Can comprehensive background knowledge be incorporated into substitution models to improve phylogenetic analyses? A case study on major arthropod relationships

<p>Abstract</p> <p>Background</p> <p>Whenever different data sets arrive at conflicting phylogenetic hypotheses, only testable causal explanations of sources of errors in at least one of the data sets allow us to critically choose among the conflicting hypotheses of relationships. The large (28S) and small (18S) subunit rRNAs are among the most popular markers for studies of deep phylogenies. However, some nodes supported by this data are suspected of being artifacts caused by peculiarities of the evolution of these molecules. Arthropod phylogeny is an especially controversial subject dotted with conflicting hypotheses which are dependent on data set and method of reconstruction. We assume that phylogenetic analyses based on these genes can be improved further i) by enlarging the taxon sample and ii) employing more realistic models of sequence evolution incorporating non-stationary substitution processes and iii) considering covariation and pairing of sites in rRNA-genes.</p> <p>Results</p> <p>We analyzed a large set of arthropod sequences, applied new tools for quality control of data prior to tree reconstruction, and increased the biological realism of substitution models. Although the split-decomposition network indicated a high noise content in the data set, our measures were able to both improve the analyses and give causal explanations for some incongruities mentioned from analyses of rRNA sequences. However, misleading effects did not completely disappear.</p> <p>Conclusion</p> <p>Analyses of data sets that result in ambiguous phylogenetic hypotheses demand for methods, which do not only filter stochastic noise, but likewise allow to differentiate phylogenetic signal from systematic biases. Such methods can only rely on our findings regarding the evolution of the analyzed data. Analyses on independent data sets then are crucial to test the plausibility of the results. Our approach can easily be extended to genomic data, as well, whereby layers of quality assessment are set up applicable to phylogenetic reconstructions in general.</p

Four myriapod relatives – but who are sisters? No end to debates on relationships among the four major myriapod subgroups

BackgroundPhylogenetic relationships among the myriapod subgroups Chilopoda, Diplopoda, Symphyla and Pauropoda are still not robustly resolved. The first phylogenomic study covering all subgroups resolved phylogenetic relationships congruently to morphological evidence but is in conflict with most previously published phylogenetic trees based on diverse molecular data. Outgroup choice and long-branch attraction effects were stated as possible explanations for these incongruencies. In this study, we addressed these issues by extending the myriapod and outgroup taxon sampling using transcriptome data.ResultsWe generated new transcriptome data of 42 panarthropod species, including all four myriapod subgroups and additional outgroup taxa. Our taxon sampling was complemented by published transcriptome and genome data resulting in a supermatrix covering 59 species. We compiled two data sets, the first with a full coverage of genes per species (292 single-copy protein-coding genes), the second with a less stringent coverage (988 genes). We inferred phylogenetic relationships among myriapods using different data types, tree inference, and quartet computation approaches. Our results unambiguously support monophyletic Mandibulata and Myriapoda. Our analyses clearly showed that there is strong signal for a single unrooted topology, but a sensitivity of the position of the internal root on the choice of outgroups. However, we observe strong evidence for a clade Pauropoda+Symphyla, as well as for a clade Chilopoda+Diplopoda.ConclusionsOur best quartet topology is incongruent with current morphological phylogenies which were supported in another phylogenomic study. AU tests and quartet mapping reject the quartet topology congruent to trees inferred with morphological characters. Moreover, quartet mapping shows that confounding signal present in the data set is sufficient to explain the weak signal for the quartet topology derived from morphological characters. Although outgroup choice affects results, our study could narrow possible trees to derivatives of a single quartet topology. For highly disputed relationships, we propose to apply a series of tests (AU and quartet mapping), since results of such tests allow to narrow down possible relationships and to rule out confounding signal

Gene content evolution in the arthropods

Arthropods comprise the largest and most diverse phylum on Earth and play vital roles in nearly every ecosystem. Their diversity stems in part from variations on a conserved body plan, resulting from and recorded in adaptive changes in the genome. Dissection of the genomic record of sequence change enables broad questions regarding genome evolution to be addressed, even across hyper-diverse taxa within arthropods. Using 76 whole genome sequences representing 21 orders spanning more than 500 million years of arthropod evolution, we document changes in gene and protein domain content and provide temporal and phylogenetic context for interpreting these innovations. We identify many novel gene families that arose early in the evolution of arthropods and during the diversification of insects into modern orders. We reveal unexpected variation in patterns of DNA methylation across arthropods and examples of gene family and protein domain evolution coincident with the appearance of notable phenotypic and physiological adaptations such as flight, metamorphosis, sociality, and chemoperception. These analyses demonstrate how large-scale comparative genomics can provide broad new insights into the genotype to phenotype map and generate testable hypotheses about the evolution of animal diversity

DNA Barcoding of <i>Trichobilharzia</i> (Trematoda: Schistosomatidae) Species and Their Detection in eDNA Water Samples

We designed and tested species-specific PCR primers to detect Trichobilharzia species via environmental DNA (eDNA) barcoding in selected Austrian water bodies. Tests were performed with eDNA samples from the field as well as with artificial samples from the lab, where snails releasing cercariae were kept in aquariums. From two localities, Trichobilharzia was documented based on the release of cercariae from snails, enabling morphological species identification. In both cases, the corresponding species were detected via eDNA: Trichobilharzia szidati and Trichobilharzia physellae. Nonetheless, the stochasticity was high in the replicates. PCR tests with aquarium water into which the cercariae had been released allowed eDNA detection even after 44 days. As in the PCRs with eDNA samples from the field, positive results of these experiments were not obtained for all samples and replicates. PCR sensitivity tests with dilution series of T. szidati genomic DNA as well as of PCR amplification products yielded successful amplification down to concentrations of 0.83 pg/µL and 0.008 pg/µL, respectively. Our results indicate that the presumed species specificity of PCR primers may not be guaranteed, even if primers were designed for specific species. This entails misidentification risks, particularly in areas with incomplete species inventories

DellAmpio_et_al_2013: Supplementary Data

Supplementary File Archives of "Decisive Datasets in Phylogenomics: Lessons from Studies on the Phylogenetic Relationships of Primarily Wingless Insects

First Record of Trichobilharzia physellae (Talbot, 1936) in Europe, a Possible Causative Agent of Cercarial Dermatitis

Several species of avian schistosomes are known to cause dermatitis in humans worldwide. In Europe, this applies above all to species of the genus Trichobilharzia. For Austria, a lot of data are available on cercarial dermatitis and on the occurrence of Trichobilharzia, yet species identification of trematodes in most cases is doubtful due to the challenging morphological determination of cercariae. During a survey of trematodes in freshwater snails, we were able to detect a species in the snail Physella acuta (Draparnaud, 1805) hitherto unknown for Austria, Trichobilharzia physellae; this is also the first time this species has been reported in Europe. Species identification was performed by integrative taxonomy combining morphological investigations with molecular genetic analyses. The results show a very close relationship between the parasite found in Austria and North American specimens (similarity found in CO1 ≥99.57%). Therefore, a recent introduction of T. physellae into Europe can be assumed

NJ tree based on K2P distances from 91 COI sequences of Protura.

<p>Newly sequenced specimens labeled with lab code number (HP), abbreviation for genus, and species name. Color code for genera: <i>Acerentomon</i> = violet, <i>Ionescuellum = </i>green, <i>Acerentulus</i> = orange, <i>Acerella</i> = red, <i>Eosentomon</i> = blue; Austrian sample sites are coded with different icons: Leopoldsberg = square, Eichkogel = triangle, and Twimberger Graben = circle. Bootstrap support (given below nodes) derived from 5000 replicates. Maximally supported clusters and subclusters are indicated by black dots. Genus abbreviations: <i>Aco</i> = <i>Acerentomon</i>, <i>Ion</i> = <i>Ionescuellum</i>, <i>Acu</i> = <i>Acerentulus</i>, <i>Ace</i> = <i>Acerella</i>, and <i>Eos</i> = <i>Eosentomon</i>.</p

List of morphologically determined species of Protura investigated in this study.

<p>Genus abbreviation: <i>Ace</i> = <i>Acerella</i>, <i>Aco</i> = <i>Acerentomon</i>, <i>Acu</i> = <i>Acerentulus, Eos</i> = <i>Eosentomon</i>, <i>Ion</i> = <i>Ionescuellum</i>; Locality abbreviation: LB = Leopoldsberg, TG = Twimberger Graben, EK = Eichkogel.</p

Comparison of COI and 28S rDNA in species discrimination of the genera <i>Ionescuellum</i> (<i>Ion</i>) and <i>Eosentomon</i> (<i>Eos</i>).

<p>NJ tree based on K2P distances of COI (left) and the mirrored 28S rDNA results (right). Bootstrap support (maximal support marked with full circles) derived from 5000 replicates is maximal for all species and polpulations. Color code for genera: <i>Acerentomon</i> = violet, <i>Ionescuellum</i> = green, <i>Acerentulus</i> = orange, <i>Acerella</i> = red, <i>Eosentomon</i> = blue; Austrian sample sites are coded with different icons: Leopoldsberg = square, Eichkogel = triangle, and Twimberger Graben = circle.</p