Categorical edge-based analyses of phylogenomic data reveal conflicting signals for difficult relationships in the avian tree

Phylogenetic analyses fail to yield a satisfactory resolution of some relationships in the tree of life even with genome-scale datasets, so the failure is unlikely to reflect limitations in the amount of data. Gene tree conflicts are particularly notable in studies focused on these contentious nodes, and taxon sampling, different analytical methods, and/or data type effects can further confound analyses. Although many efforts have been made to incorporate biological conflicts, few studies have curated individual genes for their efficiency in phylogenomic studies. Here, we conduct an edge-based analysis of Neoavian evolution, examining the phylogenetic efficacy of two recent phylogenomic bird datasets and three datatypes (ultraconserved elements [UCEs], introns, and coding regions). We assess the potential causes for biases in signal-resolution for three difficult nodes: the earliest divergence of Neoaves, the position of the enigmatic Hoatzin (Opisthocomus hoazin), and the position of owls (Strigiformes). We observed extensive conflict among genes for all data types and datasets even after meticulous curation. Edge-based analyses (EBA) increased congruence and provided information about the impact of data type, GC content variation (GCCV), and outlier genes on each of nodes we examined. First, outlier gene signals appeared to drive different patterns of support for the relationships among the earliest diverging Neoaves. Second, the placement of Hoatzin was highly variable, although our EBA did reveal a previously unappreciated data type effect with an impact on its position. It also revealed that the resolution with the most support here was Hoatzin + shorebirds. Finally, GCCV, rather than data type (i.e., coding vs non-coding) per se, was correlated with a signal that supports monophyly of owls + Accipitriformes (hawks, eagles, and vultures). Eliminating high GCCV loci increased the signal for owls + mousebirds. Categorical EBA was able to reveal the nature of each edge and provide a way to highlight especially problematic branches that warrant a further examination. The current study increases our understanding about the contentious parts of the avian tree, which show even greater conflicts than appreciated previously.

Automated summary

This study focuses on the contentious parts of avian phylogenetics and reveals even greater conflicts than previously appreciated. Edge-based analysis provides insights into the impact of data type, GC content variation, and outlier genes on signal-resolution for different nodes.