scholarly journals Constructing Phylogenetic Networks Based on the Isomorphism of Datasets

2016 ◽  
Vol 2016 ◽  
pp. 1-7
Author(s):  
Juan Wang ◽  
Zhibin Zhang ◽  
Yanjuan Li
Keyword(s):  
Molecular Evolution ◽  
Phylogenetic Trees ◽  
Phylogenetic Network ◽  
Phylogenetic Networks ◽  
The Relationship

Constructing rooted phylogenetic networks from rooted phylogenetic trees has become an important problem in molecular evolution. So far, many methods have been presented in this area, in which most efficient methods are based on the incompatible graph, such as the CASS, the LNETWORK,and the BIMLR. This paper will research the commonness of the methods based on the incompatible graph, the relationship between incompatible graph and the phylogenetic network, and the topologies of incompatible graphs. We can find out all the simplest datasets for a topologyGand construct a network for every dataset. For any one datasetC, we can compute a network from the network representing the simplest dataset which is isomorphic toC. This process will save more time for the algorithms when constructing networks.

scholarly journals Applicability of several rooted phylogenetic network algorithms for representing the evolutionary history of SARS-CoV-2

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Rosanne Wallin ◽  
Leo van Iersel ◽  
Steven Kelk ◽  
Leen Stougie
Keyword(s):  
Phylogenetic Trees ◽  
Evolutionary History ◽  
Network Inference ◽  
Phylogenetic Network ◽  
Phylogenetic Networks ◽  
Network Algorithms ◽  
Running Time ◽  
Inference Algorithms ◽  
History Of ◽  
The Impact

Abstract Background Rooted phylogenetic networks are used to display complex evolutionary history involving so-called reticulation events, such as genetic recombination. Various methods have been developed to construct such networks, using for example a multiple sequence alignment or multiple phylogenetic trees as input data. Coronaviruses are known to recombine frequently, but rooted phylogenetic networks have not yet been used extensively to describe their evolutionary history. Here, we created a workflow to compare the evolutionary history of SARS-CoV-2 with other SARS-like viruses using several rooted phylogenetic network inference algorithms. This workflow includes filtering noise from sets of phylogenetic trees by contracting edges based on branch length and bootstrap support, followed by resolution of multifurcations. We explored the running times of the network inference algorithms, the impact of filtering on the properties of the produced networks, and attempted to derive biological insights regarding the evolution of SARS-CoV-2 from them. Results The network inference algorithms are capable of constructing rooted phylogenetic networks for coronavirus data, although running-time limitations require restricting such datasets to a relatively small number of taxa. Filtering generally reduces the number of reticulations in the produced networks and increases their temporal consistency. Taxon bat-SL-CoVZC45 emerges as a major and structural source of discordance in the dataset. The tested algorithms often indicate that SARS-CoV-2/RaTG13 is a tree-like clade, with possibly some reticulate activity further back in their history. A smaller number of constructed networks posit SARS-CoV-2 as a possible recombinant, although this might be a methodological artefact arising from the interaction of bat-SL-CoVZC45 discordance and the optimization criteria used. Conclusion Our results demonstrate that as part of a wider workflow and with careful attention paid to running time, rooted phylogenetic network algorithms are capable of producing plausible networks from coronavirus data. These networks partly corroborate existing theories about SARS-CoV-2, and partly produce new avenues for exploration regarding the location and significance of reticulate activity within the wider group of SARS-like viruses. Our workflow may serve as a model for pipelines in which phylogenetic network algorithms can be used to analyse different datasets and test different hypotheses.

scholarly journals Tree-Based Unrooted Phylogenetic Networks

2017 ◽  
Vol 80 (2) ◽  
pp. 404-416 ◽  
Author(s):  
A. Francis ◽  
K. T. Huber ◽  
V. Moulton
Keyword(s):  
Gene Transfer ◽  
Horizontal Gene Transfer ◽  
Phylogenetic Tree ◽  
Phylogenetic Trees ◽  
Phylogenetic Network ◽  
Simple Graph ◽  
Phylogenetic Networks ◽  
Underlying Graph ◽  
Finite Set ◽  
Computational Properties

Abstract Phylogenetic networks are a generalization of phylogenetic trees that are used to represent non-tree-like evolutionary histories that arise in organisms such as plants and bacteria, or uncertainty in evolutionary histories. An unrooted phylogenetic network on a non-empty, finite set X of taxa, or network, is a connected, simple graph in which every vertex has degree 1 or 3 and whose leaf set is X. It is called a phylogenetic tree if the underlying graph is a tree. In this paper we consider properties of tree-based networks, that is, networks that can be constructed by adding edges into a phylogenetic tree. We show that although they have some properties in common with their rooted analogues which have recently drawn much attention in the literature, they have some striking differences in terms of both their structural and computational properties. We expect that our results could eventually have applications to, for example, detecting horizontal gene transfer or hybridization which are important factors in the evolution of many organisms.

scholarly journals Phylogenetic Trees and Networks Can Serve as Powerful and Complementary Approaches for Analysis of Genomic Data

2019 ◽  
Vol 69 (3) ◽  
pp. 593-601 ◽  
Author(s):  
Christopher Blair ◽  
Cécile Ané
Keyword(s):  
Gene Flow ◽  
Phylogenetic Trees ◽  
Evolutionary History ◽  
Incomplete Lineage Sorting ◽  
Gene Tree ◽  
Phylogenetic Network ◽  
Genomic Data ◽  
Point Of View ◽  
Phylogenetic Networks ◽  
Lineage Sorting

Abstract Genomic data have had a profound impact on nearly every biological discipline. In systematics and phylogenetics, the thousands of loci that are now being sequenced can be analyzed under the multispecies coalescent model (MSC) to explicitly account for gene tree discordance due to incomplete lineage sorting (ILS). However, the MSC assumes no gene flow post divergence, calling for additional methods that can accommodate this limitation. Explicit phylogenetic network methods have emerged, which can simultaneously account for ILS and gene flow by representing evolutionary history as a directed acyclic graph. In this point of view, we highlight some of the strengths and limitations of phylogenetic networks and argue that tree-based inference should not be blindly abandoned in favor of networks simply because they represent more parameter rich models. Attention should be given to model selection of reticulation complexity, and the most robust conclusions regarding evolutionary history are likely obtained when combining tree- and network-based inference.

scholarly journals Comparing the topology of phylogenetic network generators

2021 ◽  
Author(s):  
Remie Janssen ◽  
Pengyu Liu
Keyword(s):  
Bayesian Methods ◽  
Phylogenetic Trees ◽  
Evolutionary History ◽  
Phylogenetic Network ◽  
Random Trees ◽  
Phylogenetic Networks ◽  
Phylogeny Reconstruction ◽  
Evolutionary Analysis ◽  
Summary Statistics ◽  
History Of

Phylogenetic networks represent evolutionary history of species and can record natural reticulate evolutionary processes such as horizontal gene transfer and gene recombination. This makes phylogenetic networks a more comprehensive representation of evolutionary history compared to phylogenetic trees. Stochastic processes for generating random trees or networks are important tools in evolutionary analysis, especially in phylogeny reconstruction where they can be utilized for validation or serve as priors for Bayesian methods. However, as more network generators are developed, there is a lack of discussion or comparison for different generators. To bridge this gap, we compare a set of phylogenetic network generators by profiling topological summary statistics of the generated networks over the number of reticulations and comparing the topological profiles.

scholarly journals Display Sets of Normal and Tree-Child Networks

10.37236/9128 ◽  
2021 ◽  
Vol 28 (1) ◽  
Author(s):  
Janosch Döcker ◽  
Simone Linz ◽  
Charles Semple
Keyword(s):  
Decision Problem ◽  
Phylogenetic Trees ◽  
Phylogenetic Network ◽  
Polynomial Time Algorithm ◽  
Time Algorithm ◽  
Directed Acyclic Graphs ◽  
Phylogenetic Networks ◽  
Acyclic Graphs ◽  
Normal Network ◽  
Normal Networks

Phylogenetic networks are leaf-labelled directed acyclic graphs that are used in computational biology to analyse and represent the evolutionary relationships of a set of species or viruses. In contrast to phylogenetic trees, phylogenetic networks have vertices of in-degree at least two that represent reticulation events such as hybridisation, lateral gene transfer, or reassortment. By systematically deleting various combinations of arcs in a phylogenetic network $\mathcal N$, one derives a set of phylogenetic trees that are embedded in $\mathcal N$. We recently showed that the problem of deciding if two binary phylogenetic networks embed the same set of phylogenetic trees is computationally hard, in particular, we showed it to be $\Pi^P_2$-complete. In this paper, we establish a polynomial-time algorithm for this decision problem if the initial two networks consist of a normal network and a tree-child network; two well-studied topologically restricted subclasses of phylogenetic networks, with normal networks being more structurally constrained than tree-child networks. The running time of the algorithm is quadratic in the size of the leaf sets.

scholarly journals Contribution of recombination and selection to molecular evolution of Citrus tristeza virus

2009 ◽  
Vol 90 (6) ◽  
pp. 1527-1538 ◽  
Author(s):  
Susana Martín ◽  
Adrián Sambade ◽  
Luis Rubio ◽  
María C. Vives ◽  
Patricia Moya ◽  
...  
Keyword(s):  
Gene Flow ◽  
Molecular Evolution ◽  
Phylogenetic Trees ◽  
Phylogenetic Network ◽  
Purifying Selection ◽  
South American ◽  
Significant Gene ◽  
Selection Gene ◽  
Genomic Regions ◽  
Citrus Tristeza

The genetic variation of Citrus tristeza virus (CTV) was analysed by comparing the predominant sequence variants in seven genomic regions (p33, p65, p61, p18, p13, p20 and p23) of 18 pathogenically distinct isolates from seven different countries. Analyses of the selective constraints acting on each codon suggest that most regions were under purifying selection. Phylogenetic analysis shows diverse patterns of molecular evolution for different genomic regions. A first clade composed of isolates that are genetically close to the reference mild isolates T385 or T30 was inferred from all genomic regions. A second clade, mostly comprising virulent isolates, was defined from regions p33, p65, p13 and p23. For regions p65, p61, p18, p13 and p23, a third clade that mostly included South American isolates could not be related to any reference genotype. Phylogenetic relationships among isolates did not reflect their geographical origin, suggesting significant gene flow between geographically distant areas. Incongruent phylogenetic trees for different genomic regions suggested recombination events, an extreme that was supported by several recombination-detecting methods. A phylogenetic network incorporating the effect of recombination showed an explosive radiation pattern for the evolution of some isolates and also grouped isolates by virulence. Taken together, the above results suggest that negative selection, gene flow, sequence recombination and virulence may be important factors driving CTV evolution.

scholarly journals Biochemical and phylogenetic networks-II: X-trees and phylogenetic trees

2021 ◽  
Vol 59 (3) ◽  
pp. 699-718
Author(s):  
R. Sundara Rajan ◽  
A. Arul Shantrinal ◽  
K. Jagadeesh Kumar ◽  
T. M. Rajalaxmi ◽  
Indra Rajasingh ◽  
...  
Keyword(s):  
Phylogenetic Trees ◽  
Phylogenetic Networks

scholarly journals Phylogenetic Analysis to Explore the Association Between Anti-NMDA Receptor Encephalitis and Tumors Based on microRNA Biomarkers

Biomolecules ◽  
2019 ◽  
Vol 9 (10) ◽  
pp. 572 ◽  
Author(s):  
Wang
Keyword(s):  
Phylogenetic Analysis ◽  
Nmda Receptor ◽  
Phylogenetic Trees ◽  
Tumor Resection ◽  
Autoimmune Disorder ◽  
Control Of Gene Expression ◽  
Nmda Receptor Encephalitis ◽  
Nmdar Encephalitis ◽  
Non Coding Rna ◽  
The Relationship

MicroRNA (miRNA) is a small non-coding RNA that functions in the epigenetics control of gene expression, which can be used as a useful biomarker for diseases. Anti-NMDA receptor (anti-NMDAR) encephalitis is an acute autoimmune disorder. Some patients have been found to have tumors, specifically teratomas. This disease occurs more often in females than in males. Most of them have a significant recovery after tumor resection, which shows that the tumor may induce anti-NMDAR encephalitis. In this study, I review microRNA (miRNA) biomarkers that are associated with anti-NMDAR encephalitis and related tumors, respectively. To the best of my knowledge, there has not been any research in the literature investigating the relationship between anti-NMDAR encephalitis and tumors through their miRNA biomarkers. I adopt a phylogenetic analysis to plot the phylogenetic trees of their miRNA biomarkers. From the analyzed results, it may be concluded that (i) there is a relationship between these tumors and anti-NMDAR encephalitis, and (ii) this disease occurs more often in females than in males. This sheds light on this issue through miRNA intervention.

scholarly journals Mitochondrial DNAs provide insight into trypanosome phylogeny and molecular evolution

2020 ◽  
Author(s):  
Christopher Kay ◽  
Tom A Williams ◽  
Wendy Gibson
Keyword(s):  
Molecular Evolution ◽  
Trypanosoma Brucei ◽  
Rna Editing ◽  
Phylogenetic Trees ◽  
Nucleotide Composition ◽  
Sub Saharan Africa ◽  
African Trypanosomes ◽  
Animal Pathogens ◽  
Recent Emergence ◽  
The Impact

Abstract Background: Trypanosomes are single-celled eukaryotic parasites characterised by the unique biology of their mitochondrial DNA (mtDNA). African livestock trypanosomes impose a major burden on agriculture across sub-Saharan Africa, but are poorly understood compared to those that cause sleeping sickness and Chagas disease in humans. Here we explore the potential of trypanosome mtDNA to study the evolutionary history of trypanosomes and the molecular evolution of their mtDNAs.Results: We used long-read sequencing to completely assemble mtDNAs from four previously uncharacterized African trypanosomes, and leveraged these assemblies to scaffold and assemble a further 103 trypanosome mtDNAs from published short-read data. While synteny was largely conserved, there were repeated, independent losses of Complex I genes. Comparison of edited and non-edited genes revealed the impact of RNA editing on nucleotide composition, with non-edited genes approaching the limits of GC loss. African tsetse-transmitted trypanosomes showed high levels of RNA editing compared to other trypanosomes. Whole mtDNA coding regions were used to construct time-resolved phylogenetic trees, revealing deep divergence events among isolates of the pathogens Trypanosoma brucei and T. congolense .Conclusions: Our mtDNA data represents a new resource for experimental and evolutionary analyses of trypanosome phylogeny, molecular evolution and function. Molecular clock analyses yielded a timescale for trypanosome evolution congruent with major biogeographical events in Africa and revealed the recent emergence of Trypanosoma brucei gambiense and T. equiperdum , major human and animal pathogens.

scholarly journals Whole genome comparisons of Staphylococcus agnetis isolates from cattle and chickens

2020 ◽  
Author(s):  
Abdulkarim Shwani ◽  
Pamela R. F. Adkins ◽  
Nnamdi S. Ekesi ◽  
Adnan Alrubaye ◽  
Michael J. Calcutt ◽  
...  
Keyword(s):  
Dairy Cattle ◽  
Phylogenetic Trees ◽  
University Of Missouri ◽  
Commercial Broiler ◽  
Chicken Isolate ◽  
Broiler Farm ◽  
Molecular Relationships ◽  
The University ◽  
The Relationship ◽  
Genome Comparisons

AbstractS. agnetis has been previously associated with subclinical or clinically mild cases of mastitis in dairy cattle and is one of several Staphylococcal species that have been isolated from the bone and blood of lame broilers. We were the first to report that S. agnetis could be obtained frequently from bacterial chondronecrosis with osteomyelitis (BCO) lesions of lame broilers. Further, we showed that a particular isolate of S. agnetis, chicken isolate 908, can induce lameness in over 50% of exposed chickens, far exceeding normal BCO incidences in broiler operations. We have previously reported the assembly and annotation of the genome of isolate 908. To better understand the relationship between dairy cattle and broiler isolates, we assembled 11 additional genomes for S. agnetis isolates, including an additional chicken BCO strain, and ten isolates from milk, mammary gland secretions or udder skin, from the collection at the University of Missouri. To trace phylogenetic relationships, we constructed phylogenetic trees based on multi-locus sequence typing, and Genome-to-Genome Distance Comparisons. Chicken isolate 908 clustered with two of the cattle isolates along with three isolates from chickens in Denmark and an isolate of S. agnetis we isolated from a BCO lesion on a commercial broiler farm in Arkansas. We used a number of BLAST tools to compare the chicken isolates to those from cattle and identified 98 coding sequences distinguishing isolate 908 from the cattle isolates. None of the identified genes explain the differences in host or tissue tropism. These analyses are critical to understanding how Staphylococci colonize and infect different hosts and potentially how they can transition to alternative niches (bone vs dermis).ImportanceStaphylococcus agnetis has been recently recognized as associated with disease in dairy cattle and meat type chickens. The infections appear to be limited in cattle and systemic in broilers. This report details the molecular relationships between cattle and chicken isolates in order to understand how this recently recognized species infects different hosts with different disease manifestations. The data show the chicken and cattle isolates are very closely related but the chicken isolates all cluster together suggesting a single jump from cattle to chickens.

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