G-Mo.R-Seq

G-Mo.R-Seq constructs de novo gene models from RNA-Seq short reads by inferring exon-exon junctions and transcript structures to enable gene modeling in organisms lacking annotations.

Key Features:

• De novo gene model construction: Generates gene models directly from RNA-Seq data without requiring a predefined set of known genes or splicing events.
• Exon-exon junction inference: Focuses on exon-exon junctions to address short-read alignment across splice sites.
• Short-read RNA-Seq analysis: Analyzes RNA-Seq short reads to reconstruct transcript structures and gene boundaries.
• Next-generation cDNA sequencing support: Leverages massive-scale next-generation cDNA sequencing (RNA-Seq) datasets as input.
• Applicability to unannotated genomes: Designed for organisms with unannotated genomes or lacking comprehensive genetic databases.
• Novel gene and splicing discovery: Identifies novel genes and alternative splicing events from transcriptomic data.

Scientific Applications:

• Grapevine genome analysis: Applied to the grapevine genome to uncover gene models and alternative splicing in a complex plant genome.
• Functional genomics: Enables discovery of expressed genes and transcript variants for functional characterization.
• Comparative and evolutionary genomics: Facilitates comparison of transcriptomes and gene structures across species lacking annotations.
• Transcriptomic diversity and trait association: Supports identification of candidate genes and splice variants associated with phenotypic traits or diseases.

Methodology:

Analyzes RNA-Seq short reads with emphasis on exon-exon junctions to infer gene structures and reconstruct de novo gene models.