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opencc-by-4.0Jun 2023View details →

Fig. 5 in New record and new species of Laubierpholoe Pettibone, 1992 (Annelida, Sigalionidae) from the soft bottom of submarine caves near Marseille (Mediterranean Sea) with discussion on phylogeny and ecology of the genus

Fig. 5. Laubierpholoe massiliana Zhadan sp. nov., line drawings. A. Anterior end, dorso-anterior view. B. Notochaeta and bidentate neurochaeta. C. Parapodium, anterior view. D. Jaw. Abbreviations: ah = anterior horns; dtc = dorsal tentacular cirrus; ma = median antenna; ne = neuropodium; no = notopodium; p = prostomium; pa = palp; vbc = ventral buccal cirrus; vc = ventral cirrus; vtc = ventral tentacular cirrus. Arrows indicate papillae.

opencc-by-4.0Jun 2023View details →

Fig. 6. Bayesian phylogenetic tree obtained with the 18S rRNA and 28S in New record and new species of Laubierpholoe Pettibone, 1992 (Annelida, Sigalionidae) from the soft bottom of submarine caves near Marseille (Mediterranean Sea) with discussion on phylogeny and ecology of the genus

Fig. 6. Bayesian phylogenetic tree obtained with the 18S rRNA and 28S rRNA concatenated dataset showing position of Laubierpholoe massiliana Zhadan sp. nov. within Sigalionidae Kinberg, 1856. Posterior probabilities and bootstrap values are shown for each medium supported node.

opencc-by-4.0Jun 2023View details →

Fig. 3 in New record and new species of Laubierpholoe Pettibone, 1992 (Annelida, Sigalionidae) from the soft bottom of submarine caves near Marseille (Mediterranean Sea) with discussion on phylogeny and ecology of the genus

Fig. 3. Laubierpholoe massiliana Zhadan sp. nov., SEM. A. ZMMSU WS12292, general view. B. ZMMSU WS14001, general view, elytra omitted. C. ZMMSU WS13977, elytra. D. ZMMSU WS14001, anterior end, dorsal view. E. Same, dorso-anterior view. F. ZMMSU WS16511, anterior end, dorso-anterior view, median antenna broken. G. ZMMSU WS16511, dorso-anterior view. Abbreviations: ah = anterior horns; dtc = dorsal tentacular cirrus; e = elytrophores; ma = median antenna; ne = neuropodium; no = notopodium; p = prostomium; pa = palp; ph = pharynx; vbc = ventral buccal cirrus; vtc = ventral tentacular cirrus. Arrows indicate papillae.

Fig. 3 in Phylogeny of Maculinea blues (Lepidoptera: Lycaenidae) based on morphological and ecological characters: evolution of parasitic myrmecophily

Fig. 3. One of the four equally most parsimonious trees (length 306, CI 0.33, RI 0.63; chosen at random: individual source trees differ only in position of terminals within Phengaris, M. teleius and M. alcon group: see Fig. 2), with character states that support individual clades. Nonhomoplastic autapomorphies are black, homoplastic apomorphies white. Numbers above branches refer to characters, numbers below branches to character states (see Appendix 1 for character descriptions).

Fig. 4 in Phylogeny of Maculinea blues (Lepidoptera: Lycaenidae) based on morphological and ecological characters: evolution of parasitic myrmecophily

Fig. 4. Evolution of the life history traits of Maculinea butterflies and their relatives. Only the species for which states of all relevant characters are reliably well-known are included (see Table 1), but the overall topology of the tree including all terminals (Figs 2 & 3) is preserved. (A) Myrmecophily. M. nausithous is optimized as a modified predatory species (see ''Evolution of life histories''). (B) Host plants and habitat associations. Rosids and asterids are two well-supported clades of eudicot angiosperm plants (see Angiosperm Phylogeny Group, 2003): Fabaceae and Rosaceae are included in the former, Lamiaceae, Gentianaceae, and Campanulaceae in the latter. In some cases, character-state optimization is derived from the all-species tree (Fig. 3).

Fig. 1 in Phylogeny of Maculinea blues (Lepidoptera: Lycaenidae) based on morphological and ecological characters: evolution of parasitic myrmecophily

Fig. 1. System of coding of wing pattern traits used in the phylogenetic study of Maculinea and their relatives.

Fig. 2 in Phylogeny of Maculinea blues (Lepidoptera: Lycaenidae) based on morphological and ecological characters: evolution of parasitic myrmecophily

Fig. 2. Strict consensus of the four equally most parsimonious trees (length 306, CI 0.33, RI 0.63) showing proposed phylogenetic relationships within the ''Glaucopsyche-section'' of Lycaenidae: Polyommatini. Bootstrap and Bremer support are shown above and below the nodes, respectively.

Supplementary data for: DNA sequences are as useful as protein sequences for inferring deep phylogenies

Inference of deep phylogenies has almost exclusively used protein rather than DNA sequences, based on the perception that protein sequences are less prone to homoplasy and saturation or to issues of compositional heterogeneity than DNA sequences. Here we analyze a model of codon evolution under an idealized genetic code and demonstrate that those perceptions may be misconceptions. We conduct a simulation study to assess the utility of protein versus DNA sequences for inferring deep phylogenies, with protein-coding data generated under models of heterogeneous substitution processes across sites in the sequence and among lineages on the tree, and then analyzed using nucleotide, amino acid, and codon models. Analysis of DNA sequences under nucleotide-substitution models (possibly with the third codon positions excluded) recovered the correct tree at least as often as analysis of the corresponding protein sequences under modern amino acid models. We also applied the different data-analysis strategies to an empirical dataset to infer the metazoan phylogeny. Our results from both simulated and real data suggest that DNA sequences may be as useful as proteins for inferring deep phylogenies and should not be excluded from such analyses. Analysis of DNA data under nucleotide models has a major computational advantage over protein-data analysis, potentially making it feasible to use advanced models that account for among-site and among-lineage heterogeneity in the nucleotide-substitution process in inference of deep phylogenies.

Deep learning from phylogenies for diversification analyses

Birth-death models are widely used in combination with species phylogenies to study past diversification dynamics. Current inference approaches typically rely on likelihood-based methods. These methods are not generalizable, as a new likelihood formula must be established each time a new model is proposed; for some models, such a formula is not even tractable. Deep learning can bring solutions in such situations, as deep neural networks can be trained to learn the relation between simulations and parameter values as a regression problem. In this paper, we adapt a recently developed deep learning method from pathogen phylodynamics to the case of diversification inference, and we extend its applicability to the case of the inference of state-dependent diversification models from phylogenies associated with trait data. We demonstrate the accuracy and time efficiency of the approach for the time-constant homogeneous birth-death model and the Binary-State Speciation and Extinction model. Finally, we illustrate the use of the proposed inference machinery by reanalyzing a phylogeny of primates and their associated ecological role as seed dispersers. Deep learning inference provides at least the same accuracy as likelihood-based inference while being faster by several orders of magnitude, offering a promising new inference approach for deployment of future models in the field.

FIG. 2 in Structural and functional genes, and highly repetitive sequences commonly used in the phylogeny and species concept of the phylum Cyanobacteria

FIG. 2. — Phylogeny of common or less studied genetic markers. According to the literature review,less common studied genetic marker has been highlighted.

FIG. 1. — A in Structural and functional genes, and highly repetitive sequences commonly used in the phylogeny and species concept of the phylum Cyanobacteria

FIG. 1. — A summary of structural and functional genes, and highly repetitive sequences commonly used in the phylogeny of cyanobacteria.

opencc-zeroJul 2023View details →

Data from: A transcriptome-based phylogeny of Scarabaeoidea confirms the sister group relationship of dung beetles and phytophagous pleurostict scarabs (Coleoptera)

Scarab beetles (Scarabaeidae) are a diverse and ecologically important group of angiosperm-associated insects. As conventionally understood, scarab beetles comprise two major lineages: dung beetles and the phytophagous Pleurosticti. However, previous phylogenetic analyses have not been able to convincingly answer the question whether or not the two lineages form a monophyletic group. Here we report our results from phylogenetic analyses of more than 4,000 genes mined from transcriptomes of more than 50 species of Scarabaeidae and non-scarabaeid Scarabaeoidea. Our results provide convincing support for the monophyly of Scarabaeidae, confirming the debated sister group relationship of dung beetles and phytophagous pleurostict scarabs. Supermatrix-based maximum likelihood and multispecies coalescent phylogenetic analyses strongly imply the subfamily Melolonthinae as currently understood being paraphyletic. We consequently suggest various changes in the systematics of Melolonthinae: Sericinae Kirby, 1837 stat. rest. and sensu n. to include the tribes Sericini, Ablaberini and Diphucephalini, and Sericoidinae Erichson, 1847 stat. rest. and sensu n. to include the tribes Automoliini, Heteronychini, Liparetrini, Maechidiini, Scitalini, Sericoidini, and Phyllotocini. Both subfamilies appear to consistently form a monophyletic sister group to all remaining subfamilies so far included within pleurostict scarabs except Orphninae. Our results represent a major step towards understanding the diversification history of one of the largest angiosperm-associated radiations of beetles.

Fig. 2 in Morphology and phylogeny of a new polychaete, Prionospio expansa (Annelida: Spionidae) from the intertidal zone of the Yellow Sea, Korea

Fig. 2. Drawing of Prionospio expansa sp. nov., paratype (NIBRIV0000900992). A. Anterior body without palps. B–E. Parapodium from chaetigers 2–5, front view. F. Unilimbate capillary from first notopodium. G. Ventral sabre chaeta from chaetiger 12. H. Neuropodial hooded hook from chaetiger 17. Scale bars: A = 0.2 mm; B–E = 0.1 mm; F–H = 20 μm.

Fig. 4 in Morphology and phylogeny of a new polychaete, Prionospio expansa (Annelida: Spionidae) from the intertidal zone of the Yellow Sea, Korea

Fig. 4. SEM images of two Prionospio species from Korean waters. A–I. Prionospio expansa sp. nov. A–B, D–F. Paratype (NIBRIV0000901890). C, G–I. Paratype (NIBRIV0000901891). J–K. Korean Prionospio japonica Okuda, 1935, non-type. A. Entire body without palp, dorsal view. B. Anterior end with seven chaetigers, dorsolateral view. C. Anterior end with eight chaetigers, dorsal view. D. Anterior end, front view. E. Frontal margin of prostomium, arrows indicating frontal small peaks. F. Pygidium with middorsal cirrus and paired ventral lappets. G. Hook of middle chaetiger, hood removed, lateral view. H. Hook of posterior chaetiger, lateral view. I. Hook of posterior chaetiger, ventrolateral view. J. Anterior end with seven chaetigers, dorsolateral view. K. Pygidium. Abbreviation: tcb = transverse ciliated bands. Scale bars: A = 0.5 mm; B–D = 0.1 mm; E = 10 μm; F = 20 μm; G = 2 μm; H–I = 1 μm; J–K = 0.2 mm.

Fig. 3 in Morphology and phylogeny of a new polychaete, Prionospio expansa (Annelida: Spionidae) from the intertidal zone of the Yellow Sea, Korea

Fig. 3. Images of Prionospio expansa sp. nov. A, C. Holotype (NIBRIV0000900991). B. Paratype (NIBRIV0000901000). D–J. Paratype (NIBRIV0000900992). A. Entire body with palps. B. Live specimen, dorsolateral view. C. Anterior end with palps, dorsal view. D. Anterior end without palps, dorsal view. E. Chaetiger 2, front view, branchia missing. F. Chaetiger 3, front view. G. Chaetiger 5, front view. H. Unilimbate capillary of first monopodium. I. Sabre chaeta of chaetiger 12. J. Lateral view of hooded hook in chaetiger 17, inset indicating front view of hooded hook. Abbreviation: pig = pigmentation. Scale bars: A = 0.5 mm; B–D = 0.2 mm; E–G = 50 μm; H–I = 20 μm; J = 10 μm.

Fig. 1 in Morphology and phylogeny of a new polychaete, Prionospio expansa (Annelida: Spionidae) from the intertidal zone of the Yellow Sea, Korea

Fig. 1. Map of the sampling sites and habitat of Prionospio expansa sp. nov. A. Map of sampling locations: type locality (red star) and other examined specimens collected (black circle). B. General view of type locality. C. Live worm inhabiting sandy sediment, scale bar: 5 mm.

Fig. 5 in Morphology and phylogeny of a new polychaete, Prionospio expansa (Annelida: Spionidae) from the intertidal zone of the Yellow Sea, Korea

Fig. 5. Relationships between the total chaetigers and the first appearances of neuro- and notopodial hooks in Prionospio expansa sp. nov.

opencc-by-4.0Aug 2023View details →

16S rRNA phylogeny and clustering is not a reliable proxy for genome-based taxonomy in Streptomyces

This file is intended as supplementary information for a forthcoming publication: 16S rRNA phylogeny and clustering is not a reliable proxy for genome-based taxonomy in Streptomyces.

opencc-by-4.0Aug 2023View details →

Fig. 1. Phylogeny and habitus shots. A. Maximum Likelihood phylogeny for the genus Aname L. Koch, 1873 in Description of five new Aname L. Koch, 1873 (Araneae, Anamidae) species collected on Bush Blitz expeditions

Fig. 1. Phylogeny and habitus shots. A. Maximum Likelihood phylogeny for the genus Aname L. Koch, 1873 showing major clades and the position of new species described herein (blue taxa), support values on the phylogeny show the results of 1000 ultrafast bootstrap replicates: black circles = ≥ 95%; grey circles = 80–94%; support values less than 80% are written. Support values for some very shallow intraspecific nodes have been removed for clarity. Photos on the right (by M. Harvey) show: B. Aname ningaloo sp. nov. ♀ (WAM T148012). C. Aname salina sp. nov. ♀ (WAM T148135). D. A. salina sp. nov. ♂ (WAM T153270).