Distribution of spontaneous mutants and inferences about the replication mode of the RNA bacteriophage phi6

When a parent virus replicates inside its host, it must first use its own genome as the template for replication. However, once progeny genomes are produced, the progeny can in turn act as templates. Depending on whether the progeny genomes become templates, the distribution of mutants produced by an infection varies greatly. While information on the distribution is important for many population genetic models, it is also useful for inferring the replication mode of a virus. We have analyzed the distribution of mutants emerging from single bursts in the RNA bacteriophage phi6 and find that the distribution closely matches a Poisson distribution. The match suggests that replication in this bacteriophage is effectively by a stamping machine model in which the parental genome is the main template used for replication. However, because the distribution deviates slightly from a Poisson distribution, the stamping machine is not perfect and some progeny genomes must replicate. By fitting our data to a replication model in which the progeny genomes become replicative at a given rate or probability per round of replication, we estimated the rate to be very low and on the on the order of 10(-4). We discuss whether different replication modes may confer an adaptive advantage to viruses.     

A machine learning information retrieval approach to protein fold recognition

MOTIVATION: Recognizing proteins that have similar tertiary structure is the key step of template-based protein structure prediction methods. Traditionally, a variety of alignment methods are used to identify similar folds, based on sequence similarity and sequence-structure compatibility. Although these methods are complementary, their integration has not been thoroughly exploited. Statistical machine learning methods provide tools for integrating multiple features, but so far these methods have been used primarily for protein and fold classification, rather than addressing the retrieval problem of fold recognition-finding a proper template for a given query protein. RESULTS: Here we present a two-stage machine learning, information retrieval, approach to fold recognition. First, we use alignment methods to derive pairwise similarity features for query-template protein pairs. We also use global profile-profile alignments in combination with predicted secondary structure, relative solvent accessibility, contact map and beta-strand pairing to extract pairwise structural compatibility features. Second, we apply support vector machines to these features to predict the structural relevance (i.e. in the same fold or not) of the query-template pairs. For each query, the continuous relevance scores are used to rank the templates. The FOLDpro approach is modular, scalable and effective. Compared with 11 other fold recognition methods, FOLDpro yields the best results in almost all standard categories on a comprehensive benchmark dataset. Using predictions of the top-ranked template, the sensitivity is approximately 85, 56, and 27% at the family, superfamily and fold levels respectively. Using the 5 top-ranked templates, the sensitivity increases to 90, 70, and 48%.     

昆虫的生物光电效应与虫害治理应用

农业虫害的治理需要依据为害昆虫的特性提出与环境适宜、生态兼容的技术体系和关键技术。为害昆虫表现了对敏感光源具有个体差异性和群体一贯性的趋光性行为特征,并通过视觉神经信号响应和生理光子能量需求的方式呈现出生物光电效应的作用本质。利用昆虫的这种趋性行为诱导增益特性,一些光电诱导杀虫灯技术以及害虫诱导捕集技术广泛地应用于农业虫害的防治,具有良好的应用前景。     

Testing character correlation using pairwise comparisons on a phylogeny

In comparative biology, pairwise comparisons of species or genes (terminal taxa) are used to detect character associations. For instance, if pairs of species contrasting in the state of a particular character are examined, the member of a pair with a particular state might be more likely than the other member to show a particular state in a second character. Pairs are chosen so as to be phylogenetically separate, that is, the path between members of a pair, along the branches of the tree, does not touch the path of any other pair. On a given phylogenetic tree, pairs must be chosen carefully to achieve the maximum possible number of pairs while maintaining phylogenetic separation. Many alternative sets of pairs may have this maximum number. Algorithms are developed that find all taxon pairings that maximize the number of pairs without constraint, or with the constraint that members of each pair have contrasting states in a binary character, or that they have contrasting states in two binary characters. The comparisons chosen by these algorithms, although phylogenetically separate on the tree, are not necessarily statistically independent.     

Inferring ancestral sequences in taxon-rich phylogenies

Statistical consistency in phylogenetics has traditionally referred to the accuracy of estimating phylogenetic parameters for a fixed number of species as we increase the number of characters. However, it is also useful to consider a dual type of statistical consistency where we increase the number of species, rather than characters. This raises some basic questions: what can we learn about the evolutionary process as we increase the number of species? In particular, does having more species allow us to infer the ancestral state of characters accurately? This question is particularly important when sequence evolution varies in a complex way from character to character, as methods applicable for i.i.d. models may no longer be valid. In this paper, we assemble a collection of results to analyse various approaches for inferring ancestral information with increasing accuracy as the number of taxa increases.     

QUANTITATIVE CHARACTERS IN PHYLOGENETIC ANALYSIS

Abstract— When analysing phylogcnetic relationships at low laxonomic levels it is often the ease that many of the features that can be used to separate taxa show continuous variation. The theoretical and practical problems for the use of such quantitative characters in phylogenetic analysis arc examined. Three methods of coding continuous data into discrete characters are assessed in detail: simple gap-coding, generalised gap-coding and segment-coding, a form of range-coding. The methods are applied to a data set gathered for Eucatyptus L'Hérit. informal subgenus Symphyomyrtus section Maidenana (Myrtaceae). Each method is capable of distorting relative differences between taxa, but segment-coding produces the least amount of distortion, provided the range of variation of the character is divided into a sufficient number of character states.
Continuous quantitative characters provide data for phylogenetic analysis that arc more noisy than those provided by discrete qualitative characters and should, therefore, only be used when the number of qualitative characters is insufficient for resolution of relationships. The results of such analyses should be recognised as provisional pending the discovery of more readily informative characters.     

The role of wood anatomy in phylogeny reconstruction of Ericales

The systematic significance of wood anatomical characters within Ericales is evaluated using separate and combined parsimony analyses including 23 wood characters and 3945 informative molecular characters. Analyses of wood features alone result in poorly resolved and conflicting topologies. However, when pedomorphic character states are coded as inapplicable, the combined bootstrap topology results in an increase of resolution and support at most deeper nodes compared with the molecular analyses. This suggests that phylogenetic information from the limited number of morphological characters is not completely swamped by an overwhelming amount of molecular data. Based on the morphology of vessels and fibers, and the distribution of axial parenchyma, two major wood types can be distinguished within Ericales: (i) a “primitive” type, nearly identical to the wood structure in the more basal outgroup Cornales, which is likely to have persisted in one major clade, and (ii) a “derived” type that must have evolved in at least two separate evolutionary lines. The occurrence of the first type is strongly correlated with shrubs to small trees growing in cold temperate or tropical montane regions, while the second type is common in tall trees of tropical lowlands. This favors the inclusion of ecologically adaptive features in phylogeny reconstruction. © The Willi Hennig Society 2006.     

Assessing progress in systematics with continuous jackknife function analysis

Systematists expect their hypotheses to be asymptotically precise. As the number of phylogenetically informative characters for a set of taxa increases, the relationships implied should stabilize on some topology. If true, this increasing stability should clearly manifest itself if an index of congruence is plotted against the accumulating number of characters. Continuous jackknife function (CJF) analysis is a new graphical method that portrays the extent to which available data converge on a specified phylogenetic hypothesis, the reference tree. The method removes characters with increasing probability, analyzes the rarefied data matrices phylogenetically, and scores the clades shared between each of the resulting trees and the reference tree. As more characters are removed, the number of shared clades must decrease, but the rate of decrease will depend on how decisively the data support the reference tree. Curves for stable phylogenies are clearly asymptotic with nearly 100% congruence for a substantial part of the curve. Less stable phylogenies lose congruent nodes quickly as characters are excluded, resulting in a more linear or even a sigmoidal relationship. Curves can be interpreted as predictors of whether the addition of new data of the same type is likely to alter the hypothesis under test. Continuous jackknife function analysis makes statistical assumptions about the collection of character data. To the extent that CJF curves are sensitive to violations of unbiased character collection, they will be misleading as predictors. Convergence of data on a reference tree does not guarantee historical accuracy, but it does predict that the accumulation of further data under the sampling model will not lead to rapid changes in the hypothesis.     

THE EFFECT OF ORDERED CHARACTERS ON PHYLOGENETIC RECONSTRUCTION

Abstract Morphological structures are likely to undergo more than a single change during the course of evolution. As a result, multistate characters are common in systematic studies and must be dealt with. Particularly interesting is the question of whether or not multistate characters should be treated as ordered (additive) or unordered (non-additive). In accepting a particular hypothesis of order, numerous others are necessarily rejected. We review some of the criteria often used to order character states and the underlying assumptions inherent in these criteria.
The effects that ordered multistate characters can have on phylogenetic reconstruction are examined using 27 data sets. It has been suggested that hypotheses of character state order are more informative then hypotheses of unorder and may restrict the number of equally parsimonious trees as well as increase tree resolution. Our results indicate that ordered characters can produce more, equal or less equally parsimonious trees and can increase, decrease or have no effect on tree resolution. The effect on tree resolution can be a simple gain in resolution or a dramatic change in sister-taxa relationships. In cases where several outgroups are included in the data matrix, hypotheses of order can change character polarities by altering outgroup topology. Ordered characters result in a different topology from unordered characters only when the hierarchy of the cladogram disagrees with the investigator's a priori hypothesis of order. If the best criterion for assessing character evolution is congruence with other characters, the practice of ordering multistate characters is inappropriate.     

Feature blindness: A challenge for understanding and modelling visual object recognition

Humans rely heavily on the shape of objects to recognise them. Recently, it has been argued that Convolutional Neural Networks (CNNs) can also show a shape-bias, provided their learning environment contains this bias. This has led to the proposal that CNNs provide good mechanistic models of shape-bias and, more generally, human visual processing. However, it is also possible that humans and CNNs show a shape-bias for very different reasons, namely, shape-bias in humans may be a consequence of architectural and cognitive constraints whereas CNNs show a shape-bias as a consequence of learning the statistics of the environment. We investigated this question by exploring shape-bias in humans and CNNs when they learn in a novel environment. We observed that, in this new environment, humans (i) focused on shape and overlooked many non-shape features, even when non-shape features were more diagnostic, (ii) learned based on only one out of multiple predictive features, and (iii) failed to learn when global features, such as shape, were absent. This behaviour contrasted with the predictions of a statistical inference model with no priors, showing the strong role that shape-bias plays in human feature selection. It also contrasted with CNNs that (i) preferred to categorise objects based on non-shape features, and (ii) increased reliance on these non-shape features as they became more predictive. This was the case even when the CNN was pre-trained to have a shape-bias and the convolutional backbone was frozen. These results suggest that shape-bias has a different source in humans and CNNs: while learning in CNNs is driven by the statistical properties of the environment, humans are highly constrained by their previous biases, which suggests that cognitive constraints play a key role in how humans learn to recognise novel objects.     

CHARACTER REMOVAL AS A MEANS FOR ASSESSING STABILITY OF CLADES

Abstract— The stability of each clade resolved by a data set can be assessed as the minimum number of characters that, when removed, cause resolution of the clade to be lost; a clade is regarded as having been lost when it does occur in the strict consensus tree. The clade stability index (CSI) is the ratio of this minimum number of characters to the number of informative characters in the data set. The CSI of a clade can range from 0 (absence from the consensus tree of the complete data set) to 1 (all informative characters must be removed for the clade to fail to be resolved). Minimum character removal scores are discoverable by a procedure known as successive character removal, in which separate cladistic analyses are conducted of all possible data sets derived by the removal of individual characters and character combinations of successively increasing number.     

THE NATURE OF CLADISTIC DATA

Abstract— Cladistic data are the characters of organisms. Character is defined as a feature that can be evaluated as a variable with two or more mutually exclusive and ordered states. Cladistic characters must be treated as multistate variables, and coded as sequential numbers or in additive binary fashion. Any other interpretation and handling of cladistic data will introduce error into analysis. Character states cannot be treated independently as present or absent, i.e., as nominal variables, because redundancy is introduced into the data and information content is sacrificed. Non-additive binary coding demonstrates that treating cladistic variables as nominal data will lead to multiple, equally parsimonious solutions. Defining characters found universally in a group of organisms, but unknown outside those organisms have no alternative state that can be designated as absent. Absence, however, is valid as a character state if it can be shown to be apomorphic. When two or more character states occur within a taxon, that taxon must be coded as having an unknown state for that character, or the taxon must be split in two or more taxa. Continuously varying quantitative data are not suitable for cladistic analysis because there is no justifiable basis for recognizing discrete states among them. Quantitative data are questionable even when they exhibit mutually exclusive states because the states can be interpreted only in reference to an archetype, i.e., as implied homologies not subject to test.     

Pleiotropic mutation, modularity and evolvability

The relationship between pleiotropy and the rate of evolution of a phenotypic character (evolvability) in a population is explored using computer simulations. I present results that suggest the rate of evolution of a phenotypic character may not decline when that character is pleiotropically associated to an increasing number of other characters, provided that the characters are under pure directional selection such that they are far from their optima relative to the average magnitude of a mutation. These conditions may be relevant during adaptive radiations. Adding pleiotropic associations to a set of characters in which one is under directional selection and the other is under stabilizing selection increases the rate of adaptation of the character under directional selection provided that the new characters that come to be pleiotropically associated are under directional selection. Thus, increasing the number of pleiotropic associations under these conditions increases the rate of adaptation of a character.     

The information content of a character under a Markov model of evolution

The rate of evolutionary change associated with a character determines its utility for the reconstruction of phylogenetic history. For a given age of lineage splits, we examine the information content of a character to assess the magnitude and range of an optimal rate of substitution. On the one hand an optimal transition rate must provide sufficiently many character changes to distinguish subclades, whereas on the other hand changes must be sufficiently rare that reversals on a single branch (and hence homoplasy) are uncommon. In this study, we evolve binary characters over three tree topologies with fixed branch lengths, while varying transition rate as a parameter. We use the character state distribution obtained to measure the "information content" of a character given a transition rate. This is done with respect to several criteria-the probability of obtaining the correct tree using parsimony, the probability of infering the correct ancestral state, and Shannon-Weaver and Fisher information measures on the configuration of probability distributions. All of the information measures suggest the intuitive result of the existence of optimal rates for phylogeny reconstruction. This nonzero optimum is less pronounced if one conditions on there having been a change, in which case the parsimony-based results of minimum change being the most informative tends to hold.     

Stability of characters and construction of phylogenetic trees.

Parsimony methods infer phylogenetic trees by minimizing number of character changes required to explain observed character states. From the perspective of applicability of parsimony methods, it is important to assess whether the characters used to infer phylogeny are likely to provide a correct tree. We introduce a graph theoretical characterization that helps to assess whether given set of characters is appropriate to use with parsimony methods. Given a set of characters and a set of taxa, we construct a network called character overlap graph. We show that the character overlap graph for characters that are appropriate to use in parsimony methods is characterized by significant under-representation of subnetworks known as holes, and provide a validation for this observation. This characterization explains success in constructing evolutionary trees using parsimony method for some characters (e.g., protein domains) and lack of such success for other characters (e.g., introns). In the latter case, the understanding of obstacles to applying parsimony methods in a direct way has lead us to a new approach for detecting inconsistent and/or noisy data. Namely, we introduce the concept of stable characters which is similar but less restrictive than the well known concept of pairwise compatible characters. Application of this approach to introns produces the evolutionary tree consistent with the Coelomata hypothesis.     

Application of principal components analyses with constant character number in a study of the Bulbostylis/Fimbristylis (Cyperaceae) complex in Nigeria

Interrelationships between OTUs (operational taxonomic units) were assessed through comparisons based on a constant character number, using principal components analysis. This approach results in a uniform treatment of OTUs, despite variations in the number of definite entries for character states that could validly be made. In addition, the risk of distortion of the ordination scatter as a result of a bimodal frequency distribution of the number of characters available for comparisons is minimized. Appropriately applied, the approach also provides indications of the consistency of the features of the ordinations and reveals where more caution in interpretation is advisable.
The main analysis divided the OTUs into two unequal-sized groups, with a few intermediates; these were concluded to be more closely allied to the large than the small group. The significance of these groupings, in terms of their species contents, is discussed in relation to the method and to recent taxonomic treatments of the Bulbostylis/Fimbristylis complex. Some taxonomic conclusions must be tentative because of the limitations of the sample.     

EVOLUTIONARY CHARACTER ANALYSIS: TRACING CHARACTER CHANGE ON A CLADOGRAM

Abstract— There has been little formal discussion concerning character analysis in cladistics, even though characters and their character state trees are central to phylogenetic analyses. We refer to this field as Evolutionary Character Analysis. This paper defines the components of evolutionary character analysis: character state trees, transmodal characters, cladogram characters, attribute and character phylogenies; and the use of these components in phylogenetic inference and evolutionary studies. Character state trees and their effect on cladogram construction are discussed. A new method for numerically coding complex character state trees is described that further reduces the number of variables required to describe them. This method, ordinal coding, reduces the size of data matrices, and facilitates retrieval of state codes. This paper advocates the use of both biological evidence and evidence internal to the cladogram itself to construct character state trees (CSTs). We discuss general models of character evolution (morphocline analysis, Fitch minimum mutation model, etc.) and their role in forming CSTs. Character state trees formed with theories of character evolution are referred to as transmodal characters. These transmodal characters are contrasted with cladogram characters (Mickevich, 1982), and the place of each in a phylogenetic analysis is discussed. The method for determining cladogram characters is detailed with more complicated examples than found in previous publications. We advocate testing transmodal characters by comparing them with the resultant cladogram characters. This comparison involves transformation series analysis (TSA; Mickevich, 1982) which is viewed as an extension of reciprocal illumination. The TSA procedure and its place in hypothesis testing are reviewed. Tracing the evolution of characters interests both systematists and non-systematists alike. When character state trees (transmodal characters) are optimized on pre-existing phylogenies, character phylogenies and attribute phylogenies result. Attributes are defined as a feature that may or may not be homologous (i.e., ecological categories, plant hosts, etc.). We provide two illustrations of this approach, one involving the evolution of the anuran ear and another involving the coevolution of the butterfly Heliconius and its hostplants. Finally, the components of phylogenetic character analysis can be used to test more general evolutionary theories such as the biogenetic law and vicariance biogeography.     

ESTIMATING CHARACTER WEIGHTS DURING TREE SEARCH

Abstract— A new method for weighting characters according to their homoplasy is proposed; the method is non-iterative and does not require independent estimations of weights. It is based on searching trees with maximum total fit, with character fits defined as a concave function of homoplasy. Then, when comparing trees, differences in steps occurring in characters which show more homoplasy on the trees are less influential. The reliability of the characters is estimated, during the analysis, as a logical implication of the trees being compared. The "fittest" trees imply that the characters are maximally reliable and, given character conflict, have fewer steps for the characters which fit the tree better. If other trees save steps in some characters, it will be at the expense of gaining them in characters with less homoplasy.