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Coping with Ineffective Overlap in Multilocus Phylogenetics.

Ana Serra Silva^1,2,3, Karen Siu-Ting⁴, Christopher J Creevey⁴

¹Herpetology Lab, Science Group, The Natural History Museum, Cromwell Road, London SW7 5BD, UK.

Systematic Biology

|July 3, 2025

Summary

This summary is machine-generated.

This study introduces a new method to address missing data in phylogenetic inference, improving taxonomic stability. The approach identifies key taxa and genes for targeted sequencing, enhancing evolutionary relationship resolution.

Keywords:

Ineffective overlap matrix representation of splits phylogenomics targeted taxon/locus sampling taxonomic instability terraces

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Published on: February 5, 2014

Area of Science:

Phylogenetic Inference
Bioinformatics
Evolutionary Biology

Background:

Missing data is a persistent challenge in phylogenetic inference, leading to taxonomic instability and obscuring evolutionary relationships.
Existing methods often focus on removing taxa, which can lead to loss of valuable information.
Ineffective overlap in phylogenetic datasets can negatively impact tree resolution and the accuracy of inferred relationships.

Purpose of the Study:

To develop and validate a novel heuristic method for identifying taxa and loci candidates for targeted sequencing to mitigate missing data issues.
To improve phylogenetic tree resolution and taxonomic stability by addressing the challenges posed by ineffective overlap.
To compare the efficacy of the proposed method with existing approaches like gene sampling sufficiency.

Main Methods:

Repurposed a heuristic method for identifying unstable taxa in morphological data matrices (concatabominations).
Combined this heuristic with novel gene-tree jackknifing on matrix representation of trees (MrTree).
Applied the method to a multilocus caecilian dataset and compared results with the gene sampling sufficiency approach.

Main Results:

The developed approach successfully identified tractable numbers of loci and taxa for targeted sequencing.
Targeted sequencing based on the method's recommendations effectively mitigated topological instability caused by ineffective overlap.
The method demonstrated capacity to identify candidates for additional sequencing, even with modest data additions.

Conclusions:

The proposed heuristic and gene-tree jackknifing method offers an effective strategy for managing missing data in phylogenetics.
This approach enhances phylogenetic resolution and taxonomic stability, providing a valuable tool for evolutionary studies.
The method provides a practical solution for researchers dealing with incomplete datasets, guiding efficient data acquisition.