Disentangling biological and analytical factors that give rise to outlier genes in phylogenomic matrices

The genomic data revolution has enabled biologists to develop innovative ways to infer key episodes in the history of life. Whether genome-scale data will eventually resolve all branches of the Tree of Life remains uncertain. However, through novel means of interrogating data, some explanations for why evolutionary relationships remain recalcitrant are emerging. Here, we provide four biological and analytical factors that explain why certain genes may exhibit “outlier” behavior, namely, rate of molecular evolution, alignment length, misidentified orthology, and errors in modeling. Using empirical and simulated data we show how excluding genes based on their likelihood or inferring processes from the topology they support in a supermatrix can mislead biological inference of conflict. We next show alignment length accounts for the high influence of two genes reported in empirical datasets. Finally, we also reiterate the impact misidentified orthology and short alignments have on likelihoods in large scale phylogenetics. We suggest that researchers should systematically investigate and describe the source of influential genes, as opposed to discarding them as outliers. Disentangling whether analytical or biological factors are the source of outliers will help uncover new patterns and processes that are shaping the Tree of Life.