Mark A Ragan

Publications of Mark A Ragan

• Gene regulatory network inference: evaluation and application to ovarian cancer allows the prioritization of drug targets.

  Authors: Piyush B Madhamshettiwar, Stefan R Maetschke, Melissa J Davis, Antonio Reverter, Mark A Ragan

  Genome medicine. 05/2012; 4(5):41.

  ABSTRACT: BACKGROUND: Altered networks of gene regulation underlie many complex conditions including cancer. Inferring gene regulatory networks from high-throughput microarray expression data is aABSTRACT: BACKGROUND: Altered networks of gene regulation underlie many complex conditions including cancer. Inferring gene regulatory networks from high-throughput microarray expression data is a fundamental but challenging task in computational systems biology and its translation to genomic medicine. Although diverse computational and statistical approaches have been brought to bear on the gene regulatory network inference problem, their relative strengths and disadvantages remain poorly understood, largely because comparative analyses usually consider only small subsets of methods, use only synthetic data, and/or fail to adopt a common measure of inference quality. METHODS: We report a comprehensive comparative evaluation of nine state-of-the art gene regulatory network inference methods encompassing the main algorithmic approaches (mutual information, correlation, partial correlation, random forests, support vector machines) using 38 simulated datasets and empirical serous papillary ovarian adenocarcinoma expression-microarray data. We then apply the best-performing method to infer normal and cancer networks. We assess the druggability of the proteins encoded by our predicted target genes using the CancerResource and PharmGKB webtools and databases. RESULTS: We observe large differences in the accuracy with which these methods predict the underlying gene regulatory network depending on features of the data, network size, topology, experiment type, and parameter settings. Applying the best-performing method (the supervised method SIRENE) to the serous papillary ovarian adenocarcinoma dataset, we infer and rank regulatory interactions, some previously reported and others novel. For selected novel interactions we propose testable mechanistic models linking gene regulation to cancer. Using network analysis and visualisation we uncover cross-regulation of angiogenesis-specific genes through three key transcription factors in normal and cancer conditions. Druggabilty analysis of proteins encoded by the 10 highest-confidence target genes, and by 15 genes with differential regulation in normal and cancer conditions, reveals 75% to be potential drug targets. CONCLUSIONS: Our study represents a concrete application of gene regulatory network inference to ovarian cancer, demonstrating the complete cycle of computational systems biology research, from genome-scale data analysis via network inference, evaluation of methods, to the generation of novel testable hypotheses, their prioritisation for experimental validation, and discovery of potential drug targets.

• Automatic Selection of Reference Taxa for Protein-Protein Interaction Prediction with Phylogenetic Profiling.

  Authors: Martin Simonsen, Stefan Maetschke, Mark A Ragan

  Bioinformatics (Oxford, England). 01/2012;

  MOTIVATION: Phylogenetic profiling methods can achieve good accuracy in predicting protein-protein interactions, especially in prokaryotes. Recent studies have shown that the choice of reference taxaMOTIVATION: Phylogenetic profiling methods can achieve good accuracy in predicting protein-protein interactions, especially in prokaryotes. Recent studies have shown that the choice of reference taxa is critical for accurate prediction, but with more than 2,500 fully sequenced taxa publicly available, identifying the most-informative reference taxa is becoming increasingly difficult. Previous studies on the selection of reference taxa have provided guidelines for manual taxon selection, and for eliminating closely related taxa. However, no general strategy for automatic selection of reference taxa is currently available. RESULTS: We present three novel methods for automating the selection of reference taxa, using machine learning based on known protein-protein interaction networks. One of these methods in particular, Tree-Based Search, yields greatly improved prediction accuracies. We further show that different methods for constituting phylogenetic profiles often require very different reference taxa sets to support high prediction accuracy. AVAILABILITY: The datasets and software used in the experiments can be found at http://users-birc.au.dk/zxr/phyloprof/ CONTACT: zxr@birc.au.dk.

• Evolutionary dynamics of small RNAs in 27 Escherichia coli and Shigella genomes.

  Authors: Elizabeth Skippington, Mark A Ragan

  Genome biology and evolution. 01/2012;

  Small RNAs (sRNAs) are widespread in bacteria and play critical roles in regulating physiological processes. They are best-characterised in Escherichia coli K-12 MG1655, where 83 sRNAs constituteSmall RNAs (sRNAs) are widespread in bacteria and play critical roles in regulating physiological processes. They are best-characterised in Escherichia coli K-12 MG1655, where 83 sRNAs constitute nearly 2% of the gene complement. Most sRNAs act by base-pairing with a target mRNA, modulating its translation and/or stability; many of these RNAs share only limited complementarity to their mRNA target, and require the chaperone Hfq to facilitate base-pairing. Little is known about the evolutionary dynamics of bacterial sRNAs. Here we apply phylogenetic and network analyses to investigate the evolutionary processes and principles that govern sRNA gene distribution in 27 Escherichia coli and Shigella genomes. We identify core (encoded in all 27 genomes) and variable sRNAs; more than two-thirds of the E. coli K-12 MG1655 sRNAs are core, while the others show patterns of presence and absence that are principally due to genetic loss, not duplication or lateral genetic transfer. We present evidence that variable sRNAs are less tightly integrated into cellular genetic regulatory networks than are the core sRNAs, and that Hfq facilitates post-transcriptional cross-talk between the E. coli - Shigella core and variable genomes. Finally, we present evidence that more than 80% of genes targeted by Hfq-associated core sRNAs have been transferred within the E. coli - Shigella clade and that most of these genes have been transferred intact. These results suggest that Hfq and sRNAs help integrate laterally acquired genes into established regulatory networks.

• Gene Ontology-driven inference of protein-protein interactions using inducers.

  Authors: Stefan R Maetschke, Martin Simonsen, Melissa J Davis, Mark A Ragan

  Bioinformatics (Oxford, England). 11/2011; 28(1):69-75.

  Protein-protein interactions (PPIs) are pivotal for many biological processes and similarity in Gene Ontology (GO) annotation has been found to be one of the strongest indicators for PPI. MostProtein-protein interactions (PPIs) are pivotal for many biological processes and similarity in Gene Ontology (GO) annotation has been found to be one of the strongest indicators for PPI. Most GO-driven algorithms for PPI inference combine machine learning and semantic similarity techniques. We introduce the concept of inducers as a method to integrate both approaches more effectively, leading to superior prediction accuracies. An inducer (ULCA) in combination with a Random Forest classifier compares favorably to several sequence-based methods, semantic similarity measures and multi-kernel approaches. On a newly created set of high-quality interaction data, the proposed method achieves high cross-species prediction accuracies (Area under the ROC curve ≤ 0.88), rendering it a valuable companion to sequence-based methods. Software and datasets are available at http://bioinformatics.org.au/go2ppi/ m.ragan@uq.edu.au.

• Lateral transfer of genes and gene fragments in Staphylococcus extends beyond mobile elements.

  Authors: Cheong Xin Chan, Robert G Beiko, Mark A Ragan

  Journal of bacteriology. 05/2011; 193(15):3964-77.

  The widespread presence of antibiotic resistance and virulence among Staphylococcus isolates has been attributed in part to lateral genetic transfer (LGT), but little is known about the broaderThe widespread presence of antibiotic resistance and virulence among Staphylococcus isolates has been attributed in part to lateral genetic transfer (LGT), but little is known about the broader extent of LGT within this genus. Here we report the first systematic study of the modularity of genetic transfer among 13 Staphylococcus genomes covering four distinct named species. Using a topology-based phylogenetic approach, we found, among 1,354 sets of homologous genes examined, strong evidence of LGT in 368 (27.1%) gene sets, and weaker evidence in another 259 (19.1%). Within-gene and whole-gene transfer contribute almost equally to the topological discordance of these gene sets against a reference phylogeny. Comparing genetic transfer in single-copy and in multicopy gene sets, we observed a higher frequency of LGT in the latter, and a substantial functional bias in cases of whole-gene transfer (little such bias was observed in cases of fragmentary genetic transfer). We found evidence that lateral transfer, particularly of entire genes, impacts not only functions related to antibiotic, drug, and heavy-metal resistance, as well as membrane transport, but also core informational and metabolic functions not associated with mobile elements. Although patterns of sequence similarity support the cohesion of recognized species, LGT within S. aureus appears frequently to disrupt clonal complexes. Our results demonstrate that LGT and gene duplication play important parts in functional innovation in staphylococcal genomes.

• Mineralocorticoid receptors: evolutionary and pathophysiological considerations.

  Authors: Karin S Kassahn, Mark A Ragan, John W Funder

  Endocrinology. 02/2011; 152(5):1883-90.

  Mineralocorticoid receptors (MR), glucocorticoid receptors (GR), progesterone receptors (PR), and androgen receptors (AR) comprise a closely related subfamily within the human 49-member nuclearMineralocorticoid receptors (MR), glucocorticoid receptors (GR), progesterone receptors (PR), and androgen receptors (AR) comprise a closely related subfamily within the human 49-member nuclear receptor family. These receptors and their cognate ligands play major roles in homeostasis, reproduction, growth, and development, despite which their evolution and diversification remains incompletely understood. Several conflicting models have been advanced for the evolution of this subfamily. We have thus undertaken Bayesian and maximum likelihood phylogenetic analyses of this subfamily. The Bayesian consensus and maximum likelihood trees support a basal position for MR, with the PR and AR forming a sister clade. We next performed analyses using topological constraints to directly contrast the likelihood of seven phylogenetic models. In these analyses, three models have similar support: one proposes two sister clades (MR and GR, PR and AR); the other two propose a different subfamily member (MR or GR) to be the first to have diverged. Ancestral state reconstructions at sites critical for physiological function show that the S810L mutation in the MR, which results in the MR being similar to estrogen receptors and the more distantly related retinoic acid receptor-α is likely to reflect the ancestral receptor sequence before the divergence of this subfamily and provides further support for MR having been the first of the subfamily to diverge. Finally, we drew on pathophysiological comparisons to help to distinguish the different models. On the basis of our phylogenetic analyses and pathophysiological considerations, we propose that the MR was the first to diverge from the ancestral gene lineage from which this subfamily derived.

• Quantitative prediction of miRNA-mRNA interaction based on equilibrium concentrations.

  Authors: Chikako Ragan, Michael Zuker, Mark A Ragan

  PLoS computational biology. 02/2011; 7(2):e1001090.

  MicroRNAs (miRNAs) suppress gene expression by forming a duplex with a target messenger RNA (mRNA), blocking translation or initiating cleavage. Computational approaches have proven valuable forMicroRNAs (miRNAs) suppress gene expression by forming a duplex with a target messenger RNA (mRNA), blocking translation or initiating cleavage. Computational approaches have proven valuable for predicting which mRNAs can be targeted by a given miRNA, but currently available prediction methods do not address the extent of duplex formation under physiological conditions. Some miRNAs can at low concentrations bind to target mRNAs, whereas others are unlikely to bind within a physiologically relevant concentration range. Here we present a novel approach in which we find potential target sites on mRNA that minimize the calculated free energy of duplex formation, compute the free energy change involved in unfolding these sites, and use these energies to estimate the extent of duplex formation at specified initial concentrations of both species. We compare our predictions to experimentally confirmed miRNA-mRNA interactions (and non-interactions) in Drosophila melanogaster and in human. Although our method does not predict whether the targeted mRNA is degraded and/or its translation to protein inhibited, our quantitative estimates generally track experimentally supported results, indicating that this approach can be used to predict whether an interaction occurs at specified concentrations. Our approach offers a more-quantitative understanding of post-translational regulation in different cell types, tissues, and developmental conditions.

• Lateral genetic transfer and the construction of genetic exchange communities.

  Authors: Elizabeth Skippington, Mark A Ragan

  FEMS microbiology reviews. 01/2011; 35(5):707-35.

  Lateral genetic transfer (LGT) is a major source of phenotypic innovation among bacteria. Determinants for antibiotic resistance and other adaptive traits can spread rapidly, particularly byLateral genetic transfer (LGT) is a major source of phenotypic innovation among bacteria. Determinants for antibiotic resistance and other adaptive traits can spread rapidly, particularly by conjugative plasmids, but also phages and natural transformation. Each successive step from the uptake of foreign DNA, its genetic recombination and regulatory integration, to its establishment in the host population presents differential barriers and opportunities. The emergence of successive multidrug-resistant strains of Staphylococcus aureus illustrates the ongoing role of LGT in the combinatorial assembly of pathogens. The dynamic interplay among hosts, vectors, DNA elements, combinations of genetic determinants and environments constructs communities of genetic exchange. These relations can be abstracted as a graph, within which an exchange community might correspond to a path, transitively closed set, clique or near-clique. We provide a set-based definition, and review the features of actual genetic exchange communities (GECs), adopting first a knowledge-driven approach based on literature, and then a synoptic data-centric bioinformatic approach. GECs are diverse, but share some common features. Differential opportunity and barriers to lateral genetic transfer create bacterial communities of exchange.

• Within-species lateral genetic transfer and the evolution of transcriptional regulation in Escherichia coli and Shigella.

  Authors: Elizabeth Skippington, Mark A Ragan

  BMC genomics. 01/2011; 12:532.

  Changes in transcriptional regulation underlie many of the phenotypic differences observed within and between species of bacteria. Lateral genetic transfer (LGT) can significantly impact theChanges in transcriptional regulation underlie many of the phenotypic differences observed within and between species of bacteria. Lateral genetic transfer (LGT) can significantly impact the transcription factor (TF) genes which drive these transcriptional changes. Although much emphasis has been placed on LGT of intact genes, the units of transfer and recombination do not necessarily correspond to regions delineated by exact gene boundaries. Here we apply phylogenetic and network-based methods to investigate the relationship between units of lateral transfer and recombination within the Escherichia coli - Shigella clade and the topological properties of genes in the E. coli transcriptional regulatory network (TRN). We carried out a systematic phylogenetic study of genetic transfer among 5282 sets of putatively orthologous genes from 27 strains belonging to the E. coli - Shigella clade. We then used these results to examine the evolutionary histories of TF genes, as well as the transcriptional regulation of lateral genes. We found evidence of LGT in 2655 (50.3%) gene sets: 678 (12.8%) show evidence of recombination breakpoints within the gene boundaries. Thus, within- and whole- gene lateral transfer is widespread among strains of E. coli and Shigella. We found that unlike global regulators, which have mostly evolved vertically, neighbour regulators (genes which regulate adjacent genes on the chromosome) have frequently been subject to transfer within the E. coli - Shigella clade. At least 56 (62%) of the 90 neighbour regulator gene sets examined show evidence of LGT, 19 (34%) of which have internal recombination breakpoints. Neighbour regulators show no evidence of co-transfer with their nearby target genes. Rather, the frequency of recombination breakpoints, and conflicting evolutionary histories among neighbour regulators and their target genes, suggest that the genomic regions encoding these genes have been constructed through successive layering of LGT events within the clade. We find no difference in the relative complexity of regulation (i.e. the number of regulators) of lateral versus vertical genes. Neighbour regulators show higher frequencies of transfer than other types of regulatory genes. This implicates the topological properties of regulatory genes in the TRN, and their physical proximity to targets on the chromosome, as contributing to successful LGT. The prevalence of recombination breakpoints within regulatory and target gene sets indicates that within-gene transfer has had a significant cumulative effect on the evolution of regulatory interactions in E. coli and Shigella.

• Automatic, context-specific generation of Gene Ontology slims.

  Authors: Melissa J Davis, Muhammad Shoaib B Sehgal, Mark A Ragan

  BMC bioinformatics. 10/2010; 11:498.

  The use of ontologies to control vocabulary and structure annotation has added value to genome-scale data, and contributed to the capture and re-use of knowledge across research domains. GeneThe use of ontologies to control vocabulary and structure annotation has added value to genome-scale data, and contributed to the capture and re-use of knowledge across research domains. Gene Ontology (GO) is widely used to capture detailed expert knowledge in genomic-scale datasets and as a consequence has grown to contain many terms, making it unwieldy for many applications. To increase its ease of manipulation and efficiency of use, subsets called GO slims are often created by collapsing terms upward into more general, high-level terms relevant to a particular context. Creation of a GO slim currently requires manipulation and editing of GO by an expert (or community) familiar with both the ontology and the biological context. Decisions about which terms to include are necessarily subjective, and the creation process itself and subsequent curation are time-consuming and largely manual. Here we present an objective framework for generating customised ontology slims for specific annotated datasets, exploiting information latent in the structure of the ontology graph and in the annotation data. This framework combines ontology engineering approaches, and a data-driven algorithm that draws on graph and information theory. We illustrate this method by application to GO, generating GO slims at different information thresholds, characterising their depth of semantics and demonstrating the resulting gains in statistical power. Our GO slim creation pipeline is available for use in conjunction with any GO-annotated dataset, and creates dataset-specific, objectively defined slims. This method is fast and scalable for application to other biomedical ontologies.

• Functional implications of the emergence of alternative splicing in hnRNP A/B transcripts.

  Authors: Siew Ping Han, Karin S Kassahn, Adam Skarshewski, Mark A Ragan, Joseph A Rothnagel, Ross Smith

  RNA (New York, N.Y.). 09/2010; 16(9):1760-8.

  The heterogeneous nuclear ribonucleoproteins (hnRNPs) A/B are a family of RNA-binding proteins that participate in various aspects of nucleic acid metabolism, including mRNA trafficking, telomereThe heterogeneous nuclear ribonucleoproteins (hnRNPs) A/B are a family of RNA-binding proteins that participate in various aspects of nucleic acid metabolism, including mRNA trafficking, telomere maintenance, and splicing. They are both regulators and targets of alternative splicing, and the patterns of alternative splicing of their transcripts have diverged between paralogs and between orthologs in different species. Surprisingly, the extent of this splicing variation and its implications for post-transcriptional regulation have remained largely unexplored. Here, we conducted a detailed analysis of hnRNP A/B sequences and expression patterns across six vertebrates. Alternative exons emerged via the introduction of new splice sites, changes in the strengths of existing splice sites, and the accumulation of auxiliary splicing regulatory motifs. Observed isoform expression patterns could be attributed to the frequency and strength of cis-elements. We found a trend toward increased splicing variation in mammals and identified novel alternatively spliced isoforms in human and chicken. Pulldown and translational assays demonstrated that the inclusion of alternative exons altered the affinity of hnRNP A/B proteins for their cognate nucleic acids and modified protein expression levels. As the hnRNPs A/B regulate several key steps in mRNA processing, the involvement of diverse hnRNP isoforms in multiple cellular contexts and species implies concomitant differences in the transcriptional output of these systems. We conclude that the emergence of alternative splicing in the hnRNPs A/B has contributed to the diversification of their roles in the regulation of alternative splicing and has thus added an unexpected layer of regulatory complexity to transcription in vertebrates.

• A semantic web ontology for small molecules and their biological targets.

  Authors: Jooyoung Choi, Melissa J Davis, Andrew F Newman, Mark A Ragan

  Journal of chemical information and modeling. 05/2010; 50(5):732-41.

  A wide range of data on sequences, structures, pathways, and networks of genes and gene products is available for hypothesis testing and discovery in biological and biomedical research. However, dataA wide range of data on sequences, structures, pathways, and networks of genes and gene products is available for hypothesis testing and discovery in biological and biomedical research. However, data describing the physical, chemical, and biological properties of small molecules have not been well-integrated with these resources. Semantically rich representations of chemical data, combined with Semantic Web technologies, have the potential to enable the integration of small molecule and biomolecular data resources, expanding the scope and power of biomedical and pharmacological research. We employed the Semantic Web technologies Resource Description Framework (RDF) and Web Ontology Language (OWL) to generate a Small Molecule Ontology (SMO) that represents concepts and provides unique identifiers for biologically relevant properties of small molecules and their interactions with biomolecules, such as proteins. We instanced SMO using data from three public data sources, i.e., DrugBank, PubChem and UniProt, and converted to RDF triples. Evaluation of SMO by use of predetermined competency questions implemented as SPARQL queries demonstrated that data from chemical and biomolecular data sources were effectively represented and that useful knowledge can be extracted. These results illustrate the potential of Semantic Web technologies in chemical, biological, and pharmacological research and in drug discovery.

• A visual framework for sequence analysis using n-grams and spectral rearrangement.

  Authors: Stefan R Maetschke, Karin S Kassahn, Jasmyn A Dunn, Siew-Ping Han, Eva Z Curley, Katryn J Stacey, Mark A Ragan

  Bioinformatics (Oxford, England). 03/2010; 26(6):737-44.

  Protein sequences are often composed of regions that have distinct evolutionary histories as a consequence of domain shuffling, recombination or gene conversion. New approaches are required toProtein sequences are often composed of regions that have distinct evolutionary histories as a consequence of domain shuffling, recombination or gene conversion. New approaches are required to discover, visualize and analyze these sequence regions and thus enable a better understanding of protein evolution. Here, we have developed an alignment-free and visual approach to analyze sequence relationships. We use the number of shared n-grams between sequences as a measure of sequence similarity and rearrange the resulting affinity matrix applying a spectral technique. Heat maps of the affinity matrix are employed to identify and visualize clusters of related sequences or outliers, while n-gram-based dot plots and conservation profiles allow detailed analysis of similarities among selected sequences. Using this approach, we have identified signatures of domain shuffling in an otherwise poorly characterized family, and homology clusters in another. We conclude that this approach may be generally useful as a framework to analyze related, but highly divergent protein sequences. It is particularly useful as a fast method to study sequence relationships prior to much more time-consuming multiple sequence alignment and phylogenetic analysis. A software implementation (MOSAIC) of the framework described here can be downloaded from http://bioinformatics.org.au/mosaic/ m.ragan@uq.edu.au Supplementary data are available at Bioinformatics online.

• A visual framework for sequence analysis using

  Authors: Stefan Maetschke, Karin S. Kassahn, Jasmyn A. Dunn, Siew-Ping Han, Eva Z. Curley, Katryn J. Stacey, Mark A. Ragan

  Bioinformatics. 01/2010; 26:737-744.

• Thinking laterally about genomes.

  Authors: Mark A Ragan

  Genome informatics. International Conference on Genome Informatics. 10/2009; 23(1):221-2.

  Perhaps the most-surprising discovery of the genome era has been the extent to which prokaryotic and many eukaryotic genomes incorporate genetic material from sources other than their parent(s).Perhaps the most-surprising discovery of the genome era has been the extent to which prokaryotic and many eukaryotic genomes incorporate genetic material from sources other than their parent(s). Lateral genetic transfer (LGT) among bacteria was first observed about 100 years ago, and is now accepted to underlie important phenomena including the spread of antibiotic resistance and ability to degrade xenobiotics. LGT is invoked, perhaps too readily, to explain a breadth of awkward data including compositional heterogeneity of genomes, disagreement among gene-sequence trees, and mismatch between physiology and systematics. At the same time many details of LGT remain unknown or controversial, and some key questions have scarcely been asked. Here I critically review what we think we know about the existence, extent, mechanism and impact of LGT; identify important open questions; and point to research directions that hold particular promise for elucidating the role of LGT in genome evolution. Evidence for LGT in nature is not only inferential but also direct, and potential vectors are ubiquitous. Genetic material can pass between diverse habitats and be significantly altered during residency in viruses, complicating the inference of donors, In prokaryotes about twice as many genes are interrupted by LGT as are transferred intact, and about 5Short protein domains can be privileged units of transfer. Unresolved phylogenetic issues include the correct null hypothesis, and genes as units of analysis. Themes are beginning to emerge regarding the effect of LGT on cellular networks, but I show why generalization is premature. LGT can associate with radical changes in physiology and ecological niche. Better quantitative models of genome evolution are needed, and theoretical frameworks remain to be developed for some observations including chromosome assembly by LGT.

• Lateral genetic transfer: open issues.

  Authors: Mark A Ragan, Robert G Beiko

  Philosophical transactions of the Royal Society of London. Series B, Biological sciences. 09/2009; 364(1527):2241-51.

  Lateral genetic transfer (LGT) is an important adaptive force in evolution, contributing to metabolic, physiological and ecological innovation in most prokaryotes and some eukaryotes. GenomicLateral genetic transfer (LGT) is an important adaptive force in evolution, contributing to metabolic, physiological and ecological innovation in most prokaryotes and some eukaryotes. Genomic sequences and other data have begun to illuminate the processes, mechanisms, quantitative extent and impact of LGT in diverse organisms, populations, taxa and environments; deep questions are being posed, and the provisional answers sometimes challenge existing paradigms. At the same time, there is an enhanced appreciation of the imperfections, biases and blind spots in the data and in analytical approaches. Here we identify and consider significant open questions concerning the role of LGT in genome evolution.

• The network of life: genome beginnings and evolution. Introduction.

  Authors: Mark A. Ragan, James O. McInerney, James A. Lake

  Philosophical transactions of the Royal Society of London. Series B, Biological sciences. 09/2009; 364(1527):2169-75.

• Evolution of gene function and regulatory control after whole-genome duplication: Comparative analyses in vertebrates.

  Authors: Karin Sonja Kassahn, Vinh Toan Dang, Simon J Wilkins, Andrew C Perkins, Mark A Ragan

  Genome research. 06/2009;

  The significance of whole-genome duplications (WGD) for vertebrate evolution remains controversial, in part because the mechanisms by which WGD contributed to functional evolution or speciation areThe significance of whole-genome duplications (WGD) for vertebrate evolution remains controversial, in part because the mechanisms by which WGD contributed to functional evolution or speciation are still incompletely characterised. Fish genomes provide an ideal context in which to examine the consequences of WGD, because the teleost lineage experienced an additional WGD soon after divergence from tetrapods and five teleost genomes are available for comparative analysis. Here we present an integrated approach to characterise these post-duplication genomes based on genome-scale synteny, phylogenetic, temporal and spatial gene expression, and protein sequence data. A minimum of 3-4% of protein-coding loci have been retained in two copies in each of the five fish genomes and many of these duplicates are key developmental genes that function as transcription factors or signalling molecules. Almost all duplicate gene pairs we examined have diverged in spatial and/or temporal expression during embryogenesis. A quarter of duplicate pairs have diverged in function via the acquisition of novel protein domains or via changes in the subcellular localisation of their encoded proteins. We compared the spatial expression and protein domain architecture of zebrafish WGD-duplicates to those of their single mouse ortholog and found many examples supporting a model of neofunctionalisation. WGD-duplicates have acquired novel protein domains more often than have single-copy genes. Post-WGD changes at the gene regulatory level were more common than changes at the protein level. We conclude that the most significant consequence of WGD for vertebrate evolution has been to enable more-specialised regulatory control of development via the acquisition of novel spatio-temporal expression domains. We find limited evidence that reciprocal gene loss led to reproductive isolation and speciation in this lineage.

• IllouraTM: a software tool for analysis, visualization and semantic querying of cellular and other spatial biological data.

  Authors: Tim McComb, Oliver Cairncross, Andrew B Noske, David L. A. Wood, Brad J Marsh, Mark A. Ragan

  Bioinformatics (Oxford, England). 04/2009;

  SUMMARY: New high-resolution approaches for mapping ultrastructure of cells in three dimensions are leading to unprecedented quantities of spatial data. Here we present Illoura, a software tool forSUMMARY: New high-resolution approaches for mapping ultrastructure of cells in three dimensions are leading to unprecedented quantities of spatial data. Here we present Illoura, a software tool for the integrated management, analysis and visualization of these data within a semantic context, and illustrate its capability by analysis of spatial relationships in mammalian beta cells. Availability: http://www.visiblecell.com/illoura CONTACT: Mark Ragan (m.ragan@imb.uq.edu.au) SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

• Seevolution: visualizing chromosome evolution.

  Authors: Andrés Esteban Marcos, Aaron E Darling, Mark A Ragan

  Bioinformatics (Oxford, England). 03/2009;

  SUMMARY: Genome evolution underpins all of biology, yet its principles can be difficult to communicate to the non-specialist. To facilitate broader understanding of genome evolution, we have designedSUMMARY: Genome evolution underpins all of biology, yet its principles can be difficult to communicate to the non-specialist. To facilitate broader understanding of genome evolution, we have designed an interactive 3D environment that enables visualization of diverse genome evolution processes. The system can intuitively and interactively animate mutation histories involving genome rearrangement, point mutation, recombination, insertion, and deletion. Multiple organisms related by a phylogeny can be visualized simultaneously. As methods to infer evolutionary histories of genomes become increasingly complex, visualization of the evolutionary process will not only be useful for communication, but will also serve as an exploratory tool for discovering new patterns of genome evolution. AVAILABILITY: The software is licensed under the GNU GPL and available for download from http://seevolution.org. CONTACT: aarondarling@ucdavis.edu.