpatrick
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2005-07-29       Impact factor: 6.237

3.  Genome-based prediction of testcross values in maize.

Authors:  Theresa Albrecht; Valentin Wimmer; Hans-Jürgen Auinger; Malena Erbe; Carsten Knaak; Milena Ouzunova; Henner Simianer; Chris-Carolin Schön
Journal:  Theor Appl Genet       Date:  2011-04-20       Impact factor: 5.699

4.  Why aren't horses faster?

Authors:  W G Hill
Journal:  Nature       Date:  1988-04-21       Impact factor: 49.962

5.  Replicated selection for body weight in mice.

Authors:  D S Falconer
Journal:  Genet Res       Date:  1973-12       Impact factor: 1.588

6.  The stability of linked systems of loci with a small population size.

Authors:  J A Sved
Journal:  Genetics       Date:  1968-08       Impact factor: 4.562

7.  Selection and covariance.

Authors:  G R Price
Journal:  Nature       Date:  1970-08-01       Impact factor: 49.962

8.  Genetic and statistical analyses of strong selection on polygenic traits: what, me normal?

Authors:  M Turelli; N H Barton
Journal:  Genetics       Date:  1994-11       Impact factor: 4.562

9.  The effect of linkage on limits to artificial selection.

Authors:  W G Hill; A Robertson
Journal:  Genet Res       Date:  1966-12       Impact factor: 1.588

10.  Genome-wide prediction of traits with different genetic architecture through efficient variable selection.

Authors:  Valentin Wimmer; Christina Lehermeier; Theresa Albrecht; Hans-Jürgen Auinger; Yu Wang; Chris-Carolin Schön
Journal:  Genetics       Date:  2013-08-09       Impact factor: 4.562

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  30 in total

1.  Sewall Wright on Evolution in Mendelian Populations and the "Shifting Balance".

Authors:  Nicholas H Barton
Journal:  Genetics       Date:  2016-01       Impact factor: 4.562

2.  Genome-based establishment of a high-yielding heterotic pattern for hybrid wheat breeding.

Authors:  Yusheng Zhao; Zuo Li; Guozheng Liu; Yong Jiang; Hans Peter Maurer; Tobias Würschum; Hans-Peter Mock; Andrea Matros; Erhard Ebmeyer; Ralf Schachschneider; Ebrahim Kazman; Johannes Schacht; Manje Gowda; C Friedrich H Longin; Jochen C Reif
Journal:  Proc Natl Acad Sci U S A       Date:  2015-12-09       Impact factor: 11.205

3.  Enhancing genomic prediction with genome-wide association studies in multiparental maize populations.

Authors:  Y Bian; J B Holland
Journal:  Heredity (Edinb)       Date:  2017-02-15       Impact factor: 3.821

4.  Meuwissen et al. on Genomic Selection.

Authors:  Dirk-Jan de Koning
Journal:  Genetics       Date:  2016-05       Impact factor: 4.562

5.  Is Continued Genetic Improvement of Livestock Sustainable?

Authors:  William G Hill
Journal:  Genetics       Date:  2016-03       Impact factor: 4.562

Review 6.  Association Studies and Genomic Prediction for Genetic Improvements in Agriculture.

Authors:  Qianqian Zhang; Qin Zhang; Just Jensen
Journal:  Front Plant Sci       Date:  2022-06-02       Impact factor: 6.627

7.  Overview of Major Computer Packages for Genomic Prediction of Complex Traits.

Authors:  Giovanny Covarrubias-Pazaran
Journal:  Methods Mol Biol       Date:  2022

8.  Single-step genomic prediction of Eucalyptus dunnii using different identity-by-descent and identity-by-state relationship matrices.

Authors:  Esteban J Jurcic; Pamela V Villalba; Pablo S Pathauer; Dino A Palazzini; Gustavo P J Oberschelp; Leonel Harrand; Martín N Garcia; Natalia C Aguirre; Cintia V Acuña; María C Martínez; Juan G Rivas; Esteban F Cisneros; Juan A López; Susana N Marcucci Poltri; Sebastián Munilla; Eduardo P Cappa
Journal:  Heredity (Edinb)       Date:  2021-06-18       Impact factor: 3.832

9.  The challenges of pedigree dog health: approaches to combating inherited disease.

Authors:  Lindsay L Farrell; Jeffrey J Schoenebeck; Pamela Wiener; Dylan N Clements; Kim M Summers
Journal:  Canine Genet Epidemiol       Date:  2015-02-11

10.  Powerful detection of polygenic selection and evidence of environmental adaptation in US beef cattle.

Authors:  Troy N Rowan; Harly J Durbin; Christopher M Seabury; Robert D Schnabel; Jared E Decker
Journal:  PLoS Genet       Date:  2021-07-22       Impact factor: 5.917

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