ArticleTAG. Theoretical and applied genetics. Theoretische und angewandte Genetik2017
Omics-based hybrid prediction in maize.
Article in TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 71 papers.
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Who cites it
71 citing papers in PubMed.
- Research progress on genomic selection breeding technology for crops.Protoplasma · 2026Review
- Next-Generation Genotyping: Innovations Driving Plant Genomic Improvement.Life (Basel, Switzerland) · 2026Review
- Integrated Transcriptomic and Metabolomic Analysis Reveals Metabolic Heterosis in Hybrid Tea Plants (Genes · 2025Article
- Decades' progress and prospects on maize functional genomics and molecular breeding.Science China. Life sciences · 2025Review
- Comparing statistical 'phenomic prediction' models for remote-sensing-based phenotyping of maize susceptibility to common rust.Plant phenomics (Washington, D.C.) · 2025Article
- Quantitative Insights into the Genetic Mechanisms of Crop Heterosis.Advanced genetics (Hoboken, N.J.) · 2025Review
- Assessment of genomic prediction capabilities of transcriptome data in a barley multi-parent RIL population.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025Article
- SPDC-HG: An accelerator of genomic hybrid breeding in maize.Plant biotechnology journal · 2025Article
- Metabolic marker-assisted genomic prediction improves hybrid breeding.Plant communications · 2025Article
- Incorporating gene expression and environment for genomic prediction in wheat.Frontiers in plant science · 2025Article
- Article
- Integrating Gene Expression Data into Single-Step Method (ssBLUP) Improves Genomic Prediction Accuracy for Complex Traits of Duroc × Erhualian FCurrent issues in molecular biology · 2024Article
- Feature engineering and parameter tuning: improving phenomic prediction ability in multi-environmental durum wheat breeding trials.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2024Article
- High-dimensional multi-omics measured in controlled conditions are useful for maize platform and field trait predictions.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2024Article
- Genomic and phenomic predictions help capture low-effect alleles promoting seed germination in oilseed rape in addition to QTL analyses.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2024Article
- Optimizing selection based on BLUPs or BLUEs in multiple sets of genotypes differing in their population parameters.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2024Article
- Multi-omics assists genomic prediction of maize yield with machine learning approaches.Molecular breeding : new strategies in plant improvement · 2024Article
- Importance of genetic architecture in marker selection decisions for genomic prediction.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2023Article
- Genomic prediction in hybrid breeding: II. Reciprocal recurrent genomic selection with full-sib and half-sib families.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2023Article
- Genomic prediction in hybrid breeding: I. Optimizing the training set design.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2023Article
11 more citing papers are in PubMed but not listed here.
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16 authors.
Funding
Abstract
key messageComplementing genomic data with other "omics" predictors can increase the probability of success for predicting the best hybrid combinations using complex agronomic traits. Accurate prediction of traits with complex genetic architecture is crucial for selecting superior candidates in animal and plant breeding and for guiding decisions in personalized medicine. Whole-genome prediction has revolutionized these areas but has inherent limitations in incorporating intricate epistatic interactions. Downstream "omics" data are expected to integrate interactions within and between different biological strata and provide the opportunity to improve trait prediction. Yet, predicting traits from parents to progeny has not been addressed by a combination of "omics" data. Here, we evaluate several "omics" predictors-genomic, transcriptomic and metabolic data-measured on parent lines at early developmental stages and demonstrate that the integration of transcriptomic with genomic data leads to higher success rates in the correct prediction of untested hybrid combinations in maize. Despite the high predictive ability of genomic data, transcriptomic data alone outperformed them and other predictors for the most complex heterotic trait, dry matter yield. An eQTL analysis revealed that transcriptomic data integrate genomic information from both, adjacent and distant sites relative to the expressed genes. Together, these findings suggest that downstream predictors capture physiological epistasis that is transmitted from parents to their hybrid offspring. We conclude that the use of downstream "omics" data in prediction can exploit important information beyond structural genomics for leveraging the efficiency of hybrid breeding.
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