ArticleSystematic biology2015
Genetic distance for a general non-stationary markov substitution process.
Article in Systematic biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- piqtree: a python package for seamless phylogenetic inference with IQ-TREE.Molecular biology and evolution · 2026Article
- The effectiveness of selection in a species affects the direction of amino acid frequency evolution.bioRxiv : the preprint server for biology · 2025Article
- Spectral cluster supertree: fast and statistically robust merging of rooted phylogenetic trees.Frontiers in molecular biosciences · 2024Article
- Ecological Processes Shaping Microbiomes of Extremely Low Birthweight Infants.Frontiers in microbiology · 2022Article
- Embeddability and rate identifiability of Kimura 2-parameter matrices.Journal of mathematical biology · 2020Article
- A Novel Test for Absolute Fit of Evolutionary Models Provides a Means to Correctly Identify the Substitution Model and the Model Tree.Genome biology and evolution · 2019Article
- Comparative genomics reveals the distinct evolutionary trajectories of the robust and complex coral lineages.Genome biology · 2018Article
- Review
- Standard Codon Substitution Models Overestimate Purifying Selection for Nonstationary Data.Genome biology and evolution · 2017Article
- Trends in substitution models of molecular evolution.Frontiers in genetics · 2015Article
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The genetic distance between biological sequences is a fundamental quantity in molecular evolution. It pertains to questions of rates of evolution, existence of a molecular clock, and phylogenetic inference. Under the class of continuous-time substitution models, the distance is commonly defined as the expected number of substitutions at any site in the sequence. We eschew the almost ubiquitous assumptions of evolution under stationarity and time-reversible conditions and extend the concept of the expected number of substitutions to nonstationary Markov models where the only remaining constraint is of time homogeneity between nodes in the tree. Our measure of genetic distance reduces to the standard formulation if the data in question are consistent with the stationarity assumption. We apply this general model to samples from across the tree of life to compare distances so obtained with those from the general time-reversible model, with and without rate heterogeneity across sites, and the paralinear distance, an empirical pairwise method explicitly designed to address nonstationarity. We discover that estimates from both variants of the general time-reversible model and the paralinear distance systematically overestimate genetic distance and departure from the molecular clock. The magnitude of the distance bias is proportional to departure from stationarity, which we demonstrate to be associated with longer edge lengths. The marked improvement in consistency between the general nonstationary Markov model and sequence alignments leads us to conclude that analyses of evolutionary rates and phylogenies will be substantively improved by application of this model.
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