Selecting taxa to save or sequence: desirable criteria and a greedy solution.

Area of Science:

• Evolutionary biology
• Conservation genetics
• Bioinformatics

Background:

• Selecting representative evolutionary units (EUs) is crucial for conservation and genomic studies.
• Phylogenetic diversity (PD) is a common metric but can yield counterintuitive results.
• Desirable selection criteria include spread, stability, and applicability.

Purpose of the Study:

• To evaluate the suitability of maximizing minimum pairwise distance (MMD) as a selection criterion for EUs.
• To introduce and assess a greedy algorithm (GREEDYMMD) for approximating MMD maximization.
• To compare GREEDYMMD with PD for selecting EUs in practical scenarios.

Main Methods:

• Defined a greedy algorithm (GREEDYMMD) to approximate the maximization of minimum pairwise distance (MMD) between EUs.
• Evaluated GREEDYMMD based on spread, stability, and applicability criteria.
• Analyzed GREEDYMMD's performance under a model of evolving biodiversity and with ultrametric distances.

Main Results:

• GREEDYMMD satisfies the desirable criteria of spread, stability, and applicability.
• GREEDYMMD is suitable for biodiversity models with evolving features.
• When distances are ultrametric, GREEDYMMD optimally maximizes both MMD and PD.

Conclusions:

• GREEDYMMD provides a robust and applicable alternative to PD for selecting EUs.
• The algorithm's reliance on distances, not trees, enhances its broad applicability.
• GREEDYMMD is a valuable tool for conservation and genomic sequencing efforts.