ArticlePloS one2013
Leveraging non-targeted metabolite profiling via statistical genomics.
Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
8 citing papers in PubMed.
- Dimethylguanidino valeric acid is a marker of liver fat and predicts diabetes.The Journal of clinical investigation · 2017Trial
- Dynamic relationships among pathways producing hydrocarbons and fatty acids of maize silk cuticular waxes.Plant physiology · 2024Article
- Conformations of a highly expressed Z19 α-zein studied with AlphaFold2 and MD simulations.PloS one · 2024Article
- Applying network and genetic analysis to the potato metabolome.Frontiers in plant science · 2023Article
- Understanding Omics Driven Plant Improvement andFrontiers in genetics · 2021Review
- Plant Metabolomics: An Indispensable System Biology Tool for Plant Science.International journal of molecular sciences · 2016Review
- Natural Variation of Plant Metabolism: Genetic Mechanisms, Interpretive Caveats, and Evolutionary and Mechanistic Insights.Plant physiology · 2015Article
- Metabolome-based genome-wide association study of maize kernel leads to novel biochemical insights.Nature communications · 2014Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
One of the challenges of systems biology is to integrate multiple sources of data in order to build a cohesive view of the system of study. Here we describe the mass spectrometry based profiling of maize kernels, a model system for genomic studies and a cornerstone of the agroeconomy. Using a network analysis, we can include 97.5% of the 8,710 features detected from 210 varieties into a single framework. More conservatively, 47.1% of compounds detected can be organized into a network with 48 distinct modules. Eigenvalues were calculated for each module and then used as inputs for genome-wide association studies. Nineteen modules returned significant results, illustrating the genetic control of biochemical networks within the maize kernel. Our approach leverages the correlations between the genome and metabolome to mutually enhance their annotation and thus enable biological interpretation. This method is applicable to any organism with sufficient bioinformatic resources.
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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.