Mitochondrial genome evolution: the influence of partitioning, calibration, and gene heterogeneity on pleurodontan substitution rates

Matheus Salles, Fabricius Domingos

Substitution rate estimates are central to evolutionary biology, underpinning divergence-time inference and a wide range of macroevolutionary analyses. Mitochondrial DNA (mtDNA) rates are widely used for this purpose, yet they are often derived from a limited set of genes, closely related taxa, or a small number of model organisms. Here, we use nearly complete mitogenomes from 27 pleurodontan species (Squamata: Pleurodonta) to estimate substitution rates across the mitochondrial genome, explicitly evaluating the effects of data partitioning, calibration strategies, and model specification. Bayesian analyses revealed pronounced heterogeneity in substitution rates among codon positions and between coding and non-coding regions. Estimated rates ranged from approximately 0.004 to 0.02 substitutions per site per million years, consistent with previous lineage-specific estimates. Commonly used rates closely matched those estimated for third codon positions and for analyses based on combined partitions, suggesting that widely adopted values may primarily reflect signals from faster-evolving sites or aggregated partitioning schemes. Calibrated analyses generally yielded lower substitution rate estimates with reduced variance relative to non-calibrated analyses. However, substantial overlap in 95% highest posterior density intervals indicates limited evidence for systematic differences between these approaches, suggesting that much of the relative rate structure is already captured by the molecular data under a partitioned relaxed-clock framework. Comparisons between alternative partitioning strategies further showed that, although data-driven schemes recover broad patterns of rate variation, they may do so at the cost of reduced parameter resolution, particularly in the absence of calibration. Together, these results highlight that substitution rate estimates are sensitive to partitioning and modeling choices, and that model complexity should be evaluated in terms of parameter resolution and data informativeness rather than parameter count alone. By providing partition-specific rate estimates across the mitogenome, this study offers a robust empirical framework for improving molecular dating and evolutionary inference in squamates and other non-model systems.