ArticleGenetics2017
Reciprocal Genetics: Identifying QTL for General and Specific Combining Abilities in Hybrids Between Multiparental Populations from Two Maize (
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Article in Genetics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
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29citing papers in PubMed
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Who cites it
29 citing papers in PubMed.
- SPDC-HG: An accelerator of genomic hybrid breeding in maize.Plant biotechnology journal · 2025Article
- Integrative mapping in large inbred and hybrid association panels along with an FTAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025Article
- Using phenomic selection to predict hybrid values with NIR spectra measured on the parental lines: proof of concept on maize.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025Article
- Portability of genomic predictions trained on sparse factorial designs across two maize silage breeding cycles.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2024Article
- Genomic prediction in multi-environment trials in maize using statistical and machine learning methods.Scientific reports · 2024Article
- Genomic prediction for the Germplasm Enhancement of Maize project.The plant genome · 2022Article
- SeSAM: software for automatic construction of order-robust linkage maps.BMC bioinformatics · 2022Article
- statgenMPP: an R package implementing an IBD-based mixed model approach for QTL mapping in a wide range of multi-parent populations.Bioinformatics (Oxford, England) · 2022Article
- Genomic prediction of hybrid performance: comparison of the efficiency of factorial and tester designs used as training sets in a multiparental connected reciprocal design for maize silage.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2022Article
- Genetic mapping and prediction of flowering time and plant height in a maize Stiff Stalk MAGIC population.Genetics · 2022Article
- Efficient ReML inference in variance component mixed models using a Min-Max algorithm.PLoS computational biology · 2022Article
- An IBD-based mixed model approach for QTL mapping in multiparental populations.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2021Article
- Article
- Identifying quantitative trait loci for the general combining ability of yield-relevant traits in maize.Breeding science · 2021Article
- Comparative proteomic analysis reveals that the Heterosis of two maize hybrids is related to enhancement of stress response and photosynthesis respectively.BMC plant biology · 2021Article
- Genome-wide dissection of hybridization for fiber quality- and yield-related traits in upland cotton.The Plant journal : for cell and molecular biology · 2020Article
- Genetic basis of phenotypic plasticity and genotype × environment interactions in a multi-parental tomato population.Journal of experimental botany · 2020Article
- Accounting for Group-Specific Allele Effects and Admixture in Genomic Predictions: Theory and Experimental Evaluation in Maize.Genetics · 2020Article
- Revisiting hybrid breeding designs using genomic predictions: simulations highlight the superiority of incomplete factorials between segregating families over topcross designs.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2020Article
- Dominance Effects and Functional Enrichments Improve Prediction of Agronomic Traits in Hybrid Maize.Genetics · 2020Article
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Authors and funding
13 authors.
Héloïse GiraudGénétique Quantitative et Evolution-Le Moulon, Institut National de la Recherche Agronomique, Université Paris-Sud, Centre National de la Recherche Scientifique, AgroParisTech, Université Paris-Saclay, F-91190 Gif-sur-Yvette, France.
Cyril BaulandGénétique Quantitative et Evolution-Le Moulon, Institut National de la Recherche Agronomique, Université Paris-Sud, Centre National de la Recherche Scientifique, AgroParisTech, Université Paris-Saclay, F-91190 Gif-sur-Yvette, France.
Matthieu FalqueGénétique Quantitative et Evolution-Le Moulon, Institut National de la Recherche Agronomique, Université Paris-Sud, Centre National de la Recherche Scientifique, AgroParisTech, Université Paris-Saclay, F-91190 Gif-sur-Yvette, France.
Delphine MadurGénétique Quantitative et Evolution-Le Moulon, Institut National de la Recherche Agronomique, Université Paris-Sud, Centre National de la Recherche Scientifique, AgroParisTech, Université Paris-Saclay, F-91190 Gif-sur-Yvette, France.
Valérie CombesGénétique Quantitative et Evolution-Le Moulon, Institut National de la Recherche Agronomique, Université Paris-Sud, Centre National de la Recherche Scientifique, AgroParisTech, Université Paris-Saclay, F-91190 Gif-sur-Yvette, France.
Philippe JaminGénétique Quantitative et Evolution-Le Moulon, Institut National de la Recherche Agronomique, Université Paris-Sud, Centre National de la Recherche Scientifique, AgroParisTech, Université Paris-Saclay, F-91190 Gif-sur-Yvette, France.
Cécile MonteilGénétique Quantitative et Evolution-Le Moulon, Institut National de la Recherche Agronomique, Université Paris-Sud, Centre National de la Recherche Scientifique, AgroParisTech, Université Paris-Saclay, F-91190 Gif-sur-Yvette, France.
Jacques LabordeUnité Expérimentale 0394 SMH Maïs, Institut National de la Recherche Agronomique, F-40390 Saint-Martin-de-Hinx, France.
Carine PalaffreUnité Expérimentale 0394 SMH Maïs, Institut National de la Recherche Agronomique, F-40390 Saint-Martin-de-Hinx, France.
Antoine GaillardMaïsadour Semences S.A., F-40001 Mont-de-Marsan, France.
Philippe BlanchardEuralis Semences, F-31700 Mondonville, France.
Alain CharcossetGénétique Quantitative et Evolution-Le Moulon, Institut National de la Recherche Agronomique, Université Paris-Sud, Centre National de la Recherche Scientifique, AgroParisTech, Université Paris-Saclay, F-91190 Gif-sur-Yvette, France.
Laurence MoreauGénétique Quantitative et Evolution-Le Moulon, Institut National de la Recherche Agronomique, Université Paris-Sud, Centre National de la Recherche Scientifique, AgroParisTech, Université Paris-Saclay, F-91190 Gif-sur-Yvette, France laurence.moreau@inra.fr.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Several plant and animal species of agricultural importance are commercialized as hybrids to take advantage of the heterosis phenomenon. Understanding the genetic architecture of hybrid performances is therefore of key importance. We developed two multiparental maize (
Indexed as
Hybridization, GeneticModels, GeneticQuantitative Trait LociBiomassGenes, DominantGenetic VariationInbreedingQuantitative Trait, HeritableZea maysadditivitydominancehybridsMPPmultiparental populationsQTL detectionsilage maize
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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.