851 research outputs found

    Inversion-based genomic signatures

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    <p>Abstract</p> <p>Background</p> <p>Reconstructing complete ancestral genomes (at least in terms of their gene inventory and arrangement) is attracting much interest due to the rapidly increasing availability of whole genome sequences. While modest successes have been reported for mammalian and even vertebrate genomes, more divergent groups continue to pose a stiff challenge, mostly because current models of genomic evolution support too many choices.</p> <p>Results</p> <p>We describe a novel type of genomic signature based on rearrangements that characterizes evolutionary changes that must be common to all minimal rearrangement scenarios; by focusing on global patterns of rearrangements, such signatures bypass individual variations and sharply restrict the search space. We present the results of extensive simulation studies demonstrating that these signatures can be used to reconstruct accurate ancestral genomes and phylogenies even for widely divergent collections.</p> <p>Conclusion</p> <p>Focusing on genome triples rather than genomes pairs unleashes the full power of evolutionary analysis. Our genomic signature captures shared evolutionary events and thus can form the basis of a robust analysis and reconstruction of evolutionary history.</p

    GO4genome: A Prokaryotic Phylogeny Based on Genome Organization

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    Determining the phylogeny of closely related prokaryotes may fail in an analysis of rRNA or a small set of sequences. Whole-genome phylogeny utilizes the maximally available sample space. For a precise determination of genome similarity, two aspects have to be considered when developing an algorithm of whole-genome phylogeny: (1) gene order conservation is a more precise signal than gene content; and (2) when using sequence similarity, failures in identifying orthologues or the in situ replacement of genes via horizontal gene transfer may give misleading results. GO4genome is a new paradigm, which is based on a detailed analysis of gene function and the location of the respective genes. For characterization of genes, the algorithm uses gene ontology enabling a comparison of function independent of evolutionary relationship. After the identification of locally optimal series of gene functions, their length distribution is utilized to compute a phylogenetic distance. The outcome is a classification of genomes based on metabolic capabilities and their organization. Thus, the impact of effects on genome organization that are not covered by methods of molecular phylogeny can be studied. Genomes of strains belonging to Escherichia coli, Shigella, Streptococcus, Methanosarcina, and Yersinia were analyzed. Differences from the findings of classical methods are discussed

    Efficient algorithms for gene cluster detection in prokaryotic genomes

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    Schmidt T. Efficient algorithms for gene cluster detection in prokaryotic genomes. Bielefeld (Germany): Bielefeld University; 2005.The research in genomics science rapidly emerged in the last few years, and the availability of completely sequenced genomes continuously increases due to the use of semi-automatic sequencing machines. Also these sequences, mostly prokaryotic ones, are well annotated, which means that the positions of their genes and parts of their regulatory or metabolic pathways are known. A new task in the field of bioinformatics now is to gain gene or protein information from the comparison of genomes on a higher level. In the approach of "comparative genomics" researchers in bioinformatics are attempting to locate groups or clusters of orthologous genes that may have the same function in multiple genomes. These researches are often anchored on the simple, but biologically verified fact, that functionally related proteins are usually coded by genes placed in a region of close genomic neighborhood, in different species. From an algorithmic and combinatorial point of view, the first descriptions of the concept of "closely placed genes" were only fragmentary, and sometimes confusing. The given algorithms often lack the necessary grounds to prove their correctness, or assess their complexity. Within the first formal models of a conserved genomic neighborhood, genomes are often represented as permutations of their genes, and common intervals, i.e. intervals containing the same set of genes, are interpreted as gene clusters. But here the major disadvantage of representing genomes as permutations is the fact that paralogous copies of the same gene inside one genome can not be modelled. Since especially large genomes contain numerous paralogous genes, this model is insufficient to be used on real genomic data. In this work, we consider a modified model of gene clusters that allows paralogs, simply by representing genomes as sequences rather than permutations of genes. We define common intervals based on this model, and we present a simple algorithm that finds all common intervals of two sequences in [Theta](n2) time using [Theta](n2) space. Another, more complicated algorithm runs in [Omikron](n2) time and uses only linear space. We also show how to extend these algorithms to more than two genomes and present the implementation of the algorithms as well as the visualization of the located clusters in the tool Gecko. Since the creation of the string representation of a set of genomes is a non-trivial task, we also present the data preparation tool GhostFam that groups all genes from the given set of genomes to their families of homologs. In the evaluation on a set of 20 bacterial genomes, we show that with the presented approach it is possible to correctly locate gene clusters that are known from the literature, and to successfully predict new groups of functionally related genes

    Exploring the boundaries of shallow phylogeny in the YESS group and the dynamics of gene cluster and operon formation in bacterial genomes

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    In this thesis I look at two different problems in bacterial genomic analysis. The first involves reconstructing the evolutionary history between a group of closely related bacteria. I addressed whether or not it is possible to separate such genomes into different genera, species and strains. Specifically, I addressed how different approaches such as the use of 16S rRNA phylogenetic trees, phylogenetic supertrees and concatenation of individual genes in order to construct phylogenetic trees compare with one another. What effect will problems associated with resolving shallow-phylogeny have on recovering a tree of life? Ultimately I show that for the group of genomes involved, different methods and data produce different results and that the true tree, if a tree-like structure does indeed exist for these genomes, is unrecoverable using such approaches. In the second part of my thesis I examine the phenomenon of gene clustering in bacterial genomes. I present a software program, GenClust, for the identification, analysis and visualisation of gene clusters. I show how GenClust can be used to recover and analyse clusters of genes involved in amino acid biosynthesis across a large !-proteobacterial dataset. Finally, I examine models of gene cluster and operon formation and test them with real data, using a combined approach of comparing clusters on both structural similarity and the underlying phylogenetic signals of the clustered genes. I provide a hypothesis for the selective forces driving cluster and operon formation in bacterial genomes

    Models, algorithms, and programs for phylogeny reconciliation

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    International audienceGene sequences contain a gold mine of phylogenetic information. But unfortunately for taxonomists this information does not only tell the story of the species from which it was collected. Genes have their own complex histories which record speciation events, of course, but also many other events. Among them, gene duplications, transfers and losses are especially important to identify. These events are crucial to account for when reconstructing the history of species, and they play a fundamental role in the evolution of genomes, the diversification of organisms and the emergence of new cellular functions. We review reconciliations between gene and species trees, which are rigorous approaches for identifying duplications, transfers and losses that mark the evolution of a gene family. Existing reconciliation models and algorithms are reviewed and difficulties in modeling gene transfers are discussed. We also compare different reconciliation programs along with their advantages and disadvantages

    Bayesian phylogenetic modelling of lateral gene transfers

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    PhD ThesisPhylogenetic trees represent the evolutionary relationships between a set of species. Inferring these trees from data is particularly challenging sometimes since the transfer of genetic material can occur not only from parents to their o spring but also between organisms via lateral gene transfers (LGTs). Thus, the presence of LGTs means that genes in a genome can each have di erent evolutionary histories, represented by di erent gene trees. A few statistical approaches have been introduced to explore non-vertical evolution through collections of Markov-dependent gene trees. In 2005 Suchard described a Bayesian hierarchical model for joint inference of gene trees and an underlying species tree, where a layer in the model linked gene trees to the species tree via a sequence of unknown lateral gene transfers. In his model LGT was modeled via a random walk in the tree space derived from the subtree prune and regraft (SPR) operator on unrooted trees. However, the use of SPR moves to represent LGT in an unrooted tree is problematic, since the transference of DNA between two organisms implies the contemporaneity of both organisms and therefore it can allow unrealistic LGTs. This thesis describes a related hierarchical Bayesian phylogenetic model for reconstructing phylogenetic trees which imposes a temporal constraint on LGTs, namely that they can only occur between species which exist concurrently. This is achieved by taking into account possible time orderings of divergence events in trees, without explicitly modelling divergence times. An extended version of the SPR operator is introduced as a more adequate mechanism to represent the LGT e ect in a tree. The extended SPR operation respects the time ordering. It additionaly di ers from regular SPR as it maintains a 1-to-1 correspondence between points on the species tree and points on each gene tree. Each point on a gene tree represents the existence of a population containing that gene at some point in time. Hierarchical phylogenetic models were used in the reconstruction of each gene tree from its corresponding gene alignment, enabling the pooling of information across genes. In addition to Suchard's approach, we assume variation in the rate of evolution between di erent sites. The species tree is assumed to be xed. A Markov Chain Monte Carlo (MCMC) algorithm was developed to t the model in a Bayesian framework. A novel MCMC proposal mechanism for jointly proposing the gene tree topology and branch lengths, LGT distance and LGT history has been developed as well as a novel graphical tool to represent LGT history, the LGT Biplot. Our model was applied to simulated and experimental datasets. More speci cally we analysed LGT/reassortment presence in the evolution of 2009 Swine-Origin In uenza Type A virus. Future improvements of our model and algorithm should include joint inference of the species tree, improving the computational e ciency of the MCMC algorithm and better consideration of other factors that can cause discordance of gene trees and species trees such as gene loss

    The Orthology Road: Theory and Methods in Orthology Analysis

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    The evolution of biological species depends on changes in genes. Among these changes are the gradual accumulation of DNA mutations, insertions and deletions, duplication of genes, movements of genes within and between chromosomes, gene losses and gene transfer. As two populations of the same species evolve independently, they will eventually become reproductively isolated and become two distinct species. The evolutionary history of a set of related species through the repeated occurrence of this speciation process can be represented as a tree-like structure, called a phylogenetic tree or a species tree. Since duplicated genes in a single species also independently accumulate point mutations, insertions and deletions, they drift apart in composition in the same way as genes in two related species. The divergence of all the genes descended from a single gene in an ancestral species can also be represented as a tree, a gene tree that takes into account both speciation and duplication events. In order to reconstruct the evolutionary history from the study of extant species, we use sets of similar genes, with relatively high degree of DNA similarity and usually with some functional resemblance, that appear to have been derived from a common ancestor. The degree of similarity among different instances of the “same gene” in different species can be used to explore their evolutionary history via the reconstruction of gene family histories, namely gene trees. Orthology refers specifically to the relationship between two genes that arose by a speciation event, recent or remote, rather than duplication. Comparing orthologous genes is essential to the correct reconstruction of species trees, so that detecting and identifying orthologous genes is an important problem, and a longstanding challenge, in comparative and evolutionary genomics as well as phylogenetics. A variety of orthology detection methods have been devised in recent years. Although many of these methods are dependent on generating gene and/or species trees, it has been shown that orthology can be estimated at acceptable levels of accuracy without having to infer gene trees and/or reconciling gene trees with species trees. Therefore, there is good reason to look at the connection of trees and orthology from a different angle: How much information about the gene tree, the species tree, and their reconciliation is already contained in the orthology relation among genes? Intriguingly, a solution to the first part of this question has already been given by Boecker and Dress [Boecker and Dress, 1998] in a different context. In particular, they completely characterized certain maps which they called symbolic ultrametrics. Semple and Steel [Semple and Steel, 2003] then presented an algorithm that can be used to reconstruct a phylogenetic tree from any given symbolic ultrametric. In this thesis we investigate a new characterization of orthology relations, based on symbolic ultramterics for recovering the gene tree. According to Fitch’s definition [Fitch, 2000], two genes are (co-)orthologous if their last common ancestor in the gene tree represents a speciation event. On the other hand, when their last common ancestor is a duplication event, the genes are paralogs. The orthology relation on a set of genes is therefore determined by the gene tree and an “event labeling” that identifies each interior vertex of that tree as either a duplication or a speciation event. In the context of analyzing orthology data, the problem of reconciling event-labeled gene trees with a species tree appears as a variant of the reconciliation problem where genes trees have no labels in their internal vertices. When reconciling a gene tree with a species tree, it can be assumed that the species tree is correct or, in the case of a unknown species tree, it can be inferred. Therefore it is crucial to know for a given gene tree whether there even exists a species tree. In this thesis we characterize event-labelled gene trees for which a species tree exists and species trees to which event-labelled gene trees can be mapped. Reconciliation methods are not always the best options for detecting orthology. A fundamental problem is that, aside from multicellular eukaryotes, evolution does not seem to have conformed to the descent-with-modification model that gives rise to tree-like phylogenies. Examples include many cases of prokaryotes and viruses whose evolution involved horizontal gene transfer. To treat the problem of distinguishing orthology and paralogy within a more general framework, graph-based methods have been proposed to detect and differentiate among evolutionary relationships of genes in those organisms. In this work we introduce a measure of orthology that can be used to test graph-based methods and reconciliation methods that detect orthology. Using these results a new algorithm BOTTOM-UP to determine whether a map from the set of vertices of a tree to a set of events is a symbolic ultrametric or not is devised. Additioanlly, a simulation environment designed to generate large gene families with complex duplication histories on which reconstruction algorithms can be tested and software tools can be benchmarked is presented

    Streamlining and Large Ancestral Genomes in Archaea Inferred with a Phylogenetic Birth-and-Death Model

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    Homologous genes originate from a common ancestor through vertical inheritance, duplication, or horizontal gene transfer. Entire homolog families spawned by a single ancestral gene can be identified across multiple genomes based on protein sequence similarity. The sequences, however, do not always reveal conclusively the history of large families. To study the evolution of complete gene repertoires, we propose here a mathematical framework that does not rely on resolved gene family histories. We show that so-called phylogenetic profiles, formed by family sizes across multiple genomes, are sufficient to infer principal evolutionary trends. The main novelty in our approach is an efficient algorithm to compute the likelihood of a phylogenetic profile in a model of birth-and-death processes acting on a phylogeny
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