InsectOR

InsectOR predicts insect olfactory receptor (OR) genes in non-model genomes to enable accurate annotation of OR loci for studies of insect olfaction and pest-control target discovery.

Key Features:

• Gene prediction algorithms: Employs multiple gene prediction algorithms to identify OR gene models with high sensitivity and precision.
• Validation and refinement: Validates predicted OR loci and refines gene boundaries, including resolution of tandem OR genes.
• Performance benchmarking: Demonstrated performance superior to MAKER and NCBI eukaryotic genome annotation tools, achieving over 95% nucleotide-level precision.
• High sensitivity and low miss rate: Tested on two distantly related insect genomes with sensitivity at base, exon, and locus levels, missing less than 2% of gene loci where MAKER missed 55% for Drosophila melanogaster under identical conditions.
• Implementation: Core pipeline developed in Perl and implemented with Python using Jinja2 templating plus Bootstrap, HTML, CSS, and JavaScript/Ajax.

Scientific Applications:

• OR annotation in non-model organisms: Enables annotation of olfactory receptor repertoires in newly sequenced or non-model insect genomes, including cases lacking antennal transcriptome data.
• Sensory biology and evolution: Supports comparative and evolutionary studies of insect olfaction by providing refined OR gene models.
• Pest-control target discovery: Informs development of repellents and pesticides by supplying accurate OR gene annotations for functional characterization.

Methodology:

Uses multiple gene prediction algorithms, validates and refines predicted OR loci including tandem-gene boundary resolution, and benchmarks performance against MAKER and NCBI eukaryotic genome annotation tools on two distantly related insect genomes; implemented with a Perl core pipeline and a Python/Jinja2/Bootstrap/HTML/CSS/JavaScript-Ajax deployment stack.