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Search Results: 1 - 10 of 214289 matches for " Robert G Beiko "
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Telling the whole story in a 10,000-genome world
Robert G Beiko
Biology Direct , 2011, DOI: 10.1186/1745-6150-6-34
Abstract: Complex relationships among even the most-similar genomes demonstrate that proxy-based approaches to simplifying large sets of genomes are not alone sufficient to solve the analysis problem. A phylogenomic analysis of 1173 sequenced bacterial and archaeal genomes generated phylogenetic trees for 159,905 distinct homologous gene sets. The relationships inferred from this set can be heavily dependent on the inclusion of other taxa: for example, phyla such as Spirochaetes, Proteobacteria and Firmicutes are recovered as cohesive groups or split depending on the presence of other specific lineages. Furthermore, named groups such as Acidithiobacillus, Coprothermobacter and Brachyspira show a multitude of affiliations that are more consistent with their ecology than with small subunit ribosomal DNA-based taxonomy. Network and graph representations can illustrate the multitude of conflicting affinities, but all methods impose constraints on the input data and create challenges of construction and interpretation.These complex relationships highlight the need for an inclusive approach to genomic data, and current methods with minor alterations will likely scale to allow the analysis of data sets with 10,000 or more genomes. The main challenges lie in the visualization and interpretation of genomic relationships, and the redefinition of microbial taxonomy when subsets of genomic data are so evidently in conflict with one another, and with the "canonical" molecular taxonomy.The manuscript was reviewed by William Martin, W. Ford Doolittle, Joel Velasco and Eugene Koonin.Our current understanding of microbial diversity, function, and ecology owes a great deal to the ready availability of genome sequence data for a multitude of microorganisms. Genomes, predicted genes and functional annotations can be easily acquired from many online databases, and many of these offer multiple methods of automated retrieval. With a small amount of coding skill, a researcher can couple the acquisit
Assembling networks of microbial genomes using linear programming
Catherine Holloway, Robert G Beiko
BMC Evolutionary Biology , 2010, DOI: 10.1186/1471-2148-10-360
Abstract: We have developed a new approach that uses linear programming to find between-genome relationships, by treating tables of genetic affinities (here, represented by transformed BLAST e-values) as an optimization problem. Validation trials on simulated data demonstrate the effectiveness of the approach in recovering and representing vertical and lateral relationships among genomes. Application of the technique to a set comprising Aquifex aeolicus and 75 other thermophiles showed an important role for large genomes as 'hubs' in the gene sharing network, and suggested that genes are preferentially shared between organisms with similar optimal growth temperatures. We were also able to discover distinct and common genetic contributors to each sequenced representative of genus Pseudomonas.The linear programming approach we have developed can serve as an effective inference tool in its own right, and can be an efficient first step in a more-intensive phylogenomic analysis.Although lateral genetic transfer (LGT) has been recognized for many decades as a potentially important force driving the evolution of prokaryotes [1-3], only in the genome sequencing era has its frequency and importance been fully appreciated [4-6]. LGT mediated by processes of DNA transfer and recombination occurs within populations of closely related bacterial strains [7,8], can operate at great phylogenetic distances [9-11], and can affect bacteriophage, viruses, protists and multicellular eukaryotes [12]. Some observed LGT events are obviously transient and likely part of a cycle of saltation and purging [13], while others confer clear adaptive advantages to their host, and have become fixed in a set of descendent lineages [14,15]. The principal evolutionary consequence of LGT is that traits do not need to be invented ab initio within a genome through (for example) neofunctionalization of a paralogous sequence, but can instead be rapidly acquired from another organism and integrated into the host regul
Phylogenetic identification of lateral genetic transfer events
Robert G Beiko, Nicholas Hamilton
BMC Evolutionary Biology , 2006, DOI: 10.1186/1471-2148-6-15
Abstract: Efficient Evaluation of Edit Paths (EEEP) is a new tree comparison algorithm that uses evolutionarily reasonable constraints to identify and eliminate many unproductive search avenues, reducing the time required to solve many edit path problems. The performance of EEEP compares favourably to that of other algorithms when applied to strictly bifurcating trees with specified numbers of SPR operations. We also used EEEP to recover edit paths from over 19 000 unrooted, incompletely resolved protein trees containing up to 144 taxa as part of a large phylogenomic study. While inferred protein trees were far more similar to a reference supertree than random trees were to each other, the phylogenetic distance spanned by random versus inferred transfer events was similar, suggesting that real transfer events occur most frequently between closely related organisms, but can span large phylogenetic distances as well. While most of the protein trees examined here were very similar to the reference supertree, requiring zero or one edit operations for reconciliation, some trees implied up to 40 transfer events within a single orthologous set of proteins.Since sequence trees typically have no implied root and may contain unresolved or multifurcating nodes, the strategy implemented in EEEP is the most appropriate for phylogenomic analyses. The high degree of consistency among inferred protein trees shows that vertical inheritance is the dominant pattern of evolution, at least for the set of organisms considered here. However, the edit paths inferred using EEEP suggest an important role for genetic transfer in the evolution of microbial genomes as well.An unexpected observation from the early genome sequencing era has been the extent to which different sets of putatively orthologous genes often yield strongly supported but incompatible tree topologies. Whether this disagreement is due primarily to violations of phylogenetic assumptions or to lateral genetic transfer (LGT) is still th
GANN: Genetic algorithm neural networks for the detection of conserved combinations of features in DNA
Robert G Beiko, Robert L Charlebois
BMC Bioinformatics , 2005, DOI: 10.1186/1471-2105-6-36
Abstract: GANN (available at http://bioinformatics.org.au/gann webcite) is a machine learning tool for the detection of conserved features in DNA. The software suite contains programs to extract different regions of genomic DNA from flat files and convert these sequences to indices that reflect sequence and structural composition or the presence of specific protein binding sites. The machine learning component allows the classification of different types of sequences based on subsamples of these indices, and can identify the best combinations of indices and machine learning architecture for sequence discrimination. Another key feature of GANN is the replicated splitting of data into training and test sets, and the implementation of negative controls. In validation experiments, GANN successfully merged important sequence and structural features to yield good predictive models for synthetic and real regulatory regions.GANN is a flexible tool that can search through large sets of sequence and structural feature combinations to identify those that best characterize a set of sequences.The minimal requirement for transcriptional activation is recruitment of an RNA polymerase complex to a promoter sequence of DNA upstream of an open reading frame (ORF). Most genes are also potentially under the control of DNA-binding regulatory proteins or transcription factors that can activate or silence transcription. In bacteria, activator and repressor proteins bind to operator sequences that are typically found near the promoter, and promoter specificity is typically conferred through the sigma subunit of RNA polymerase, which binds the promoter directly [1]. Eukaryotic transcription factors interact with DNA within the promoter, and are responsible for recruitment of the RNA polymerase complex [2]. Regulatory proteins also bind to conserved sites near the promoter region, as well as to enhancers that can be far (> 10 000 nucleotides) upstream or downstream of the promoter. In all domains of l
Lateral gene transfer of an ABC transporter complex between major constituents of the human gut microbiome
Meehan Conor J,Beiko Robert G
BMC Microbiology , 2012, DOI: 10.1186/1471-2180-12-248
Abstract: Background Several links have been established between the human gut microbiome and conditions such as obesity and inflammatory bowel syndrome. This highlights the importance of understanding what properties of the gut microbiome can affect the health of the human host. Studies have been undertaken to determine the species composition of this microbiome and infer functional profiles associated with such host properties. However, lateral gene transfer (LGT) between community members may result in misleading taxonomic attributions for the recipient organisms, thus making species-function links difficult to establish. Results We identified a peptides/nickel transport complex whose components differed in abundance based upon levels of host obesity, and assigned the encoded proteins to members of the microbial community. Each protein was assigned to several distinct taxonomic groups, with moderate levels of agreement observed among different proteins in the complex. Phylogenetic trees of these proteins produced clusters that differed greatly from taxonomic attributions and indicated that habitat-directed LGT of this complex is likely to have occurred, though not always between the same partners. Conclusions These findings demonstrate that certain membrane transport systems may be an important factor within an obese-associated gut microbiome and that such complexes may be acquired several times by different strains of the same species. Additionally, an example of individual proteins from different organisms being transferred into one operon was observed, potentially demonstrating a functional complex despite the donors of the subunits being taxonomically disparate. Our results also highlight the potential impact of habitat-directed LGT on the resident microbiota.
A phylogenomic view of ecological specialization in the Lachnospiraceae, a family of digestive tract-associated bacteria
Conor J. Meehan,Robert G Beiko
PeerJ , 2015, DOI: 10.7287/peerj.preprints.168v1
Abstract: Several bacterial families are known to be highly abundant within the human microbiome, but their ecological roles and evolutionary histories have yet to be investigated in depth. One such family, Lachnospiraceae (phylum Firmicutes, class Clostridia) is abundant in the digestive tracts of many mammals and relatively rare elsewhere. Members of this family have been linked to obesity and protection from colon cancer in humans, mainly due to the association of this group with the production of butyric acid, a substance that is important for both microbial and host epithelial cell growth. We examined the genomes of 30 Lachnospiraceae isolates to better understand the phylogenetic relationships and basis of ecological differentiation within this group. Although this family is often used as an indicator of butyric acid production, fewer than half of the examined genomes contained genes from either of the known pathways that produce butyrate, with the distribution of this function likely arising in part from lateral gene transfer. An investigation of environment-specific functional signatures indicated that human gut-associated Lachnospiraceae possessed genes for endospore formation while other members of this family lacked key sporulation-associated genes, an observation supported by analysis of metagenomes from the human gut, oral cavity and bovine rumen. Our analysis demonstrates that despite a lack of agreement between Lachnospiraceae phylogeny and assigned habitat there are several examples of genetic signatures of habitat preference derived from both lateral gene transfer and gene loss.
Supertrees based on the subtree prune-and-regraft distance
Chris Whidden,Norbert Zeh,Robert G Beiko
PeerJ , 2015, DOI: 10.7287/peerj.preprints.18v1
Abstract: Supertree methods reconcile a set of phylogenetic trees into a single structure that is often interpreted as a branching history of species. A key challenge is combining conflicting evolutionary histories that are due to artifacts of phylogenetic reconstruction and phenomena such as lateral gene transfer (LGT). Although they often work well in practice, existing supertree approaches use optimality criteria that do not reflect underlying processes, have known biases and may be unduly influenced by LGT. We present the first method to construct supertrees by using the subtree prune-and-regraft (SPR) distance as an optimality criterion. Although calculating the rooted SPR distance between a pair of trees is NP-hard, our new maximum agreement forest-based methods can reconcile trees with hundreds of taxa and > 50 transfers in fractions of a second, which enables repeated calculations during the course of an iterative search. Our approach can accommodate trees in which uncertain relationships have been collapsed to multifurcating nodes. Using a series of simulated benchmark datasets, we show that SPR supertrees are more similar to correct species histories under plausible rates of LGT than supertrees based on parsimony or Robinson-Foulds distance criteria. We successfully constructed an SPR supertree from a phylogenomic dataset of 40,631 gene trees that covered 244 genomes representing several major bacterial phyla. Our SPR-based approach also allowed direct inference of highways of gene transfer between bacterial classes and genera; a small number of these highways connect genera in different phyla and can highlight specific genes implicated in long-distance LGT.
Fixed-Parameter and Approximation Algorithms for Maximum Agreement Forests
Chris Whidden,Robert G. Beiko,Norbert Zeh
Computer Science , 2011,
Abstract: We present new and improved fixed-parameter algorithms for computing maximum agreement forests (MAFs) of pairs of rooted binary phylogenetic trees. The size of such a forest for two trees corresponds to their subtree prune-and-regraft distance and, if the agreement forest is acyclic, to their hybridization number. These distance measures are essential tools for understanding reticulate evolution. Our algorithm for computing maximum acyclic agreement forests is the first depth-bounded search algorithm for this problem. Our algorithms substantially outperform the best previous algorithms for these problems.
Fixed-Parameter and Approximation Algorithms for Maximum Agreement Forests of Multifurcating Trees
Chris Whidden,Robert G. Beiko,Norbert Zeh
Computer Science , 2013,
Abstract: We present efficient algorithms for computing a maximum agreement forest (MAF) of a pair of multifurcating (nonbinary) rooted trees. Our algorithms match the running times of the currently best algorithms for the binary case. The size of an MAF corresponds to the subtree prune-and-regraft (SPR) distance of the two trees and is intimately connected to their hybridization number. These distance measures are essential tools for understanding reticulate evolution, such as lateral gene transfer, recombination, and hybridization. Multifurcating trees arise naturally as a result of statistical uncertainty in current tree construction methods.
Detecting recombination in evolving nucleotide sequences
Cheong Chan, Robert G Beiko, Mark A Ragan
BMC Bioinformatics , 2006, DOI: 10.1186/1471-2105-7-412
Abstract: We assessed the effect of subsequent substitutions on the detection of simulated recombination events within sets of four nucleotide sequences under a homogeneous evolutionary model. The amount of subsequent substitutions per site, prior evolutionary history of the sequences, and reciprocality or non-reciprocality of the recombination event all affected the accuracy of the recombination-detecting programs examined. Bayesian phylogenetic-based approaches showed high accuracy in detecting evidence of recombination event and in identifying recombination breakpoints. These approaches were less sensitive to parameter settings than other methods we tested, making them easier to apply to various data sets in a consistent manner.Post-recombination substitutions tend to diminish the predictive accuracy of recombination-detecting programs. The best method for detecting recombined regions is not necessarily the most accurate in identifying recombination breakpoints. For difficult detection problems involving highly divergent sequences or large data sets, different types of approach can be run in succession to increase efficiency, and can potentially yield better predictive accuracy than any single method used in isolation.A homologous recombination event between two DNA sequences can be either reciprocal or non-reciprocal. In reciprocal recombination, genetic information is transferred or exchanged between two similar DNA sequences. In non-reciprocal recombination, a contiguous region of DNA is replaced by, rather than exchanged with, the transferred region. Both types of recombination are a consequence of the DNA mismatch repair mechanism which protects genetic information from damage. Gene conversion, for example, is a cross-over process between homologous sequences in which a DNA strand replaces a damaged partner DNA strand with a copy of its own sequence [1]. A number of models describe the mechanisms of recombination, addressing issues of strand breakage, displacement and
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