Does a tree-like phylogeny only exist at the tips in the prokaryotes?

The extent to which prokaryotic evolution has been influenced by horizontal gene transfer (HGT) and therefore might be more of a network than a tree is unclear. Here we use supertree methods to ask whether a definitive prokaryotic phylogenetic tree exists and whether it can be confidently inferred using orthologous genes. We analysed an 11-taxon dataset spanning the deepest divisions of prokaryotic relationships, a 10-taxon dataset spanning the relatively recent gamma-proteobacteria and a 61-taxon dataset spanning both, using species for which complete genomes are available. Congruence among gene trees spanning deep relationships is not better than random. By contrast, a strong, almost perfect phylogenetic signal exists in gamma-proteobacterial genes. Deep-level prokaryotic relationships are difficult to infer because of signal erosion, systematic bias, hidden paralogy and/or HGT. Our results do not preclude levels of HGT that would be inconsistent with the notion of a prokaryotic phylogeny. This approach will help decide the extent to which we can say that there is a prokaryotic phylogeny and where in the phylogeny a cohesive genomic signal exists.     

An information-based sequence distance and its application to whole mitochondrial genome phylogeny

MOTIVATION: Traditional sequence distances require an alignment and therefore are not directly applicable to the problem of whole genome phylogeny where events such as rearrangements make full length alignments impossible. We present a sequence distance that works on unaligned sequences using the information theoretical concept of Kolmogorov complexity and a program to estimate this distance. RESULTS: We establish the mathematical foundations of our distance and illustrate its use by constructing a phylogeny of the Eutherian orders using complete unaligned mitochondrial genomes. This phylogeny is consistent with the commonly accepted one for the Eutherians. A second, larger mammalian dataset is also analyzed, yielding a phylogeny generally consistent with the commonly accepted one for the mammals. AVAILABILITY: The program to estimate our sequence distance, is available at http://www.cs.cityu.edu.hk/~cssamk/gencomp/GenCompress1.htm. The distance matrices used to generate our phylogenies are available at http://www.math.uwaterloo.ca/~mli/distance.html.     

A compression-based approach for coding sequences identification. I. Application to prokaryotic genomes.

Most of the gene prediction algorithms for prokaryotes are based on Hidden Markov Models or similar machine-learning approaches, which imply the optimization of a high number of parameters. The present paper presents a novel method for the classification of coding and non-coding regions in prokaryotic genomes, based on a suitably defined compression index of a DNA sequence. The main features of this new method are the non-parametric logic and the costruction of a dictionary of words extracted from the sequences. These dictionaries can be very useful to perform further analyses on the genomic sequences themselves. The proposed approach has been applied on some prokaryotic complete genomes, obtaining optimal scores of correctly recognized coding and non-coding regions. Several false-positive and false-negative cases have been investigated in detail, which have revealed that this approach can fail in the presence of highly structured coding regions (e.g., genes coding for modular proteins) or quasi-random non-coding regions (e.g., regions hosting non-functional fragments of copies of functional genes; regions hosting promoters or other protein-binding sequences). We perform an overall comparison with other gene-finder software, since at this step we are not interested in building another gene-finder system, but only in exploring the possibility of the suggested approach.     

生命之树的原核枝——组分矢量方法的贡献

The Composition Vector Tree (CVTree) is a parameter-free and alignment-free method to infer prokaryotic phylogeny from their complete genomes. It is distinct from the traditional 16S rRNA analysis in both the input data and the methodology. The prokaryotic phylogenetic trees constructed by using the CVTree method agree well with the Bergey's taxonomy in all major groupings and fine branching patterns. Thus, combined use of the CVTree approach and the 16S rRNA analysis may provide an objective and reliable reconstruction of the prokaryotic branch of the Tree of Life.     

Genome phylogenetic analysis based on extended gene contents

With the rapid growth of entire genome data, whole-genome approaches such as gene content become popular for genome phylogeny inference, including the tree of life. However, the underlying model for genome evolution is unclear, and the proposed (ad hoc) genome distance measure may violate the additivity. In this article, we formulate a stochastic framework for genome evolution, which provides a basis for defining an additive genome distance. However, we show that it is difficult to utilize the typical gene content data-i.e., the presence or absence of gene families across genomes-to estimate the genome distance. We solve this problem by introducing the concept of extended gene content; that is, the status of a gene family in a given genome could be absence, presence as single copy, or presence as duplicates, any of which can be used to estimate the genome distance and phylogenetic inference. Computer simulation shows that the new tree-making method is efficient, consistent, and fairly robust. The example of 35 microbial complete genomes demonstrates that it is useful not only to study the universal tree of life but also to explore the evolutionary pattern of genomes.     

A Survey of Codon and Amino Acid Frequency Bias in Microbial Genomes Focusing on Translational Efficiency

Unequal use of synonymous codons has been found in several prokaryotic and eukaryotic genomes. This bias has been associated with translational efficiency. The prevalence of this bias across lineages is currently unknown. Here, a new method (GCB) to measure codon usage bias is presented. It uses an iterative approach for the determination of codon scores and allows the computation of an index of codon bias suitable for interspecies comparison. A server to calculate GCB-values of individual genes as well as a list of compiled results are available at . The method was applied to complete bacterial genomes. The relation of codon usage bias with amino acid composition and the choice of stop codons were determined and discussed.     

Comparison of Methods of Detection of Exceptional Sequences in Prokaryotic Genomes

Many proteins need recognition of specific DNA sequences for functioning. The number of recognition sites and their distribution along the DNA might be of biological importance. For example, the number of restriction sites is often reduced in prokaryotic and phage genomes to decrease the probability of DNA cleavage by restriction endonucleases. We call a sequence an exceptional one if its frequency in a genome significantly differs from one predicted by some mathematical model. An exceptional sequence could be either under- or over-represented, depending on its frequency in comparison with the predicted one. Exceptional sequences could be considered biologically meaningful, for example, as targets of DNA-binding proteins or as parts of abundant repetitive elements. Several methods to predict frequency of a short sequence in a genome, based on actual frequencies of certain its subsequences, are used. The most popular are methods based on Markov chain models. But any rigorous comparison of the methods has not previously been performed. We compared three methods for the prediction of short sequence frequencies: the maximum-order Markov chain model-based method, the method that uses geometric mean of extended Markovian estimates, and the method that utilizes frequencies of all subsequences including discontiguous ones. We applied them to restriction sites in complete genomes of 2500 prokaryotic species and demonstrated that the results depend greatly on the method used: lists of 5% of the most under-represented sites differed by up to 50%. The method designed by Burge and coauthors in 1992, which utilizes all subsequences of the sequence, showed a higher precision than the other two methods both on prokaryotic genomes and randomly generated sequences after computational imitation of selective pressure. We propose this method as the first choice for detection of exceptional sequences in prokaryotic genomes.     

Evolutionary sequence analysis of complete eukaryote genomes

Background  

Gene duplication and gene loss during the evolution of eukaryotes have hindered attempts to estimate phylogenies and divergence times of species. Although current methods that identify clusters of orthologous genes in complete genomes have helped to investigate gene function and gene content, they have not been optimized for evolutionary sequence analyses requiring strict orthology and complete gene matrices. Here we adopt a relatively simple and fast genome comparison approach designed to assemble orthologs for evolutionary analysis. Our approach identifies single-copy genes representing only species divergences (panorthologs) in order to minimize potential errors caused by gene duplication. We apply this approach to complete sets of proteins from published eukaryote genomes specifically for phylogeny and time estimation.     

Early eukaryote evolution based on mitochondrial gene order breakpoints.

The comparison of the gene orders in a set of genomes can be used to infer their phylogenetic relationships and to reconstruct ancestral gene orders. For three genomes this is done by solving the "median problem for breakpoints"; this solution can then be incorporated into a routine for estimating optimal gene orders for all the ancestral genomes in a fixed phylogeny. For the difficult (and most prevalent) case where the genomes contain partially different sets of genes, we present a general heuristic for the median problem for induced breakpoints. A fixed-phylogeny optimization based on this is applied in a phylogenetic study of a set of completely sequenced protist mitochondrial genomes, confirming some of the recent sequence-based groupings which have been proposed and, conversely, confirming the usefulness of the breakpoint method as a phylogenetic tool even for small genomes.     

Annotation-free delineation of prokaryotic homology groups

Phylogenomic studies of prokaryotic taxa often assume conserved marker genes are homologous across their length. However, processes such as horizontal gene transfer or gene duplication and loss may disrupt this homology by recombining only parts of genes, causing gene fission or fusion. We show using simulation that it is necessary to delineate homology groups in a set of bacterial genomes without relying on gene annotations to define the boundaries of homologous regions. To solve this problem, we have developed a graph-based algorithm to partition a set of bacterial genomes into Maximal Homologous Groups of sequences (MHGs) where each MHG is a maximal set of maximum-length sequences which are homologous across the entire sequence alignment. We applied our algorithm to a dataset of 19 Enterobacteriaceae species and found that MHGs cover much greater proportions of genomes than markers and, relatedly, are less biased in terms of the functions of the genes they cover. We zoomed in on the correlation between each individual marker and their overlapping MHGs, and show that few phylogenetic splits supported by the markers are supported by the MHGs while many marker-supported splits are contradicted by the MHGs. A comparison of the species tree inferred from marker genes with the species tree inferred from MHGs suggests that the increased bias and lack of genome coverage by markers causes incorrect inferences as to the overall relationship between bacterial taxa.     

Fast algorithms for large-scale genome alignment and comparison

We describe a suffix-tree algorithm that can align the entire genome sequences of eukaryotic and prokaryotic organisms with minimal use of computer time and memory. The new system, MUMmer 2, runs three times faster while using one-third as much memory as the original MUMmer system. It has been used successfully to align the entire human and mouse genomes to each other, and to align numerous smaller eukaryotic and prokaryotic genomes. A new module permits the alignment of multiple DNA sequence fragments, which has proven valuable in the comparison of incomplete genome sequences. We also describe a method to align more distantly related genomes by detecting protein sequence homology. This extension to MUMmer aligns two genomes after translating the sequence in all six reading frames, extracts all matching protein sequences and then clusters together matches. This method has been applied to both incomplete and complete genome sequences in order to detect regions of conserved synteny, in which multiple proteins from one organism are found in the same order and orientation in another. The system code is being made freely available by the authors.     

Distilling artificial recombinants from large sets of complete mtDNA genomes

Background

Large-scale genome sequencing poses enormous problems to the logistics of laboratory work and data handling. When numerous fragments of different genomes are PCR amplified and sequenced in a laboratory, there is a high immanent risk of sample confusion. For genetic markers, such as mitochondrial DNA (mtDNA), which are free of natural recombination, single instances of sample mix-up involving different branches of the mtDNA phylogeny would give rise to reticulate patterns and should therefore be detectable.

Methodology/Principal Findings

We have developed a strategy for comparing new complete mtDNA genomes, one by one, to a current skeleton of the worldwide mtDNA phylogeny. The mutations distinguishing the reference sequence from a putative recombinant sequence can then be allocated to two or more different branches of this phylogenetic skeleton. Thus, one would search for two (or three) near-matches in the total mtDNA database that together best explain the variation seen in the recombinants. The evolutionary pathway from the mtDNA tree connecting this pair together with the recombinant then generate a grid-like median network, from which one can read off the exchanged segments.

Conclusions

We have applied this procedure to a large collection of complete human mtDNA sequences, where several recombinants could be distilled by our method. All these recombinant sequences were subsequently corrected by de novo experiments – fully concordant with the predictions from our data-analytical approach.     

Distance-Based Genome Rearrangement Phylogeny

Evolution operates on whole genomes through direct rearrangements of genes, such as inversions, transpositions, and inverted transpositions, as well as through operations, such as duplications, losses, and transfers, that also affect the gene content of the genomes. Because these events are rare relative to nucleotide substitutions, gene order data offer the possibility of resolving ancient branches in the tree of life; the combination of gene order data with sequence data also has the potential to provide more robust phylogenetic reconstructions, since each can elucidate evolution at different time scales. Distance corrections greatly improve the accuracy of phylogeny reconstructions from DNA sequences, enabling distance-based methods to approach the accuracy of the more elaborate methods based on parsimony or likelihood at a fraction of the computational cost. This paper focuses on developing distance correction methods for phylogeny reconstruction from whole genomes. The main question we investigate is how to estimate evolutionary histories from whole genomes with equal gene content, and we present a technique, the empirically derived estimator (EDE), that we have developed for this purpose. We study the use of EDE on whole genomes with identical gene content, and we explore the accuracy of phylogenies inferred using EDE with the neighbor joining and minimum evolution methods under a wide range of model conditions. Our study shows that tree reconstruction under these two methods is much more accurate when based on EDE distances than when based on other distances previously suggested for whole genomes. Electronic Supplementary Material Electronic Supplementary material is available for this article at and accessible for authorised users. [Reviewing Editor: Dr. Martin Kreitman]     

Signature genes as a phylogenomic tool

Gene content has been shown to contain a strong phylogenetic signal, yet its usage for phylogenetic questions is hampered by horizontal gene transfer and parallel gene loss and until now required completely sequenced genomes. Here, we introduce an approach that allows the phylogenetic signal in gene content to be applied to any set of sequences, using signature genes for phylogenetic classification. The hundreds of publicly available genomes allow us to identify signature genes at various taxonomic depths, and we show how the presence of signature genes in an unspecified sample can be used to characterize its taxonomic composition. We identify 8,362 signature genes specific for 112 prokaryotic taxa. We show that these signature genes can be used to address phylogenetic questions on the basis of gene content in cases where classic gene content or sequence analyses provide an ambiguous answer, such as for Nanoarchaeum equitans, and even in cases where complete genomes are not available, such as for metagenomics data. Cross-validation experiments leaving out up to 30% of the species show that approximately 92% of the signature genes correctly place the species in a related clade. Analyses of metagenomics data sets with the signature gene approach are in good agreement with the previously reported species distributions based on phylogenetic analysis of marker genes. Summarizing, signature genes can complement traditional sequence-based methods in addressing taxonomic questions.     

Prokaryote phylogeny without sequence alignment: from avoidance signature to composition distance

This is a review of a new and essentially simple method of inferring phylogenetic relationships from complete genome data without using sequence alignment. The method is based on counting the appearance frequency of oligopeptides of a fixed length (up to K = 6) in the collection of protein sequences of a species. It is a method without fine adjustment and choice of genes. Applied to prokaryotic genomes it has led to results comparable with the bacteriologists' systematics as reflected in the latest 2002 outline of the Bergey's Manual of Systematic Bacteriology. The method has also been used to compare chloroplast genomes and to the phylogeny of Coronaviruses including human SARS-CoV. A key point in our approach is subtraction of a random background from the original counts by using a Markov model of order K-2 in order to highlight the shaping role of natural selection. The implications of the subtraction procedure is specially analyzed and further development of the new approach is indicated.     

Correlation between strand asymmetry and phylogeny in mitochondrial DNA

An evolutionary distance is introduced in order to propose an efficient and feasible procedure for phylogeny studies. Our analysis are based on the strand asymmetry property of mitochondrial DNA, but can be applied to other genomes. Comparison of our results with those reported in conventional phylogenetic trees, gives confidence about our approximation. Our findings support the hypotheses about the origin of the skew and its dependence upon evolutionary pressures, and improves previous efforts on using the strand asymmetry property of genomes for phylogeny inference. For the evolutionary distance introduced here, we observe that the more adequate technique for tree reconstructions correspond to an average link method which employs a sequential clustering algorithm.     

The prokaryotic selenoproteome

In the genetic code, the UGA codon has a dual function as it encodes selenocysteine (Sec) and serves as a stop signal. However, only the translation terminator function is used in gene annotation programs, resulting in misannotation of selenoprotein genes. Here, we applied two independent bioinformatics approaches to characterize a selenoprotein set in prokaryotic genomes. One method searched for selenoprotein genes by identifying RNA stem-loop structures, selenocysteine insertion sequence elements; the second approach identified Sec/Cys pairs in homologous sequences. These analyses identified all or almost all selenoproteins in completely sequenced bacterial and archaeal genomes and provided a view on the distribution and composition of prokaryotic selenoproteomes. In addition, lineage-specific and core selenoproteins were detected, which provided insights into the mechanisms of selenoprotein evolution. Characterization of selenoproteomes allows interpretation of other UGA codons in completed genomes of prokaryotes as terminators, addressing the UGA dual-function problem.     

From Gene Trees to Organismal Phylogeny in Prokaryotes:The Case of the γ-Proteobacteria

The rapid increase in published genomic sequences for bacteria presents the first opportunity to reconstruct evolutionary events on the scale of entire genomes. However, extensive lateral gene transfer (LGT) may thwart this goal by preventing the establishment of organismal relationships based on individual gene phylogenies. The group for which cases of LGT are most frequently documented and for which the greatest density of complete genome sequences is available is the γ-Proteobacteria, an ecologically diverse and ancient group including free-living species as well as pathogens and intracellular symbionts of plants and animals. We propose an approach to multigene phylogeny using complete genomes and apply it to the case of the γ-Proteobacteria. We first applied stringent criteria to identify a set of likely gene orthologs and then tested the compatibilities of the resulting protein alignments with several phylogenetic hypotheses. Our results demonstrate phylogenetic concordance among virtually all (203 of 205) of the selected gene families, with each of the exceptions consistent with a single LGT event. The concatenated sequences of the concordant families yield a fully resolved phylogeny. This topology also received strong support in analyses aimed at excluding effects of heterogeneity in nucleotide base composition across lineages. Our analysis indicates that single-copy orthologous genes are resistant to horizontal transfer, even in ancient bacterial groups subject to high rates of LGT. This gene set can be identified and used to yield robust hypotheses for organismal phylogenies, thus establishing a foundation for reconstructing the evolutionary transitions, such as gene transfer, that underlie diversity in genome content and organization.