The mtREV [ 20] model with gamma correction and invariable-site assumption (mtREV + I + Γ) was used in the analysis for the protein-coding genes of dataset #2.
Maximum-likelihood (ML) analysis using dataset #1 under the transversional substitution model with gamma correction and invariable-site assumption (TVM + I + Γ) produced exactly the same tree topology as that found in the BI analyses (figure not shown).
The general time reversible (GTR) model with gamma correction and invariable-site assumption was used in the analysis for dataset #1, and for tRNA and rRNA genes of dataset #2.
Maximum-likelihood (ML) analysis for dataset #1 using PAUP* 4.0b10 [ 46] was performed under a transversional substitution model with gamma correction and invariable-site assumption (TVM + I + Γ), which was chosen as the most fit for the present case based on hierarchical likelihood tests by Modeltest 3.6 [ 47].
Partitioned Bayesian inference (BI) phylogenetic analysis of the 11 mitogenomes from the concatenated nucleotide sequences from 13 protein-coding genes, 22 tRNA genes, plus 2 rRNA genes (dataset #1) under the general time reversible model with gamma correction and invariable-site assumption (GTR + I + Γ) [ 19] yielded a topology with resolution of the branching pattern among lancelets.
Although among site-rate heterogeneity can be efficiently modelled by fitting a gamma-distribution [ 24] or by assuming a proportion of invariable sites [ 25], these standard models make several assumptions, such as the independent evolution of nucleotide sites, and the spatial homogeneity of the substitution process across sites.
The condensed bootstrap maximum likelihood dendrogram was constructed from the General Time Reversible (GTR) model with a Gamma of 2.83 (+G) and an assumption that a fraction of sites (0.27) are evolutionarily invariable (+ I).
Hence the system's memory of - or dynamic adaptation to - the preceding events may not only help the photoreceptors to produce invariable representations of the visual world, but also break the simple additivity assumption.
We emphasize that the difficulties to detect subtle alterations in the distribution width of the measurements obtained for a given CKC component has important consequences even under the assumption that the spatial distribution of CKC components is essentially invariable in individual kinetochores.
Traditional dynamic method for temperature measurement is generally based on the assumption that the thermal inertia coefficient of a thermocouple junction is invariable (time constant) within the whole measuring process.
