Reliable Inference of Phylogenomic Relationship via Assembly-Based Strategy Accommodating Raw Reads and Proteins

Area of Science:

• Genomics
• Bioinformatics
• Evolutionary Biology

Background:

• Phylogenomics uses genomic data for evolutionary relationship inference.
• High-quality data and extensive processing are required, posing challenges for rare species.
• Fragmented DNA is often the only available data for deep-sea organisms.

Purpose of the Study:

• To develop a versatile and user-friendly phylogenomic pipeline (VEHoP).
• To automate the generation of orthologous sequence alignments and phylogenetic trees.
• To make phylogenomic analyses accessible for diverse data types and expertise levels.

Main Methods:

• VEHoP infers protein-coding regions from various inputs (raw reads, draft genomes, transcriptomes).
• The pipeline automates orthologous sequence alignment, concatenated matrix generation, and phylogenetic tree construction.
• VEHoP accommodates diverse data types, expanding taxonomic sampling.

Main Results:

• Validated VEHoP on oysters, catfish, and insects, producing robust trees with strong bootstrap support.
• VEHoP outperformed assembly-free methods in phylogenetic accuracy.
• Successfully reconstructed the phylogeny of deep-sea gastropods (Neomphalida), establishing a well-supported backbone.

Conclusions:

• VEHoP streamlines phylogenomic workflows and enhances accessibility for researchers.
• The tool effectively handles diverse and fragmented genomic data, crucial for understudied taxa.
• VEHoP offers a robust solution for inferring evolutionary relationships across various disciplines.