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bioRxiv
BIORXIV
bioRxiv
2692-8205
Cold Spring Harbor Laboratory

10.1101/2024.09.03.610719
preprint
1
Article
An independent base composition of each rate class for improved likelihood-based phylogeny estimation; the 5rf model
Waddell Peter J.
Bouckaert Remco
07 9 2024
2024.09.03.610719https://creativecommons.org/licenses/by-nc-nd/4.0/ This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which allows reusers to copy and distribute the material in any medium or format in unadapted form only, for noncommercial purposes only, and only so long as attribution is given to the creator.
http://biorxiv.org/lookup/doi/10.1101/2024.09.03.610719
nihpp-2024.09.03.610719.pdf
Abstract

The combination of a t ime r eversible Markov process with a “hidden” mixture of g amma distributed relative site rates plus i nvariant sites have become the most favoured options for likelihood and other probabilistic models of nucleotide evolution (e.g., tr4gi which approximates a gamma with four rate classes). However, these models assume a homogeneous and stationary distribution of nucleotide (character or base) frequencies. Here, we explore the potential benefits and pitfalls of allowing each rate category (rate class) of a 4gi mixture model to have its own base frequencies. This is achieved by starting each of the five rate classes, at the tree’s r oot, with its own free choice of nucleotide f requencies to create a 4gi5rf model or a 5rf model in shorthand.

We assess the practical identifiability of this approach with a BEAST 2 implementation, aiming to determine if it can accurately estimate credibility intervals and expected values for a wide range of plausible parameter values. Practical identifiability, as distinguished from mathematical identifiability, gauges the model’s ability to identify parameters in real-world scenarios, as opposed to theoretically with infinite data.

One of the most common types of phylogenetic data is mitochondrial DNA (mtDNA) protein coding sequence. It is often assumed current models analyse robustly such data and that higher likelihood/posterior probability models do better. However, this abstract shows that vertebrate mtDNA remains a very difficult type of data to fully model, and that dramatically higher likelihoods do not mean a model is measurably more accurate with respect to recovering key parameters of biological interest (e.g., monophyletic groups, their support and their ages). The 4gi5rf model considerably improves marginal likelihoods and seems to reverse some apparent errors exacerbated by the 4gi model, while introducing others. Problems appear to be linked to non-stationary DNA repair processes that alter the mutation/substitution spectra across lineages and time. We also show such problems are not unique to mtDNA and are encountered in analysing nuclear sequences. Non-stationarity of DNA repair processes mutation/substitution spectra thus pose an active challenge to obtaining reliable inferences of relationships and divergence times near the root of placental mammals, for example.

An open source implementation is available under the LGPL 3.0 license in the beastbooster package for BEAST 2, available from https://github.com/rbouckaert/beastbooster .
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