Covariation of GC content and the silent site substitution rate in rodents: implications for methodology and for the evolution of isochores

Many attempts to test selectionist and neutralist models employ estimates o f synonymous (Ks) and non-synonymous (Ka) substitution rates of orthologous genes. For example, a stronger Ka-Ks correlation than expected under neutr ality has been argued to indicate a role for selection and the absence of a Ks-GC4 correlation has been argued to be inconsistent with neutral models for isochore evolution. However, both of these results, we have shown previ ously, are sensitive to the method by which Ka and Ks are estimated. Using a maximum likelihood (ML) estimator (GY94) we found a positive correlation between Ks and GC4 and only a weak correlation between Ka and Ks, lower tha n expected under neutral expectations. This ML method is computationally sl ow. Recently, a new ad hoc approximation of this ML method has been provide d (YN00). This is effectively an extension of Li's protocol but that also a llows for codon usage bias. This method is computationally near-instantaneo us and therefore potentially of great utility for analysis of large dataset s. Here we ask whether this method might have such applicability. To this e nd we ask whether it too recovers the two unusual results. We report that w hen the ML and earlier ad hoc methods disagree, YN00 recovers the results d escribed by the ML methods, i.e. a positive correlation between GC4 and Ks and only a weak correlation between Ks and Ka. If the ML method can be trus ted, then YN00 can also be considered an adequately reliable method for ana lysis of large datasets. Assuming this to be so we also analyze further the patterns. We show, for example, that the positive correlation between GC4 and Ks is probably in part a mutational bias, there being more methyl induc ed CpG --> TpG mutations in GC rich regions. As regards the evolution of is ochores, it seems inappropriate to use the claimed lack of a correlation be tween GC and Ks as definitive evidence either against or for any model. If the positive correlation is real then, we argue, this is hard to reconcile with the biased gene conversion model for isochore formation as this predic ts a negative correlation. (C) 2000 Elsevier Science B.V. All rights reserv ed.