| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 5919961 | Molecular Phylogenetics and Evolution | 2013 | 15 Pages |
One of the main challenges in analyzing multi-locus phylogenomic data is to find an optimal data partitioning strategy to account for variable evolutionary histories of different loci for any given dataset. Although a number of studies have addressed the issue of data partitioning in a Bayesian phylogenetic framework, such studies in a maximum likelihood framework are comparatively lacking. Furthermore, a rigorous statistical exploration of possible data partitioning schemes has not been applied to mitochondrial genome (mtgenome) data, which provide a complex, but manageable platform for addressing various challenges in analyzing phylogenomic data. In this study, we investigate the issue of data partitioning in the maximum likelihood framework in the context of the mitochondrial phylogenomics of an orthopteran superfamily Acridoidea (Orthoptera: Caelifera). The present study analyzes 34 terminals representing all 8 superfamilies within Caelifera, which includes newly sequenced partial or complete mtgenomes for 11 families. Using a new partition-selection method implemented in the software PartitionFinder, we compare a large number of data partitioning schemes in an attempt to identify the most effective method of analyzing the mtgenome data. We find that the best-fit partitioning scheme selected by PartitionFinder is superior to any a priori schemes commonly utilized in mitochondrial phylogenomics. We also show that over-partitioning is often detrimental to phylogenetic reconstruction. A comparative analysis of mtgenome structures finds that the tRNA gene rearrangement between cytochrome c oxidase subunit II and ATP synthase protein 8 does not occur in the most basal caeliferan lineage Tridactyloidea, suggesting that this gene rearrangement must have evolved at least in the common ancestor of Tetrigoidea and Acridomorpha. We find that mtgenome data contain sufficient phylogenetic information to broadly resolve the relationships across Acridomorpha and Acridoidea.
Graphical abstractDownload full-size imageHighlights⺠We study the effect of data partitioning in mitochondrial phylogenomics. ⺠A priori partitioning schemes are usually suboptimal. ⺠PartitionFinder is capable of searching for the best-fit partitioning scheme. ⺠Over-partitioning is detrimental to accurate phylogenetic reconstruction. ⺠Mtgenome data broadly resolve the relationships across Acridomorpha.
