image: Schematic overview of the DrosGB database. The framework integrates multi-omics data resources, including genomic annotations, 876 RNA-seq datasets, and approximately 0.42 million predicted protein structures across 35 Drosophila species. A high-confidence ortholog set is generated by combining four orthology inference tools (Foldseek, TOGA, OrthoFinder, and SonicParanoid2), enabling classification of core conserved genes involved in basic metabolic processes and intracellular transport, as well as unique genes associated with sperm motility and flagellar function. The DrosGB platform provides comprehensive analytical tools, including gene search, genome synteny, gene tree construction, 3D structure visualization, gene expression analysis, ID mapping, BLAST, and primer design.
Credit: hLife
Drosophila species serve as pivotal model organisms for genetic and functional genomic research. The availability of high-quality genomes for multiple Drosophila species has created unprecedented opportunities for cross-species comparative analyses and gene function prediction. However, accurate identification of orthologs is essential to connect evolutionary relationships and infer functional conservation. Current databases largely focus on the model species Drosophila melanogaster, with limited integration of resources for other Drosophila species, thereby constraining systematic comparative genomics studies.
In a recent study published in hLife, a team led by Dr. Mo Liu at the Sino-French Hoffmann Institute, Guangzhou Medical University, together with Dr. Xiangrui Cai from Nankai University, introduced DrosGB, a comprehensive multi-omics database for 35 Drosophila species. DrosGB consolidates genomic annotations, transcriptomic profiles, and predicted three-dimensional protein structures. Critically, it delivers a high-confidence ortholog set derived from the consensus of four distinct inference methods, establishing a robust foundation for comparative and functional investigations across the Drosophila genus.
"DrosGB bridges a critical resource gap by providing a unified, multi-layered platform for ortholog mapping and functional annotation across diverse Drosophila species," said Mo Liu, Principal Investigator at the Sino-French Hoffmann Institute, Guangzhou Medical University. "The integration of multiple computational approaches significantly enhances reliability, enabling researchers to explore evolutionary conservation and lineage-specific adaptations with greater confidence."
DrosGB aggregates genomic data from FlyBase and NCBI for 35 species, using D. melanogaster as the reference. Orthologs were independently inferred by OrthoFinder, TOGA, Foldseek, and SonicParanoid2, followed by integration and filtering. Gene identifiers were harmonized using UniProt, Ensembl, and NCBI annotations. Indirect human ortholog relationships for non-melanogaster species were extrapolated via DIOPT. To ensure reliability, only ortholog pairs supported by at least three tools (Sum≥3) were retained in the high-confidence set. The database further incorporates protein structure predictions, functional annotations, and gene expression profiles. The online platform features five modules: Home, Tools, Browse, Download, and About. The Tools module integrates gene search, ortholog ID mapping, BLAST, phylogenetic tree construction, sequence retrieval, primer design, genome collinearity, and 3D structure search.
Analyses using DrosGB revealed that approximately 90% of genes in non-melanogaster species have counterparts in D. melanogaster, with about 70% maintained under stringent high-confidence criteria. Phylogenetic classification identified 6,889 core genes shared across all 35 species, enriched in fundamental metabolic processes and intracellular transport. In contrast, D. melanogaster-specific genes were associated with sperm motility and flagellar assembly, suggesting roles in reproductive adaptation. The user-friendly interface and comprehensive analytical tools allow researchers to seamlessly transition from data retrieval to in-depth analysis. As additional species and omics layers are incorporated, DrosGB is poised to become an indispensable platform for evolutionary genomics and functional discovery in Drosophila.
About Author:
Mo Liu is a Professor at the Sino-French Hoffmann Institute, Guangzhou Medical University. He earned his bachelor's degree from Nankai University in 2013 and completed his joint PhD in Bioinformatics at Duke University and the National University of Singapore in 2021. His research focuses on cancer genomics and comparative genomics. In the past five years, Dr. Liu has published over 10 peer-reviewed articles in leading journals, including Nature, PNAS, Molecular Biology and Evolution, and Cancer Discovery. His work has received more than 1,000 citations, with two papers recognized as Highly Cited.
Journal
hLife
Article Title
DrosGB: Integrated multi-omics database for comparative genomics across 35 Drosophila species
Article Publication Date
17-Feb-2026