Literature DB >> 30666392

Assessment of breeding programs sustainability: application of phenotypic and genomic indicators to a North European grain maize program.

Antoine Allier1,2, Simon Teyssèdre2, Christina Lehermeier2, Bruno Claustres2, Stéphane Maltese2, Stéphane Melkior2, Laurence Moreau1, Alain Charcosset3.   

Abstract

KEY MESSAGE: We review and propose easily implemented and affordable indicators to assess the genetic diversity and the potential of a breeding population and propose solutions for its long-term management. Successful plant breeding programs rely on balanced efforts between short-term goals to develop competitive cultivars and long-term goals to improve and maintain diversity in the genetic pool. Indicators of the sustainability of response to selection in breeding pools are of key importance in this context. We reviewed and proposed sets of indicators based on temporal phenotypic and genotypic data and applied them on an early maize grain program implying two breeding pools (Dent and Flint) selected in a reciprocal manner. Both breeding populations showed a significant positive genetic gain summing up to 1.43 qx/ha/year but contrasted evolutions of genetic variance. Advances in high-throughput genotyping permitted the identification of regions of low diversity, mainly localized in pericentromeric regions. Observed changes in genetic diversity were multiple, reflecting a complex breeding system. We estimated the impact of linkage disequilibrium (LD) and of allelic diversity on the additive genetic variance at a genome-wide and chromosome-wide scale. Consistently with theoretical expectation under directional selection, we found a negative contribution of LD to genetic variance, which was unevenly distributed between chromosomes. This suggests different chromosome selection histories and underlines the interest to recombine specific chromosome regions. All three sets of indicators valorize in house data and are easy to implement in the era of genomic selection in every breeding program.

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Year:  2019        PMID: 30666392     DOI: 10.1007/s00122-019-03280-w

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


  45 in total

1.  Prediction of total genetic value using genome-wide dense marker maps.

Authors:  T H Meuwissen; B J Hayes; M E Goddard
Journal:  Genetics       Date:  2001-04       Impact factor: 4.562

2.  Inferring the trajectory of genetic variance in the course of artificial selection.

Authors:  D Sorensen; R Fernando; D Gianola
Journal:  Genet Res       Date:  2001-02       Impact factor: 1.588

3.  Evolution in Mendelian Populations.

Authors:  S Wright
Journal:  Genetics       Date:  1931-03       Impact factor: 4.562

4.  Estimation of average heterozygosity and genetic distance from a small number of individuals.

Authors:  M Nei
Journal:  Genetics       Date:  1978-07       Impact factor: 4.562

5.  Temporal changes in allele frequencies in two European F(2) flint maize populations under modified recurrent full-sib selection.

Authors:  K C Falke; C Flachenecker; A E Melchinger; H-P Piepho; H P Maurer; M Frisch
Journal:  Theor Appl Genet       Date:  2007-02-16       Impact factor: 5.699

6.  Recent human effective population size estimated from linkage disequilibrium.

Authors:  Albert Tenesa; Pau Navarro; Ben J Hayes; David L Duffy; Geraldine M Clarke; Mike E Goddard; Peter M Visscher
Journal:  Genome Res       Date:  2007-03-09       Impact factor: 9.043

7.  Molecular population genetics and evolution.

Authors:  M Nei
Journal:  Front Biol       Date:  1975

8.  Impact of interpopulation divergence on additive and dominance variance in hybrid populations.

Authors:  J C Reif; F-M Gumpert; S Fischer; A E Melchinger
Journal:  Genetics       Date:  2007-05-16       Impact factor: 4.562

9.  Linkage disequilibrium in two European F(2) flint maize populations under modified recurrent full-sib selection.

Authors:  K C Falke; H P Maurer; A E Melchinger; H- P Piepho; C Flachenecker; M Frisch
Journal:  Theor Appl Genet       Date:  2007-04-28       Impact factor: 5.699

10.  Trends in population parameters and best linear unbiased prediction of progeny performance in a European F(2) maize population under modified recurrent full-sib selection.

Authors:  C Flachenecker; M Frisch; K C Falke; A E Melchinger
Journal:  Theor Appl Genet       Date:  2005-12-13       Impact factor: 5.699

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  5 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 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

3.  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

4.  Temporal and genomic analysis of additive genetic variance in breeding programmes.

Authors:  Letícia A de C Lara; Ivan Pocrnic; Thiago de P Oliveira; R Chris Gaynor; Gregor Gorjanc
Journal:  Heredity (Edinb)       Date:  2021-12-15       Impact factor: 3.821

5.  Optimized breeding strategies to harness genetic resources with different performance levels.

Authors:  Antoine Allier; Simon Teyssèdre; Christina Lehermeier; Laurence Moreau; Alain Charcosset
Journal:  BMC Genomics       Date:  2020-05-11       Impact factor: 3.969

  5 in total

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