ArticleScientific reports2016
Metabolic prediction of important agronomic traits in hybrid rice (Oryza sativa L.).
Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
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Who cites it
26 citing papers in PubMed, 45 citations in OpenAlex.
- Additive and Partially Dominant Effects from Genomic Variation Contribute to Rice Heterosis.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Integrating predictive models and GWAS to identify candidate loci and genes for agronomic traits in rice.Frontiers in plant science · 2026Article
- Structural Variations Contribute to Subspeciation and Yield Heterosis in Rice.Plant biotechnology journal · 2025Article
- Quantitative Insights into the Genetic Mechanisms of Crop Heterosis.Advanced genetics (Hoboken, N.J.) · 2025Review
- Morphological and metabolomics profiling of intraspecific Arabidopsis hybrids in relation to biomass heterosis.Scientific reports · 2023Article
- Relative importance of genotype, gene expression, and DNA methylation on complex traits in perennial ryegrass.The plant genome · 2022Article
- Integration of DNA Methylation and Transcriptome Data Improves Complex Trait Prediction inPlants (Basel, Switzerland) · 2022Article
- Can biochemical traits bridge the gap between genomics and plant performance? A study in rice under drought.Plant physiology · 2022Article
- Leveraging a graft collection to develop metabolome-based trait prediction for the selection of tomato rootstocks with enhanced salt tolerance.Horticulture research · 2022Article
- The metabolomic landscape of rice heterosis highlights pathway biomarkers for predicting complex phenotypes.Plant physiology · 2021Article
- Remote estimation of leaf area index (LAI) with unmanned aerial vehicle (UAV) imaging for different rice cultivars throughout the entire growing season.Plant methods · 2021Article
- Multi-omics-based prediction of hybrid performance in canola.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2021Article
- Incorporation of parental phenotypic data into multi-omic models improves prediction of yield-related traits in hybrid rice.Plant biotechnology journal · 2021Article
- The Contribution of Metabolomics to Systems Biology: Current Applications Bridging Genotype and Phenotype in Plant Science.Advances in experimental medicine and biology · 2021Article
- Genome-wide association study on metabolite accumulation in a wild barley NAM population reveals natural variation in sugar metabolism.PloS one · 2021Article
- Article
- Accurate Prediction of a Quantitative Trait Using the Genes Controlling the Trait for Gene-Based Breeding in Cotton.Frontiers in plant science · 2020Article
- Metabolome-based prediction of yield heterosis contributes to the breeding of elite rice.Life science alliance · 2020Article
- A metabolome-based core hybridisation strategy for the prediction of rice grain weight across environments.Plant biotechnology journal · 2019Article
- Efficient genetic value prediction using incomplete omics data.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2019Article
Corrections and comments
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Hybrid crops have contributed greatly to improvements in global food and fodder production over the past several decades. Nevertheless, the growing population and changing climate have produced food crises and energy shortages. Breeding new elite hybrid varieties is currently an urgent task, but present breeding procedures are time-consuming and labour-intensive. In this study, parental metabolic information was utilized to predict three polygenic traits in hybrid rice. A complete diallel cross population consisting of eighteen rice inbred lines was constructed, and the hybrids' plant height, heading date and grain yield per plant were predicted using 525 metabolites. Metabolic prediction models were built using the partial least square regression method, with predictive abilities ranging from 0.858 to 0.977 for the hybrid phenotypes, relative heterosis, and specific combining ability. Only slight changes in predictive ability were observed between hybrid populations, and nearly no changes were detected between reciprocal hybrids. The outcomes of prediction of the three highly polygenic traits demonstrated that metabolic prediction was an accurate (high predictive abilities) and efficient (unaffected by population genetic structures) strategy for screening promising superior hybrid rice. Exploitation of this pre-hybridization strategy may contribute to rice production improvement and accelerate breeding programs.
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