FINDER

FINDER automates eukaryotic gene annotation from raw RNA-Seq reads and associated protein sequences to identify transcripts, alternative splice variants, and assign evidence-based confidence scores.

Key Features:

• Raw RNA-Seq and protein integration: Directly ingests raw RNA-Seq reads and associated protein sequences for combined evidence-based annotation.
• BRAKER2-based gene prediction: Optimizes gene prediction using the BRAKER2 framework with RNA-Seq and protein evidence.
• Transcript and gene reporting: Identifies transcripts and genes expressed under specific conditions.
• Alternative splicing analysis: Generates alternatively spliced transcript variants from RNA-Seq data to represent transcript diversity.
• Read coverage pattern analysis: Analyzes read coverage patterns to refine existing transcript models and to generate new transcript models.
• Confidence scoring: Assigns confidence scores to gene predictions based on evidence aggregated across multiple datasets.
• Handling complex genomic features: Addresses overlapping genes, numerous transcripts per gene, transposable elements, and diverse sequence repeats.
• Scalability: Processes eukaryotic genomes of varying sizes without manual intervention.

Scientific Applications:

• Eukaryotic gene annotation: Automated annotation of genes and transcripts in eukaryotic genomes using RNA-Seq and protein evidence.
• Condition-specific expression analysis: Identification of transcripts and genes expressed under particular tissues or experimental conditions.
• Alternative splice variant characterization: Comprehensive identification of alternatively spliced transcripts to study transcriptomic diversity.
• Transcript model refinement and novel transcript discovery: Refinement of existing annotations and generation of new transcript models based on read coverage patterns.
• Annotation of complex genomic landscapes: Annotation in genomes containing overlapping genes, transposable elements, and diverse sequence repeats.

Methodology:

FINDER processes raw RNA-Seq reads, integrates associated protein sequences, uses BRAKER2 for gene prediction, analyzes read coverage to refine or generate transcript models, generates alternative splice variants, and assigns confidence scores based on evidence across datasets.