ArticleHeredity2018
Metabolome-wide association studies for agronomic traits of rice.
Article in Heredity, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.
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Who cites it
20 citing papers in PubMed, 1 synthesis or guideline pooled it, 41 citations in OpenAlex.
- Multi-omics revolution to promote plant breeding efficiency.Frontiers in plant science · 2022Pooled it
- Climate change and crop resilience: harnessing metabolomics for predicting stress tolerance.The New phytologist · 2026Review
- METRIN-KG: A knowledge graph integrating plant metabolites, traits, and biotic interactions.GigaScience · 2026Article
- Integrating predictive models and GWAS to identify candidate loci and genes for agronomic traits in rice.Frontiers in plant science · 2026Article
- Responses and adaptations of plants to abiotic stress: transcriptional regulation of secondary metabolic pathways, metabolomics, and nanobiological approaches.Frontiers in genetics · 2026Review
- Metabolic marker-assisted genomic prediction improves hybrid breeding.Plant communications · 2025Article
- Yield-associated putative gene regulatory networks in Oryza sativa L. subsp. indica and their association with high-yielding genotypes.Molecular biology reports · 2022Article
- Analysis of chemotypes and their markers in leaves of core collections ofFrontiers in plant science · 2022Article
- Review
- Large-scale transcriptome sequencing in broiler chickens to identify candidate genes for breast muscle weight and intramuscular fat content.Genetics, selection, evolution : GSE · 2021Article
- Toward Integrated Multi-Omics Intervention: Rice Trait Improvement and Stress Management.Frontiers in plant science · 2021Review
- A Fast Multi-Locus Ridge Regression Algorithm for High-Dimensional Genome-Wide Association Studies.Frontiers in genetics · 2021Article
- Overcoming the Challenges to Enhancing Experimental Plant Biology With Computational Modeling.Frontiers in plant science · 2021Review
- Dissection of complex traits of tomato in the post-genome era.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2020Review
- Integrating transcriptome and metabolome reveals molecular networks involved in genetic and environmental variation in tobacco.DNA research : an international journal for rapid publication of reports on genes and genomes · 2020Article
- Metabolite database for root, tuber, and banana crops to facilitate modern breeding in understudied crops.The Plant journal : for cell and molecular biology · 2020Article
- Article
- Identification of optimal prediction models using multi-omic data for selecting hybrid rice.Heredity · 2019Article
- Dissecting the genetics underlying the relationship between protein content and grain yield in a large hybrid wheat population.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2019Article
- The Application of Multi-Locus GWAS for the Detection of Salt-Tolerance Loci in Rice.Frontiers in plant science · 2018Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Identification of trait-associated metabolites will advance the knowledge and understanding of the biosynthetic and catabolic pathways that are relevant to the complex traits of interest. In the past, the association between metabolites (treated as quantitative traits) and genetic variants (e.g., SNPs) has been extensively studied using metabolomic quantitative trait locus (mQTL) mapping. Nevertheless, the research on the association between metabolites with agronomic traits has been inadequate. In practice, the regular approaches for QTL mapping analysis may be adopted for metabolites-phenotypes association analysis due to the similarity in data structure of these two types of researches. In the study, we compared four regular QTL mapping approaches, i.e., simple linear regression (LR), linear mixed model (LMM), Bayesian analysis with spike-slab priors (Bayes B) and least absolute shrinkage and selection operator (LASSO), by testing their performances on the analysis of metabolome-phenotype associations. Simulation studies showed that LASSO had the higher power and lower false positive rate than the other three methods. We investigated the associations of 839 metobolites with five agronomic traits in a collection of 533 rice varieties. The results implied that a total of 25 metabolites were significantly associated with five agronomic traits. Literature search and bioinformatics analysis indicated that the identified 25 metabolites are significantly involved in some growth and development processes potentially related to agronomic traits. We also explored the predictability of agronomic traits based on the 839 metabolites through cross-validation, which showed that metabolomic prediction was efficient and its application in plant breeding has been justified.
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Registered trials
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.