Using the method of natural samples for studying the variability in sugar beat (<Emphasis Type="Italic">Beta vulgaris</Emphasis> L.) agamospermous seed progeny

The existence of natural genetic and natural mixed samples of seeds was theoretically grounded and experimentally demonstrated. A natural genetic sample is detected when analyzing the seed agamospermous progeny in the sequence coinciding with the sequence of seed setting, i.e., in the order they are located on a branch. The method of natural genetic samples has demonstrated the presence of individual regions with nonrandom distribution of phenotypic classes of agamospermous seeds on the branches of sugar beet plants. This phenotype distribution reflects the state of somatic cells on extended branch regions and the manifestation of this state in seed-bud cells. In turn, the genotype of each seed reflects the state of the seed-bud cell (apozygote) that gave rise to embryo development. We also demonstrated heterogeneity in the ratios of enzyme phenotypes of the seeds set on individual branches, regarding it as a result of the changes arising in somatic tissues at the moment of branching. Analysis of the ratios of seed phenotypes on individual branches of the same plant was named the method of natural mixed samples. The combination of natural genetic and natural mixed samples provides for identifying and analyzing various modes of seed setting (gamospermy and agamospermy) and studying the factors that influence the variability in these processes. We postulated that the nonrandom distribution and ratio of the seed phenotypes on plant branches resulted from a nonrandom endoreduplication of the homologous regions in homologous chromosomes carrying the marker locus alleles.     

Adaptive evolution of conserved noncoding elements in mammals

Conserved noncoding elements (CNCs) are an abundant feature of vertebrate genomes. Some CNCs have been shown to act as cis-regulatory modules, but the function of most CNCs remains unclear. To study the evolution of CNCs, we have developed a statistical method called the “shared rates test” to identify CNCs that show significant variation in substitution rates across branches of a phylogenetic tree. We report an application of this method to alignments of 98,910 CNCs from the human, chimpanzee, dog, mouse, and rat genomes. We find that ~68% of CNCs evolve according to a null model where, for each CNC, a single parameter models the level of constraint acting throughout the phylogeny linking these five species. The remaining ~32% of CNCs show departures from the basic model including speed-ups and slow-downs on particular branches and occasionally multiple rate changes on different branches. We find that a subset of the significant CNCs have evolved significantly faster than the local neutral rate on a particular branch, providing strong evidence for adaptive evolution in these CNCs. The distribution of these signals on the phylogeny suggests that adaptive evolution of CNCs occurs in occasional short bursts of evolution. Our analyses suggest a large set of promising targets for future functional studies of adaptation.     

PHYLOGENETIC ANALYSIS OF THE EVOLUTIONARY CORRELATION USING LIKELIHOOD

Many evolutionary processes can lead to a change in the correlation between continuous characters over time or on different branches of a phylogenetic tree. Shifts in genetic or functional constraint, in the selective regime, or in some combination thereof can influence both the evolution of continuous traits and their relation to each other. These changes can often be mapped on a phylogenetic tree to examine their influence on multivariate phenotypic diversification. We propose a new likelihood method to fit multiple evolutionary rate matrices (also called evolutionary variance–covariance matrices) to species data for two or more continuous characters and a phylogeny. The evolutionary rate matrix is a matrix containing the evolutionary rates for individual characters on its diagonal, and the covariances between characters (of which the evolutionary correlations are a function) elsewhere. To illustrate our approach, we apply the method to an empirical dataset consisting of two features of feeding morphology sampled from 28 centrarchid fish species, as well as to data generated via phylogenetic numerical simulations. We find that the method has appropriate type I error, power, and parameter estimation. The approach presented herein is the first to allow for the explicit testing of how and when the evolutionary covariances between characters have changed in the history of a group.     

Statistical Properties of Pairwise Distances between Leaves on a Random Yule Tree

A Yule tree is the result of a branching process with constant birth and death rates. Such a process serves as an instructive null model of many empirical systems, for instance, the evolution of species leading to a phylogenetic tree. However, often in phylogeny the only available information is the pairwise distances between a small fraction of extant species representing the leaves of the tree. In this article we study statistical properties of the pairwise distances in a Yule tree. Using a method based on a recursion, we derive an exact, analytic and compact formula for the expected number of pairs separated by a certain time distance. This number turns out to follow a increasing exponential function. This property of a Yule tree can serve as a simple test for empirical data to be well described by a Yule process. We further use this recursive method to calculate the expected number of the n-most closely related pairs of leaves and the number of cherries separated by a certain time distance. To make our results more useful for realistic scenarios, we explicitly take into account that the leaves of a tree may be incompletely sampled and derive a criterion for poorly sampled phylogenies. We show that our result can account for empirical data, using two families of birds species.     

A test of frequency‐dependent selection in the evolution of a generalist phenotype

A solitary population of consumers frequently evolves to the middle of a resource gradient and an intermediate mean phenotype compared to a sympatric pair of competing species that diverge to either side via character displacement. The forces governing the distribution of phenotypes in these allopatric populations, however, are little investigated. Theory predicts that the intermediate mean phenotype of the generalist should be maintained by negative frequency‐dependent selection, whereby alternate extreme phenotypes are favored because they experience reduced competition for resources when rare. However, the theory makes assumptions that are not always met, and alternative explanations for an intermediate phenotype are possible. We provide a test of this prediction in a mesocosm experiment using threespine stickleback that are ecologically and phenotypically intermediate between the more specialized stickleback species that occur in pairs. We manipulated the frequency distribution of phenotypes in two treatments and then measured effects on a focal intermediate population. We found a slight frequency‐dependent effect on survival in the predicted direction but not on individual growth rates. This result suggests that frequency‐dependent selection might be a relatively weak force across the range of phenotypes within an intermediate population and we suggest several general reasons why this might be so. We propose that allopatric populations might often be maintained at an intermediate phenotype instead by stabilizing or fluctuating directional selection.     

Inferring gene expression dynamics via functional regression analysis

Background

The recent emergence of high-throughput automated image acquisition technologies has forever changed how cell biologists collect and analyze data. Historically, the interpretation of cellular phenotypes in different experimental conditions has been dependent upon the expert opinions of well-trained biologists. Such qualitative analysis is particularly effective in detecting subtle, but important, deviations in phenotypes. However, while the rapid and continuing development of automated microscope-based technologies now facilitates the acquisition of trillions of cells in thousands of diverse experimental conditions, such as in the context of RNA interference (RNAi) or small-molecule screens, the massive size of these datasets precludes human analysis. Thus, the development of automated methods which aim to identify novel and biological relevant phenotypes online is one of the major challenges in high-throughput image-based screening. Ideally, phenotype discovery methods should be designed to utilize prior/existing information and tackle three challenging tasks, i.e. restoring pre-defined biological meaningful phenotypes, differentiating novel phenotypes from known ones and clarifying novel phenotypes from each other. Arbitrarily extracted information causes biased analysis, while combining the complete existing datasets with each new image is intractable in high-throughput screens.

Results

Here we present the design and implementation of a novel and robust online phenotype discovery method with broad applicability that can be used in diverse experimental contexts, especially high-throughput RNAi screens. This method features phenotype modelling and iterative cluster merging using improved gap statistics. A Gaussian Mixture Model (GMM) is employed to estimate the distribution of each existing phenotype, and then used as reference distribution in gap statistics. This method is broadly applicable to a number of different types of image-based datasets derived from a wide spectrum of experimental conditions and is suitable to adaptively process new images which are continuously added to existing datasets. Validations were carried out on different dataset, including published RNAi screening using Drosophila embryos [Additional files 1, 2], dataset for cell cycle phase identification using HeLa cells [Additional files 1, 3, 4] and synthetic dataset using polygons, our methods tackled three aforementioned tasks effectively with an accuracy range of 85%–90%. When our method is implemented in the context of a Drosophila genome-scale RNAi image-based screening of cultured cells aimed to identifying the contribution of individual genes towards the regulation of cell-shape, it efficiently discovers meaningful new phenotypes and provides novel biological insight. We also propose a two-step procedure to modify the novelty detection method based on one-class SVM, so that it can be used to online phenotype discovery. In different conditions, we compared the SVM based method with our method using various datasets and our methods consistently outperformed SVM based method in at least two of three tasks by 2% to 5%. These results demonstrate that our methods can be used to better identify novel phenotypes in image-based datasets from a wide range of conditions and organisms.

Conclusion

We demonstrate that our method can detect various novel phenotypes effectively in complex datasets. Experiment results also validate that our method performs consistently under different order of image input, variation of starting conditions including the number and composition of existing phenotypes, and dataset from different screens. In our findings, the proposed method is suitable for online phenotype discovery in diverse high-throughput image-based genetic and chemical screens.     

Advances in the use of DNA barcodes to build a community phylogeny for tropical trees in a Puerto Rican forest dynamics plot

Background

Species number, functional traits, and phylogenetic history all contribute to characterizing the biological diversity in plant communities. The phylogenetic component of diversity has been particularly difficult to quantify in species-rich tropical tree assemblages. The compilation of previously published (and often incomplete) data on evolutionary relationships of species into a composite phylogeny of the taxa in a forest, through such programs as Phylomatic, has proven useful in building community phylogenies although often of limited resolution. Recently, DNA barcodes have been used to construct a robust community phylogeny for nearly 300 tree species in a forest dynamics plot in Panama using a supermatrix method. In that study sequence data from three barcode loci were used to generate a well-resolved species-level phylogeny.

Methodology/Principal Findings

Here we expand upon this earlier investigation and present results on the use of a phylogenetic constraint tree to generate a community phylogeny for a diverse, tropical forest dynamics plot in Puerto Rico. This enhanced method of phylogenetic reconstruction insures the congruence of the barcode phylogeny with broadly accepted hypotheses on the phylogeny of flowering plants (i.e., APG III) regardless of the number and taxonomic breadth of the taxa sampled. We also compare maximum parsimony versus maximum likelihood estimates of community phylogenetic relationships as well as evaluate the effectiveness of one- versus two- versus three-gene barcodes in resolving community evolutionary history.

Conclusions/Significance

As first demonstrated in the Panamanian forest dynamics plot, the results for the Puerto Rican plot illustrate that highly resolved phylogenies derived from DNA barcode sequence data combined with a constraint tree based on APG III are particularly useful in comparative analysis of phylogenetic diversity and will enhance research on the interface between community ecology and evolution.     

The roots of phylogeny: how did Haeckel build his trees?

Haeckel created much of our current vocabulary in evolutionary biology, such as the term phylogeny, which is currently used to designate trees. Assuming that Haeckel gave the same meaning to this term, one often reproduces Haeckel's trees as the first illustrations of phylogenetic trees. A detailed analysis of Haeckel's own evolutionary vocabulary and theory revealed that Haeckel's trees were genealogical trees and that Haeckel's phylogeny was a morphological concept. However, phylogeny was actually the core of Haeckel's tree reconstruction, and understanding the exact meaning Haeckel gave to phylogeny is crucial to understanding the information Haeckel wanted to convey in his famous trees. Haeckel's phylogeny was a linear series of main morphological stages along the line of descent of a given species. The phylogeny of a single species would provide a trunk around which lateral branches were added as mere ornament; the phylogeny selected for drawing a tree of a given group was considered the most complete line of progress from lower to higher forms of this group, such as the phylogeny of Man for the genealogical tree of Vertebrates. Haeckel's phylogeny was mainly inspired by the idea of the scala naturae, or scale of being. Therefore, Haeckel's genealogical trees, which were only branched on the surface, mainly represented the old idea of scale of being. Even though Haeckel decided to draw genealogical trees after reading On the Origin of Species and was called the German Darwin, he did not draw Darwinian branching diagrams. Although Haeckel always saw Lamarck, Goethe, and Darwin as the three fathers of the theory of evolution, he was mainly influenced by Lamarck and Goethe in his approach to tree reconstruction.     

Summarizing a posterior distribution of trees using agreement subtrees

Bayesian inference of phylogeny is unique among phylogenetic reconstruction methods in that it produces a posterior distribution of trees rather than a point estimate of the best tree. The most common way to summarize this distribution is to report the majority-rule consensus tree annotated with the marginal posterior probabilities of each partition. Reporting a single tree discards information contained in the full underlying distribution and reduces the Bayesian analysis to simply another method for finding a point estimate of the tree. Even when a point estimate of the phylogeny is desired, the majority-rule consensus tree is only one possible method, and there may be others that are more appropriate for the given data set and application. We present a method for summarizing the distribution of trees that is based on identifying agreement subtrees that are frequently present in the posterior distribution. This method provides fully resolved binary trees for subsets of taxa with high marginal posterior probability on the entire tree and includes additional information about the spread of the distribution.     

Taxon ordering in phylogenetic trees: a workbench test

Background  

Phylogenetic trees are an important tool for representing evolutionary relationships among organisms. In a phylogram or chronogram, the ordering of taxa is not considered meaningful, since complete topological information is given by the branching order and length of the branches, which are represented in the root-to-node direction. We apply a novel method based on a (λ + μ)-Evolutionary Algorithm to give meaning to the order of taxa in a phylogeny. This method applies random swaps between two taxa connected to the same node, without changing the topology of the tree. The evaluation of a new tree is based on different distance matrices, representing non-phylogenetic information such as other types of genetic distance, geographic distance, or combinations of these. To test our method we use published trees of Vesicular stomatitis virus, West Nile virus and Rice yellow mottle virus.     

Joint Bayesian estimation of alignment and phylogeny

We describe a novel model and algorithm for simultaneously estimating multiple molecular sequence alignments and the phylogenetic trees that relate the sequences. Unlike current techniques that base phylogeny estimates on a single estimate of the alignment, we take alignment uncertainty into account by considering all possible alignments. Furthermore, because the alignment and phylogeny are constructed simultaneously, a guide tree is not needed. This sidesteps the problem in which alignments created by progressive alignment are biased toward the guide tree used to generate them. Joint estimation also allows us to model rate variation between sites when estimating the alignment and to use the evidence in shared insertion/deletions (indels) to group sister taxa in the phylogeny. Our indel model makes use of affine gap penalties and considers indels of multiple letters. We make the simplifying assumption that the indel process is identical on all branches. As a result, the probability of a gap is independent of branch length. We use a Markov chain Monte Carlo (MCMC) method to sample from the posterior of the joint model, estimating the most probable alignment and tree and their support simultaneously. We describe a new MCMC transition kernel that improves our algorithm's mixing efficiency, allowing the MCMC chains to converge even when started from arbitrary alignments. Our software implementation can estimate alignment uncertainty and we describe a method for summarizing this uncertainty in a single plot.     

Large scale genotype-phenotype correlation analysis based on phylogenetic trees

We provide two methods for identifying changes in genotype that are correlated with changes in a phenotype implied by phylogenetic trees. The first method, VENN, works when the number of branches over which the change occurred are modest. VENN looks for genetic changes that are completely penetrant with phenotype changes on a tree. The second method, CCTSWEEP, allows for a partial matching between changes in phenotypes and genotypes and provides a score for each change using Maddison's concentrated changes test. The mutations that are highly correlated with phenotypic change can be ranked by score. We use these methods to find SNPs correlated with resistance to Bacillus anthracis in inbred mouse strains. Our findings are consistent with the current biological literature, and also suggest potential novel candidate genes.     

Genome-based phylogenetic analysis of Streptomyces and its relatives

MotivationStreptomyces is one of the best-studied genera of the order Actinomycetales due to its great importance in medical science, ecology and the biotechnology industry. A comprehensive, detailed and robust phylogeny of Streptomyces and its relatives is needed for understanding how this group emerged and maintained such a vast diversity throughout evolution and how soil-living mycelial forms (e.g., Streptomyces s. str.) are related to parasitic, unicellular pathogens (e.g., Mycobacterium tuberculosis) or marine species (e.g., Salinispora tropica). The most important application area of such a phylogenetic analysis will be in the comparative re-annotation of genome sequences and the reconstruction of Streptomyces metabolic networks for biotechnology.MethodsClassical 16S-rRNA-based phylogenetic reconstruction does not guarantee to produce well-resolved robust trees that reflect the overall relationship between bacterial species with widespread horizontal gene transfer. In our study we therefore combine three whole genome-based phylogenies with eight different, highly informative single-gene phylogenies to determine a new robust consensus tree of 45 Actinomycetales species with completely sequenced genomes.ResultsNone of the individual methods achieved a resolved phylogeny of Streptomyces and its relatives. Single-gene approaches failed to yield a detailed phylogeny; even though the single trees are in good agreement among each other, they show very low resolution of inner branches. The three whole genome-based methods improve resolution considerably. Only by combining the phylogenies from single gene-based and genome-based approaches we finally obtained a consensus tree with well-resolved branches for the entire set of Actinomycetales species. This phylogenetic information is stable and informative enough for application to the system-wide comparative modeling of bacterial physiology.     

CONFIDENCE LIMITS ON PHYLOGENIES: THE BOOTSTRAP REVISITED

Abstract— The bootstrap, a non-parametric statistical analysis, can be used to assess confidence limits on phylogcnics. The method most widely used tests the monophyly of individual clades. This paper proposes additional applications of the bootstrap which provide useful information about phylogeny even when many clades are found not to be supported with confidence (as often occurs in practice). In such cases it is still possible to place a constraint on the phylogenetic position of taxa by examining the relative size of the smallest monophyletic groups that contain them. In addition, the taxonomic composition of these larger clades can be determined, as well as the relative likelihood of their occurrence. The distinction between hypotheses about membership in particular clades and hypotheses about entire topologies is also discussed. To investigate the latter, the bootstrap is used to estimate the sampling distribution of tree similarity indices. All methods are illustrated by reference to a large data set on the angiosperm family Asteraccae, selected from the literature.     

Evolution of adult male horn developmental phenotypes and character displacement in Xylotrupes beetles (Scarabaeidae)

Character displacement that leads to divergent phenotypes between sympatric species has been hypothesized to facilitate coexistence and promote the accumulation of biodiversity. However, there are alternative evolutionary mechanisms that may also lead to the evolution of phenotypic divergence between sympatric species; one of the mechanisms is evolutionary contingency. We studied the evolution of the presence and absence of a major male horn phenotype, which may have ecological implications for promoting coexistence between sympatric beetles, across geographic populations from different Xylotrupes beetles. By using a previously published phylogeny with 80 Xylotrupes taxa, we estimated the transition rates between the two phenotypic states (i.e., presence vs. absence of a major male phenotype). Based on the estimated transition rates, we then simulated possible phenotypic outcomes between sympatric species. We found that sympatric species were equally likely to evolve the same versus distinct phenotypic states based on the estimated transition rates given the phylogeny. The empirically observed number of sympatric species showing different phenotypic states can be explained by evolutionary contingency alone. We discussed the importance of applying phylogenetic comparative methods when studying phenotypic evolution and more generally to investigate the effect of stochastic processes before making deterministic inferences.     

High-model abundance may permit the gradual evolution of Batesian mimicry: an experimental test

In Batesian mimicry, a harmless species (the ‘mimic’) resembles a dangerous species (the ‘model’) and is thus protected from predators. It is often assumed that the mimetic phenotype evolves from a cryptic phenotype, but it is unclear how a population can transition through intermediate phenotypes; such intermediates may receive neither the benefits of crypsis nor mimicry. Here, we ask if selection against intermediates weakens with increasing model abundance. We also ask if mimicry has evolved from cryptic phenotypes in a mimetic clade. We first present an ancestral character-state reconstruction showing that mimicry of a coral snake (Micrurus fulvius) by the scarlet kingsnake (Lampropeltis elapsoides) evolved from a cryptic phenotype. We then evaluate predation rates on intermediate phenotypes relative to cryptic and mimetic phenotypes under conditions of both high- and low-model abundances. Our results indicate that where coral snakes are rare, intermediate phenotypes are attacked more often than cryptic and mimetic phenotypes, indicating the presence of an adaptive valley. However, where coral snakes are abundant, intermediate phenotypes are not attacked more frequently, resulting in an adaptive landscape without a valley. Thus, high-model abundance may facilitate the evolution of Batesian mimicry.     

HGT-Gen: a tool for generating a phylogenetic tree with horizontal gene transfer

Horizontal gene transfer (HGT) is a common event in prokaryotic evolution. Therefore, it is very important to consider HGT in the study of molecular evolution of prokaryotes. This is true also for conducting computer simulations of their molecular phylogeny because HGT is known to be a serious disturbing factor for estimating their correct phylogeny. To the best of our knowledge, no existing computer program has generated a phylogenetic tree with HGT from an original phylogenetic tree. We developed a program called HGT-Gen that generates a phylogenetic tree with HGT on the basis of an original phylogenetic tree of a protein or gene. HGT-Gen converts an operational taxonomic unit or a clade from one place to another in a given phylogenetic tree. We have also devised an algorithm to compute the average length between any pair of branches in the tree. It defines and computes the relative evolutionary time to normalize evolutionary time for each lineage. The algorithm can generate an HGT between a pair of donor and acceptor lineages at the same evolutionary time. HGT-Gen is used with a sequence-generating program to evaluate the influence of HGT on the molecular phylogeny of prokaryotes in a computer simulation study.

Availability

The database is available for free at http://www.grl.shizuoka.ac.jp/˜thoriike/HGT-Gen.html     

Efficient selection of branch-specific models of sequence evolution

The analysis of extant sequences shows that molecular evolution has been heterogeneous through time and among lineages. However, for a given sequence alignment, it is often difficult to uncover what factors caused this heterogeneity. In fact, identifying and characterizing heterogeneous patterns of molecular evolution along a phylogenetic tree is very challenging, for lack of appropriate methods. Users either have to a priori define groups of branches along which they believe molecular evolution has been similar or have to allow each branch to have its own pattern of molecular evolution. The first approach assumes prior knowledge that is seldom available, and the second requires estimating an unreasonably large number of parameters. Here we propose a convenient and reliable approach where branches get clustered by their pattern of molecular evolution alone, with no need for prior knowledge about the data set under study. Model selection is achieved in a statistical framework and therefore avoids overparameterization. We rely on substitution mapping for efficiency and present two clustering approaches, depending on whether or not we expect neighbouring branches to share more similar patterns of sequence evolution than distant branches. We validate our method on simulations and test it on four previously published data sets. We find that our method correctly groups branches sharing similar equilibrium GC contents in a data set of ribosomal RNAs and recovers expected footprints of selection through dN/dS. Importantly, it also uncovers a new pattern of relaxed selection in a phylogeny of Mantellid frogs, which we are able to correlate to life-history traits. This shows that our programs should be very useful to study patterns of molecular evolution and reveal new correlations between sequence and species evolution. Our programs can run on DNA, RNA, codon, or amino acid sequences with a large set of possible models of substitutions and are available at http://biopp.univ-montp2.fr/forge/testnh.     

Exceptional cryptic diversity and multiple origins of parthenogenesis in a freshwater ostracod

The persistence of asexual reproduction in many taxa depends on a balance between the origin of new asexual lineages and the extinction of old ones. This turnover determines the diversity of extant asexual populations and so influences the interaction between sexual and asexual modes of reproduction. Species with mixed reproduction, like the freshwater ostracod (Crustacea) morphospecies Eucypris virens, are a good model to examine these dynamics. This species is also a geographic parthenogen, in which sexual females and males co-exist with asexual females in the circum-Mediterranean area only, whereas asexual females occur all over Europe. A molecular phylogeny of E. virens based on the mitochondrial COI and 16S fragments is presented. It is characterised by many distinct clusters of haplotypes which are either exclusively sexual or asexual, with only one exception, and are often separated by deep branches. Analysis of the phylogeny reveals an astonishing cryptic diversity, which indicates the existence of a species complex with more than 40 cryptic taxa. We therefore suggest a revision of the single species status of E. virens. The phylogeny indicates multiple transitions from diverse sexual ancestor populations to asexuality. Although many transitions appear to be ancient, we argue that this may be an artefact of the existence of unsampled or extinct sexual lineages.     

Genome-based phylogeny of dsDNA viruses by a novel alignment-free method

Sequence alignment is not directly applicable to whole genome phylogeny since several events such as rearrangements make full length alignments impossible. Here, a novel alignment-free method derived from the standpoint of information theory is proposed and used to construct the whole-genome phylogeny for a population of viruses from 13 viral families comprising 218 dsDNA viruses. The method is based on information correlation (IC) and partial information correlation (PIC). We observe that (i) the IC-PIC tree segregates the population into clades, the membership of each is remarkably consistent with biologist's systematics only with little exceptions; (ii) the IC-PIC tree reveals potential evolutionary relationships among some viral families; and (iii) the IC-PIC tree predicts the taxonomic positions of certain “unclassified” viruses. Our approach provides a new way for recovering the phylogeny of viruses, and has practical applications in developing alignment-free methods for sequence classification.