WGDI

WGDI performs integrated analyses of whole-genome duplications (WGDs) to detect polyploidy, infer genomic homology, and reconstruct ancestral karyotypes for evolutionary studies.

Key Features:

• Comprehensive Workflows: Supports three primary workflows—Polyploid Inference, Hierarchical Inference of Genomic Homology, and Ancestral Chromosomal Karyotyping—for WGD analyses.
• Enhanced Collinearity Detection: Implements a more sensitive and accurate algorithm for detecting gene collinearity resulting from recursive polyploidizations.
• Cross-Species Genome Alignments: Performs genome alignments across species to enable comparative genomic and evolutionary analyses.
• Efficiency, Flexibility, and Scalability: Offers computational efficiency, flexibility in application, and scalability for large genomic datasets.

Scientific Applications:

• WGD detection and characterization: Detects and characterizes polyploidization events and their impacts on gene collinearity.
• Karyotype evolution reconstruction: Reconstructs ancestral chromosomal karyotypes to trace chromosomal evolution following WGDs.
• Comparative genomics of Aquilegia coerulea and Vitis vinifera: Has been applied to elucidate karyotype evolution and genomic history in Aquilegia coerulea and Vitis vinifera.
• Evaluation of allopolyploid origin hypotheses in core dicots: Contributes to testing and refining hypotheses regarding allopolyploid origins in core dicots.

Methodology:

Python-based implementation that detects gene collinearity using a sensitive algorithm, performs cross-species genome alignments, and implements workflows for polyploid inference, hierarchical inference of genomic homology, and ancestral chromosomal karyotyping.