List of software for ancestral reconstruction.

List of software for ancestral reconstruction.</p

Ancestral Reconstruction - Fig 5

<p><b>Plots of 200 trajectories of each of: Brownian motion with drift 0 and <i>σ</i>² = 1 (black); Ornstein–Uhlenbeck with <i>σ</i>² = 1 and <i>α</i> = −4 (green); and Ornstein–Uhlenbeck with <i>σ</i>² = 1 and <i>α</i> = −40 (orange)</b>.</p

Graphical representation of an asymmetrical five-state 2-parameter Markov chain model.

<p>Graphical representation of an asymmetrical five-state 2-parameter Markov chain model.</p

Example of a four-state 1 parameter Markov chain model.

<p>Note that in this diagram, transitions between states <i>A</i> and <i>D</i> have been disallowed; it is conventional to not draw the arrow rather than to draw it with a rate of 0.</p

Ancestral Reconstruction - Fig 2

<p><b>A general two-state Markov chain representing the rate of jumps from allele <i>a</i> to allele <i>A</i>.</b> The different types of jumps are allowed to have different rates.</p

Phylogeny of a hypothetical genus of plants with pollination states of either “bees”, “hummingbirds”, or “wind” denoted by pictues at the tips.

<p>Pollination state nodes in the phylogenetic tree inferred under maximum parsimony are coloured on the branches leading into them (yellow represents “bee” pollination, red representing “hummingbird” pollination, and black representing “wind” pollination, dual coloured branches are equally parsimonious for the two states coloured). Assignment of “hummingbird” as the root state (because of prior knowledge from the fossil record) leads to the pattern of ancestral states represented by symbols at the nodes of the phylogeny, the state requiring the fewest number of changes to give rise to the pattern observed at the tips is circled at each node.</p

Phylogeny of seven regional strains of <i>Drosophila pseudoobscura</i>, as inferred by Sturtevant and Dobzhansky [64].

<p>Displayed sequences do not correspond to the original paper, but were derived from the notation in the authors' companion paper [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004763#pcbi.1004763.ref008" target="_blank">8</a>] as follows: A (63A–65B), B (65C–68D), C (69A–70A), D (70B–70D), E (71A–71B), F (71A–73C), G (74A–74C), H (75A–75C), I (76A–76B), J (76C–77B), K (78A–79D), L (80A–81D). Inversions inferred by the authors are highlighted in blue along branches.</p

A visualization of RNA virus phylogenies in the tree shape kernel space (, ) using t-distributed stochastic neighbor embedding (t-SNE).

<p>The t-SNE algorithm attempts to find the optimal map of high-dimensional data into a low-dimensional space while preserving the distances among points as much as possible. Thus, the distance between pair of viruses or virus clades (labelled by the same abbreviations as <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0078122#pone-0078122-g004" target="_blank">Figure 4</a>) is approximately proportional to their mean kernel distance. Groups of virus clades of particular interest are highlighted with the corresponding colours: HIV, red; HCV, yellow; Dengue (DEN), green; IAV-H3, IAV-H1, and IBV (blue).</p

Mapping the Shapes of Phylogenetic Trees from Human and Zoonotic RNA Viruses

<div><p>A phylogeny is a tree-based model of common ancestry that is an indispensable tool for studying biological variation. Phylogenies play a special role in the study of rapidly evolving populations such as viruses, where the proliferation of lineages is constantly being shaped by the mode of virus transmission, by adaptation to immune systems, and by patterns of human migration and contact. These processes may leave an imprint on the shapes of virus phylogenies that can be extracted for comparative study; however, tree shapes are intrinsically difficult to quantify. Here we present a comprehensive study of phylogenies reconstructed from 38 different RNA viruses from 12 taxonomic families that are associated with human pathologies. To accomplish this, we have developed a new procedure for studying phylogenetic tree shapes based on the ‘kernel trick’, a technique that maps complex objects into a statistically convenient space. We show that our kernel method outperforms nine different tree balance statistics at correctly classifying phylogenies that were simulated under different evolutionary scenarios. Using the kernel method, we observe patterns in the distribution of RNA virus phylogenies in this space that reflect modes of transmission and pathogenesis. For example, viruses that can establish persistent chronic infections (such as HIV and hepatitis C virus) form a distinct cluster. Although the visibly ‘star-like’ shape characteristic of trees from these viruses has been well-documented, we show that established methods for quantifying tree shape fail to distinguish these trees from those of other viruses. The kernel approach presented here potentially represents an important new tool for characterizing the evolution and epidemiology of RNA viruses.</p></div

Distribution of mean normalized Colless’ indices.

<p>Each label represents the mean index of a virus or virus clade. The vertical axis is used to elucidate the clustering of points by forcing overlapping labels (phylogenies with similar indices) to ‘pile up’ like a histogram. A higher Colless’ index corresponds to a less ‘balanced’ tree in which branching events tend to occur along the same lineage. A conventional histogram is displayed in the background. Labels are defined as follows: AstV = <i>astrovirus</i>; CCHF = <i>Crimean-Congo hemorrhagic fever virus</i>; ChikV = <i>chikungunya virus</i>; CA24v = <i>coxsackievirus A24</i>; DEN = <i>dengue virus</i>; E30 = <i>echovirus 30</i>; EMCV = <i>encephalomyocarditis virus</i>; EV71 = <i>enterovirus 71</i>; GBVC = <i>GB virus C</i>; HTNV = <i>Hantaan virus</i>; H[A-E]V = <i>hepatitis [A-E] virus</i>; HIV = <i>human immunodeficiency virus type 1</i>; I[A-C]V = <i>influenza [A-C] virus</i>; JEV = <i>Japanese encephalitis virus</i>; MeV = <i>measles virus</i>; MuV = <i>mumps virus</i>; MVEV = <i>Murray valley encephalitis virus</i>; NV = <i>Norwalk virus</i>; OROV = <i>Oropouche virus</i>; hPIV-1 = <i>human parainfluenza virus</i>; PV = <i>poliovirus</i>; Rab = <i>rabies virus</i>; Rot = <i>human rotavirus</i>; RhiV = <i>human rhinovirus</i>; RSV = <i>human respiratory syncytical virus</i>; Rub = <i>rubella virus</i>; RVF = <i>Rift valley fever virus</i>; SapV = <i>sapovirus</i>; SeoV = <i>Seoul virus</i>; TBEV = <i>tick-borne encephalitis virus</i>; WNV = <i>West Nile virus</i>; YFV = <i>yellow fever virus</i>.</p