The majority of source data were available as gridded datasets partitioned into bins at standardised depth levels (z-layers), and ranged in depth from 0 to ∼5500 m (z-binned datasets, e.g. temperature), whilst others were available as only a single layer at the surface (e.g. surface primary productivity) (Table 1).
The upshot is that, for many phylogenetic datasets, partitioned models of molecular evolution may be inadequate, thus limiting the accuracy of downstream phylogenetic analyses.
Concatenated maximum likelihood phylogeny inferred using RAxML, from the full 29 species, 107 locus dataset, partitioned by gene.
For the dataset partitioned only by gene and codons, we applied to each partition the GTRGAMMA (GTR+ Γ) + Invariant site option.
Phylogenetic estimates using ML were performed using both the combined, unpartitioned dataset as well as the combined dataset partitioned by locus (Additional file 2: Table S2).
We also demonstrate the utility of these models by application to a single-gene dataset partitioned according to tertiary structure (abalone sperm lysin), and a multi-gene dataset partitioned according to the functional category of the gene (flagellar-related proteins of Listeria).
For the nucleotide dataset, partitioned Bayesian analyses were carried out using a GTR + Γ(4) + I model for each codon position with parameter settings optimized independently for each of the three codon partitions.
We used the HKY [ 47] substitution model with the dataset partitioned into 3 codon positions, no site heterogeneity, substitution models for all nuclear loci linked (apart from the gdpgmp intron) and a strict clock.
All datasets, partition files and starting trees, except for the unpublished dataset d37831_6, are available for download at http://wwwkramer.in.tum.de/exelixis/pointerMeshData.tar.bz2.
Phylogenetic trees with bootstrap values (BS) and posterior probabilities (PP) were built based on the six datasets partitions.
