Literature DB >> 27913832

General and specific combining abilities in a maize (Zea mays L.) test-cross hybrid panel: relative importance of population structure and genetic divergence between parents.

A Larièpe1,2, L Moreau1, J Laborde3, C Bauland1, S Mezmouk2, L Décousset2, T Mary-Huard1, J B Fiévet1, A Gallais1, P Dubreuil2, A Charcosset4.   

Abstract

KEY MESSAGE: General and specific combining abilities of maize hybrids between 288 inbred lines and three tester lines were highly related to population structure and genetic distance inferred from SNP data. Many studies have attempted to provide reliable and quick methods to identify promising parental lines and combinations in hybrid breeding programs. Since the 1950s, maize germplasm has been organized into heterotic groups to facilitate the exploitation of heterosis. Molecular markers have proven efficient tools to address the organization of genetic diversity and the relationship between lines or populations. The aim of the present work was to investigate to what extent marker-based evaluations of population structure and genetic distance may account for general (GCA) and specific (SCA) combining ability components in a population composed of 800 inter and intra-heterotic group hybrids obtained by crossing 288 inbred lines and three testers. Our results illustrate a strong effect of groups identified by population structure analysis on both GCA and SCA components. Including genetic distance between parental lines of hybrids in the model leads to a significant decrease of SCA variance component and an increase in GCA variance component for all the traits. The latter suggests that this approach can be efficient to better estimate the potential combining ability of inbred lines when crossed with unrelated lines, and limits the consequences of tester choice. Significant residual GCA and SCA variance components of models taking into account structure and/or genetic distance highlight the variation available for breeding programs within structure groups.

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Year:  2016        PMID: 27913832     DOI: 10.1007/s00122-016-2822-z

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


  31 in total

1.  Inference of population structure using multilocus genotype data.

Authors:  J K Pritchard; M Stephens; P Donnelly
Journal:  Genetics       Date:  2000-06       Impact factor: 4.562

2.  Genetic diversity for restriction fragment length polymorphisms and heterosis for two diallel sets of maize inbreds.

Authors:  A E Melchinger; M Lee; K R Lamkey; A R Hallauer; W L Woodman
Journal:  Theor Appl Genet       Date:  1990-10       Impact factor: 5.699

3.  Genetic diversity among progenitors and elite lines from the Iowa Stiff Stalk Synthetic (BSSS) maize population: comparison of allozyme and RFLP data.

Authors:  M M Messmer; A E Melchinger; M Lee; W L Woodman; E A Lee; K R Lamkey
Journal:  Theor Appl Genet       Date:  1991-11       Impact factor: 5.699

4.  Relationship between single-cross performance and molecular marker heterozygosity.

Authors:  R Bernardo
Journal:  Theor Appl Genet       Date:  1992-03       Impact factor: 5.699

5.  Maize adaptation to temperate climate: relationship between population structure and polymorphism in the Dwarf8 gene.

Authors:  Létizia Camus-Kulandaivelu; Jean-Baptiste Veyrieras; Delphine Madur; Valérie Combes; Marie Fourmann; Stéphanie Barraud; Pierre Dubreuil; Brigitte Gouesnard; Domenica Manicacci; Alain Charcosset
Journal:  Genetics       Date:  2006-01-16       Impact factor: 4.562

6.  Key impact of Vgt1 on flowering time adaptation in maize: evidence from association mapping and ecogeographical information.

Authors:  Sébastien Ducrocq; Delphine Madur; Jean-Baptiste Veyrieras; Létizia Camus-Kulandaivelu; Monika Kloiber-Maitz; Thomas Presterl; Milena Ouzunova; Domenica Manicacci; Alain Charcosset
Journal:  Genetics       Date:  2008-04       Impact factor: 4.562

7.  Effect of population structure corrections on the results of association mapping tests in complex maize diversity panels.

Authors:  Sofiane Mezmouk; Pierre Dubreuil; Mickaël Bosio; Laurent Décousset; Alain Charcosset; Sébastien Praud; Brigitte Mangin
Journal:  Theor Appl Genet       Date:  2011-01-11       Impact factor: 5.699

8.  Breeding maize as biogas substrate in Central Europe: I. Quantitative-genetic parameters for testcross performance.

Authors:  Christoph Grieder; Baldev S Dhillon; Wolfgang Schipprack; Albrecht E Melchinger
Journal:  Theor Appl Genet       Date:  2011-12-13       Impact factor: 5.699

9.  Evaluation of Hbr (MITE) markers for assessment of genetic relationships among maize ( Zea mays L.) inbred lines.

Authors:  A M Casa; S E Mitchell; O S Smith; J C Register; S R Wessler; S Kresovich
Journal:  Theor Appl Genet       Date:  2002-01       Impact factor: 5.699

10.  Genomic BLUP including additive and dominant variation in purebreds and F1 crossbreds, with an application in pigs.

Authors:  Zulma G Vitezica; Luis Varona; Jean-Michel Elsen; Ignacy Misztal; William Herring; Andrès Legarra
Journal:  Genet Sel Evol       Date:  2016-01-29       Impact factor: 4.297

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  12 in total

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Authors:  Saurabh Singh; S S Dey; Reeta Bhatia; Raj Kumar; Kanika Sharma; T K Behera
Journal:  PLoS One       Date:  2019-08-19       Impact factor: 3.240

2.  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

3.  Testcross performance of doubled haploid lines from European flint maize landraces is promising for broadening the genetic base of elite germplasm.

Authors:  Pedro C Brauner; Wolfgang Schipprack; H Friedrich Utz; Eva Bauer; Manfred Mayer; Chris-Carolin Schön; Albrecht E Melchinger
Journal:  Theor Appl Genet       Date:  2019-03-15       Impact factor: 5.699

4.  Genomic prediction with a maize collaborative panel: identification of genetic resources to enrich elite breeding programs.

Authors:  Antoine Allier; Simon Teyssèdre; Christina Lehermeier; Alain Charcosset; Laurence Moreau
Journal:  Theor Appl Genet       Date:  2019-10-08       Impact factor: 5.699

5.  Omics-based hybrid prediction in maize.

Authors:  Matthias Westhues; Tobias A Schrag; Claas Heuer; Georg Thaller; H Friedrich Utz; Wolfgang Schipprack; Alexander Thiemann; Felix Seifert; Anita Ehret; Armin Schlereth; Mark Stitt; Zoran Nikoloski; Lothar Willmitzer; Chris C Schön; Stefan Scholten; Albrecht E Melchinger
Journal:  Theor Appl Genet       Date:  2017-06-24       Impact factor: 5.699

6.  Dissecting the Genetic Basis Underlying Combining Ability of Plant Height Related Traits in Maize.

Authors:  Zhiqiang Zhou; Chaoshu Zhang; Xiaohuan Lu; Liwei Wang; Zhuanfang Hao; Mingshun Li; Degui Zhang; Hongjun Yong; Hanyong Zhu; Jianfeng Weng; Xinhai Li
Journal:  Front Plant Sci       Date:  2018-08-02       Impact factor: 5.753

7.  Use of F2 Bulks in Training Sets for Genomic Prediction of Combining Ability and Hybrid Performance.

Authors:  Frank Technow
Journal:  G3 (Bethesda)       Date:  2019-05-07       Impact factor: 3.154

8.  Bayesian analysis and prediction of hybrid performance.

Authors:  Filipe Couto Alves; Ítalo Stefanine Correa Granato; Giovanni Galli; Danilo Hottis Lyra; Roberto Fritsche-Neto; Gustavo de Los Campos
Journal:  Plant Methods       Date:  2019-02-07       Impact factor: 4.993

9.  Assessment of heterosis based on parental genetic distance estimated with SSR and SNP markers in upland cotton (Gossypium hirsutum L.).

Authors:  Xiaoli Geng; Yujie Qu; Yinhua Jia; Shoupu He; Zhaoe Pan; Liru Wang; Xiongming Du
Journal:  BMC Genomics       Date:  2021-02-18       Impact factor: 3.969

10.  Optimizing Genomic-Enabled Prediction in Small-Scale Maize Hybrid Breeding Programs: A Roadmap Review.

Authors:  Roberto Fritsche-Neto; Giovanni Galli; Karina Lima Reis Borges; Germano Costa-Neto; Filipe Couto Alves; Felipe Sabadin; Danilo Hottis Lyra; Pedro Patric Pinho Morais; Luciano Rogério Braatz de Andrade; Italo Granato; Jose Crossa
Journal:  Front Plant Sci       Date:  2021-07-01       Impact factor: 5.753

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