Literature DB >> 28364262

Mitigation of inbreeding while preserving genetic gain in genomic breeding programs for outbred plants.

Zibei Lin1,2, Fan Shi3, Ben J Hayes3,4, Hans D Daetwyler3,4.   

Abstract

KEY MESSAGE: Heuristic genomic inbreeding controls reduce inbreeding in genomic breeding schemes without reducing genetic gain. Genomic selection is increasingly being implemented in plant breeding programs to accelerate genetic gain of economically important traits. However, it may cause significant loss of genetic diversity when compared with traditional schemes using phenotypic selection. We propose heuristic strategies to control the rate of inbreeding in outbred plants, which can be categorised into three types: controls during mate allocation, during selection, and simultaneous selection and mate allocation. The proposed mate allocation measure GminF allocates two or more parents for mating in mating groups that minimise coancestry using a genomic relationship matrix. Two types of relationship-adjusted genomic breeding values for parent selection candidates ([Formula: see text]) and potential offspring ([Formula: see text]) are devised to control inbreeding during selection and even enabling simultaneous selection and mate allocation. These strategies were tested in a case study using a simulated perennial ryegrass breeding scheme. As compared to the genomic selection scheme without controls, all proposed strategies could significantly decrease inbreeding while achieving comparable genetic gain. In particular, the scenario using [Formula: see text] in simultaneous selection and mate allocation reduced inbreeding to one-third of the original genomic selection scheme. The proposed strategies are readily applicable in any outbred plant breeding program.

Entities:  

Mesh:

Year:  2017        PMID: 28364262     DOI: 10.1007/s00122-017-2863-y

Source DB:  PubMed          Journal:  Theor Appl Genet        ISSN: 0040-5752            Impact factor:   5.699


  23 in total

Review 1.  Improving plant breeding with exotic genetic libraries.

Authors:  D Zamir
Journal:  Nat Rev Genet       Date:  2001-12       Impact factor: 53.242

2.  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

3.  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

4.  Efficient methods to compute genomic predictions.

Authors:  P M VanRaden
Journal:  J Dairy Sci       Date:  2008-11       Impact factor: 4.034

Review 5.  Genomic selection in plant breeding: from theory to practice.

Authors:  Jean-Luc Jannink; Aaron J Lorenz; Hiroyoshi Iwata
Journal:  Brief Funct Genomics       Date:  2010-02-15       Impact factor: 4.241

6.  Genetic Gain and Inbreeding from Genomic Selection in a Simulated Commercial Breeding Program for Perennial Ryegrass.

Authors:  Zibei Lin; Noel O I Cogan; Luke W Pembleton; German C Spangenberg; John W Forster; Ben J Hayes; Hans D Daetwyler
Journal:  Plant Genome       Date:  2016-03       Impact factor: 4.089

7.  Common SNPs explain a large proportion of the heritability for human height.

Authors:  Jian Yang; Beben Benyamin; Brian P McEvoy; Scott Gordon; Anjali K Henders; Dale R Nyholt; Pamela A Madden; Andrew C Heath; Nicholas G Martin; Grant W Montgomery; Michael E Goddard; Peter M Visscher
Journal:  Nat Genet       Date:  2010-06-20       Impact factor: 38.330

8.  Novel strategies to minimize progeny inbreeding while maximizing genetic gain using genomic information.

Authors:  J E Pryce; B J Hayes; M E Goddard
Journal:  J Dairy Sci       Date:  2012-01       Impact factor: 4.034

9.  The effect of genomic information on optimal contribution selection in livestock breeding programs.

Authors:  Samuel A Clark; Brian P Kinghorn; John M Hickey; Julius H J van der Werf
Journal:  Genet Sel Evol       Date:  2013-10-30       Impact factor: 4.297

10.  Association studies using family pools of outcrossing crops based on allele-frequency estimates from DNA sequencing.

Authors:  Bilal H Ashraf; Just Jensen; Torben Asp; Luc L Janss
Journal:  Theor Appl Genet       Date:  2014-03-26       Impact factor: 5.699

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  12 in total

1.  Improving genomic predictions with inbreeding and nonadditive effects in two admixed maize hybrid populations in single and multienvironment contexts.

Authors:  Morgane Roth; Aurélien Beugnot; Tristan Mary-Huard; Laurence Moreau; Alain Charcosset; Julie B Fiévet
Journal:  Genetics       Date:  2022-04-04       Impact factor: 4.402

2.  Genomic Prediction of Complex Traits in Forage Plants Species: Perennial Grasses Case.

Authors:  Philippe Barre; Torben Asp; Stephen Byrne; Michael Casler; Marty Faville; Odd Arne Rognli; Isabel Roldan-Ruiz; Leif Skøt; Marc Ghesquière
Journal:  Methods Mol Biol       Date:  2022

3.  Optimal cross selection for long-term genetic gain in two-part programs with rapid recurrent genomic selection.

Authors:  Gregor Gorjanc; R Chris Gaynor; John M Hickey
Journal:  Theor Appl Genet       Date:  2018-06-06       Impact factor: 5.699

4.  Optimizing Selection and Mating in Genomic Selection with a Look-Ahead Approach: An Operations Research Framework.

Authors:  Saba Moeinizade; Guiping Hu; Lizhi Wang; Patrick S Schnable
Journal:  G3 (Bethesda)       Date:  2019-07-09       Impact factor: 3.154

5.  Boosting Genetic Gain in Allogamous Crops via Speed Breeding and Genomic Selection.

Authors:  Abdulqader Jighly; Zibei Lin; Luke W Pembleton; Noel O I Cogan; German C Spangenberg; Ben J Hayes; Hans D Daetwyler
Journal:  Front Plant Sci       Date:  2019-11-15       Impact factor: 5.753

6.  Improving Short- and Long-Term Genetic Gain by Accounting for Within-Family Variance in Optimal Cross-Selection.

Authors:  Antoine Allier; Christina Lehermeier; Alain Charcosset; Laurence Moreau; Simon Teyssèdre
Journal:  Front Genet       Date:  2019-10-29       Impact factor: 4.599

7.  Simulation-based optimization of genomic selection scheme for accelerating genetic gain while preventing inbreeding depression in onion breeding.

Authors:  Daisuke Sekine; Shiori Yabe
Journal:  Breed Sci       Date:  2020-11-17       Impact factor: 2.086

8.  Impact of Mislabeling on Genomic Selection in Cassava Breeding.

Authors:  Shiori Yabe; Hiroyoshi Iwata; Jean-Luc Jannink
Journal:  Crop Sci       Date:  2018-06-21       Impact factor: 2.319

9.  Diversity and Genome Analysis of Australian and Global Oilseed Brassica napus L. Germplasm Using Transcriptomics and Whole Genome Re-sequencing.

Authors:  M Michelle Malmberg; Fan Shi; German C Spangenberg; Hans D Daetwyler; Noel O I Cogan
Journal:  Front Plant Sci       Date:  2018-04-19       Impact factor: 5.753

10.  Effects of Different Strategies for Exploiting Genomic Selection in Perennial Ryegrass Breeding Programs.

Authors:  Hadi Esfandyari; Dario Fè; Biructawit Bekele Tessema; Lucas L Janss; Just Jensen
Journal:  G3 (Bethesda)       Date:  2020-10-05       Impact factor: 3.154

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