Collection of maize populations and provides necessary information to understand the population structures.

All annotated metabolites information including metabolites' names, classification, distribution, and chemical structural formulas.

Provides of metabolites difference between different corn groups including T-test, fold-change, and variable importance in projection (VIP).

Collection of maize phenotypes and related genetic locus, including GWAS loci, genes, and corresponding haplotypes.



Related Publications

Li, et al. Large-scale metabolomic landscape of edible maize reveals convergent changes in metabolite differentiation and facilitates its breeding improvement, 28 February 2025, Online now, available at Molecular Plant [https://www.cell.com/molecular-plant/fulltext/S1674-2052(25)00090-5]

Resource

The sequencing data have been uploaded to the CNCB database with the project number PRJCA020612.
Released!

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Maize association mapping panel

Collection of more than 450 inbreds for association mapping panel (AMP) with different populations including Field; Waxy; Sweet.

PCA:PC1 PC2
PCA:PC1 PC3

452 Group INFO


Metabolite data of our panel

We conducted a study to analyze the metabolites present in maize kernels using a comprehensive LC-MS/MS-based metabolic profiling method. In total, we identified 3020 unique metabolites. Among these, we were able to annotate and classify 802 metabolites, which is a significant improvement compared to previous studies. The annotated metabolites span a wide range of classes, including flavonoids, lipids, alkaloids, amino acids, organic acids, phenolic acids, nucleotides, saccharides, alcohols, vitamins, lignans, coumarins, terpenoids, steroids, tannins, and unclassified metabolites. The flavonoid class, for example, consisted of various subclasses such as flavones, flavonols, flavone C-gly, dihydroflavone, and flavanols. This comprehensive dataset provides valuable insights into the metabolome of maize and enhances our understanding of its biochemical composition.


Annotated metabolite INFO


Differentially accumulated metabolites information

The comprehensive dataset of metabolites offers an opportunity to gain insights into the metabolic divergence during the domestication and improvement of maize. Partial least squares discriminant analysis (PLS-DA) was employed to identify the metabolites that significantly contribute to subgroup divergence. Our results indicated that 43.5% and 47.2% of the metabolite features are associated with the divergence in Field-Waxy and Field-Sweet, respectively, as evidenced by variable importance in projection (VIP) scores exceeding 0.8. Even with stringent criteria, with VIP scores exceeding 1, 28.9% and 34.0% of the metabolites were found to be significant in Field-Waxy and Field-Sweet, respectively. Furthermore, the paired t-test (adjusted for false discovery rate (FDR) < 0.05) or fold change (|Fold Change| ≥ 2 or 1.2) analysis of metabolite levels revealed that a majority of these metabolite features exhibit noteworthy divergence or significant changes.


Differentially accumulated metabolites INFO


Loci & haplotype

We conducted a comprehensive genome-wide association study (GWAS) using a linear mixed model (LMM) on a set of 20.3Mb credible single nucleotide polymorphisms (SNPs). To determine significant associations between metabolic traits and genetic variations, we applied a Bonferroni correction with a threshold of P = 4.63 × 10-8. However, it is important to note that the presence of significant genetic differences between sweet corns and other corn varieties (such as waxy and field corns) might obscure the effects of loci with underlying contributions. To overcome this limitation, we identified significant signals in sweet corns, other corn varieties, and all accessions to obtain a more comprehensive understanding of the associations. Remarkably, nearly all of the detected metabolites (755 out of 802) exhibited at least one significant association with genetic variations, with an average of 8.36 associations per metabolite. Furthermore, more than 42% (337 out of 755) of the metabolites displayed no more than 5 associations, indicating that the majority of metabolites are regulated by a small number of genes. To further investigate these candidate genes, we performed haplotype analysis for each gene.


Loci & haplotype INFO

Prediction of relative metabolite content




            

Comparative Analysis of Metabolites in Sweet/Waxy Corn Within a Population Level






The EMMDB is a website database, which developed using the R Shiny package, for interactive search and download metabolome data of the maize excellent inbred lines.

For the detail of this website, check the Tutorial submenu of the Help menu.


Citation


Software references

  1. R Development Core Team. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna. R version 4.2.1 (2022)
  2. RStudio and Inc. shiny: Web Application Framework for R. R package version 1.7.2 (2022)
  3. Xiaodong Deng. ECharts2Shiny: Embedding Interactive Charts Generated with ECharts Library into Shiny Applications. R package version 0.2.13 (2017)
  4. Yihui Xie. DT: A Wrapper of the JavaScript Library 'DataTables'. R package version 0.23 (2022)
  5. Jasmine Dumas. shinyLP: Bootstrap Landing Home Pages for Shiny Applications. R package version 1.1.2 (2018)
  6. Winston Chang. shinythemes: Themes for Shiny. R package version 1.2.0 (2021)
  7. Matt Dowle. data.table: Extension of 'data.frame'. R package version 1.14.2 (2021)
  8. Dean Attali. shinyforms: Easily create questionnaire-type forms with Shiny. (2021)
  9. JJ Allaire, Jeffrey Horner, Vicent Marti and Natacha Porte. markdown: “Markdown” Rendering for R. R package version 1.1 (2019)

Further references

This application was created by Zhiyong Li and Chunhui Li. Please send bugs and feature requests to Feedback panel. This application uses the shiny package from RStudio.

Note

For Mac users, we recommend using EMMDB with the Google Chrome browser or other browsers developed based on Chrominum.





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