Literature DB >> 27389871

Optimum breeding strategies using genomic selection for hybrid breeding in wheat, maize, rye, barley, rice and triticale.

Jose J Marulanda1, Xuefei Mi2, Albrecht E Melchinger1, Jian-Long Xu2, T Würschum3, C Friedrich H Longin4.   

Abstract

KEY MESSAGE: A breeding strategy with moderate nursery selection followed by genomic selection and one-stage phenotypic selection maximizes annual selection gain for grain yield across a wide range of hybrid breeding scenarios. Genomic selection (GS) is a promising method for the selection of quantitatively inherited traits but its most effective implementation in routine hybrid breeding schemes requires further research. We compared five breeding strategies and varied their available budget, the costs for doubled haploid (DH) line and hybrid seed production as well as variance components for grain yield in a wide range. In contrast to previous studies, we included a nursery selection for disease resistance just before GS on grain yield. The breeding strategy GSrapid with moderate nursery selection followed by one stage GS and one final stage with phenotypic selection on grain yield had the highest annual selection gain across all strategies, budgets, costs and variance components considered and we, therefore, highly recommend its use in hybrid breeding of cereals. Although selecting on traits not correlated with grain yield in the observation nursery, this selection reduced the selection gain of grain yield, especially in the breeding schemes with GS and for selected fractions smaller than 0.3. Owing to the very high number of test candidates entering breeding strategies with GS, the costs for DH line production had a larger impact on the annual selection gain than the hybrid seed production costs. The optimum allocation of test resources maximizing annual selection gain in classical two-stage phenotypic selection on grain yield and for the recommended breeding strategy GSrapid is finally explored for maize, wheat, rye, barley, rice and triticale.

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Year:  2016        PMID: 27389871     DOI: 10.1007/s00122-016-2748-5

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


  24 in total

Review 1.  Breeding schemes for the implementation of genomic selection in wheat (Triticum spp.).

Authors:  Filippo M Bassi; Alison R Bentley; Gilles Charmet; Rodomiro Ortiz; Jose Crossa
Journal:  Plant Sci       Date:  2015-09-06       Impact factor: 4.729

2.  Genomic selection in a commercial winter wheat population.

Authors:  Sang He; Albert Wilhelm Schulthess; Vilson Mirdita; Yusheng Zhao; Viktor Korzun; Reiner Bothe; Erhard Ebmeyer; Jochen C Reif; Yong Jiang
Journal:  Theor Appl Genet       Date:  2016-01-08       Impact factor: 5.699

3.  Does genomic selection have a future in plant breeding?

Authors:  Elisabeth Jonas; Dirk-Jan de Koning
Journal:  Trends Biotechnol       Date:  2013-07-16       Impact factor: 19.536

4.  Optimum allocation of test resources and comparison of breeding strategies for hybrid wheat.

Authors:  C Friedrich H Longin; Xuefei Mi; Albrecht E Melchinger; Jochen C Reif; Tobias Würschum
Journal:  Theor Appl Genet       Date:  2014-08-08       Impact factor: 5.699

5.  Long-term perspective of hybrid versus line breeding in wheat based on quantitative genetic theory.

Authors:  C Friedrich H Longin; Jochen C Reif; Tobias Würschum
Journal:  Theor Appl Genet       Date:  2014-05-21       Impact factor: 5.699

6.  Genome-based prediction of maize hybrid performance across genetic groups, testers, locations, and years.

Authors:  Theresa Albrecht; Hans-Jürgen Auinger; Valentin Wimmer; Joseph O Ogutu; Carsten Knaak; Milena Ouzunova; Hans-Peter Piepho; Chris-Carolin Schön
Journal:  Theor Appl Genet       Date:  2014-04-11       Impact factor: 5.699

7.  Improved efficiency of doubled haploid generation in hexaploid triticale by in vitro chromosome doubling.

Authors:  Tobias Würschum; Matthew R Tucker; Jochen C Reif; Hans Peter Maurer
Journal:  BMC Plant Biol       Date:  2012-07-18       Impact factor: 4.215

8.  Economic aspects of implementing genomic evaluations in a pig sire line breeding scheme.

Authors:  Thierry Tribout; Catherine Larzul; Florence Phocas
Journal:  Genet Sel Evol       Date:  2013-10-15       Impact factor: 4.297

9.  Effectiveness of genomic prediction of maize hybrid performance in different breeding populations and environments.

Authors:  Vanessa S Windhausen; Gary N Atlin; John M Hickey; Jose Crossa; Jean-Luc Jannink; Mark E Sorrells; Babu Raman; Jill E Cairns; Amsal Tarekegne; Kassa Semagn; Yoseph Beyene; Pichet Grudloyma; Frank Technow; Christian Riedelsheimer; Albrecht E Melchinger
Journal:  G3 (Bethesda)       Date:  2012-11-01       Impact factor: 3.154

10.  The importance of phenotypic data analysis for genomic prediction - a case study comparing different spatial models in rye.

Authors:  Angela-Maria Bernal-Vasquez; Jens Möhring; Malthe Schmidt; Manfred Schönleben; Chris-Carolin Schön; Hans-Peter Piepho
Journal:  BMC Genomics       Date:  2014-08-04       Impact factor: 3.969

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  25 in total

1.  Applications of Doubled Haploids in Plant Breeding and Applied Research.

Authors:  Jens Weyen
Journal:  Methods Mol Biol       Date:  2021

2.  Evaluation of the genetic architecture and the potential of genomics-assisted breeding of quality traits in two large panels of durum wheat.

Authors:  M Rapp; A Sieber; Ebrahim Kazman; Willmar L Leiser; T Würschum; C F H Longin
Journal:  Theor Appl Genet       Date:  2019-03-18       Impact factor: 5.699

3.  Haploid male fertility and spontaneous chromosome doubling evaluated in a diallel and recurrent selection experiment in maize.

Authors:  Willem S Molenaar; Wolfgang Schipprack; Pedro C Brauner; Albrecht E Melchinger
Journal:  Theor Appl Genet       Date:  2019-05-06       Impact factor: 5.699

4.  Novel strategies for genomic prediction of untested single-cross maize hybrids using unbalanced historical data.

Authors:  K O G Dias; H P Piepho; L J M Guimarães; P E O Guimarães; S N Parentoni; M O Pinto; R W Noda; J V Magalhães; C T Guimarães; A A F Garcia; M M Pastina
Journal:  Theor Appl Genet       Date:  2019-11-22       Impact factor: 5.699

5.  Assessing the variation and genetic architecture of asparagine content in wheat: What can plant breeding contribute to a reduction in the acrylamide precursor?

Authors:  Matthias Rapp; Klaus Schwadorf; Willmar L Leiser; Tobias Würschum; C Friedrich H Longin
Journal:  Theor Appl Genet       Date:  2018-08-20       Impact factor: 5.699

6.  A deep convolutional neural network approach for predicting phenotypes from genotypes.

Authors:  Wenlong Ma; Zhixu Qiu; Jie Song; Jiajia Li; Qian Cheng; Jingjing Zhai; Chuang Ma
Journal:  Planta       Date:  2018-08-12       Impact factor: 4.116

7.  Genome-wide regression models considering general and specific combining ability predict hybrid performance in oilseed rape with similar accuracy regardless of trait architecture.

Authors:  Christian R Werner; Lunwen Qian; Kai P Voss-Fels; Amine Abbadi; Gunhild Leckband; Matthias Frisch; Rod J Snowdon
Journal:  Theor Appl Genet       Date:  2017-10-28       Impact factor: 5.699

8.  Genomic assisted selection for enhancing line breeding: merging genomic and phenotypic selection in winter wheat breeding programs with preliminary yield trials.

Authors:  Sebastian Michel; Christian Ametz; Huseyin Gungor; Batuhan Akgöl; Doru Epure; Heinrich Grausgruber; Franziska Löschenberger; Hermann Buerstmayr
Journal:  Theor Appl Genet       Date:  2016-11-08       Impact factor: 5.699

9.  Simultaneous improvement of grain yield and protein content in durum wheat by different phenotypic indices and genomic selection.

Authors:  M Rapp; V Lein; F Lacoudre; J Lafferty; E Müller; G Vida; V Bozhanova; A Ibraliu; P Thorwarth; H P Piepho; W L Leiser; T Würschum; C F H Longin
Journal:  Theor Appl Genet       Date:  2018-03-06       Impact factor: 5.699

10.  Genetic relationships and identification of core germplasm among rice photoperiod- and thermo-sensitive genic male sterile lines.

Authors:  Xianwen Zhang; Qiang He; Wuhan Zhang; Fu Shu; Weiping Wang; Zhizhou He; Hairong Xiong; Junhua Peng; Huafeng Deng
Journal:  BMC Plant Biol       Date:  2021-07-02       Impact factor: 4.215

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