Integrated Multi-Omics Analysis of Sugarcane Tillering in Four Genotypes

Integrated transcriptomic, phytohormone metabolomic, and ionomic data from four sugarcane genotypes at peak tillering stage. The dataset includes three biological replicates per genotype and tissue combination, generated by Shimiao Chen and last updated in April 2026. It is a 556.8 KB ZIP file licensed under CC-BY-4.0.

Use Cases

• Identify gene expression patterns correlated with tillering capacity based on transcriptomic data.
• Analyze hormonal trade-offs between growth and defense pathways based on metabolite profiles.
• Model nutrient allocation in tiller tissues based on ionomic signatures.
• Perform weighted gene co-expression network analysis (WGCNA) to link modules with specific metabolites.

Strengths

• Includes three biological replicates per genotype and tissue combination, supporting statistical analysis.
• Integrates three distinct omics layers: transcriptomics, targeted phytohormone metabolomics, and ionomics.
• Provides specific metabolite fold-change values (e.g., tryptamine Log2FC = 4.97) and correlation coefficients (e.g., r = 0.71) in the description.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The dataset is small (556.8 KB), indicating a limited scope focused on a specific experimental setup.

Provenance

Source

figshare, author Shimiao Chen.

Collection Method

Field-grown sugarcane plants were analyzed using integrated transcriptomics, targeted phytohormone metabolomics, and ionomics.

Time Range

Data collected at the peak tillering stage of the plants.

Freshness

Last updated 2026-04-20 05:19:25; freshness should be verified.

Geography

Field-grown plants; specific location is unknown.