InsectBase

InsectBase provides a centralized repository of insect genomic and transcriptomic data to support comparative genomics, gene family characterization, non-coding RNA analysis, pathway mapping, and evolutionary studies.

Key Features:

• Data collection: The database contains 138 insect genomes, 116 insect transcriptomes, and 61 insect gene sets, and catalogs 36 gene families across 60 insect species.
• Non-coding RNAs: InsectBase includes 7,544 microRNAs from 69 insects, 96,925 piRNAs from Drosophila melanogaster and Chilo suppressalis, and 2,439 long non-coding RNAs from Nilaparvata lugens.
• Pathways: The resource contains 22,536 pathways across 78 insect species for metabolic and signaling network analyses.
• Sequence data: The database provides 678,881 untranslated regions (UTRs) from 84 insects and 160,905 coding sequences (CDS) from 70 insect species.
• BLAST server: A BLAST server is available for sequence alignment and similarity searches.
• GBrowse: GBrowse is provided for genomic visualization of sequence and annotation data.
• Pathway construction: The platform supports insect-specific pathway construction for mapping biological processes.
• Phylogenetic analysis: The resource supports phylogenetic analyses on selected genes to investigate evolutionary relationships.

Scientific Applications:

• Comparative genomics: Cross-species genome and gene set comparisons enabled by the collected genomes and gene families.
• Functional genomics: Analysis of CDS and UTR datasets to infer gene function and regulatory elements.
• Non-coding RNA research: Investigation of microRNA, piRNA, and lncRNA roles in post-transcriptional regulation, germline development, and transposon silencing.
• Pathway and network analysis: Mapping and analysis of metabolic and signaling pathways across 78 insect species.
• Phylogenetics and evolution: Gene-level phylogenetic analyses to study evolutionary relationships among insect species.
• Applied entomology: Genomic resources to support studies relevant to pest control and biodiversity conservation.

Methodology:

Computational methods explicitly include BLAST-based sequence alignment and similarity searches, GBrowse genomic visualization, insect pathway construction, and phylogenetic analyses.