MYB

MYB annotates the MYB transcription factor gene family in plant genome and transcriptome assemblies, identifying candidate sequences, providing domain-based functional classification, and placing sequences in a phylogenetic context to support evolutionary and functional analyses.

Key Features:

• Automatic Identification: Identifies candidate MYB transcription factor sequences within genome and transcriptome assemblies by screening for characterized sequences and MYB-specific motifs using Python.
• Functional Annotation: Detects MYB domains and other critical motifs and compares candidate sequences against well-characterized reference sequences to assign functional classification within the MYB family.
• Phylogenetic Contextualization: Places identified MYB sequences into a phylogenetic framework using established reference sequences to infer evolutionary relationships and functional diversification.
• Benchmarking and Validation: Validates accuracy by comparison against existing annotations with demonstrated analyses on the Croton tiglium transcriptome assembly and the Castanea crenata annotated genome sequence.
• Efficiency: Processes genome and transcriptome assemblies with performance that scales according to the number of predicted sequences and the size of the MYB gene family.

Scientific Applications:

• Plant developmental and metabolic research: Enables genome-wide identification and classification of MYB genes to investigate their roles in plant development and specialized metabolism.
• Comparative genomics: Supports cross-species comparative studies to explore evolutionary patterns and functional diversification within the MYB family.
• Evolutionary genomics and ortholog analysis: Facilitates detection of gene duplication and deletion events through ortholog identification to study MYB family evolution.

Methodology:

The pipeline, implemented in Python, processes genome or transcriptome assemblies by screening sequences for MYB-specific domains and motifs to identify candidates, comparing candidates to well-characterized reference sequences for functional annotation, and placing annotated genes within a phylogenetic framework for evolutionary contextualization.