Abstract
In phylogenetic inference, we commonly use models of substitution which assume that sequence evolution is stationary, reversible, and homogeneous (SRH). Although the use of such models is often criticized, the extent of SRH violations and their effects on phylogenetic inference of tree topologies and edge lengths are not well understood. Here, we introduce and apply the maximal matched-pairs tests of homogeneity to assess the scale and impact of SRH model violations on 3,572 partitions from 35 published phylogenetic data sets. We show that roughly one-quarter of all the partitions we analyzed (23.5%) reject the SRH assumptions, and that for 25% of data sets, tree topologies inferred from all partitions differ significantly from topologies inferred using the subset of partitions that do not reject the SRH assumptions. This proportion increases when comparing trees inferred using the subset of partitions that rejects the SRH assumptions, to those inferred from partitions that do not reject the SRH assumptions. These results suggest that the extent and effects of model violation in phylogenetics may be substantial. They highlight the importance of testing for model violations and possibly excluding partitions that violate models prior to tree reconstruction. Our results also suggest that further effort in developing models that do not require SRH assumptions could lead to large improvements in the accuracy of phylogenomic inference. The scripts necessary to perform the analysis are available in https://github.com/roblanf/SRHtests, and the new tests we describe are available as a new option in IQ-TREE (http://www.iqtree.org).
Highlights
Phylogenetics is an essential tool for inferring evolutionary relationships between individuals, species, genes, and genomes
Stationarity implies that the marginal frequencies of the nucleotides or amino acids are constant over time, reversibility implies that the evolutionary process is stationary and undirected, and homogeneity implies that the instantaneous substitution rates are constant along the tree or over an edge (Felsenstein 2004; Yang and Rannala 2012; Jermiin et al 2017)
As phylogenetic data sets are steadily growing in terms of taxonomic and site sampling, it is vital that we develop and employ methods to measure and understand the extent to which systematic error affects phylogenetic inference, and explore ways of mitigating this systematic bias in empirical studies
Summary
Phylogenetics is an essential tool for inferring evolutionary relationships between individuals, species, genes, and genomes. Stationarity implies that the marginal frequencies of the nucleotides or amino acids are constant over time, reversibility implies that the evolutionary process is stationary and undirected (substitution rates between nucleotides or amino acids are equal in both directions), and homogeneity implies that the instantaneous substitution rates are constant along the tree or over an edge (Felsenstein 2004; Yang and Rannala 2012; Jermiin et al 2017) These simplifying assumptions are often violated by real data (Foster and Hickey 1999; Tarrıo et al 2001; Paton et al 2002; Goremykin and Hellwig 2005; Murray et al 2005; Bourlat et al 2006; Hyman et al 2007; Sheffield et al 2009; Nesnidal et al 2010; Nabholz et al 2011; Martijn et al 2018). As phylogenetic data sets are steadily growing in terms of taxonomic and site sampling, it is vital that we develop and employ methods to measure and understand the extent to which systematic error affects phylogenetic inference (systematic bias), and explore ways of mitigating this systematic bias in empirical studies
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
