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.

Background Classification of the Acanthocephala, a clade of obligate endoparasites, remains unresolved because of insufficiently strong resolution of morphological characters and scarcity of molecular data with a sufficient resolution. Mitochondrial genomes may be a suitable candidate, but they are available for a small number of species and their suitability for the task has not been tested thoroughly. Methods Herein, we sequenced the first mitogenome for the large family Rhadinorhynchidae: Micracanthorhynchina dakusuiensis. These are also the first molecular data generated for this entire genus. We conducted a series of phylogenetic analyses using concatenated nucleotides (NUC) and amino acids (AAs) of all 12 protein-coding genes, three different algorithms, and the entire available acanthocephalan mitogenomic dataset. Results We found evidence for strong compositional heterogeneity in the dataset, and Micracanthorhynchina dakusuiensis exhibited a disproportionately long branch in all analyses. This caused a long-branch attraction artefact (LBA) of M. dakusuiensis resolved at the base of the Echinorhynchida clade when the NUC dataset was used in combination with standard phylogenetic algorithms, maximum likelihood (ML) and Bayesian inference (BI). Both the use of the AA dataset (BI-AAs and ML-AAs) and the CAT-GTR model designed for suppression of LBA (CAT-GTR-AAs and CAT-GTR-NUC) at least partially attenuated this LBA artefact. The results support Illiosentidae as the basal radiation of Echinorhynchida and Rhadinorhynchidae forming a clade with Echinorhynchidae and Pomporhynchidae. The questions of the monophyly of Rhadinorhynchidae and its sister lineage remain unresolved. The order Echinorhynchida was paraphyletic in all of our analyses. Conclusions Future studies should take care to attenuate compositional heterogeneity-driven LBA artefacts when applying mitogenomic data to resolve the phylogeny of Acanthocephala. Graphical Abstract

The evidence that parasitic lineages exhibit elevated evolutionary rates is limited to Arthropoda and inconsistent. Similarly, the evidence that mitogenomic evolution is faster in species with low locomotory capacity (LC) is limited to a handful of animal lineages. We hypothesised that these two variables are associated and that LC is a major underlying factor driving the elevated evolutionary rates in parasites. We tested this hypothesis by studying mitogenomic evolutionary patterns in 10,911 bilaterian species classified according to their locomotory capacity and parasitic/free-living life history (LH). Evolutionary rates were significantly elevated in endoparasites, ectoparasites with reduced LC, and free-living lineages with reduced LC, but not in ectoparasites and parasitoids with high LC. Nematoda and Arachnida were the only lineages where parasitism was not associated with faster evolution. We propose that LC may also explain these two major outliers. Overall, the LH categorisation explained 35-37%, LC categorisation 26-28%, and together they explained 41-44% of the variance in branch lengths across the Bilateria. Our findings suggest that these two variables play a major role in calibrating the molecular clock in bilaterian animals.

Background Acanthocephala is a clade of obligate endoparasites whose mitochondrial genomes (mitogenomes) and evolution remain relatively poorly understood. Previous studies reported that atp8 is lacking from acanthocephalan mitogenomes, and that tRNA genes often have nonstandard structures. Heterosentis pseudobagri (Arhythmacanthidae) is an acanthocephalan fish endoparasite for which no molecular data are currently available, and biological information is unavailable in the English language. Furthermore, there are currently no mitogenomes available for Arhythmacanthidae. Methods We sequenced its mitogenome and transcriptome, and conducted comparative mitogenomic analyses with almost all available acanthocephalan mitogenomes. Results The mitogenome had all genes encoded on the same strand and unique gene order in the dataset. Among the 12 protein-coding genes, several genes were highly divergent and annotated with difficulty. Moreover, several tRNA genes could not be identified automatically, so we had to identify them manually via a detailed comparison with orthologues. As common in acanthocephalans, some tRNAs lacked either the TWC arm or the DHU arm, but in several cases, we annotated tRNA genes only on the basis of the conserved narrow central segment comprising the anticodon, while the flanking 5’ and 3’ ends did not exhibit any resemblance to orthologues and they could not be folded into a tRNA secondary structure. We corroborated that these are not sequencing artefacts by assembling the mitogenome from transcriptomic data. Although this phenomenon was not observed in previous studies, our comparative analyses revealed the existence of highly divergent tRNAs in multiple acanthocephalan lineages. Conclusions These findings indicate either that multiple tRNA genes are non-functional or that (some) tRNA genes in (some) acanthocephalans might undergo extensive posttranscriptional tRNA processing which restores them to more conventional structures. It is necessary to sequence mitogenomes from yet unrepresented lineages and further explore the unusual patterns of tRNA evolution in Acanthocephala.