A multiple-outgroup approach to resolving division-level phylogenetic relationships using 16S rDNA data

Area of Science:

• Microbiology
• Evolutionary Biology
• Bioinformatics

Background:

• The 16S ribosomal RNA gene (16S rDNA) is a primary marker for prokaryotic phylogeny.
• Vast numbers of 16S rDNA sequences exist, posing challenges for phylogenetic dataset construction.
• Dataset composition significantly impacts inferred evolutionary relationships and tree topology.

Purpose of the Study:

• To address the dilemma of selecting reference organisms in phylogenetic analysis.
• To propose and validate a novel multiple-outgroup approach for resolving division-level phylogenetic relationships.
• To assess the monophyly of bacterial divisions OP9 and OP10 using the proposed method.

Main Methods:

• Utilizing a large dataset of 16S rDNA sequences.
• Implementing a multiple-outgroup strategy in phylogenetic analyses.
• Conducting case studies on bacterial divisions OP9 and OP10.

Main Results:

• Demonstrated that dataset composition affects phylogenetic outcomes, particularly for distantly related sequences.
• The multiple-outgroup approach provides a robust method for inferring division-level relationships.
• Case studies illustrated the utility of the method in evaluating the monophyly of proposed bacterial divisions.

Conclusions:

• The choice of reference organisms is critical for accurate prokaryotic phylogenetics.
• A multiple-outgroup approach enhances the reliability of 16S rDNA phylogenetic analyses at the division level.
• This method aids in clarifying the evolutionary placement of novel bacterial groups.