Evidence map›Paper›PMID 32393177›Full record

ArticleBMC genomics2020

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

Antoine Allier, Simon Teyssèdre, Christina Lehermeier, Laurence Moreau, Alain Charcosset

Open access · goldAbstract read
In one paragraph

Article in BMC genomics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers.

0numbers the graph read from it
0cells of the map it votes in
40citing papers in PubMed
8.3field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

40 citing papers in PubMed, 97 citations in OpenAlex.

  1. Review
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  3. Restructuring breeding programs 1: Integration of diversity.Genetics, selection, evolution : GSE · 2026
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  6. Uncovering natural variation inFrontiers in plant science · 2026
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  8. Rapid cycling genomic selection in maize landraces: a step toward closing the yield gap.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025
    Article
  9. Article
  10. Article
  11. Review
  12. Rapid cycling genomic selection in maize landraces.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025
    Article
  13. Article
  14. Article
  15. Review
  16. Article
  17. Article
  18. Article
  19. Article
  20. Genetic gains in IRRI's rice salinity breeding and elite panel development as a future breeding resource.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2024
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 1 institution in 2 countries.

Antoine AllierGQE - Le Moulon, INRAE, University Paris-Sud, CNRS, AgroParisTech, Université Paris-Saclay, 91190, Gif-sur-Yvette, France. allierantoine@gmail.com.ORCID http://orcid.org/0000-0001-6578-1715
Simon TeyssèdreRAGT2n, Statistical Genetics Unit, 12510, Druelle, France.
Christina LehermeierRAGT2n, Statistical Genetics Unit, 12510, Druelle, France.
Laurence MoreauGQE - Le Moulon, INRAE, University Paris-Sud, CNRS, AgroParisTech, Université Paris-Saclay, 91190, Gif-sur-Yvette, France.
Alain CharcossetGQE - Le Moulon, INRAE, University Paris-Sud, CNRS, AgroParisTech, Université Paris-Saclay, 91190, Gif-sur-Yvette, France. alain.charcosset@inrae.fr.
Centre National de la Recherche Scientifique · FR

Funding

ANRT CIFRE 2016/1281
6 · The paper itself

Abstract

backgroundThe narrow genetic base of elite germplasm compromises long-term genetic gain and increases the vulnerability to biotic and abiotic stresses in unpredictable environmental conditions. Therefore, an efficient strategy is required to broaden the genetic base of commercial breeding programs while not compromising short-term variety release. Optimal cross selection aims at identifying the optimal set of crosses that balances the expected genetic value and diversity. We propose to consider genomic selection and optimal cross selection to recurrently improve genetic resources (i.e. pre-breeding), to bridge the improved genetic resources with elites (i.e. bridging), and to manage introductions into the elite breeding population. Optimal cross selection is particularly adapted to jointly identify bridging, introduction and elite crosses to ensure an overall consistency of the genetic base broadening strategy.

resultsWe compared simulated breeding programs introducing donors with different performance levels, directly or indirectly after bridging. We also evaluated the effect of the training set composition on the success of introductions. We observed that with recurrent introductions of improved donors, it is possible to maintain the genetic diversity and increase mid- and long-term performances with only limited penalty at short-term. Considering a bridging step yielded significantly higher mid- and long-term genetic gain when introducing low performing donors. The results also suggested to consider marker effects estimated with a broad training population including donor by elite and elite by elite progeny to identify bridging, introduction and elite crosses.

conclusionResults of this study provide guidelines on how to harness polygenic variation present in genetic resources to broaden elite germplasm.

Indexed as

Models, GeneticBreedingGenetic VariationPrincipal Component AnalysisSelection, GeneticGenetic base broadeningGenetic diversityGenetic resourcesGenomic predictionOptimal cross selectionPre-breeding

Identifiers

PMID32393177
PMCPMC7216646
OpenAlexW3025086961

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.