Biotectonics of Sulawesi: Principles, methodology, and area relationships

Biotectonics is an approach to historical biogeography based on the analysis of independently derived biological and tectonic data, which we demonstrate using the island of Sulawesi as an example. We describe the tectonic development of Sulawesi and discuss the relationship between tectonic models and phylogenetic hypotheses. We outline the problem of interpreting areagrams based on single phylogenies and stress the importance of combining all available data into a general areagram. We analysed the distributions of Sulawesi area of endemism endemics (AEEs) using 30 published phylogenies, which were converted into paralogy-free taxon-area cladograms using the programme LisBeth (Zaragüeta-Bagalis et al. 2012) from which Adam’s consensus trees were constructed using PAUP (Swofford 2002). The results of our analyses show that the relationship between the areas of endemism is congruent with the terrane history of the island. A further 79 phylogenies of Sulawesi species with extralimital distributions were analysed to determine area relationships of Sulawesi within the broader Indo-Pacific region. We demonstrate the utility of data partitioning when dealing with areas that are geologically and biologically composite by showing that analysing Asian and Australasian elements of the Sulawesi biota separately produced general areagrams that avoid artifice and are interpretable in the light of current tectonic models.

ConTreeDP: A consensus method of tumor trees based on maximum directed partition support problem

Phylogenetic inference has become a crucial tool for interpreting cancer genomic data, but continuing advances in our understanding of somatic mutability in cancer, genomic technolo- gies for profiling it, and the scale of data available have created a persistent need for new algorithms able to deal with these challenges. One particular need has been for new forms of consensus tree algorithms, which present special challenges in the cancer space for dealing with heterogeneous data, short evolutionary time scales, and rapid mutation by a wide variety of somatic mutability mechanisms. We develop a new consensus tree method for clonal phy- logenetics, ConTreeDP, based on a formulation of the Maximum Directed Partition Support Consensus Tree (MDPSCT) problem. We demonstrate theoretically and empirically that our approach can efficiently and accurately compute clonal consensus trees from cancer genomic data.

Building alternative consensus trees and supertrees using k-means and Robinson and Foulds distance

Each gene has its own evolutionary history which can substantially differ from the evolutionary histories of other genes. For example, some individual genes or operons can be affected by specific horizontal gene transfer and recombination events. Thus, the evolutionary history of each gene should be represented by its own phylogenetic tree which may display different evolutionary patterns from the species tree that accounts for the main patterns of vertical descent. The output of traditional consensus tree or supertree inference methods is a unique consensus tree or supertree. Here, we describe a new efficient method for inferring multiple alternative consensus trees and supertrees to best represent the most important evolutionary patterns of a given set of phylogenetic trees (i.e. additive trees or X-trees). We show how a specific version of the popular k-means clustering algorithm, based on some interesting properties of the Robinson and Foulds topological distance, can be used to partition a given set of trees into one (when the data are homogeneous) or multiple (when the data are heterogeneous) cluster(s) of trees. We adapt the popular Caliński-Harabasz, Silhouette, Ball and Hall, and Gap cluster validity indices to tree clustering with k-means. A special attention is paid to the relevant but very challenging problem of inferring alternative supertrees, built from phylogenies constructed for different, but mutually overlapping, sets of taxa. The use of the Euclidean approximation in the objective function of the method makes it faster than the existing tree clustering techniques, and thus perfectly suitable for the analysis of large genomic datasets. In this study, we apply it to discover alternative supertrees characterizing the main patterns of evolution of SARS-CoV-2 and the related betacoronaviruses.

Revision of the Ropalopus ungaricus/insubricus group (Coleoptera: Cerambycidae: Callidiini) from the western Palaearctic region

This paper revises the taxonomy and phylogeny of Ropalopus (Coleoptera: Cerambycidae: Callidiini) species belonging to the taxonomically intricate Ropalopus ungaricus/insubricus group from the western Palaearctic. Specimens from all taxa were studied and compared. The key characters, including the male terminalia, were examined by means of scanning electron microscopy. High-quality stacked photographs of the habitus of the specimens (dorsal, ventral) are presented. The phylogenetic analyses were based on 34 adult morphological characters. Both the strict and majority consensus trees revealed the monophyly of the revised group. Identification keys are provided for every taxon from this group, and their geographical distributions are also mapped. All European populations are reduced to subspecies of Ropalopus ungaricus. Additionally, a new subspecies from Greece, Ropalopus ungaricus ossae subsp. nov., is described and illustrated. A new synonymy for Ropalopus insubricus fischeri is proposed: Callidium insubricum = Callidium fischeri. Ropalopus nataliyae, which was described based on only a single female, is herein redescribed owing to the collection of abundant new material. Apart from geographical barriers, the main differentiating factor in this group is proved to be the elevation above sea level. Taxa of the R. ungaricus/insubricus group are therefore allopatric or, when parapatric, are isolated by elevation.

Phylogenetic relationships of Echeveria (Crassulaceae) and related genera from Mexico, based on three DNA barcoding loci

Mexico is considered as diversification and endemism center of the genus Echeveria. Previous tree inference studies have shown the genus to be non-monophyletic in relation to other genera, but sampling for Echeveria has been poor, and has not allowed to understand the relationships within the genus. In this work, Bayesian and maximum likelihood phylogenetic analysis were performed, using a combined standard DNA barcoding loci matrix (rbcL, matK and ITS2) and GenBank ITS2 accessions for Graptopetalum, some Sedum and few Echeveria taxa. The selection of taxa encompasses all current infrageneric categories of the genus Echeveria, as well as species from genera previously associated with it. The inferred consensus trees suggested that Echeveria is paraphyletic. Instead, four main clades were retrieved within the “Echeveria group”: Clade I includes exclusively Pachyphytum species. Clade II is formed by the majority of series Urbiniae; Clade III encompasses series Chloranthae, Ciliatae, Echeveria, Mucronatae, Nudae, Racemosae, Thyrsiflorae, Pachyphytum cuicatecananum and Thompsonella; Clade IV contains series Angulatae, Gibbiflorae, Occidentales, Pruinosae, Secundae, some Urbiniae species, Valvatae. genera Cremnophila, Graptopetalum and Reidmorania. Pachyphytum and Thompsonella were retrieved as monophyletic groups, but the first outside Echeveria while the latter inside. Results of our study suggest that Echeveria and the Echeveria Group require a redefinition.

The phylogeny of desmostylians revisited: proposal of new clades based on robust phylogenetic hypotheses

Background Desmostylia is a clade of extinct aquatic mammals with no living members. Today, this clade is considered belonging to either Afrotheria or Perissodactyla. In the currently-accepted taxonomic scheme, Desmostylia includes two families, 10 to 12 genera, and 13–14 species. There have been relatively few phylogenetic analyses published on desmostylian interrelationship compared to other vertebrate taxa, and two main, alternative phylogenetic hypotheses have been proposed in previous studies. One major problem with those previous studies is that the numbers of characters and OTUs were small. Methods In this study, we analyzed the phylogenetic interrelationship of Desmostylia based on a new data matrix that includes larger numbers of characters and taxa than in any previous studies. The new data matrix was compiled mainly based on data matrices of previous studies and included three outgroups and 13 desmostylian ingroup taxa. Analyses were carried out using five kinds of parsimonious methods. Results Strict consensus trees of the most parsimonious topologies obtained in all analyses supported the monophyly of Desmostylidae and paraphyly of traditional Paleoparadoxiidae. Based on these results, we propose phylogenetic definitions of the clades Desmostylidae and Paleoparadoxiidae based on common ancestry.

Summarizing the solution space in tumor phylogeny inference by multiple consensus trees

Motivation Cancer phylogenies are key to studying tumorigenesis and have clinical implications. Due to the heterogeneous nature of cancer and limitations in current sequencing technology, current cancer phylogeny inference methods identify a large solution space of plausible phylogenies. To facilitate further downstream analyses, methods that accurately summarize such a set T of cancer phylogenies are imperative. However, current summary methods are limited to a single consensus tree or graph and may miss important topological features that are present in different subsets of candidate trees. Results We introduce the Multiple Consensus Tree (MCT) problem to simultaneously cluster T and infer a consensus tree for each cluster. We show that MCT is NP-hard, and present an exact algorithm based on mixed integer linear programming (MILP). In addition, we introduce a heuristic algorithm that efficiently identifies high-quality consensus trees, recovering all optimal solutions identified by the MILP in simulated data at a fraction of the time. We demonstrate the applicability of our methods on both simulated and real data, showing that our approach selects the number of clusters depending on the complexity of the solution space T. Availability and implementation https://github.com/elkebir-group/MCT. Supplementary information Supplementary data are available at Bioinformatics online.

A Corpus-based Computational Stylometric Analysis of the Word “Árabe” in Three Spanish Generación Del 98 Writers

Although the Generation of ’98 writers represents a group of renown Spanish novelists, philosophers, essayists and poets active during the 1898 Spanish-American war, no previous studies have attempted to analyze the diverse linguistic and stylistic features employed by such writers. This study aims to use computational stylometry to detect hidden stylistic and linguistic patterns employed by three Generation of ’98 writers, namely Pío Baroja, Vicente Blasco Ibáñez and Miguel de Unamuno. We employ a large corpus comprising 1,702,243 words representing nineteen works by the three writers. Several rigorous criteria were satisfied in designing the corpora such as authorship, genre, topic and register. Concordance, wordclouds, consensus trees, multidimensional and cluster analyses were performed to reveal the different stylistic and linguistic patterns used by the three writers. Although we focus solely on the use of the word “árabe”, we show that computational stylometry techniques can be used to help detect hidden stylistic and linguistic patterns employed by different writers. This result is significant since it can help the reader navigate across various possibilities of expressions and terminologies employed by different writers.