The Generalized Robinson-Foulds Distance for Phylogenetic Trees

A forest is more than its trees: haplotypes and ancestral recombination graphs

Foreshadowing haplotype-based methods of the genomics era, it is an old observation that the "junction" between two distinct haplotypes produced by recombination is inherited as a Mendelian marker. In a genealogical context, this recombination-mediated information reflects the persistence of ancestral haplotypes across local genealogical trees in which they do not represent coalescences. We show how these non-coalescing haplotypes ("locally-unary nodes") may be inserted into ancestral recombination graphs (ARGs), a compact but information-rich data structure describing the genealogical relationships among recombinant sequences. The resulting ARGs are smaller, faster to compute with, and the additional ancestral information that is inserted is nearly always correct where the initial ARG is correct. We provide efficient algorithms to infer locally-unary nodes within existing ARGs, and explore some consequences for ARGs inferred from real data. To do this, we introduce new metrics of agreement and disagreement between ARGs that, unlike previous methods, consider ARGs as describing relationships between haplotypes rather than just a collection of trees.

Piikun: an information theoretic toolkit for analysis and visualization of species delimitation metric space

BACKGROUND

Existing software for comparison of species delimitation models do not provide a (true) metric or distance functions between species delimitation models, nor a way to compare these models in terms of relative clustering differences along a lattice of partitions.

RESULTS

Piikun is a Python package for analyzing and visualizing species delimitation models in an information theoretic framework that, in addition to classic measures of information such as the entropy and mutual information [1], provides for the calculation of the Variation of Information (VI) criterion [2], a true metric or distance function for species delimitation models that is aligned with the lattice of partitions.

CONCLUSIONS

Piikun is available under the MIT license from its public repository ( https://github.com/jeetsukumaran/piikun ), and can be installed locally using the Python package manager 'pip'.

Microbiome divergence of marine gastropod species separated by the Isthmus of Panama

The rise of the Isthmus of Panama separated the populations of many marine organisms, which then diverged into new geminate sister species currently living in the Eastern Pacific Ocean and the Caribbean Sea. However, we know very little about how such evolutionary divergences of host species have shaped the compositions of their microbiomes. Here, we compared the microbiomes of whole-body and shell-surface samples of geminate species of marine gastropods in the genera Cerithium and Cerithideopsis to those of congeneric outgroups. Our results suggest that the effects of ~3 million years of separation and isolation on microbiome composition varied among host genera and between sample types within the same hosts. In the whole-body samples, microbiome compositions of geminate species pairs tended to be similar, likely due to host filtering, although the strength of this relationship varied among the two groups and across similarity metrics. Shell-surface microbiomes show contrasting patterns, with co-divergence between the host taxa and a small number of microbial clades evident in Cerithideopsis but not Cerithium. These results suggest that (i) isolation of host populations after the rise of the Isthmus of Panama affected microbiomes of geminate hosts in a complex and host-specific manner, and (ii) host-associated microbial taxa respond differently to vicariance events than the hosts themselves.IMPORTANCEWhile considerable work has been done on evolutionary divergences of marine species in response to the rise of the Isthmus of Panama, which separated two previously connected oceans, how this event shaped the microbiomes of these marine hosts remains poorly known. Using whole-body and shell-surface microbiomes of closely related gastropod species from opposite sides of the Isthmus, we show that divergences of microbial taxa after the formation of the Isthmus are often not concordant with those of their gastropod hosts. Our results show that evolutionary responses of marine gastropod-associated microbiomes to major environmental perturbations are complex and are shaped more by local environments than host evolutionary history.

Comparison of phylogenetic trees defined on different but mutually overlapping sets of taxa: A review

Phylogenetic trees represent the evolutionary relationships and ancestry of various species or groups of organisms. Comparing these trees by measuring the distance between them is essential for applications such as tree clustering and the Tree of Life project. Many distance metrics for phylogenetic trees focus on trees defined on the same set of taxa. However, some problems require calculating distances between trees with different but overlapping sets of taxa. This study reviews state-of-the-art distance measures for such trees, covering six major approaches, including the constraint-based Robinson-Foulds (RF) distance RF(-), the completion-based RF(+), the generalized RF (GRF), the dissimilarity measure, the vectorial tree distance, and the geodesic distance in the extended Billera-Holmes-Vogtmann tree space. Among these, three RF-based methods, RF(-), RF(+), and GRF, were examined in detail on generated clusters of phylogenetic trees defined on different but mutually overlapping sets of taxa. Additionally, we reviewed nine related techniques, including leaf imputation methods, the tree edit distance, and visual comparison. A comparison of the related distance measures, highlighting their principal advantages and shortcomings, is provided. This review offers valuable insights into their applicability and performance, guiding the appropriate use of these metrics based on tree type (rooted or unrooted) and information type (topological or branch lengths).

Weighted centroid trees: a general approach to summarize phylogenies in single-labeled tumor mutation tree inference

MOTIVATION

Tumor trees, which depict the evolutionary process of cancer, provide a backbone for discovering recurring evolutionary processes in cancer. While they are not the primary information extracted from genomic data, they are valuable for this purpose. One such extraction method involves summarizing multiple trees into a single representative tree, such as consensus trees or supertrees.

RESULTS

We define the "weighted centroid tree problem" to find the centroid tree of a set of single-labeled rooted trees through the following steps: (i) mapping the given trees into the Euclidean space, (ii) computing the weighted centroid matrix of the mapped trees, and (iii) finding the nearest mapped tree (NMTP) to the centroid matrix. We show that this setup encompasses previously studied parent-child and ancestor-descendent metrics as well as the GraPhyC and TuELiP consensus tree algorithms. Moreover, we show that, while the NMTP problem is polynomial-time solvable for the adjacency embedding, it is NP-hard for ancestry and distance mappings. We introduce integer linear programs for NMTP in different setups where we also provide a new algorithm for the case of ancestry embedding called 2-AncL2, that uses a novel weighting scheme for ancestry signals. Our experimental results show that 2-AncL2 has a superior performance compared to available consensus tree algorithms. We also illustrate our setup's application on providing representative trees for a large real breast cancer dataset, deducing that the cluster centroid trees summarize reliable evolutionary information about the original dataset.

AVAILABILITY AND IMPLEMENTATION

https://github.com/vasei/WAncILP.

The k-Robinson-Foulds Dissimilarity Measures for Comparison of Labeled Trees

Understanding the mutational history of tumor cells is a critical endeavor in unraveling the mechanisms that drive the onset and progression of cancer. Modeling tumor cell evolution with labeled trees motivates researchers to develop different measures to compare labeled trees. Although the Robinson-Foulds (RF) distance is widely used for comparing species trees, its applicability to labeled trees reveals certain limitations. This study introduces the k-RF dissimilarity measures, tailored to address the challenges of labeled tree comparison. The RF distance is succinctly expressed as n-RF in the space of labeled trees with n nodes. Like the RF distance, the k-RF is a pseudometric for multiset-labeled trees and becomes a metric in the space of 1-labeled trees. By setting k to a small value, the k-RF dissimilarity can capture analogous local regions in two labeled trees with different size or different labels.

Application of nanopore sequencing in diagnosis of secondary infections in patients with severe COVID-19

To explore the application value of nanopore sequencing technique in the diagnosis and treatment of secondary infections in patients with severe coronavirus disease 2019 (COVID-19). A total of 77 clinical specimens from 3 patients with severe COVID-19 were collected. After heat inactivation, all samples were subjected to total nucleic acid extraction based on magnetic bead enrichment. The extracted DNA was used for DNA library construction, then nanopore real-time sequencing detection was performed. The sequencing data were subjected to Centrifuge software database species matching and R program differential analysis to obtain potential pathogen identification. Nanopore sequencing results were compared with respiratory pathogen qPCR panel screening and conventional microbiological testing results to verify the effectiveness of nanopore sequencing detection. Nanopore sequencing results showed that positive pathogen were obtained in 44 specimens (57.1%). The potential pathogens identified by nanopore sequencing included , , and , et al. , , were also detected in clinical microbiological culture-based detection; was detected in respiratory pathogen screening qPCR panel; was only detected by the nanopore sequencing technique. Comprehensive considerations with the clinical symptoms, the patient was treated with antibiotics against , and the infection was controlled. Nanopore sequencing may assist the diagnosis and treatment of severe COVID-19 patients through rapid identification of potential pathogens.