An SVD-based comparison of nine whole eukaryotic genomes supports a coelomate rather than ecdysozoan lineage

BACKGROUND: Eukaryotic whole genome sequences are accumulating at an impressive rate. Effective methods for comparing multiple whole eukaryotic genomes on a large scale are needed. Most attempted solutions involve the production of large scale alignments, and many of these require a high stringency pre-screen for putative orthologs in order to reduce the effective size of the dataset and provide a reasonably high but unknown fraction of correctly aligned homologous sites for comparison. As an alternative, highly efficient methods that do not require the pre-alignment of operationally defined orthologs are also being explored. RESULTS: A non-alignment method based on the Singular Value Decomposition (SVD) was used to compare the predicted protein complement of nine whole eukaryotic genomes ranging from yeast to man. This analysis resulted in the simultaneous identification and definition of a large number of well conserved motifs and gene families, and produced a species tree supporting one of two conflicting hypotheses of metazoan relationships. CONCLUSIONS: Our SVD-based analysis of the entire protein complement of nine whole eukaryotic genomes suggests that highly conserved motifs and gene families can be identified and effectively compared in a single coherent definition space for the easy extraction of gene and species trees. While this occurs without the explicit definition of orthologs or homologous sites, the analysis can provide a basis for these definitions

Homoplasy in genome-wide analysis of rare amino acid replacements: the molecular-evolutionary basis for Vavilov's law of homologous series

<p>Abstract</p> <p>Background</p> <p>Rare genomic changes (RGCs) that are thought to comprise derived shared characters of individual clades are becoming an increasingly important class of markers in genome-wide phylogenetic studies. Recently, we proposed a new type of RGCs designated RGC_CAMs (after Conserved Amino acids-Multiple substitutions) that were inferred using genome-wide identification of amino acid replacements that were: i) located in unambiguously aligned regions of orthologous genes, ii) shared by two or more taxa in positions that contain a different, conserved amino acid in a much broader range of taxa, and iii) require two or three nucleotide substitutions. When applied to animal phylogeny, the RGC_CAM approach supported the coelomate clade that unites deuterostomes with arthropods as opposed to the ecdysozoan (molting animals) clade. However, a non-negligible level of homoplasy was detected.</p> <p>Results</p> <p>We provide a direct estimate of the level of homoplasy caused by parallel changes and reversals among the RGC_CAMs using 462 alignments of orthologous genes from 19 eukaryotic species. It is shown that the impact of parallel changes and reversals on the results of phylogenetic inference using RGC_CAMs cannot explain the observed support for the Coelomata clade. In contrast, the evidence in support of the Ecdysozoa clade, in large part, can be attributed to parallel changes. It is demonstrated that parallel changes are significantly more common in internal branches of different subtrees that are separated from the respective common ancestor by relatively short times than in terminal branches separated by longer time intervals. A similar but much weaker trend was detected for reversals. The observed evolutionary trend of parallel changes is explained in terms of the covarion model of molecular evolution. As the overlap between the covarion sets in orthologous genes from different lineages decreases with time after divergence, the likelihood of parallel changes decreases as well.</p> <p>Conclusion</p> <p>The level of homoplasy observed here appears to be low enough to justify the utility of RGC_CAMs and other types of RGCs for resolution of hard problems in phylogeny. Parallel changes, one of the major classes of events leading to homoplasy, occur much more often in relatively recently diverged lineages than in those separated from their last common ancestor by longer time intervals of time. This pattern seems to provide the molecular-evolutionary underpinning of Vavilov's law of homologous series and is readily interpreted within the framework of the covarion model of molecular evolution.</p> <p>Reviewers</p> <p>This article was reviewed by Alex Kondrashov, Nicolas Galtier, and Maximilian Telford and Robert Lanfear (nominated by Laurence Hurst).</p

Proper Distance Metrics for Phylogenetic Analysis Using Complete Genomes without Sequence Alignment

A shortcoming of most correlation distance methods based on the composition vectors without alignment developed for phylogenetic analysis using complete genomes is that the “distances” are not proper distance metrics in the strict mathematical sense. In this paper we propose two new correlation-related distance metrics to replace the old one in our dynamical language approach. Four genome datasets are employed to evaluate the effects of this replacement from a biological point of view. We find that the two proper distance metrics yield trees with the same or similar topologies as/to those using the old “distance” and agree with the tree of life based on 16S rRNA in a majority of the basic branches. Hence the two proper correlation-related distance metrics proposed here improve our dynamical language approach for phylogenetic analysis

The Evolution of Word Composition in Metazoan Promoter Sequence

The field of molecular evolution provides many examples of the principle that molecular differences between species contain information about evolutionary history. One surprising case can be found in the frequency of short words in DNA: more closely related species have more similar word compositions. Interest in this has often focused on its utility in deducing phylogenetic relationships. However, it is also of interest because of the opportunity it provides for studying the evolution of genome function. Word-frequency differences between species change too slowly to be purely the result of random mutational drift. Rather, their slow pattern of change reflects the direct or indirect action of purifying selection and the presence of functional constraints. Many such constraints are likely to exist, and an important challenge is to distinguish them. Here we develop a method to do so by isolating the effects acting at different word sizes. We apply our method to 2-, 4-, and 8-base-pair (bp) words across several classes of noncoding sequence. Our major result is that similarities in 8-bp word frequencies scale with evolutionary time for regions immediately upstream of genes. This association is present although weaker in intronic sequence, but cannot be detected in intergenic sequence using our method. In contrast, 2-bp and 4-bp word frequencies scale with time in all classes of noncoding sequence. These results suggest that different genomic processes are involved at different word sizes. The pattern in 2-bp and 4-bp words may be due to evolutionary changes in processes such as DNA replication and repair, as has been suggested before. The pattern in 8-bp words may reflect evolutionary changes in gene-regulatory machinery, such as changes in the frequencies of transcription-factor binding sites, or in the affinity of transcription factors for particular sequences

Characteristics of the nuclear (18S, 5.8S, 28S and 5S) and mitochondrial (12S and 16S) rRNA genes of Apis mellifera (Insecta: Hymenoptera): structure, organization, and retrotransposable elements

As an accompanying manuscript to the release of the honey bee genome, we report the entire sequence of the nuclear (18S, 5.8S, 28S and 5S) and mitochondrial (12S and 16S) ribosomal RNA (rRNA)-encoding gene sequences (rDNA) and related internally and externally transcribed spacer regions of Apis mellifera (Insecta: Hymenoptera: Apocrita). Additionally, we predict secondary structures for the mature rRNA molecules based on comparative sequence analyses with other arthropod taxa and reference to recently published crystal structures of the ribosome. In general, the structures of honey bee rRNAs are in agreement with previously predicted rRNA models from other arthropods in core regions of the rRNA, with little additional expansion in non-conserved regions. Our multiple sequence alignments are made available on several public databases and provide a preliminary establishment of a global structural model of all rRNAs from the insects. Additionally, we provide conserved stretches of sequences flanking the rDNA cistrons that comprise the externally transcribed spacer regions (ETS) and part of the intergenic spacer region (IGS), including several repetitive motifs. Finally, we report the occurrence of retrotransposition in the nuclear large subunit rDNA, as R2 elements are present in the usual insertion points found in other arthropods. Interestingly, functional R1 elements usually present in the genomes of insects were not detected in the honey bee rRNA genes. The reverse transcriptase products of the R2 elements are deduced from their putative open reading frames and structurally aligned with those from another hymenopteran insect, the jewel wasp Nasonia (Pteromalidae). Stretches of conserved amino acids shared between Apis and Nasonia are illustrated and serve as potential sites for primer design, as target amplicons within these R2 elements may serve as novel phylogenetic markers for Hymenoptera. Given the impending completion of the sequencing of the Nasonia genome, we expect our report eventually to shed light on the evolution of the hymenopteran genome within higher insects, particularly regarding the relative maintenance of conserved rDNA genes, related variable spacer regions and retrotransposable elements

An SVD-based comparison of nine whole eukaryotic genomes supports a coelomate rather than ecdysozoan lineage

Abstract Background Eukaryotic whole genome sequences are accumulating at an impressive rate. Effective methods for comparing multiple whole eukaryotic genomes on a large scale are needed. Most attempted solutions involve the production of large scale alignments, and many of these require a high stringency pre-screen for putative orthologs in order to reduce the effective size of the dataset and provide a reasonably high but unknown fraction of correctly aligned homologous sites for comparison. As an alternative, highly efficient methods that do not require the pre-alignment of operationally defined orthologs are also being explored. Results A non-alignment method based on the Singular Value Decomposition (SVD) was used to compare the predicted protein complement of nine whole eukaryotic genomes ranging from yeast to man. This analysis resulted in the simultaneous identification and definition of a large number of well conserved motifs and gene families, and produced a species tree supporting one of two conflicting hypotheses of metazoan relationships. Conclusions Our SVD-based analysis of the entire protein complement of nine whole eukaryotic genomes suggests that highly conserved motifs and gene families can be identified and effectively compared in a single coherent definition space for the easy extraction of gene and species trees. While this occurs without the explicit definition of orthologs or homologous sites, the analysis can provide a basis for these definitions.</p

SVD-based proteome phylogeny (A) of nine eukaryotes with percentage branch support: top – bootstrap; bottom – novel jackknife

<p><b>Copyright information:</b></p><p>Taken from "An SVD-based comparison of nine whole eukaryotic genomes supports a coelomate rather than ecdysozoan lineage"</p><p>BMC Bioinformatics 2004;5():204-204.</p><p>Published online 17 Dec 2004</p><p>PMCID:PMC544558.</p><p>Copyright © 2004 Stuart and Berry; licensee BioMed Central Ltd.</p> An unsupported alternative phylogeny containing the "ecdysozoan" lineage is indicated by the dashed red branches. Percentage branch support values for the various clades of the tree are also provided to the left (B) for trees built using all proteins, as well as trees built after poorly described proteins are removed using either of two alternative vector magnitude inclusion values (>0.005, >0.05)

Understanding Patient Safety Reports via Multi-label Text Classification and Semantic Representation

Medical errors are the results of problems in health care delivery. One of the key steps to eliminate errors and improve patient safety is through patient safety event reporting. A patient safety report may record a number of critical factors that are involved in the health care when incidents, near misses, and unsafe conditions occur. Therefore, clinicians and risk management can generate actionable knowledge by harnessing useful information from reports. To date, efforts have been made to establish a nationwide reporting and error analysis mechanism. The increasing volume of reports has been driving improvement in quantity measures of patient safety. For example, statistical distributions of errors across types of error and health care settings have been well documented. Nevertheless, a shift to quality measure is highly demanded. In a health care system, errors are likely to occur if one or more components (e.g., procedures, equipment, etc.) that are intrinsically associated go wrong. However, our understanding of what and how these components are connected is limited for at least two reasons. Firstly, the patient safety reports present difficulties in aggregate analysis since they are large in volume and complicated in semantic representation. Secondly, an efficient and clinically valuable mechanism to identify and categorize these components is absent. I strive to make my contribution by investigating the multi-labeled nature of patient safety reports. To facilitate clinical implementation, I propose that machine learning and semantic information of reports, e.g., semantic similarity between terms, can be used to jointly perform automated multi-label classification. My work is divided into three specific aims. In the first aim, I developed a patient safety ontology to enhance semantic representation of patient safety reports. The ontology supports a number of applications including automated text classification. In the second aim, I evaluated multilabel text classification algorithms on patient safety reports. The results demonstrated a list of productive algorithms with balanced predictive power and efficiency. In the third aim, to improve the performance of text classification, I developed a framework for incorporating semantic similarity and kernel-based multi-label text classification. Semantic similarity values produced by different semantic representation models are evaluated in the classification tasks. Both ontology-based and distributional semantic similarity exerted positive influence on classification performance but the latter one shown significant efficiency in terms of the measure of semantic similarity. Our work provides insights into the nature of patient safety reports, that is a report can be labeled by multiple components (e.g., different procedures, settings, error types, and contributing factors) it contains. Multi-labeled reports hold promise to disclose system vulnerabilities since they provide the insight of the intrinsically correlated components of health care systems. I demonstrated the effectiveness and efficiency of the use of automated multi-label text classification embedded with semantic similarity information on patient safety reports. The proposed solution holds potential to incorporate with existing reporting systems, significantly reducing the workload of aggregate report analysis

Advances in diapriid (Hymenoptera: diapriidae) systematics, with contributions to cybertaxonomy and the analysis of rRNA sequence data

Diapriids (Hymenoptera: Diapriidae) are small parasitic wasps. Though found throughout the world they are relatively unknown. A framework for advancing diapriid systematics is developed by introducing a new web-based application/database capable of storing a broad range of systematic data, and the first molecular phylogeny specifically focused at examining intrafamilial relationships. In addition to these efforts, a description of a new taxon is provided. Several advantages of digital description, including linking descriptions to an ontology of morphological terms, are highlighted. The functionality of the database is further illustrated in the production of a catalog of diapriid host associations. The hosts database currently holds over 450 association records, for over 500 named taxa (parasitoids and hosts), and over 180 references. Diapriids are found to be primarily endoparasitoids of Diptera emerging from the host pupa. Phylogenetic inference for a molecular dataset of 28S and 18S rRNA sequence data, derived from a diverse selection of diapriids, is accomplished with a new suite of tools developed for handling complex rRNA datasets. Several parsimony-based methodologies, including an alignment-free method of analyzing multiple sequences, are reviewed and applied using the new software tools. Diapriid phylogenetic relationships are shown to be broadly congruent with existing morphology-based classifications. Methods for analyzing typically excluded sequence data are shown to recover phylogenetic signal that would otherwise be lost and the alignment-free method performed remarkably well in this regard. Empirically, phylogenetic approaches that incorporate structural data were not notably different than those that did not