ArticleFrontiers in genetics2020
Strategies Using Genomic Selection to Increase Genetic Gain in Breeding Programs for Wheat.
Article in Frontiers in genetics, 2020. 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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Who cites it
29 citing papers in PubMed.
- Efficiency under epistasis of haplotype-based genomic selection for pure line breeding.Heredity · 2026Article
- Integrating genomic selection into potato breeding: A comparison of genotyping platforms and cross-environmental predictions.The plant genome · 2026Article
- Progeny-based genomic selection reveals untapped genetic potential in an underutilized medicinal plant,Molecular breeding : new strategies in plant improvement · 2026Article
- Integrating genomic predictions into an applied Central European wheat breeding program.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026Article
- Genomic prediction for grain yield and biotic stress resistance in field pea (Frontiers in plant science · 2026Article
- Optimizing genomic selection models for wheat breeding under contrasting water regimes in a mediterranean environment.Plant methods · 2025Article
- Harnessing big data for enhanced genome-wide prediction in winter wheat breeding.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025Article
- AdaptiveGS: an explainable genomic selection framework based on adaptive stacking ensemble machine learning.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025Article
- Whole-genome resequencing of a global collection of Napier grass (Cenchrus purpureus) to explore global population structure and QTL governing yield and feed quality traits.G3 (Bethesda, Md.) · 2025Article
- Enhancing prediction accuracy of key biomass partitioning traits in wheat using multi-kernel genomic prediction models integrating secondary traits and environmental covariates.The plant genome · 2025Article
- Genetic analysis of predicted vegetative biomass and biomass-related traits from digital phenotyping of strawberry.The plant genome · 2025Article
- Optimizing the selection of quantitative traits in plant breeding using simulation.Frontiers in plant science · 2025Review
- Genome-wide association study of biological nitrogen fixation traits in mini-core cowpea germplasm.PloS one · 2025Article
- ADAM-multi: software to simulate complex breeding programs for animals and plants with different ploidy levels and generalized genotypic effect models to account for multiple alleles.Frontiers in genetics · 2025Article
- Deciphering the genetic basis of novel traits that discriminate useful and non-useful biomass to enhance harvest index in wheat.The plant genome · 2024Article
- Leveraging genomic prediction to surpass current yield gains in spring barley.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2024Article
- Evaluation of deep learning for predicting rice traits using structural and single-nucleotide genomic variants.Plant methods · 2024Article
- Use of simulation to optimize a sweet corn breeding program: implementing genomic selection and doubled haploid technology.G3 (Bethesda, Md.) · 2024Article
- Breeding in bread-making wheat varieties for Mediterranean climate: the need to get resilient varieties.Frontiers in nutrition · 2024Article
- Stochastic simulation to optimize rice breeding at IRRI.Frontiers in plant science · 2024Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Conventional wheat-breeding programs involve crossing parental lines and subsequent selfing of the offspring for several generations to obtain inbred lines. Such a breeding program takes more than 8 years to develop a variety. Although wheat-breeding programs have been running for many years, genetic gain has been limited. However, the use of genomic information as selection criterion can increase selection accuracy and that would contribute to increased genetic gain. The main objective of this study was to quantify the increase in genetic gain by implementing genomic selection in traditional wheat-breeding programs. In addition, we investigated the effect of genetic correlation between different traits on genetic gain. A stochastic simulation was used to evaluate wheat-breeding programs that run simultaneously for 25 years with phenotypic or genomic selection. Genetic gain and genetic variance of wheat-breeding program based on phenotypes was compared to the one with genomic selection. Genetic gain from the wheat-breeding program based on genomic estimated breeding values (GEBVs) has tripled compared to phenotypic selection. Genomic selection is a promising strategy for improving genetic gain in wheat-breeding programs.
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