Coping with Ineffective Overlap in Multilocus Phylogenetics

TL;DR

The paper introduces a new method to handle missing data in phylogenetics by identifying taxa and loci for targeted sequencing to improve tree stability.

Contribution

The novel approach combines concatabominations with gene-tree jackknifing to identify candidates for additional sequencing.

Findings

The method successfully identifies taxa and loci for targeted sequencing to reduce topological instability.

It performs well even with modest amounts of added data.

Results are compared with a mathematics-based gene sampling approach.

Abstract

Missing data is a long-standing issue in phylogenetic inference, which often results in high levels of taxonomic instability, obscuring otherwise well-supported relationships. Multiple approaches have been developed to deal with the negative effects of ineffective overlap on tree resolution, often by identifying taxa for removal. Here, we repurpose a heuristic method developed to identify unstable taxa in morphological data matrices, concatabominations, and combine it with a novel gene-tree jackknifing on matrix representation of trees to identify candidates for targeted sequencing. Using a multilocus caecilian data set, we illustrate the method’s capacity to identify candidate taxa and loci for additional sequencing, compare the results with those of the mathematics-based gene sampling sufficiency approach, and explore the terrace space associated with the multilocus data set. We show that our approach yields tractable numbers of loci/taxa for targeted sequencing that successfully mitigate topological instability due to ineffective overlap, even when modest amounts of data are added.

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