MRF

MRF identifies missing genomic regions and coding sequences relative to a reference genome to standardize nomenclature and support comparative genomics of viruses such as white spot syndrome virus (WSSV).

Key Features:

• Standardization of Nomenclature: Implements a uniform nomenclature to address inconsistent annotation arising from genome circularity and variable length in WSSV.
• Integration with MUMmer: Combines the standard MUMmer software with custom scripts to detect missing regions and coding sequences relative to a reference genome.
• Documentation of Missing Elements: Systematically documents missing coding sequences and genome regions to enable downstream functional analysis.
• Identification of Deletion Hotspots: Detects deletion hotspots and associates them with biological functions such as ubiquitination, transcription regulation, nucleotide metabolism, and virus assembly.
• Structural Protein Mapping: Highlights essential structural proteins including VP19, VP26, and VP28 in the context of identified missing regions.
• Handling Low-Complexity and Repeat-Rich Regions: Operates on low-complexity, repeat-rich, and highly similar regions to resolve annotation discrepancies.
• Graphic and Tabular Outputs: Produces detailed graphic and tabular outputs for reporting identified missing regions and coding sequences.
• Applicability to Diverse Viruses: Applicable to large, highly similar, and length-varying viral genomes with inconsistent annotations beyond WSSV.

Scientific Applications:

• Comparative Genomics of Pathogenic Viruses: Enables standardized comparisons across viral isolates and strains to study genomic variation.
• Isolate and Strain Differentiation: Rapidly identifies critical genomic differences between viral isolates or strains.
• Prioritization of Virulence-Related Elements: Supports prioritization of genetic elements that may influence virulence and pathogenesis.
• Complement to Similarity-Based Tools: Complements similarity-based analyses by explicitly documenting missing regions and their potential functional implications.
• Cross-Virus Comparative Studies: Facilitates comparative studies across diverse viral genomes that are large, highly similar, and length-varying with inconsistent annotations.

Methodology:

Combines MUMmer with custom scripts to identify missing regions and coding sequences relative to a reference genome; employs phylogenomics, machine learning models, and analysis of homologous genes to explore associations; detects deletion hotspots and links them to functions including ubiquitination, transcription regulation, nucleotide metabolism, virus assembly, and structural proteins VP19, VP26, and VP28.