ArticleBMC genomics2009
Correlation exploration of metabolic and genomic diversity in rice.
Article in BMC genomics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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11 citing papers in PubMed.
- Lignans of Sesame (Molecules (Basel, Switzerland) · 2021Review
- FoodPro: A Web-Based Tool for Evaluating Covariance and Correlation NMR Spectra Associated with Food Processes.Metabolites · 2016Article
- Crop improvement using life cycle datasets acquired under field conditions.Frontiers in plant science · 2015Review
- Article
- Characterization of the natural variation in Arabidopsis thaliana metabolome by the analysis of metabolic distance.Metabolomics : Official journal of the Metabolomic Society · 2012Article
- Concentration of metabolites from low-density planktonic communities for environmental metabolomics using nuclear magnetic resonance spectroscopy.Journal of visualized experiments : JoVE · 2012Article
- ECOMICS: a web-based toolkit for investigating the biomolecular web in ecosystems using a trans-omics approach.PloS one · 2012Article
- Advances in omics and bioinformatics tools for systems analyses of plant functions.Plant & cell physiology · 2011Review
- Exploring molecular backgrounds of quality traits in rice by predictive models based on high-coverage metabolomics.BMC systems biology · 2011Article
- Metabolomic and functional genomic analyses reveal varietal differences in bioactive compounds of cooked rice.PloS one · 2010Article
- Genomics and bioinformatics resources for crop improvement.Plant & cell physiology · 2010Review
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5 authors.
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Abstract
backgroundIt is essential to elucidate the relationship between metabolic and genomic diversity to understand the genetic regulatory networks associated with the changing metabolo-phenotype among natural variation and/or populations. Recent innovations in metabolomics technologies allow us to grasp the comprehensive features of the metabolome. Metabolite quantitative trait analysis is a key approach for the identification of genetic loci involved in metabolite variation using segregated populations. Although several attempts have been made to find correlative relationships between genetic and metabolic diversity among natural populations in various organisms, it is still unclear whether it is possible to discover such correlations between each metabolite and the polymorphisms found at each chromosomal location. To assess the correlative relationship between the metabolic and genomic diversity found in rice accessions, we compared the distance matrices for these two "omics" patterns in the rice accessions.
resultsWe selected 18 accessions from the world rice collection based on their population structure. To determine the genomic diversity of the rice genome, we genotyped 128 restriction fragment length polymorphism (RFLP) markers to calculate the genetic distance among the accessions. To identify the variations in the metabolic fingerprint, a soluble extract from the seed grain of each accession was analyzed with one dimensional (1)H-nuclear magnetic resonance (NMR). We found no correlation between global metabolic diversity and the phylogenetic relationships among the rice accessions (r(s) = 0.14) by analyzing the distance matrices (calculated from the pattern of the metabolic fingerprint in the 4.29- to 0.71-ppm (1)H chemical shift) and the genetic distance on the basis of the RFLP markers. However, local correlation analysis between the distance matrices (derived from each 0.04-ppm integral region of the (1)H chemical shift) against genetic distance matrices (derived from sets of 3 adjacent markers along each chromosome), generated clear correlations (r(s) > 0.4, p < 0.001) at 34 RFLP markers.
conclusionThis combinatorial approach will be valuable for exploring the correlative relationships between metabolic and genomic diversity. It will facilitate the elucidation of complex regulatory networks and those of evolutionary significance in plant metabolic systems.
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