FlatNJ: a novel network-based approach to visualize evolutionary and biogeographical relationships.

Area of Science:

• Evolutionary biology
• Bioinformatics
• Phylogenetics

Background:

• Phylogenetic networks visualize evolutionary relationships and data conflicts.
• Existing methods like split decomposition and NeighborNet have limitations in visualizing complex evolutionary scenarios.

Purpose of the Study:

• To present FlatNetJoining (FlatNJ), a new method for constructing phylogenetic networks.
• To demonstrate FlatNJ's capability in visualizing detailed evolutionary information, especially for complex datasets.

Main Methods:

• FlatNetJoining (FlatNJ) constructs planar phylogenetic networks.
• The method allows labels to be placed within the network, enhancing visualization.
• Applied to whole HIV genome sequences, coral fluorescent proteins, and gall wasp mitochondrial DNA.

Main Results:

• FlatNJ generates phylogenetic networks with enhanced visualization capabilities.
• The method effectively visualizes conflict in evolutionary data, including recombination events and ancestral sequences.
• Networks facilitate the study of genetic variation and processes like intra-locus recombination.

Conclusions:

• FlatNJ offers an improved approach for constructing and visualizing phylogenetic networks.
• The method aids in understanding complex evolutionary histories and genetic variation.
• FlatNJ is freely available as a Java implementation.