Phylogenetic analysis has entered the genomics (multilocus) era. For less experienced researchers, conquering the large number of software programs required for a multilocus-based phylogenetic reconstruction can be somewhat daunting and time-consuming. PhyloSuite, a software with a user-friendly GUI, was designed to make this process more accessible by integrating multiple software programs needed for multilocus and single-gene phylogenies and further streamlining the whole process. In this protocol, we aim to explain how to conduct each step of the phylogenetic pipeline and tree-based analyses in PhyloSuite. We also present a new version of PhyloSuite (v1.2.3), wherein we fixed some bugs, made some optimizations, and introduced some new functions, including a number of tree-based analyses, such as signal-tonoise calculation, saturation analysis, spurious species identification, and etc. The step-by-step protocol includes background information (i.e., what the step does), reasons (i.e., why do the step), and operations (i.e., how to do it). This protocol will help researchers quick-start their way through the multilocus phylogenetic analysis, especially those interested in conducting organellebased analyses.

The long-prevailing paradigm of the adaptive evolution of organism complexity has been challenged in the last two decades by a competing theory that nonadaptive processes are the major driver of evolutionary patterns (Lynch, 2007;Lynch et al., 2006;Pouyet et al., 2017). Mitochondrial genomes (mitogenomes) were not spared this proposed paradigm shift, as their evolution in animals is suggested

The phylogeny of Isopoda, a speciose order of crustaceans, remains unresolved, with different datasets often producing starkly incongruent phylogenetic hypotheses. We hypothesised that extreme diversity in their life histories might be causing compositional heterogeneity/heterotachy in their mitochondrial genomes, and compromising the phylogenetic reconstruction. We tested the effects of different datasets (mitochondrial, nuclear, nucleotides, amino acids, concatenated genes, individual genes, gene orders), phylogenetic algorithms (assuming data homogeneity, heterogeneity, and heterotachy), and partitioning; and found that almost all of them produced unique topologies. As we also found that mitogenomes of Asellota and two Cymothoida families (Cymothoidae and Corallanidae) possess inversed base (GC) skew patterns in comparison to other isopods, we concluded that inverted skews cause long-branch attraction phylogenetic artefacts between these taxa. These asymmetrical skews are most likely driven by multiple independent inversions of origin of replication (i.e., nonadaptive mutational pressures). Although the PhyloBayes CAT-GTR algorithm managed to attenuate some of these artefacts (and outperform partitioning), mitochondrial data have limited applicability for reconstructing the phylogeny of Isopoda. Regardless of this, our analyses allowed us to propose solutions to some unresolved phylogenetic debates, and support Asellota are the most likely candidate for the basal isopod branch. As our findings show that architectural rearrangements can produce major compositional biases even on short evolutionary timescales, the implications are that proving the suitability of data via composition skew analyses should be a prerequisite for every study that aims to use mitochondrial data for phylogenetic reconstruction, even among closely related taxa.

No abstract

Despite several decades of intensive research on spirurine nematodes, molecular data on some of the main lineages are still absent, which makes taxonomic classification insufficiently resolved. In the present study, we sequenced the first complete mitogenome for the family Quimperiidae, belonging to P. sinensis (Spirurina: Quimperiidae), a parasite living in the intestines of snakehead (Ophiocephalus argus). The circular mitogenome is 13,874 bp long, and it contains the standard nematode gene set: 22 transfer RNAs, 2 ribosomal RNAs and 12 protein-coding genes. There are also two long non-coding regions (NCR), in addition to only 8 other intergenic regions, ranging in size from 1 to 58 bp. To investigate its phylogenetic position and study the relationships among other available Spirurina, we performed the phylogenetic analysis using Bayesian inference and maximum likelihood approaches by concatenating the nucleotide sequences of all 36 genes on a dataset containing all available mitogenomes of the suborder Spirurina from NCBI and compared with gene order phylogenies using the MLGO program. Both supported the closer relationship of Ascaridoidea to Seuratoidea than to Spiruroidea. Pingus formed a sister-group with the Cucullanus genus. The results provide a new insights into the relationships within Spirurina.