PlantTribes

PlantTribes performs gene-family classification and comparative evolutionary analysis of plant genomes to support genome annotation, phylogenetic inference, detection of duplication events, and analysis of selective pressures.

Key Features:

• Pre-computed orthologous gene family clusters: Organizes annotated protein sequences from high-quality plant genomes into objective orthogroup clusters enriched with functional annotation.
• Transcript model enhancement and categorization: Improves transcript models and assigns them to gene family clusters for downstream analysis.
• Support for user-provided datasets: Accepts external genomic and transcriptomic inputs for integration with pre-computed clusters.
• Multiple sequence alignment: Aligns sequences within gene families to identify conserved regions and variation.
• Gene family phylogeny: Constructs phylogenetic trees to resolve evolutionary relationships among family members.
• Synonymous and non-synonymous substitution rate estimation: Computes Ka/Ks and related metrics among homologous sequences to infer selective pressures.
• Inference of large-scale duplication events: Detects genome-scale duplication signatures that have shaped gene family evolution.
• Functional annotation enrichment: Associates gene families with functional annotations to support comparative and evolutionary interpretation.
• Scalability and customization for genome-scale analyses: Supports large datasets and configurable analyses and visualizations for targeted gene-family studies.

Scientific Applications:

• Genome annotation enhancement: Uses orthogroup context and functional annotation to improve annotation of plant genomes and transcriptomes.
• Comparative genomics and evolutionary studies: Facilitates comparative analyses across model and non-model plants to study gene family evolution and genome trajectories.
• Empirical studies in specific plant families: Has been applied to transcriptomics in Orobanchaceae and core orthogroup (CROG) analyses in Rosaceae to investigate gene function and evolution.

Methodology:

Computational steps explicitly include objective classification of annotated protein sequences into pre-computed orthologous gene family clusters, enhancement and categorization of transcript models, multiple sequence alignment, phylogenetic tree construction, estimation of synonymous and non-synonymous substitution rates (Ka/Ks), inference of large-scale duplication events, and enrichment of clusters with functional annotation.