Uneven Missing Data Skew Phylogenomic Relationships within the Lories and Lorikeets

Area of Science:

• Genomics
• Evolutionary Biology
• Bioinformatics

Background:

• Advances in DNA sequencing have accelerated the resolution of the Tree of Life.
• Historical museum specimens are vital for dense taxon sampling but yield degraded DNA, posing challenges for phylogenomic inference.

Purpose of the Study:

• To evaluate the impact of data coverage and missing data on phylogenomic inference using historical and modern samples.
• To identify specific data characteristics that influence phylogenetic tree topology.

Main Methods:

• Phylogenomic analysis of ultraconserved elements in 105 Australasian lory and lorikeet taxa.
• Evaluation of low-coverage characters and missing data effects on tree topology.
• Application of outlier analysis and data reduction techniques based on data completeness.

Main Results:

• Trees inferred with low-coverage data showed clade relationships influenced by sample origin (historical vs. modern).
• Outlier analysis identified specific sites and loci driving topological differences, with historical samples exhibiting significantly more missing data.
• A data completeness threshold of 70% was necessary to avoid spurious phylogenetic relationships.

Conclusions:

• Stringent data filtering, particularly addressing missing data in historical specimens, is essential for robust phylogenomic inference.
• Understanding data quality and applying appropriate analytical methods ensures accurate evolutionary reconstructions.
• A more stable phylogenetic hypothesis for lories and lorikeets was inferred after accounting for data biases.