Evidence map›Paper›PMID 41032152›Full record

ArticleTAG. Theoretical and applied genetics. Theoretische und angewandte Genetik2025

Genomic prediction-aided incorporation of genetic resources into elite breeding: lessons from a collaborative multiparental design in flint maize.

Dimitri Sanchez, Sarah Ben Sadoun, Tristan Mary-Huard, Cyril Bauland, Carine Palaffre, Bernard Lagardère, Delphine Madur, Valérie Combes, Stéphane Melkior, Laurent Bettinger and 3 more

Abstract read
In one paragraph

Article in TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

13 authors.

Dimitri SanchezUniversité Paris-Saclay, INRAE, CNRS, AgroParisTech, Génétique Quantitative et Evolution - Le Moulon, 91190, Gif-sur-Yvette, France.ORCID http://orcid.org/0000-0002-5526-2417
Sarah Ben SadounUniversité Paris-Saclay, INRAE, CNRS, AgroParisTech, Génétique Quantitative et Evolution - Le Moulon, 91190, Gif-sur-Yvette, France.ORCID http://orcid.org/0000-0001-8110-0422
Tristan Mary-HuardUniversité Paris-Saclay, INRAE, CNRS, AgroParisTech, Génétique Quantitative et Evolution - Le Moulon, 91190, Gif-sur-Yvette, France.ORCID http://orcid.org/0000-0002-3839-9067
Cyril BaulandUniversité Paris-Saclay, INRAE, CNRS, AgroParisTech, Génétique Quantitative et Evolution - Le Moulon, 91190, Gif-sur-Yvette, France.ORCID https://orcid.org/0000-0001-9916-2744
Carine PalaffreUE 0394 SMH, INRAE, 2297 Route de L'INRA, 40390, Saint-Martin-de-Hinx, France.
Bernard LagardèreUE 0394 SMH, INRAE, 2297 Route de L'INRA, 40390, Saint-Martin-de-Hinx, France.
Delphine MadurUniversité Paris-Saclay, INRAE, CNRS, AgroParisTech, Génétique Quantitative et Evolution - Le Moulon, 91190, Gif-sur-Yvette, France.
Valérie CombesUniversité Paris-Saclay, INRAE, CNRS, AgroParisTech, Génétique Quantitative et Evolution - Le Moulon, 91190, Gif-sur-Yvette, France.
Stéphane MelkiorRAGT2n, 12510, Druelle, France.
Laurent BettingerLIDEA FRANCE, Avenue Gaston Phoebus, 64230, Lescar, France.
Alain MurigneuxLimagrain Europe, 28 Route d'Ennezat, 63720, Chappes, France.
Laurence MoreauUniversité Paris-Saclay, INRAE, CNRS, AgroParisTech, Génétique Quantitative et Evolution - Le Moulon, 91190, Gif-sur-Yvette, France.ORCID http://orcid.org/0000-0002-7195-1327
Alain CharcossetUniversité Paris-Saclay, INRAE, CNRS, AgroParisTech, Génétique Quantitative et Evolution - Le Moulon, 91190, Gif-sur-Yvette, France. alain.charcosset@inrae.fr.ORCID http://orcid.org/0000-0001-6125-503X

Funding

ANRT 2019/1019Promaïs ValRG
6 · The paper itself

Abstract

key messageA public private cooperative mating design between elite maize inbred lines and diversity donors shows that genomic prediction holds great promise to improve the use of genetic resources. Genetic diversity is essential for plant breeding, enabling long-term gains and adaptation to climate change and new agronomical practices. Breeders can access diverse genetic resources to enhance elite germplasm and introduce new favorable variations. The limited performance of genetic resources may hamper their use. To overcome this, a bridging population can be implemented to evaluate and select progenies from crosses between diversity donors and elite lines before their introduction in breeding programs. The choice of such crosses can be dealt with the usefulness criterion (UC), which determines its ability to produce transgressive individuals. This paper investigates the use of genome-wide marker effects to predict (i) the performance of individuals derived from crosses between donors and elite lines and (ii) the UC of crosses not observed yet. It also compares donor introduction strategies based on the UC or the H criterion, which considers the genome-wide donor-elite complementarity. We used a flint maize collaborative multi-parental BC1-S2 population, consisting in materials from six breeding companies and one public institute crossed to different donors. The 20 crosses had contrasted means and genetic variances, and most of them presented transgressive individuals above the elite parent. Results emphasize the importance of half-siblings derived from the elite line parent of the predicted cross to efficiently predict progeny performances or the UC. They also showed that using the H criterion appears promising to select iteratively donors that best complement initial elite materials. The paper concludes with guidelines for implementing a bridging population using genome-wide marker-based predictions.

Indexed as

Genome, PlantGenomicsPlant BreedingZea maysCrosses, GeneticGenetic MarkersGenetic VariationGenotypePhenotypeGenetic Markers

Identifiers

PMID41032152
PMCPMC12488772

What OpenQuestion holds

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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.