TropiCODB: A multi-omics database unlocking the genetic potential of tropical crops

By integrating genomic, transcriptomic, metabolomic, variomic, and phenotypic datasets for eight major crops—including cassava, sugarcane, and oil palm—the platform addresses long-standing data gaps that have limited research in tropical agriculture.

Tropical crops are vital for global food security, economic resilience, and ecological sustainability, particularly in regions with high biodiversity but limited agricultural resources. Despite their importance, these crops face unique challenges: complex genomic structures, exposure to diverse stress conditions, and fewer dedicated research resources compared with temperate staples. While multi-omics technologies have transformed biological research by linking genes, metabolites, and traits, their application to tropical crops has been constrained by the lack of a centralized, high-quality database. This knowledge gap has hindered the identification of candidate genes, slowed trait improvement, and limited the use of cutting-edge breeding strategies. TropiCODB was created to fill this void.

A study (DOI:10.1016/j.bidere.2025.100003) published in BioDesign Research on 27 February 2025 by Fei Chen’s team, Hainan University, provides advanced tools for gene family analysis, miRNA profiling, and CRISPR guideRNA design, offering a robust foundation for functional genomics, trait improvement, and sustainable agricultural development.

To evaluate the effectiveness of TropiCODB, researchers first established an integrative framework that combined genomic, transcriptomic, metabolomic, variomic, and phenotypic datasets from more than 20 varieties of eight tropical crops, sourcing information from public repositories and experimental studies. This centralized platform was designed with dynamic visualization tools, modular architecture, and interactive analytical modules to support functional genomics research. Using this approach, the team incorporated high-quality genome assemblies, including telomere-to-telomere cassava sequences, and enriched them with functional annotations such as GO and KEGG classifications. Transcriptome data were curated from 174 RNA-seq samples representing multiple tissues, developmental stages, and stress responses, and were supported by visualization tools like eFP-gene and heatmap generators for gene expression profiling. Variomic datasets, including 573 cassava and 98 oil palm samples, were processed using advanced pipelines such as BWA and GATK to identify SNPs and indels, enabling population-level insights. Metabolomic data encompassed hundreds of annotated compounds across crops, allowing correlation with key agronomic traits, while phenotypic datasets captured yield, stress tolerance, and quality characteristics. Functional tools were then applied, including gene search and family analysis for comparative genomics, miRNA profiling for post-transcriptional regulation, and guideRNA design for CRISPR-based genome editing. Visualization modules such as JBrowse enabled chromosomal mapping of loci linked to traits like sugar biosynthesis in sugarcane. The utility of these methods was validated through case studies. In cassava, TropiCODB facilitated the identification and functional annotation of the Branching Enzyme 1 gene (Manes.08G022400), confirming its role in starch biosynthesis and leaf-specific expression. A second case study examined Manes.17G101400, homologous to Arabidopsis SRBP1, and revealed its downregulation during Xanthomonas infection, suggesting a role in cassava immunity. Together, these results demonstrate that TropiCODB not only accelerates data mining and functional analysis but also provides reliable insights into genetic mechanisms, underscoring its value as a benchmark multi-omics platform for tropical crop research.

TropiCODB sets a new benchmark for tropical crop research by bridging fragmented datasets into a single, intuitive resource. Researchers can now identify stress-resistant genes, design CRISPR targets for crop improvement, and compare expression patterns across developmental stages. The database reduces analysis time and increases usability, helping scientists explore complex biological pathways that underlie yield, resilience, and nutritional quality. For breeders, TropiCODB provides actionable insights into candidate genes and marker-trait associations, accelerating the development of varieties tailored to challenging tropical environments.

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References

DOI

10.1016/j.bidere.2025.100003

Original Source URL

https://doi.org/10.1016/j.bidere.2025.100003

Funding information

This work is supported by Hainan Province Science and Technology Special Fund (ZDYF2023XDNY050), National Key Laboratory for Tropical Crop Breeding (NO. NKLTCB202337), and Hainan Province Graduate Student Innovation Research Project (Qhys2023-268).

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