How do insect nuclear and mitochondrial gene substitution patterns differ? Insights from Bayesian analyses of combined datasets

We analyzed 12 combined mitochondrial and nuclear gene datasets in seven orders of insects using both equal weights parsimony (to evaluate phylogenetic utility) and Bayesian methods (to investigate substitution patterns). For the Bayesian analyses we used relatively complex models (e.g., general time reversible models with rate variation) that allowed us to quantitatively compare relative rates among genes and codon positions, patterns of rate variation among genes, and substitution patterns within genes. Our analyses indicate that nuclear and mitochondrial genes differ in a number of important ways, some of which are correlated with phylogenetic utility. First and most obviously, nuclear genes generally evolve more slowly than mitochondrial genes (except in one case), making them better markers for deep divergences. Second, nuclear genes showed universally high values of CI and (generally) contribute more to overall tree resolution than mitochondrial genes (as measured by partitioned Bremer support). Third, nuclear genes show more homogeneous patterns of among-site rate variation (higher values of α than mitochondrial genes). Finally, nuclear genes show more symmetrical transformation rate matrices than mitochondrial genes. The combination of low values of α and highly asymmetrical transformation rate matrices may explain the overall poor performance of mitochondrial genes when compared to nuclear genes in the same analysis. Our analyses indicate that some parameters are highly correlated. For example, A/T bias was positively and significantly associated with relative rate and CI was positively and significantly associated with α (the shape of the gamma distribution). These results provide important insights into the substitution patterns that might characterized high quality genes for phylogenetic analysis: high values of α, unbiased base composition, and symmetrical transformation rate matrices. We argue that insect molecular systematists should increasingly focus on nuclear rather than mitochondrial gene datasets because nuclear genes do not suffer from the same substitutional biases that characterize mitochondrial genes.