Literature DB >> 28854179

Genomic prediction unifies animal and plant breeding programs to form platforms for biological discovery.

John M Hickey1, Tinashe Chiurugwi2, Ian Mackay2, Wayne Powell3.   

Abstract

The rate of annual yield increases for major staple crops must more than double relative to current levels in order to feed a predicted global population of 9 billion by 2050. Controlled hybridization and selective breeding have been used for centuries to adapt plant and animal species for human use. However, achieving higher, sustainable rates of improvement in yields in various species will require renewed genetic interventions and dramatic improvement of agricultural practices. Genomic prediction of breeding values has the potential to improve selection, reduce costs and provide a platform that unifies breeding approaches, biological discovery, and tools and methods. Here we compare and contrast some animal and plant breeding approaches to make a case for bringing the two together through the application of genomic selection. We propose a strategy for the use of genomic selection as a unifying approach to deliver innovative 'step changes' in the rate of genetic gain at scale.

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Year:  2017        PMID: 28854179     DOI: 10.1038/ng.3920

Source DB:  PubMed          Journal:  Nat Genet        ISSN: 1061-4036            Impact factor:   38.330


  16 in total

1.  Effect of total allelic relationship on accuracy of evaluation and response to selection.

Authors:  A Nejati-Javaremi; C Smith; J P Gibson
Journal:  J Anim Sci       Date:  1997-07       Impact factor: 3.159

2.  Strategy for applying genome-wide selection in dairy cattle.

Authors:  L R Schaeffer
Journal:  J Anim Breed Genet       Date:  2006-08       Impact factor: 2.380

Review 3.  Methods for linkage disequilibrium mapping in crops.

Authors:  Ian Mackay; Wayne Powell
Journal:  Trends Plant Sci       Date:  2007-01-16       Impact factor: 18.313

Review 4.  Strategies to utilize marker-quantitative trait loci associations.

Authors:  C S Haley; P M Visscher
Journal:  J Dairy Sci       Date:  1998-09       Impact factor: 4.034

5.  Resemblance between two relatives – animal and plant breeding.

Authors:  C C Schön; H Simianer
Journal:  J Anim Breed Genet       Date:  2015-02       Impact factor: 2.380

Review 6.  Lights, camera, action: high-throughput plant phenotyping is ready for a close-up.

Authors:  Noah Fahlgren; Malia A Gehan; Ivan Baxter
Journal:  Curr Opin Plant Biol       Date:  2015-02-27       Impact factor: 7.834

7.  Estimation of relatedness by DNA fingerprinting.

Authors:  M Lynch
Journal:  Mol Biol Evol       Date:  1988-09       Impact factor: 16.240

8.  Potential of promotion of alleles by genome editing to improve quantitative traits in livestock breeding programs.

Authors:  Janez Jenko; Gregor Gorjanc; Matthew A Cleveland; Rajeev K Varshney; C Bruce A Whitelaw; John A Woolliams; John M Hickey
Journal:  Genet Sel Evol       Date:  2015-07-02       Impact factor: 4.297

9.  Understanding and using quantitative genetic variation.

Authors:  William G Hill
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2010-01-12       Impact factor: 6.237

10.  Quantitative genetics in the genomics era.

Authors:  William G Hill
Journal:  Curr Genomics       Date:  2012-05       Impact factor: 2.236

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  82 in total

1.  One Hundred Years of Linkage Disequilibrium.

Authors:  John A Sved; William G Hill
Journal:  Genetics       Date:  2018-07       Impact factor: 4.562

Review 2.  Predicting Polygenic Risk of Psychiatric Disorders.

Authors:  Alicia R Martin; Mark J Daly; Elise B Robinson; Steven E Hyman; Benjamin M Neale
Journal:  Biol Psychiatry       Date:  2018-12-28       Impact factor: 13.382

3.  Weighting genomic and genealogical information for genetic parameter estimation and breeding value prediction in tropical beef cattle.

Authors:  Fernanda S S Raidan; Laercio R Porto-Neto; Yutao Li; Sigrid A Lehnert; Antonio Reverter
Journal:  J Anim Sci       Date:  2018-03-06       Impact factor: 3.159

4.  Incorporation of parental phenotypic data into multi-omic models improves prediction of yield-related traits in hybrid rice.

Authors:  Yang Xu; Yue Zhao; Xin Wang; Ying Ma; Pengcheng Li; Zefeng Yang; Xuecai Zhang; Chenwu Xu; Shizhong Xu
Journal:  Plant Biotechnol J       Date:  2020-09-02       Impact factor: 9.803

Review 5.  From markers to genome-based breeding in wheat.

Authors:  Awais Rasheed; Xianchun Xia
Journal:  Theor Appl Genet       Date:  2019-01-23       Impact factor: 5.699

Review 6.  African Orphan Crops Consortium (AOCC): status of developing genomic resources for African orphan crops.

Authors:  Prasad S Hendre; Samuel Muthemba; Robert Kariba; Alice Muchugi; Yuan Fu; Yue Chang; Bo Song; Huan Liu; Min Liu; Xuezhu Liao; Sunil Kumar Sahu; Sibo Wang; Linzhou Li; Haorong Lu; Shufeng Peng; Shifeng Cheng; Xun Xu; Huanming Yang; Jian Wang; Xin Liu; Anthony Simons; Howard-Yana Shapiro; Rita H Mumm; Allen Van Deynze; Ramni Jamnadass
Journal:  Planta       Date:  2019-05-09       Impact factor: 4.116

7.  Genomic prediction with multiple biparental families.

Authors:  Pedro C Brauner; Dominik Müller; Willem S Molenaar; Albrecht E Melchinger
Journal:  Theor Appl Genet       Date:  2019-10-08       Impact factor: 5.699

Review 8.  Accelerating crop genetic gains with genomic selection.

Authors:  Kai Peter Voss-Fels; Mark Cooper; Ben John Hayes
Journal:  Theor Appl Genet       Date:  2018-12-19       Impact factor: 5.699

Review 9.  Rapid gene cloning in cereals.

Authors:  Jan Bettgenhaeuser; Simon G Krattinger
Journal:  Theor Appl Genet       Date:  2018-10-19       Impact factor: 5.699

Review 10.  Speed breeding orphan crops.

Authors:  Tinashe Chiurugwi; Stuart Kemp; Wayne Powell; Lee T Hickey
Journal:  Theor Appl Genet       Date:  2018-10-19       Impact factor: 5.699

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