99 research outputs found
Evaluating Ortholog Prediction Algorithms in a Yeast Model Clade
RSD, respectively, so that
they can predict orthologs across multiple taxa) against a set of 2,723
groups of high-quality curated orthologs from 6 Saccharomycete yeasts in the
Yeast Gene Order Browser. of all algorithms dramatically increased in these traps.) for evolutionary and functional
genomics studies where the objective is the accurate inference of
single-copy orthologs (e.g., molecular phylogenetics), but that all
algorithms fail to accurately predict orthologs when paralogy is
rampant
Comparative genomic analysis of toxin-negative strains of Clostridium difficile from humans and animals with symptoms of gastrointestinal disease
Background: Clostridium difficile infections (CDI) are a significant health problem to humans and food animals. Clostridial toxins ToxA and ToxB encoded by genes tcdA and tcdB are located on a pathogenicity locus known as the PaLoc and are the major virulence factors of C. difficile. While toxin-negative strains of C. difficile are often isolated from faeces of animals and patients suffering from CDI, they are not considered to play a role in disease. Toxin-negative strains of C. difficile have been used successfully to treat recurring CDI but their propensity to acquire the PaLoc via lateral gene transfer and express clinically relevant levels of toxins has reinforced the need to characterise them genetically. In addition, further studies that examine the pathogenic potential of toxin-negative strains of C. difficile and the frequency by which toxin-negative strains may acquire the PaLoc are needed. Results: We undertook a comparative genomic analysis of five Australian toxin-negative isolates of C. difficile that lack tcdA, tcdB and both binary toxin genes cdtA and cdtB that were recovered from humans and farm animals with symptoms of gastrointestinal disease. Our analyses show that the five C. difficile isolates cluster closely with virulent toxigenic strains of C. difficile belonging to the same sequence type (ST) and have virulence gene profiles akin to those in toxigenic strains. Furthermore, phage acquisition appears to have played a key role in the evolution of C. difficile. Conclusions: Our results are consistent with the C. difficile global population structure comprising six clades each containing both toxin-positive and toxin-negative strains. Our data also suggests that toxin-negative strains of C. difficile encode a repertoire of putative virulence factors that are similar to those found in toxigenic strains of C. difficile, raising the possibility that acquisition of PaLoc by toxin-negative strains poses a threat to human health. Studies in appropriate animal models are needed to examine the pathogenic potential of toxin-negative strains of C. difficile and to determine the frequency by which toxin-negative strains may acquire the PaLoc
Improving phylogeny reconstruction at the strain level using peptidome datasets
Typical bacterial strain differentiation methods are often challenged by high genetic similarity between strains. To address this problem, we introduce a novel in silico peptide fingerprinting method based on conventional wet-lab protocols that enables the identification of potential strain-specific peptides. These can be further investigated using in vitro approaches, laying a foundation for the development of biomarker detection and application-specific methods. This novel method aims at reducing large amounts of comparative peptide data to binary matrices while maintaining a high phylogenetic resolution. The underlying case study concerns the Bacillus cereus group, namely the differentiation of Bacillus thuringiensis, Bacillus anthracis and Bacillus cereus strains. Results show that trees based on cytoplasmic and extracellular peptidomes are only marginally in conflict with those based on whole proteomes, as inferred by the established Genome-BLAST Distance Phylogeny (GBDP) method. Hence, these results indicate that the two approaches can most likely be used complementarily even in other organismal groups. The obtained results confirm previous reports about the misclassification of many strains within the B. cereus group. Moreover, our method was able to separate the B. anthracis strains with high resolution, similarly to the GBDP results as benchmarked via Bayesian inference and both Maximum Likelihood and Maximum Parsimony. In addition to the presented phylogenomic applications, whole-peptide fingerprinting might also become a valuable complementary technique to digital DNA-DNA hybridization, notably for bacterial classification at the species and subspecies level in the future.This research was funded by Grant AGL2013-44039-R from the Spanish “Plan Estatal de I+D+I”, and by Grant EM2014/046 from the “Plan Galego de investigación, innovación e crecemento 2011-2015”. BS was recipient of a Ramón y Cajal postdoctoral contractfrom the Spanish Ministry of Economyand Competitiveness. This work was also partially funded by the [14VI05] Contract-Programme from the University of Vigo and the Agrupamento INBIOMED from DXPCTSUG-FEDER unha maneira de facer Europa (2012/273).The research leading to these results has also received funding from the European Union’s Seventh Framework Programme FP7/REGPOT-2012-2013.1 under grant agreement n˚ 316265, BIOCAPS. This document reflects only the authors’ views and the European Union is not liable for any use that may be made of the information contained herein. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript
Pan-cancer analysis of whole genomes
Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale(1-3). Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter(4); identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation(5,6); analyses timings and patterns of tumour evolution(7); describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity(8,9); and evaluates a range of more-specialized features of cancer genomes(8,10-18).Peer reviewe
Assessing parallel gene histories in viral genomes
Background: The increasing abundance of sequence data has exacerbated a long known problem: gene trees and species trees for the same terminal taxa are often incongruent. Indeed, genes within a genome have not all followed the same evolutionary path due to events such as incomplete lineage sorting, horizontal gene transfer, gene duplication and deletion, or recombination. Considering conflicts between gene trees as an obstacle, numerous methods have been developed to deal with these incongruences and to reconstruct consensus evolutionary histories of species despite the heterogeneity in the history of their genes. However, inconsistencies can also be seen as a source of information about the specific evolutionary processes that have shaped genomes.
Results: The goal of the approach here proposed is to exploit this conflicting information: we have compiled eleven variables describing phylogenetic relationships and evolutionary pressures and submitted them to dimensionality reduction techniques to identify genes with similar evolutionary histories. To illustrate the applicability of the method, we have chosen two viral datasets, namely papillomaviruses and Turnip mosaic virus (TuMV) isolates, largely dissimilar in genome, evolutionary distance and biology. Our method pinpoints viral genes with common evolutionary patterns. In the case of papillomaviruses, gene clusters match well our knowledge on viral biology and life cycle, illustrating the potential of our approach. For the less known TuMV, our results trigger new hypotheses about viral evolution and gene interaction.
Conclusions: The approach here presented allows turning phylogenetic inconsistencies into evolutionary information, detecting gene assemblies with similar histories, and could be a powerful tool for comparative pathogenomics.IGB was funded by the disappeared Spanish Ministry for Science and Innovation (CGL2010-16713). Work in Valencia was supported by grant BFU2012-30805 from the Spanish Ministry of Economy and Competitiveness (MINECO) to SFE. BMC is the recipient of an IDIBELL PhD fellowship.Mengual-Chuliá, B.; Bedhomme, S.; Lafforgue, G.; Elena Fito, SF.; Bravo, IG. (2016). Assessing parallel gene histories in viral genomes. BMC Evolutionary Biology. 16:1-15. https://doi.org/10.1186/s12862-016-0605-4S11516Hess J, Goldman N. Addressing inter-gene heterogeneity in maximum likelihood phylogenomic analysis: Yeasts revisited. PLoS ONE. 2011;6:e22783.Salichos L, Rokas A. Inferring ancient divergences requires genes with strong phylogenetic signals. 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Extracting phylogenetic signal and accounting for bias in whole-genome data sets supports the Ctenophora as sister to remaining Metazoa
BACKGROUND: Understanding the phylogenetic relationships among major lineages of multicellular animals (the Metazoa) is a prerequisite for studying the evolution of complex traits such as nervous systems, muscle tissue, or sensory organs. Transcriptome-based phylogenies have dramatically improved our understanding of metazoan relationships in recent years, although several important questions remain. The branching order near the base of the tree, in particular the placement of the poriferan (sponges, phylum Porifera) and ctenophore (comb jellies, phylum Ctenophora) lineages is one outstanding issue. Recent analyses have suggested that the comb jellies are sister to all remaining metazoan phyla including sponges. This finding is surprising because it suggests that neurons and other complex traits, present in ctenophores and eumetazoans but absent in sponges or placozoans, either evolved twice in Metazoa or were independently, secondarily lost in the lineages leading to sponges and placozoans. RESULTS: To address the question of basal metazoan relationships we assembled a novel dataset comprised of 1080 orthologous loci derived from 36 publicly available genomes representing major lineages of animals. From this large dataset we procured an optimized set of partitions with high phylogenetic signal for resolving metazoan relationships. This optimized data set is amenable to the most appropriate and computationally intensive analyses using site-heterogeneous models of sequence evolution. We also employed several strategies to examine the potential for long-branch attraction to bias our inferences. Our analyses strongly support the Ctenophora as the sister lineage to other Metazoa. We find no support for the traditional view uniting the ctenophores and Cnidaria. Our findings are supported by Bayesian comparisons of topological hypotheses and we find no evidence that they are biased by long-branch attraction. CONCLUSIONS: Our study further clarifies relationships among early branching metazoan lineages. Our phylogeny supports the still-controversial position of ctenophores as sister group to all other metazoans. This study also provides a workflow and computational tools for minimizing systematic bias in genome-based phylogenetic analyses. Future studies of metazoan phylogeny will benefit from ongoing efforts to sequence the genomes of additional invertebrate taxa that will continue to inform our view of the relationships among the major lineages of animals. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-015-2146-4) contains supplementary material, which is available to authorized users
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Comprehensive analysis of chromothripsis in 2,658 human cancers using whole-genome sequencing
Chromothripsis is a mutational phenomenon characterized by massive, clustered genomic rearrangements that occurs in cancer and other diseases. Recent studies in selected cancer types have suggested that chromothripsis may be more common than initially inferred from low-resolution copy-number data. Here, as part of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA), we analyze patterns of chromothripsis across 2,658 tumors from 38 cancer types using whole-genome sequencing data. We find that chromothripsis events are pervasive across cancers, with a frequency of more than 50% in several cancer types. Whereas canonical chromothripsis profiles display oscillations between two copy-number states, a considerable fraction of events involve multiple chromosomes and additional structural alterations. In addition to non-homologous end joining, we detect signatures of replication-associated processes and templated insertions. Chromothripsis contributes to oncogene amplification and to inactivation of genes such as mismatch-repair-related genes. These findings show that chromothripsis is a major process that drives genome evolution in human cancer
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