59 results on '"Evgenia V. Kriventseva"'
Search Results
2. OrthoDB in 2020: evolutionary and functional annotations of orthologs.
- Author
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Evgeny M. Zdobnov, Dmitry Kuznetsov, Fredrik Tegenfeldt, Mosè Manni, Matthew Berkeley, and Evgenia V. Kriventseva
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- 2021
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- View/download PDF
3. OrthoDB v10: sampling the diversity of animal, plant, fungal, protist, bacterial and viral genomes for evolutionary and functional annotations of orthologs.
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Evgenia V. Kriventseva, Dmitry Kuznetsov, Fredrik Tegenfeldt, Mosè Manni, Renata Dias, Felipe A. Simão, and Evgeny M. Zdobnov
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- 2019
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4. OrthoDB v9.1: cataloging evolutionary and functional annotations for animal, fungal, plant, archaeal, bacterial and viral orthologs.
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Evgeny M. Zdobnov, Fredrik Tegenfeldt, Dmitry Kuznetsov, Robert M. Waterhouse, Felipe A. Simão, Panagiotis Ioannidis 0001, Mathieu Seppey, Alexis Loetscher, and Evgenia V. Kriventseva
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- 2017
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5. OrthoDB v8: update of the hierarchical catalog of orthologs and the underlying free software.
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Evgenia V. Kriventseva, Fredrik Tegenfeldt, Tom J. Petty, Robert M. Waterhouse, Felipe A. Simão, Igor A. Pozdnyakov, Panagiotis Ioannidis 0001, and Evgeny M. Zdobnov
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- 2015
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6. OrthoDB v11: annotation of orthologs in the widest sampling of organismal diversity
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Dmitry Kuznetsov, Fredrik Tegenfeldt, Mosè Manni, Mathieu Seppey, Matthew Berkeley, Evgenia V Kriventseva, and Evgeny M Zdobnov
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Genetics - Abstract
OrthoDB provides evolutionary and functional annotations of genes in a diverse sampling of eukaryotes, prokaryotes, and viruses. Genomics continues to accelerate our exploration of gene diversity and orthology is the most precise way of bridging gene functional knowledge with the rapidly expanding universe of genomic sequences. OrthoDB samples the most diverse organisms with the best quality genomics data to provide the leading coverage of species diversity. This update of the underlying data to over 18 000 prokaryotes and almost 2000 eukaryotes with over 100 million genes propels the coverage to another level. This achievement also demonstrates the scalability of the underlying OrthoLoger software for delineation of orthologs, freely available from https://orthologer.ezlab.org. In addition to the ab-initio computations of gene orthology used for the OrthoDB release, the OrthoLoger software allows mapping of novel gene sets to precomputed orthologs and thereby links to their annotations. The LEMMI-style benchmarking of OrthoLoger ensures its state-of-the-art performance and is available from https://lemortho.ezlab.org. The OrthoDB web interface has been further developed to include a pairwise orthology view from any gene to any other sampled species. OrthoDB-computed evolutionary annotations as well as extensively collated functional annotations can be accessed via REST API or SPARQL/RDF, downloaded or browsed online from https://www.orthodb.org.
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- 2022
7. Automation of Protein Sequence Characterization and Its Application in Whole Proteome Analysis.
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Rolf Apweiler, Margaret Biswas, Wolfgang Fleischmann, Evgenia V. Kriventseva, and Nicola J. Mulder
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- 2002
8. Theoretical analysis of alternative splice forms using computational methods.
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Stéphanie Boué, Martin Vingron, Evgenia V. Kriventseva, and Ina Koch
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- 2002
9. OrthoDB: a hierarchical catalog of animal, fungal and bacterial orthologs.
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Robert M. Waterhouse, Fredrik Tegenfeldt, Jia Li, Evgeny M. Zdobnov, and Evgenia V. Kriventseva
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- 2013
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10. BUSCO: assessing genome assembly and annotation completeness with single-copy orthologs.
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Felipe A. Simão, Robert M. Waterhouse, Panagiotis Ioannidis 0001, Evgenia V. Kriventseva, and Evgeny M. Zdobnov
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- 2015
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11. Proteome Analysis: Application of InterPro and CluSTr for the Functional Classification of Proteins in Whole Genomes.
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Margaret Biswas, Rolf Apweiler, Wolfgang Fleischmann, Alexander Kanapin, Youla Karavidopoulou, Paul J. Kersey, Evgenia V. Kriventseva, Virginie Mittard, Nicola J. Mulder, Thomas M. Oinn, Isabelle Phan, and Evgeni M. Zdobnov
- Published
- 2000
12. OrthoDB: the hierarchical catalog of eukaryotic orthologs in 2011.
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Robert M. Waterhouse, Evgeny M. Zdobnov, Fredrik Tegenfeldt, Jia Li, and Evgenia V. Kriventseva
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- 2011
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13. miROrtho: computational survey of microRNA genes.
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Daniel Gerlach, Evgenia V. Kriventseva, Nazim Rahman, Charles E. Vejnar, and Evgeni M. Zdobnov
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- 2009
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14. OrthoDB in 2020: evolutionary and functional annotations of orthologs
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Matthew R Berkeley, F. Tegenfeldt, Evgeny M. Zdobnov, Evgenia V. Kriventseva, Dmitry Kuznetsov, and Mosè Manni
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AcademicSubjects/SCI00010 ,media_common.quotation_subject ,Computational biology ,Biology ,Genome ,Evolution, Molecular ,03 medical and health sciences ,OrthoDB ,User-Computer Interface ,Sequence Homology, Nucleic Acid ,Databases, Genetic ,Genetics ,SPARQL ,Database Issue ,Animals ,RDF ,Phyletic gradualism ,030304 developmental biology ,media_common ,0303 health sciences ,030302 biochemistry & molecular biology ,Molecular Sequence Annotation ,computer.file_format ,Biological classification ,User interface ,computer ,Software - Abstract
OrthoDB provides evolutionary and functional annotations of orthologs, inferred for a vast number of available organisms. OrthoDB is leading in the coverage and genomic diversity sampling of Eukaryotes, Prokaryotes and Viruses, and the sampling of Bacteria is further set to increase three-fold. The user interface has been enhanced in response to the massive growth in data. OrthoDB provides three views on the data: (i) a list of orthologous groups related to a user query, which are now arranged to visualize their hierarchical relations, (ii) a detailed view of an orthologous group, now featuring a Sankey diagram to facilitate navigation between the levels of orthology, from more finely-resolved to more general groups of orthologs, as well as an arrangement of orthologs into an interactive organism taxonomy structure, and (iii) we added a gene-centric view, showing the gene functional annotations and the pair-wise orthologs in example species. The OrthoDB standalone software for delineation of orthologs, Orthologer, is freely available. Online BUSCO assessments and mapping to OrthoDB of user-uploaded data enable interactive exploration of related annotations and generation of comparative charts. OrthoDB strives to predict orthologs from the broadest coverage of species, as well as to extensively collate available functional annotations, and to compute evolutionary annotations such as evolutionary rate and phyletic profile. OrthoDB data can be assessed via SPARQL RDF, REST API, downloaded or browsed online from https://orthodb.org.
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- 2020
15. OrthoDB: the hierarchical catalog of eukaryotic orthologs.
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Evgenia V. Kriventseva, Nazim Rahman, Octavio Espinosa, and Evgeni M. Zdobnov
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- 2008
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16. The Proteome Analysis database: a tool for the in silico analysis of whole proteomes.
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Manuela Pruess, Wolfgang Fleischmann, Alexander Kanapin, Youla Karavidopoulou, Paul J. Kersey, Evgenia V. Kriventseva, Virginie Mittard, Nicola J. Mulder, Isabelle Phan, Florence Servant, and Rolf Apweiler
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- 2003
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17. Applications of InterPro in Protein Annotation and Genome Analysis.
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Margaret Biswas, Joseph F. O'Rourke, Evelyn Camon, Gillian Fraser, Alexander Kanapin, Youla Karavidopoulou, Paul J. Kersey, Evgenia V. Kriventseva, Virginie Mittard, Nicola J. Mulder, Isabelle Phan, Florence Servant, and Rolf Apweiler
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- 2002
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18. CluSTr: a database of clusters of SWISS-PROT+TrEMBL proteins.
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Evgenia V. Kriventseva, Wolfgang Fleischmann, Evgeni M. Zdobnov, and Rolf Apweiler
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- 2001
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19. Proteome Analysis Database: online application of InterPro and CluSTr for the functional classification of proteins in whole genomes.
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Rolf Apweiler, Margaret Biswas, Wolfgang Fleischmann, Alexander Kanapin, Youla Karavidopoulou, Paul J. Kersey, Evgenia V. Kriventseva, Virginie Mittard, Nicola J. Mulder, Isabelle Phan, and Evgeni M. Zdobnov
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- 2001
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20. ACI‐1 beta‐lactamase is widespread across human gut microbiomes in Negativicutes due to transposons harboured by tailed prophages
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Evgeny M. Zdobnov, Harald Brüssow, Evgenia V. Kriventseva, Elizaveta V. Starikova, Chris M Rands, and Vadim M. Govorun
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0301 basic medicine ,China ,Gene Transfer, Horizontal ,Prophages ,Bacteria/classification/drug effects/genetics/metabolism ,030106 microbiology ,Drug Resistance ,Bacterial/genetics ,Gene Transfer ,Firmicutes ,Context (language use) ,Biology ,Microbiology ,beta-Lactamases ,Anti-Bacterial Agents/pharmacology ,Horizontal ,03 medical and health sciences ,Antibiotic resistance ,Drug Resistance, Bacterial ,Humans ,ddc:576.5 ,Phylogeny ,Ecology, Evolution, Behavior and Systematics ,Prophage ,Genetics ,Acidaminococcus intestini ,Negativicutes ,Bacteria ,Prophages/genetics ,Human microbiome ,biology.organism_classification ,United States ,Anti-Bacterial Agents ,Gastrointestinal Microbiome ,Beta-Lactamases/genetics/metabolism ,Europe ,030104 developmental biology ,Horizontal gene transfer ,Metagenome ,Firmicutes/genetics ,Mobile genetic elements - Abstract
Antibiotic resistance is increasing among pathogens, and the human microbiome contains a reservoir of antibiotic resistance genes. Acidaminococcus intestini is the first Negativicute bacterium (Gram-negative Firmicute) shown to be resistant to beta-lactam antibiotics. Resistance is conferred by the aci1 gene, but its evolutionary history and prevalence remain obscure. We discovered that ACI-1 proteins are phylogenetically distinct from beta-lactamases of Gram-positive Firmicutes and that aci1 occurs in bacteria scattered across the Negativicute clade, suggesting lateral gene transfer. In the reference A. intestini RyC-MR95 genome, we found transposons residing within a tailed prophage context are likely vehicles for aci1's mobility. We found aci1 in 56 (4.4%) of 1,267 human gut metagenomes, mostly hosted within A. intestini, and, where could be determined, mostly within a consistent mobile element constellation. These samples are from Europe, China and the USA, showing that aci1 is distributed globally. We found that for most Negativicute assemblies with aci1, the prophage observed in A. instestini is absent, but in all cases aci1 is flanked by varying transposons. The chimeric mobile elements we identify here likely have a complex evolutionary history and potentially provide multiple complementary mechanisms for antibiotic resistance gene transfer both within and between cells.
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- 2018
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21. Improvements to CluSTr: the database of SWISS-PROT+TrEMBL protein clusters.
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Evgenia V. Kriventseva, Florence Servant, and Rolf Apweiler
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- 2003
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22. Interactive InterPro-based comparisons of proteins in whole genomes.
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Alexander Kanapin, Rolf Apweiler, Margaret Biswas, Wolfgang Fleischmann, Youla Karavidopoulou, Paul J. Kersey, Evgenia V. Kriventseva, Virginie Mittard, Nicola J. Mulder, Thomas M. Oinn, Isabelle Phan, Florence Servant, and Evgeni M. Zdobnov
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- 2002
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23. A collection of well characterised integral membrane proteins.
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Steffen Möller, Evgenia V. Kriventseva, and Rolf Apweiler
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- 2000
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24. OrthoDB v10: sampling the diversity of animal, plant, fungal, protist, bacterial and viral genomes for evolutionary and functional annotations of orthologs
- Author
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Evgeny M. Zdobnov, Evgenia V. Kriventseva, Dmitry Kuznetsov, Mosè Manni, Felipe A. Simão, Renata O. Dias, and F. Tegenfeldt
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Genomics ,Computational biology ,Genome, Viral ,Biology ,Genome ,Evolution, Molecular ,03 medical and health sciences ,OrthoDB ,0302 clinical medicine ,Phylogenetics ,Databases, Genetic ,Genetics ,SPARQL ,Ensembl ,Animals ,Database Issue ,ddc:576.5 ,Phylogeny ,030304 developmental biology ,0303 health sciences ,Fungal genetics ,Eukaryota ,Genetic Variation ,Molecular Sequence Annotation ,computer.file_format ,UniProt ,Genome, Fungal ,computer ,030217 neurology & neurosurgery ,Genome, Bacterial ,Genome, Plant ,Software - Abstract
OrthoDB (https://www.orthodb.org) provides evolutionary and functional annotations of orthologs. This update features a major scaling up of the resource coverage, sampling the genomic diversity of 1271 eukaryotes, 6013 prokaryotes and 6488 viruses. These include putative orthologs among 448 metazoan, 117 plant, 549 fungal, 148 protist, 5609 bacterial, and 404 archaeal genomes, picking up the best sequenced and annotated representatives for each species or operational taxonomic unit. OrthoDB relies on a concept of hierarchy of levels-of-orthology to enable more finely resolved gene orthologies for more closely related species. Since orthologs are the most likely candidates to retain functions of their ancestor gene, OrthoDB is aimed at narrowing down hypotheses about gene functions and enabling comparative evolutionary studies. Optional registered-user sessions allow on-line BUSCO assessments of gene set completeness and mapping of the uploaded data to OrthoDB to enable further interactive exploration of related annotations and generation of comparative charts. The accelerating expansion of genomics data continues to add valuable information, and OrthoDB strives to provide orthologs from the broadest coverage of species, as well as to extensively collate available functional annotations and to compute evolutionary annotations. The data can be browsed online, downloaded or assessed via REST API or SPARQL RDF compatible with both UniProt and Ensembl.
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- 2018
25. BUSCO Applications from Quality Assessments to Gene Prediction and Phylogenomics
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Felipe A. Simão, Evgeny M. Zdobnov, Guennadi Klioutchnikov, Mosè Manni, Mathieu Seppey, Evgenia V. Kriventseva, Robert M. Waterhouse, and Panagiotis Ioannidis
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0106 biological sciences ,0301 basic medicine ,transcriptomics ,metagenomics ,bioinformatics ,evolution ,genomics ,Gene prediction ,Genomics ,Biology ,computer.software_genre ,01 natural sciences ,Software release life cycle ,03 medical and health sciences ,Phylogenomics ,Genetics ,ddc:576.5 ,Molecular Biology ,Ecology, Evolution, Behavior and Systematics ,030304 developmental biology ,Comparative genomics ,0303 health sciences ,Benchmarking ,Data science ,030104 developmental biology ,ComputingMethodologies_PATTERNRECOGNITION ,Code refactoring ,Metagenomics ,Fast Track ,Data mining ,computer ,010606 plant biology & botany - Abstract
Genomics promises comprehensive surveying of genomes and metagenomes, but rapidly changing technologies and expanding data volumes make evaluation of completeness a challenging task. Technical sequencing quality metrics can be complemented by quantifying completeness of genomic data sets in terms of the expected gene content of Benchmarking Universal Single-Copy Orthologs (BUSCO, http://busco.ezlab.org). The latest software release implements a complete refactoring of the code to make it more flexible and extendable to facilitate high-throughput assessments. The original six lineage assessment data sets have been updated with improved species sampling, 34 new subsets have been built for vertebrates, arthropods, fungi, and prokaryotes that greatly enhance resolution, and data sets are now also available for nematodes, protists, and plants. Here, we present BUSCO v3 with example analyses that highlight the wide-ranging utility of BUSCO assessments, which extend beyond quality control of genomics data sets to applications in comparative genomics analyses, gene predictor training, metagenomics, and phylogenomics.
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- 2018
26. OrthoDB v8: update of the hierarchical catalog of orthologs and the underlying free software
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Igor A. Pozdnyakov, Evgeny M. Zdobnov, Tom J. Petty, Evgenia V. Kriventseva, Panagiotis Ioannidis, Felipe A. Simão, F. Tegenfeldt, and Robert M. Waterhouse
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InterPro ,Sequence Homology ,Computational biology ,Biology ,Genome ,Evolution, Molecular ,03 medical and health sciences ,OrthoDB ,Annotation ,0302 clinical medicine ,Databases, Genetic ,Genetics ,Database Issue ,Animals ,Humans ,ddc:576.5 ,Cluster analysis ,Data Curation ,030304 developmental biology ,0303 health sciences ,Data curation ,Eukaryota ,Genome, Microbial ,Eukaryota/genetics ,User interface ,UniProt ,Algorithms ,Software ,030217 neurology & neurosurgery - Abstract
Orthology, refining the concept of homology, is the cornerstone of evolutionary comparative studies. With the ever-increasing availability of genomic data, inference of orthology has become instrumental for generating hypotheses about gene functions crucial to many studies. This update of the OrthoDB hierarchical catalog of orthologs (http://www.orthodb.org) covers 3027 complete genomes, including the most comprehensive set of 87 arthropods, 61 vertebrates, 227 fungi and 2627 bacteria (sampling the most complete and representative genomes from over 11,000 available). In addition to the most extensive integration of functional annotations from UniProt, InterPro, GO, OMIM, model organism phenotypes and COG functional categories, OrthoDB uniquely provides evolutionary annotations including rates of ortholog sequence divergence, copy-number profiles, sibling groups and gene architectures. We re-designed the entirety of the OrthoDB website from the underlying technology to the user interface, enabling the user to specify species of interest and to select the relevant orthology level by the NCBI taxonomy. The text searches allow use of complex logic with various identifiers of genes, proteins, domains, ontologies or annotation keywords and phrases. Gene copy-number profiles can also be queried. This release comes with the freely available underlying ortholog clustering pipeline (http://www.orthodb.org/software).
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- 2015
27. ACI-1 class A beta-lactamase is widespread across human gut microbiomes due to transposons harboured by tailed prophages
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Vadim M. Govorun, Evgenia V. Kriventseva, Elizaveta V. Starikova, Harald Brüssow, Evgeny M. Zdobnov, and Chris M Rands
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Genetics ,Transposable element ,0303 health sciences ,Acidaminococcus intestini ,Negativicutes ,030306 microbiology ,Context (language use) ,Biology ,biology.organism_classification ,Genome ,03 medical and health sciences ,Mobile genetic elements ,Gene ,Prophage ,030304 developmental biology - Abstract
Antibiotic resistance is increasing among pathogens at unprecedented rates and the human body contains a large pool of antibiotic resistance genes that can be spread among bacteria by mobile genetic elements. Acidaminococcus intestini, a bacterium found in the human gut that belongs to the class of Negativicutes, is the first gram-negative coccus shown to be resistant to beta-lactam antibiotics. Resistance is conferred by aci1, a gene encoding the ACI-1 class A beta-lactamase, but the evolutionary history of aci1 and its distribution across other Negativicutes and in the human gut microbiota remains obscure. We discovered that ACI-1 proteins are phylogenetically distinct from class A beta-lactamases of gram-positive Firmicutes and that the aci1 gene occurs in bacteria scattered across the Negativicutes clade, suggesting possible mobilization. In the reference A. intestini RyC-MR95 strain, we found that aci1 is surrounded by mobile DNA, transposon derived sequences directly flank aci1 and are likely the vehicle for its mobility. These transposon sequences reside within a prophage context consisting of two likely degraded tailed prophages, the first prophages to be characterised in A. intestini. We found aci1 in at least 56 (4.4%) out of 1,267 human gut metagenome samples, mostly hosted within A. intestini, and, where could be determined, mostly within a similar constellation of mobile elements to that found in the reference A. intestini genome. These human samples are from individuals in Europe, China and the USA, showing that aci1 is widely distributed globally. Additionally, we examined the nine different Negativicute genome assemblies that contain aci1, and found that only two of these strains show a similar mobile element context around aci1 to the reference A. intestini with transposons adjacent to a tailed prophage. However, in all nine cases aci1 is flanked by transposon derived sequences, and these sequences are diverse, suggesting the activity and degradation of multiple transposons. Overall, we show that ACI-1 proteins form a distinct class A beta lactamase family, and that the aci1 gene is present in human guts worldwide within Negativicute bacterial hosts, due to transposons, sometimes inserted into tailed prophages.
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- 2017
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28. Taxon sampling unequally affects individual nodes in a phylogenetic tree: consequences for model gene tree construction in SwissTree
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Adrian M. Altenhoff, Evgenia V. Kriventseva, Ioannis Xenarios, Brigitte Boeckmann, Christophe Dessimoz, Lydie Bougueleret, David Dylus, Sébastien Moretti, Toni Gabaldón, C-M Train, and Eyal Privman
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0303 health sciences ,Phylogenetic tree ,Ecology ,0206 medical engineering ,Locus (genetics) ,02 engineering and technology ,Phylogenetic network ,Biology ,03 medical and health sciences ,Tree (data structure) ,Phylogenetics ,Evolutionary biology ,Tree rearrangement ,Computational phylogenetics ,Gene family ,020602 bioinformatics ,030304 developmental biology - Abstract
Medium to large phylogenetic gene trees constructed from datasets of different species density and taxonomic range are rarely topologically consistent because of missing phylogenetic signal, non-phylogenetic signal and error. In this study, we first use simulations to show that taxon sampling unequally affects nodes in a gene tree, which likely contributes to controversial conclusions from taxon sampling experiments and contradicting species phylogenies such as for the boreoeutherians. Hence, because it is unlikely that a large gene tree can be reconstructed correctly based on a single optimized dataset, we take a two-step approach for the construction of model gene trees. First, stable and unstable clades are identified by comparing phylogenetic trees inferred from multiple datasets and data types (nucleotide, amino acid, codon) from the same gene family. Subsequently, data subsets are optimized for the analysis of individual uncertain clades. Results are summarized in form of a model tree that illustrates the evolutionary relationship of gene loci. A case study shows how a seemingly complex gene phylogeny becomes increasingly consistent with the reference species tree by attentive taxon sampling and subtree analysis. The procedure is progressively introduced to SwissTree (http://swisstree.vital-it.ch), a resource of high confidence model gene (locus) trees. Finally we demonstrate the usefulness of SwissTree for orthology benchmarking.
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- 2017
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29. OrthoDB: a hierarchical catalog of animal, fungal and bacterial orthologs
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Evgeny M. Zdobnov, Evgenia V. Kriventseva, Jia Li, F. Tegenfeldt, and Robert M. Waterhouse
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0106 biological sciences ,InterPro ,Genome evolution ,Genes, Fungal ,Genomics ,Computational biology ,Biology ,Synteny ,010603 evolutionary biology ,01 natural sciences ,Evolution, Molecular ,Mice ,03 medical and health sciences ,OrthoDB ,Phylogenomics ,Databases, Genetic ,Genetics ,Animals ,Cluster Analysis ,Humans ,ddc:576.5 ,FlyBase : A Database of Drosophila Genes & Genomes ,Phylogeny ,030304 developmental biology ,Comparative genomics ,Internet ,0303 health sciences ,Molecular Sequence Annotation ,Articles ,Phenotype ,Genes ,Genes, Bacterial ,UniProt - Abstract
The concept of orthology provides a foundation for formulating hypotheses on gene and genome evolution, and thus forms the cornerstone of comparative genomics, phylogenomics and metagenomics. We present the update of OrthoDB-the hierarchical catalog of orthologs (http://www.orthodb.org). From its conception, OrthoDB promoted delineation of orthologs at varying resolution by explicitly referring to the hierarchy of species radiations, now also adopted by other resources. The current release provides comprehensive coverage of animals and fungi representing 252 eukaryotic species, and is now extended to prokaryotes with the inclusion of 1115 bacteria. Functional annotations of orthologous groups are provided through mapping to InterPro, GO, OMIM and model organism phenotypes, with cross-references to major resources including UniProt, NCBI and FlyBase. Uniquely, OrthoDB provides computed evolutionary traits of orthologs, such as gene duplicability and loss profiles, divergence rates, sibling groups, and now extended with exon-intron architectures, syntenic orthologs and parent-child trees. The interactive web interface allows navigation along the species phylogenies, complex queries with various identifiers, annotation keywords and phrases, as well as with gene copy-number profiles and sequence homology searches. With the explosive growth of available data, OrthoDB also provides mapping of newly sequenced genomes and transcriptomes to the current orthologous groups.
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- 2017
30. miROrtho: computational survey of microRNA genes
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Charles E. Vejnar, Daniel Gerlach, Evgeny M. Zdobnov, Evgenia V. Kriventseva, and Nazim Rahman
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Sequence alignment ,Computational biology ,Biology ,Genome ,MiRBase ,Nucleic acid secondary structure ,User-Computer Interface ,03 medical and health sciences ,0302 clinical medicine ,microRNA ,Genetics ,ddc:576.5 ,Gene ,030304 developmental biology ,Comparative genomics ,Internet ,0303 health sciences ,RNA ,Articles ,Genomics ,MicroRNAs ,030220 oncology & carcinogenesis ,Nucleic Acid Conformation ,Databases, Nucleic Acid ,Sequence Alignment - Abstract
MicroRNAs (miRNAs) are short, non-protein coding RNAs that direct the widespread phenomenon of post-transcriptional regulation of metazoan genes. The mature approximately 22-nt long RNA molecules are processed from genome-encoded stem-loop structured precursor genes. Hundreds of such genes have been experimentally validated in vertebrate genomes, yet their discovery remains challenging, and substantially higher numbers have been estimated. The miROrtho database (http://cegg.unige.ch/mirortho) presents the results of a comprehensive computational survey of miRNA gene candidates across the majority of sequenced metazoan genomes. We designed and applied a three-tier analysis pipeline: (i) an SVM-based ab initio screen for potent hairpins, plus homologs of known miRNAs, (ii) an orthology delineation procedure and (iii) an SVM-based classifier of the ortholog multiple sequence alignments. The web interface provides direct access to putative miRNA annotations, ortholog multiple alignments, RNA secondary structure conservation, and sequence data. The miROrtho data are conceptually complementary to the miRBase catalog of experimentally verified miRNA sequences, providing a consistent comparative genomics perspective as well as identifying many novel miRNA genes with strong evolutionary support.
- Published
- 2017
31. The common marmoset genome provides insight into primate biology and evolution
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San Juana Ruiz, Daniel Gerlach, Tomas Vinar, Brona Brejova, Saba Sajjadian, Miriam K. Konkel, Muthuswamy Raveendran, Yih Shin Liu, Paul Flicek, Lubomir Tomaska, Donna M. Muzny, Daniel R. Schrider, Megan C. Ranck, Kjersti Aagaard, Huyen Dinh, Jayantha B. Tennakoon, Lucinda Fulton, Lynne V. Nazareth, Brygg Ullmer, George M. Weinstock, Kim D. Delehaunty, Xose S. Puente, Charles E. Vejnar, Shyam Prabhakar, Matthew W. Hahn, J. Scott Moncrieff, Mark A. Batzer, Tina Graves, Catherine C. Fontenot, Carlos López-Otín, Corinna N. Ross, Catrina Fronick, Jeffrey Rogers, Nirmala Arul Rayan, Mario Ventura, Pieter J. De Jong, Elaine R. Mardis, Steve Searle, Christie LKovar, David Haig, Ngoc Nguyen, Shalini N. Jhangiani, Margaret Morgan, Crystal M. Warner, Mimi M. Chandrabose, Keith G. Mansfield, Vandita Joshi, Kathryn Beal, Saverio B. Capuano, Magali Ruffier, Ling Ling Pu, Jerilyn A. Walker, Marvin Diep Dao, John Lopez, Irene Newsham, Yuanqing Wu, Jan Hinnerk Vogel, Arian F.A. Smit, Javier Herrero, Andrew Cree, Tomas Marques-Bonet, Oronzo Capozzi, LaDeana W. Hillier, Robert S. Fulton, Claudio Casola, Mariano Rocchi, Benjamin Soibam, Suzette D. Tardif, Derek E. Wildman, Evgenia V. Kriventseva, Kim C. Worley, Baoli Zhu, Jennifer F. Hughes, Robert Hubley, Geoffrey Okwuonu, Jennifer Hume, Lora Lewis, Ricardo C.H. del Rosario, Devin P. Locke, Lora Perales, David Rio Deiros, David J. Witherspoon, Yi Han, Brian J. Raney, David Rodríguez, Stephen Fitzgerald, Jireh Santibanez, Albert J. Vilella, R. Gerald Fowler, Qing Wang, Belen Lorente-Galdos, Ramatu Ayiesha Gabisi, Víctor Quesada, Weimin Xiao, Nicoletta Archidiacono, Emre Karakor, Helen Skaletsky, R. Alan Harris, Evgeny M. Zdobnov, Richard A. Gibbs, Wesley C. Warren, Patrick Minx, Preethi H. Gunaratne, Rita A. Wright, Doriana Misceo, Jinchuan Xing, Evan E. Eichler, Lynn B. Jorde, Carolin Kosiol, Rick K. Wilson, Sandra L. Lee, University of St Andrews. School of Biology, University of St Andrews. Centre for Biological Diversity, National Human Genome Research Institute (US), National Institutes of Health (US), National Science Foundation (US), Howard Hughes Medical Institute, Louisiana State University, Cullen Foundation, European Research Council, Ministerio de Ciencia e Innovación (España), Instituto Nacional de Bioinformática (España), Gerlach, Daniel, Kriventseva, Evgenia, and Zdobnov, Evgeny
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endocrine system ,animal structures ,Evolució molecular ,Evolution ,QH301 Biology ,animal diseases ,Molecular Sequence Data ,QH426 Genetics ,Polymorphism, Single Nucleotide ,Genome ,Article ,Evolution, Molecular ,QH301 ,Phylogenetics ,biology.animal ,Genetics ,Animals ,ddc:576.5 ,Primate ,Amino Acid Sequence ,Polymorphism ,QH426 ,Phylogeny ,New World monkey ,biology ,Reproduction ,Polimorfisme genètic ,Callithrix/genetics ,Molecular ,Marmoset ,Callithrix ,Single Nucleotide ,Sequence Analysis, DNA ,biology.organism_classification ,Reproduction/genetics ,DNA/methods ,body regions ,MicroRNAs/genetics ,MicroRNAs ,Evolutionary biology ,Female ,Sequence Analysis - Abstract
The Marmoset Genome Sequencing and Analysis Consortium.-- Worley, Kim C. et al., We report the whole-genome sequence of the common marmoset (Callithrix jacchus). The 2.26-Gb genome of a female marmoset was assembled using Sanger read data (6×) and a whole-genome shotgun strategy. A first analysis has permitted comparison with the genomes of apes and Old World monkeys and the identification of specific features that might contribute to the unique biology of this diminutive primate, including genetic changes that may influence body size, frequent twinning and chimerism. We observed positive selection in growth hormone/insulin-like growth factor genes (growth pathways), respiratory complex I genes (metabolic pathways), and genes encoding immunobiological factors and proteases (reproductive and immunity pathways). In addition, both protein-coding and microRNA genes related to reproduction exhibited evidence of rapid sequence evolution. This genome sequence for a New World monkey enables increased power for comparative analyses among available primate genomes and facilitates biomedical research application. © 2014 Nature America, Inc., The marmoset genome project was funded by the National Human Genome Research Institute (NHGRI), including from grants U54 HG003273 (R.A. Gibbs) and U54 HG003079 (R.K.W.), with additional support from the US National Institutes of Health (NIH), including from grants R01 DK077639 (S.D.T.), R01 GM59290 (L.B.J. and M.A.B.), HG002385 (E.E.E.) and P51-OD011133 (Southwest NPRC), and support from the National Science Foundation (NSF BCS-0751508 to D.E.W.) and the VEGA grant agency: 1/0719/14 (T.V.) and 1/1085/12 (B.B.). C.C.F. and M.C.R. were supported in part by a Howard Hughes Medical Institute grant to Louisiana State University through the Undergraduate Biological Sciences Education program. J.X. was supported by NHGRI grant K99 HG005846. P.H.G. was supported by the Cullen Foundation. T.M.-B. was supported by European Research Council Starting Grant (260372) and MICINN (Spain) grant BFU2011-28549. B.L.-G. was supported by the Spanish National Institute of Bioinformatics (see URLs).
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- 2014
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32. OrthoDB v9.1: cataloging evolutionary and functional annotations for animal, fungal, plant, archaeal, bacterial and viral orthologs
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Alexis Loetscher, Felipe A. Simão, Mathieu Seppey, Evgenia V. Kriventseva, F. Tegenfeldt, Dmitry Kuznetsov, Robert M. Waterhouse, Panagiotis Ioannidis, and Evgeny M. Zdobnov
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0106 biological sciences ,0301 basic medicine ,Most recent common ancestor ,Cataloging ,Genomics ,Computational biology ,Biology ,Web Browser ,Bioinformatics ,010603 evolutionary biology ,01 natural sciences ,Evolution, Molecular ,03 medical and health sciences ,Upload ,OrthoDB ,User-Computer Interface ,Databases, Genetic ,Genetics ,Animals ,Database Issue ,ddc:576.5 ,Comparative genomics ,Bacteria ,business.industry ,Fungi ,Computational Biology ,Usability ,Molecular Sequence Annotation ,Plants ,Archaea ,030104 developmental biology ,Viruses ,business ,Algorithms ,Software - Abstract
OrthoDB is a comprehensive catalog of orthologs, genes inherited by extant species from a single gene in their last common ancestor. In 2016 OrthoDB reached its 9th release, growing to over 22 million genes from over 5000 species, now adding plants, archaea and viruses. In this update we focused on usability of this fast-growing wealth of data: updating the user and programmatic interfaces to browse and query the data, and further enhancing the already extensive integration of available gene functional annotations. Collating functional annotations from over 100 resources, and enabled us to propose descriptive titles for 87% of ortholog groups. Additionally, OrthoDB continues to provide computed evolutionary annotations and to allow user queries by sequence homology. The OrthoDB resource now enables users to generate publication-quality comparative genomics charts, as well as to upload, analyze and interactively explore their own private data. OrthoDB is available from http://orthodb.org.
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- 2016
33. Genome sequence of Aedes aegypti, a major arbovirus vector
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Sergio Verjovski-Almeida, James E. Galagan, Ryan C. Kennedy, Zhiyong Xi, Jason R. Miller, Eric Eisenstadt, Kyanne R. Reidenbach, Robert V. Bruggner, Yu-Hui Rogers, Hadi Quesneville, Doreen Werner, Owen White, Alexander S. Raikhel, Mario Stanke, J. Spencer Johnston, Diane D. Lovin, Evgenia V. Kriventseva, Ian T. Paulsen, Kathryn S. Campbell, Norman H. Lee, Ewan Birney, Karyn Megy, Hean Koo, David Kulp, Shelby L. Bidwell, Jingsong Zhu, Philip Montgomery, Paolo Amedeo, Yongmei Zhao, Chinnappa D. Kodira, Javier Costas, Michael C. Schatz, Steven P. Sinkins, Claire M. Fraser-Liggett, Martin Shumway, Kurt LaButti, Akio Mori, Brendan J. Loftus, Manfred Grabherr, Eric O. Stinson, Frank H. Collins, Zhijian Jake Tu, Monique R. Coy, Matt Crawford, Janice P. Vanzee, William M. Gelbart, Joshua Orvis, Peter Arensburger, Chunhong Mao, Evgeny M. Zdobnov, Saul A. Kravitz, Suely Lopes Gomes, David DeCaprio, David G. Hogenkamp, Daniel Lawson, Dennis L. Knudson, David W. Severson, George Dimopoulos, Marcelo B. Soares, Sinéad B. O'Leary, Peter W. Atkinson, David M. Jaffe, Becky deBruyn, Martin Hammond, Ana L. T. O. Nascimento, Jim Biedler, Stefan Wyder, Jose M. C. Tubio, Bruce W. Birren, Catherine A. Hill, Chad Nusbaum, Eduardo Lee, Song Li, Susan E. Brown, Jennifer R. Wortman, James R. Hogan, Hamza El-Dorry, Qi Zhao, Linda Hannick, Carlos Frederico Martins Menck, Vishvanath Nene, Jonathan Crabtree, Steven L. Salzberg, Michael H. Holmes, Maria de Fatima Bonaldo, Quinghu Ren, Mihaela Pertea, Charles Roth, Evan Mauceli, Karin Eiglmeier, Horacio Naveira, Brian J. Haas, Qiandong Zeng, Neil F. Lobo, Jennifer R. Schneider, The Institute for Genomic Research, The Institute for Genomic Research, Rockville, European Bioinformatics Institute [Hinxton] ( EMBL-EBI ), European Molecular Biology Laboratory [Hinxton], Broad Institute of MIT and Harvard ( BROAD INSTITUTE ), Broad Institute of MIT and Harvard, Virginia Polytechnic Institute and State University [Blacksburg], University College Dublin [Dublin] ( UCD ), Bloomberg School of Public Health, Johns Hopkins University ( JHU ) -Bloomberg School of Public Health, University of Geneva Medical School, Swiss Institute of Bioinformatics-University of Geneva Medical School, University of Notre Dame ( UND ), Harvard University [Cambridge], College of Agricultural Sciences Colorado State University, Colorado State University [Fort Collins] ( CSU ) -College of Agricultural Sciences, Northwestern University [Evanston], University of California [Riverside] ( UCR ), Department of Atmospheric, Oceanic and Planetary Physics [Oxford] ( AOPP ), University of Oxford [Oxford], Purdue University [West Lafayette], Centro Nacional de Genotipado Fundación Pública Galega de Medicina Xenómica Hospital Clínico Universitario de Santiago, Centro Nacional de Genotipado-Fundación Pública Galega de Medicina Xenómica-Hospital Clínico Universitario de Santiago, Institut Pasteur [Paris], Universidade de Sao Paulo Instituto de Quimica, Universidade de São Paulo ( USP ) -Instituto de Quimica, Texas A&M University [College Station], Joint Technology Center, University of Massachusetts [Amherst] ( UMass Amherst ), Universidade de Sao Paulo, Institute of Biomedical Sciences, Universidade de São Paulo ( USP ) -Institute of Biomedical Sciences, Instituto Butantan [São Paulo], Universidade da Coruña, University of Maryland [College Park], Institut Jacques Monod ( IJM ), Université Paris Diderot - Paris 7 ( UPD7 ) -Centre National de la Recherche Scientifique ( CNRS ), University of California [Santa Cruz] ( UCSC ), Complexo Hospitalario Universitario de Santiago, Universität Göttingen, Georg-August-Universität Göttingen, George Washington University Medical Center, George Washington University ( GW ), The Institute for Genomic Research (TIGR), European Bioinformatics Institute [Hinxton] (EMBL-EBI), EMBL Heidelberg, Broad Institute of MIT and Harvard (BROAD INSTITUTE), Harvard Medical School [Boston] (HMS)-Massachusetts Institute of Technology (MIT)-Massachusetts General Hospital [Boston], University College Dublin [Dublin] (UCD), Johns Hopkins Bloomberg School of Public Health [Baltimore], Johns Hopkins University (JHU), Swiss Institute of Bioinformatics [Lausanne] (SIB), Université de Lausanne (UNIL)-Université de Lausanne (UNIL)-University of Geneva Medical School, University of Notre Dame [Indiana] (UND), Colorado State University [Fort Collins] (CSU)-College of Agricultural Sciences, University of California [Riverside] (UCR), University of California, Department of Atmospheric, Oceanic and Planetary Physics [Oxford] (AOPP), Universidade de São Paulo (USP)-Instituto de Quimica, University of Massachusetts [Amherst] (UMass Amherst), University of Massachusetts System (UMASS), Universidade de São Paulo (USP)-Institute of Biomedical Sciences (ICB/USP), Universidade de São Paulo (USP), University of Maryland System, Institut Jacques Monod (IJM (UMR_7592)), Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS), University of California [Santa Cruz] (UCSC), Georg-August-University [Göttingen], The George Washington University (GW), George Washington University (GW), Université de Lausanne = University of Lausanne (UNIL)-Université de Lausanne = University of Lausanne (UNIL)-University of Geneva Medical School, Harvard University, University of California [Riverside] (UC Riverside), University of California (UC), University of Oxford, Institut Pasteur [Paris] (IP), Universidade de São Paulo = University of São Paulo (USP)-Instituto de Quimica, Universidade de São Paulo = University of São Paulo (USP)-Institute of Biomedical Sciences (ICB/USP), Universidade de São Paulo = University of São Paulo (USP), University of California [Santa Cruz] (UC Santa Cruz), Georg-August-University = Georg-August-Universität Göttingen, Zdobnov, Evgeny, and Wyder, Stefan
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0106 biological sciences ,Male ,Transcription, Genetic ,Genome, Insect ,transposons ,receptors ,Genes, Insect ,Aedes/ genetics/metabolism ,MESH: Genes, Insect ,Yellow Fever/prevention & control/transmission ,MESH: Base Sequence ,01 natural sciences ,Dengue/prevention & control/transmission ,MESH: Protein Structure, Tertiary ,MESH: Arboviruses ,MESH : Insect Vectors ,MESH: Insect Proteins ,MESH : Anopheles gambiae ,MESH: Animals ,MESH : Arboviruses ,insects ,MESH: Yellow Fever ,superfamily ,ddc:616 ,0303 health sciences ,Anopheles ,MESH : Genes, Insect ,3. Good health ,yellow-fever mosquito ,anopheles-gambiae ,drosophila-melanogaster ,expression ,evolution ,organization ,Drosophila melanogaster ,MESH: DNA Transposable Elements ,[ SDV.BBM.GTP ] Life Sciences [q-bio]/Biochemistry, Molecular Biology/Genomics [q-bio.GN] ,Multigene Family ,Public Health ,MESH : Protein Structure, Tertiary ,MESH: Sex Characteristics ,Molecular Sequence Data ,MESH : Multigene Family ,MESH: Sex Determination (Genetics) ,MESH : Sex Determination (Genetics) ,Arbovirus ,Article ,03 medical and health sciences ,Species Specificity ,[SDV.BBM.GTP]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Genomics [q-bio.GN] ,MESH: Anopheles gambiae ,Yellow Fever ,MESH: Species Specificity ,Humans ,MESH: Humans ,MESH: Molecular Sequence Data ,fungi ,MESH : Humans ,MESH : Sex Characteristics ,Membrane Transport Proteins ,Sex Determination Processes ,medicine.disease ,Insect Vectors ,Protein Structure, Tertiary ,Sex Determination (Genetics) ,MESH: Multigene Family ,MESH: Female ,MESH : Sequence Analysis, DNA ,MESH: Sequence Analysis, DNA ,Drosophila melanogaster/genetics ,MESH : Molecular Sequence Data ,Odorant binding ,Insect Proteins/genetics ,Anopheles gambiae ,MESH: Dengue ,Genome ,MESH: Membrane Transport Proteins ,Dengue ,MESH : Membrane Transport Proteins ,Aedes ,Insect Vectors/ genetics/metabolism ,MESH : Drosophila melanogaster ,MESH : Female ,Membrane Transport Proteins/genetics ,Genetics ,MESH : Insect Proteins ,Sex Characteristics ,Multidisciplinary ,MESH: Synteny ,MESH: Aedes ,MESH : Genome, Insect ,MESH : DNA Transposable Elements ,Insect Proteins ,Female ,Orthologous Gene ,MESH : Male ,MESH : Dengue ,Aedes aegypti ,MESH: Insect Vectors ,Biology ,010603 evolutionary biology ,Synteny ,MESH: Drosophila melanogaster ,Protein Structure, Tertiary/genetics ,MESH : Yellow Fever ,parasitic diseases ,medicine ,MESH : Species Specificity ,Animals ,030304 developmental biology ,MESH : Aedes ,Base Sequence ,MESH: Genome, Insect ,MESH: Transcription, Genetic ,MESH : Synteny ,MESH : Transcription, Genetic ,Sequence Analysis, DNA ,biology.organism_classification ,MESH: Male ,DNA Transposable Elements ,MESH : Base Sequence ,MESH : Animals ,Arboviruses ,Anopheles gambiae/genetics/metabolism - Abstract
We present a draft sequence of the genome of Aedes aegypti , the primary vector for yellow fever and dengue fever, which at ∼1376 million base pairs is about 5 times the size of the genome of the malaria vector Anopheles gambiae . Nearly 50% of the Ae. aegypti genome consists of transposable elements. These contribute to a factor of ∼4 to 6 increase in average gene length and in sizes of intergenic regions relative to An. gambiae and Drosophila melanogaster . Nonetheless, chromosomal synteny is generally maintained among all three insects, although conservation of orthologous gene order is higher (by a factor of ∼2) between the mosquito species than between either of them and the fruit fly. An increase in genes encoding odorant binding, cytochrome P450, and cuticle domains relative to An. gambiae suggests that members of these protein families underpin some of the biological differences between the two mosquito species.
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- 2016
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34. Correlating Traits of Gene Retention, Sequence Divergence, Duplicability and Essentiality in Vertebrates, Arthropods, and Fungi
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Evgenia V. Kriventseva, Evgeny M. Zdobnov, and Robert M. Waterhouse
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0106 biological sciences ,InterPro ,orthologs ,Proteome ,Lineage (evolution) ,Quantitative Trait Loci ,Biology ,arthropods ,010603 evolutionary biology ,01 natural sciences ,Genome ,Evolution, Molecular ,03 medical and health sciences ,Vertebrates/classification/genetics ,Phylogenetics ,Gene Duplication ,Gene duplication ,Arthropods/classification/genetics ,Genetics ,essential genes ,Animals ,ddc:576.5 ,Fungi/classification/genetics ,Gene ,Ecology, Evolution, Behavior and Systematics ,Research Articles ,Phylogeny ,030304 developmental biology ,Sequence (medicine) ,0303 health sciences ,Genes, Essential ,molecular evolution ,Fungi ,Computational Biology ,Essential gene ,Vertebrates - Abstract
Delineating ancestral gene relations among a large set of sequenced eukaryotic genomes allowed us to rigorously examine links between evolutionary and functional traits. We classified 86% of over 1.36 million protein-coding genes from 40 vertebrates, 23 arthropods, and 32 fungi into orthologous groups and linked over 90% of them to Gene Ontology or InterPro annotations. Quantifying properties of ortholog phyletic retention, copy-number variation, and sequence conservation, we examined correlations with gene essentiality and functional traits. More than half of vertebrate, arthropod, and fungal orthologs are universally present across each lineage. These universal orthologs are preferentially distributed in groups with almost all single-copy or all multicopy genes, and sequence evolution of the predominantly single-copy orthologous groups is markedly more constrained. Essential genes from representative model organisms, Mus musculus, Drosophila melanogaster, and Saccharomyces cerevisiae, are significantly enriched in universal orthologs within each lineage, and essential-gene-containing groups consistently exhibit greater sequence conservation than those without. This study of eukaryotic gene repertoire evolution identifies shared fundamental principles and highlights lineage-specific features, it also confirms that essential genes are highly retained and conclusively supports the "knockout-rate prediction" of stronger constraints on essential gene sequence evolution. However, the distinction between sequence conservation of single- versus multicopy orthologs is quantitatively more prominent than between orthologous groups with and without essential genes. The previously underappreciated difference in the tolerance of gene duplications and contrasting evolutionary modes of "single-copy control" versus "multicopy license" may reflect a major evolutionary mechanism that allows extended exploration of gene sequence space.
- Published
- 2010
35. Genome sequences of the human body louse and its primary endosymbiont provide insights into the permanent parasitic lifestyle
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Daniel Gerlach, Reed M. Johnson, Granger G. Sutton, Si Hyeock Lee, Didier Raoult, Hongmei Li, Weilin Sun, Robert V. Bruggner, Greg Madey, NaiKuan Wang, Ryan C. Kennedy, Joseph P. Strycharz, David L. Reed, Hugh M. Robertson, Stephen C. Barker, Ewen F. Kirkness, Jeanne Romero-Severson, Montserrat Aguadé, Janice P. Vanzee, Scott Christley, Emily C. Kraus, Frank H. Collins, Brian J. Haas, Shelby L. Bidwell, Evgenia V. Kriventseva, Stephen L. Cameron, Omprakash Mittapalli, Justin Johnson, J. Craig Venter, Venu M. Margam, Julio Rozas, Aleksandar Popadić, Juan Manuel Anzola, Yoshinori Tomoyasu, Jan A. Veenstra, Catherine A. Hill, Evgeny M. Zdobnov, Jose M. C. Tubio, Allison A. Regier, Elisabet Caler, Christine G. Elsik, Claudio J. Struchiner, David Alvarez-Ponce, Dan Graur, Gregory A. Dasch, Manfredo J. Seufferheld, Brian P. Walenz, Barry R. Pittendrigh, Linda Hannick, Robert L. Strausberg, Henk R. Braig, Renfu Shao, Sara Guirao-Rico, Neil F. Lobo, Justin T. Reese, Robert M. Waterhouse, Jason M. Meyer, José M. C. Ribeiro, Marta Tojo, M. Alejandra Perotti, John M. Clark, Eran Elhaik, Lakshmi D. Viswanathan, Filipe G. Vieira, Kyong Sup Yoon, J. Spencer Johnston, May R. Berenbaum, Daniel Lawson, Maria F. Unger, T. Utterback, Vinita Joardar, Gerlach, Daniel, Kriventseva, Evgenia, Waterhouse, Robert, and Zdobnov, Evgeny
- Subjects
0106 biological sciences ,Genome, Insect ,Molecular Sequence Data ,Genes, Insect ,Genomics ,Louse ,Pediculus humanus ,010603 evolutionary biology ,01 natural sciences ,Genome ,03 medical and health sciences ,Enterobacteriaceae ,Genome, Insect/*genetics ,biology.animal ,Lice Infestations/parasitology ,medicine ,Animals ,Genes, Insect/genetics ,Humans ,ddc:576.5 ,Pediculus/*genetics/*microbiology ,Symbiosis ,Genome, Bacterial/*genetics ,030304 developmental biology ,Comparative genomics ,Genetics ,0303 health sciences ,Multidisciplinary ,biology ,Enterobacteriaceae/genetics ,Pediculus ,Sequence Analysis, DNA ,Genome project ,Lice Infestations ,Biological Sciences ,Body louse ,biology.organism_classification ,medicine.disease ,Trench fever ,Genomics/methods ,Genes, Bacterial ,Genes, Bacterial/genetics ,Genome, Bacterial - Abstract
As an obligatory parasite of humans, the body louse ( Pediculus humanus humanus ) is an important vector for human diseases, including epidemic typhus, relapsing fever, and trench fever. Here, we present genome sequences of the body louse and its primary bacterial endosymbiont Candidatus Riesia pediculicola. The body louse has the smallest known insect genome, spanning 108 Mb. Despite its status as an obligate parasite, it retains a remarkably complete basal insect repertoire of 10,773 protein-coding genes and 57 microRNAs. Representing hemimetabolous insects, the genome of the body louse thus provides a reference for studies of holometabolous insects. Compared with other insect genomes, the body louse genome contains significantly fewer genes associated with environmental sensing and response, including odorant and gustatory receptors and detoxifying enzymes. The unique architecture of the 18 minicircular mitochondrial chromosomes of the body louse may be linked to the loss of the gene encoding the mitochondrial single-stranded DNA binding protein. The genome of the obligatory louse endosymbiont Candidatus Riesia pediculicola encodes less than 600 genes on a short, linear chromosome and a circular plasmid. The plasmid harbors a unique arrangement of genes required for the synthesis of pantothenate, an essential vitamin deficient in the louse diet. The human body louse, its primary endosymbiont, and the bacterial pathogens that it vectors all possess genomes reduced in size compared with their free-living close relatives. Thus, the body louse genome project offers unique information and tools to use in advancing understanding of coevolution among vectors, symbionts, and pathogens.
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- 2010
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36. Creating hierarchical models of protein families based on Expressed Sequence Tags: The 'Sprockets' analysis pipeline
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Evgenia V. Kriventseva, Paul M. K. Gordon, Christian Weinel, Carsten Jacobi, Udo Kämpf, and Christoph Wilhelm Sensen
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InterPro ,Expressed sequence tag ,Multiple sequence alignment ,business.product_category ,Chemistry ,Computational biology ,Biochemistry ,Pipeline (software) ,Analytical Chemistry ,Environmental Chemistry ,business ,Hidden Markov model ,Sprocket ,Spectroscopy ,Sequence (medicine) ,Sequence clustering - Abstract
We have created an analysis pipeline called Sprockets, which can be used to classify proteins into various hierarchical "families", and build searchable models of these families. The construction of these families is based on data from Expressed Sequence Tags (ESTs) and Coding DNA Sequences (CDSs), making Sprockets clusters especially suitable for studying gene families in organisms for which the completely sequenced genome does not (yet) exist. The pipeline consists of two main parts: pair-wise analysis and grouping of sequences with Z-score statistics, followed by hierarchical splitting of clusters into alignable protein families. Various computational and statistical techniques applied in Sprockets allow it to act like a massive and selective multiple sequence alignment engine for combining individual sequence collections and related public sequences. The end result is a database of gene Hidden Markov Models, each related to the other by three levels of similarity: secondary structure, function and evolutionary origin. For a sample 20,000 EST set from Lactuca spp., Sprockets provided a 9% improvement in mapping of function to unknown sequences over traditional pair-wise search methods and InterPro mapping.
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- 2006
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37. Clustering and analysis of protein families
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Evgenia V. Kriventseva, Margaret Biswas, and Rolf Apweiler
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Genetics ,InterPro ,Databases, Factual ,Protein family ,Phylogenetic tree ,Amino Acid Motifs ,Proteins ,Sequence alignment ,Computational biology ,Biology ,Domain (software engineering) ,Structural biology ,Structural Biology ,Protein function prediction ,Cluster analysis ,Sequence Alignment ,Molecular Biology ,Phylogeny - Abstract
Various sequence-motif and sequence-cluster databases have been integrated into a new resource known as InterPro. Because the contributing databases have different clustering principles and scoring sensitivities, the combined assignments complement each other for grouping protein families and delineating domains. InterPro and new developments in the analysis of both the phylogenetic profiles of protein families and domain fusion events improve the prediction of specific functions for numerous proteins.
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- 2001
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38. Social insect genomes exhibit dramatic evolution in gene composition and regulation while preserving regulatory features linked to sociality
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Chris Smith, Robert M. Waterhouse, Greg Donahue, Martin Helmkampf, Christopher D. Smith, Monica Munoz-Torres, Brian J. Parker, Jürgen Gadau, Sanne Nygaard, Laurent Keller, Julien Roux, Christine G. Elsik, Jiayu Wen, Lothar Wissler, Neil D. Tsutsui, Jacobus J. Boomsma, Brendan G. Hunt, Eran Elhaik, Cameron R. Currie, Danny Reinberg, Evgenia V. Kriventseva, Justin T. Reese, Daniel F. Simola, Garret Suen, Lumi Viljakainen, Christopher P. Childers, Alan Rawls, Yannick Wurm, Darren E. Hagen, Shelley L. Berger, Jürgen Liebig, Karl M. Glastad, Elizabeth Cash, Michael A. D. Goodisman, Evgeny M. Zdobnov, Dan Graur, Erich Bornberg-Bauer, and Eyal Privman
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0106 biological sciences ,Genome, Insect ,Biology ,Regulatory Sequences, Nucleic Acid ,010603 evolutionary biology ,01 natural sciences ,Genome ,Synteny ,Evolution, Molecular ,03 medical and health sciences ,Species Specificity ,Molecular evolution ,Genetics ,Gene family ,Animals ,ddc:576.5 ,Social Behavior ,Gene ,Genetics (clinical) ,Conserved Sequence ,Phylogeny ,030304 developmental biology ,Regulation of gene expression ,0303 health sciences ,Binding Sites ,Behavior, Animal ,Models, Genetic ,Ants ,Research ,fungi ,food and beverages ,Sequence Analysis, DNA ,DNA Methylation ,Eusociality ,Hymenoptera ,MicroRNAs ,Gene Expression Regulation ,Insect Proteins ,Orthologous Gene ,Transcription Factors - Abstract
Genomes of eusocial insects code for dramatic examples of phenotypic plasticity and social organization. We compared the genomes of seven ants, the honeybee, and various solitary insects to examine whether eusocial lineages share distinct features of genomic organization. Each ant lineage contains ∼4000 novel genes, but only 64 of these genes are conserved among all seven ants. Many gene families have been expanded in ants, notably those involved in chemical communication (e.g., desaturases and odorant receptors). Alignment of the ant genomes revealed reduced purifying selection compared with Drosophila without significantly reduced synteny. Correspondingly, ant genomes exhibit dramatic divergence of noncoding regulatory elements; however, extant conserved regions are enriched for novel noncoding RNAs and transcription factor–binding sites. Comparison of orthologous gene promoters between eusocial and solitary species revealed significant regulatory evolution in both cis (e.g., Creb) and trans (e.g., fork head) for nearly 2000 genes, many of which exhibit phenotypic plasticity. Our results emphasize that genomic changes can occur remarkably fast in ants, because two recently diverged leaf-cutter ant species exhibit faster accumulation of species-specific genes and greater divergence in regulatory elements compared with other ants or Drosophila. Thus, while the “socio-genomes” of ants and the honeybee are broadly characterized by a pervasive pattern of divergence in gene composition and regulation, they preserve lineage-specific regulatory features linked to eusociality. We propose that changes in gene regulation played a key role in the origins of insect eusociality, whereas changes in gene composition were more relevant for lineage-specific eusocial adaptations.
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- 2013
39. OrthoDB: the hierarchical catalog of eukaryotic orthologs in 2011
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Evgenia V. Kriventseva, Jia Li, Evgeny M. Zdobnov, F. Tegenfeldt, and Robert M. Waterhouse
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Drosophila melanogaster/genetics ,media_common.quotation_subject ,Saccharomyces cerevisiae ,Biology ,Genome ,Homology (biology) ,Saccharomyces cerevisiae/genetics ,Evolution, Molecular ,03 medical and health sciences ,OrthoDB ,Mice ,Phylogenetics ,Databases, Genetic ,Genetics ,Animals ,ddc:576.5 ,Fungi/genetics ,Phyletic gradualism ,Gene ,Arthropods ,Phylogeny ,030304 developmental biology ,media_common ,0303 health sciences ,Sequence Homology, Amino Acid ,030302 biochemistry & molecular biology ,Fungi ,Proteins ,Molecular Sequence Annotation ,Articles ,Arthropods/genetics ,Genomics ,Vertebrates/genetics ,Protein Structure, Tertiary ,Drosophila melanogaster ,Genes ,Evolutionary biology ,Vertebrates ,Proteins/genetics ,Evolutionary divergence ,Gene evolution - Abstract
The concept of homology drives speculation on a gene’s function in any given species when its biological roles in other species are characterized. With reference to a specific species radiation homologous relations define orthologs, i.e. descendants from a single gene of the ancestor. The large-scale delineation of gene genealogies is a challenging task, and the numerous approaches to the problem reflect the importance of the concept of orthology as a cornerstone for comparative studies. Here, we present the updated OrthoDB catalog of eukaryotic orthologs delineated at each radiation of the species phylogeny in an explicitly hierarchical manner of over 100 species of vertebrates, arthropods and fungi (including the metazoa level). New database features include functional annotations, and quantification of evolutionary divergence and relations among orthologous groups. The interface features extended phyletic profile querying and enhanced text-based searches. The ever-increasing sampling of sequenced eukaryotic genomes brings a clearer account of the majority of gene genealogies that will facilitate informed hypotheses of gene function in newly sequenced genomes. Furthermore, uniform analysis across lineages as different as vertebrates, arthropods and fungi with divergence levels varying from several to hundreds of millions of years will provide essential data for uncovering and quantifying long-term trends of gene evolution. OrthoDB is freely accessible from http://cegg.unige.ch/orthodb.
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- 2011
40. Comparative Genome Analysis
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Robert M. Waterhouse, Evgenia V. Kriventseva, and Evgeny M. Zdobnov
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- 2009
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41. The genome sequence of taurine cattle: A window to ruminant biology and evolution
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Heather M Deobald, Gerald R. Fowler, Clay Davis, Judith Herdandez, Donna Maglott, Lin Chen, Gonzalo Rincon, Darren E. Hagen, James T. Warren, Evgenia V. Kriventseva, Ingrid Olsaker, Debora L. Hamernik, Charles Moen, Oliver C. Jann, Yuri Kapustin, Erdogan Memili, Timothy Connelley, Ling Ling Pu, Terhi Iso-Touru, Gemma Marie Payne, Ye Cheng, Amy Egan, Alexandre Reymond, Aniko Sabo, J. Bruce German, Jason R. Grant, Joseph Chacko, Ronnie D. Green, Isabel Kinney Ferreira de Miranda Santos, Raffaele Mazza, A.J. Molenaar, Richard A. Moore, Christian J. Buhay, Henry Song, Cham G. Kumar, Marion L. Greaser, Hasan Khatib, Harris A. Lewin, Olga Ermolaeva, Jonathan V. Sweedler, Steven J.M. Jones, Rosemeire Conceição Parra Pastor, Paul Stothard, Adam J. Colley, Antti Livanainen, Francesca Panzitta, Dan Graur, Aaron Ingham, David L. Adelson, Timothy P. L. Smith, Shirley A. Ellis, Andy Cree, Jingkun Zhang, Carolyn T.A. Herzig, Jason Goodell, Colette A. Abbey, Feng-Qi Zhao, Mimi M. Chandrabose, Ross L. Tellam, Alex Astashyn, Yanru Ren, Laura Elnitski, Bella Mayurkumar Patel, Sem Genini, Lassudara G. Almeida, Jacqueline E. Schein, Theresa Casey, Hanni Salih, José Fernando Garcia, Zhiquan Wang, Carolyn Fitzsimmons, Evan E. Eichler, Ngoc Nguyen, Kaitlin E. Donohue, Ariel Fernando Amadio, Clayton R. Boldt, John C. McEwan, Juan Manuel Anzola, Francisco Câmara, Shoba Ranganathan, Eran Elhaik, Stefan Hiendleder, George M. Weinstock, Lora Lewis, Jeremy F. Taylor, Dimos Kapetis, Andrew J. Roberts, Lee Alexander, Nelida Rodriguez-Osorio, Alexandre Souvorov, Justin C. Lee, Bruce R. Southey, Boris Kiryutin, Michael Holder, Xiang Qin, Warren M. Snelling, Abhirami Ratnakumar, Marcelo Fábio Gouveia Nogueira, Angela K. Walker, Hatam A. Hakimov, Fernando H. Biase, Roderic Guigó, Shannon Dugan-Rocha, Sean McWilliam, Rex Lee Williams, Jacqueline Chrast, Huyen Dinh, Robert C. Edgar, Huaiyang Jiang, Justin T. Reese, John W. Keele, George E. Liu, Yufeng Shen, Jireh Santibanez, Kim C. Worley, Sandra L. Lee, Sari S. Khalil, Marta Hernández, Stephen N. White, Suria M. Bahadue, Changxi Li, Kim D. Pruitt, Kirsty Jensen, C. Michael Dickens, Jung-Woo Choi, Jennifer Harrow, Tatiana A. DeCampos, Richard A. Gibbs, Ryan J. Lozado, Yoshikazu Sugimoto, Sigbjam Lien, Anna K. Bennett, Curtis P. Van Tassell, Eve Devinoy, Gustavo Garcia, R. Baxter, Satyanarayana Rachagani, Kevin K. Lahmers, Stylianos E. Antonarakis, D. Kolbehdari, Cynthia L. Baldwin, Lillian Sando, Darryl L. Hadsell, Elen Anatriello, Ze Cheng, Richard C. Waterman, Paul Havlak, Peter Dove, Laura Sherman, Wes Barris, Imke Tammen, Geoffrey Okwuonu, Jennifer Hume, Denis M. Larkin, Robert D. Schnabel, Zhi-Liang Hu, Evgeny M. Zdobnov, Danielle G. Lemay, Stephanie Bell, Roberto Malinverni, Jiuzhou Song, David Steffen, James M. Reecy, Lynne V. Nazareth, Carlo José Freire de Oliveira, E. Marques, Cody J. Gladney, Donna M. Muzny, Candice L. Brinkmeyer-Larigford, Lakshmi K. Matukumalli, Jan Aerts, Stephen S. Moore, Margaret Morgan, Kim L. McLean, Juan F. Medrano, Felix Kokocinski, Marco A. Marra, Gregory P. Harhay, Frank W. Nicholas, Loren C. Skow, Fiona S. L. Brinkman, Tovah Kerr, Krista L. Fritz, Stacey M. Curry, Charlotte N. Henrichsen, Catherine Ucla, David J. Lynn, Victor V. Solovyev, Natasha E. Romero, Sandra Hines, Joy M. Raison, Alessandra Mara Franzin, Selina Vattathil, Jeffery A. Carroll, Brian P. Dalrymple, Katarzyna Wilczek-Boney, Seongwon Seo, Richard J. Leach, Mireya Plass, Paul Kitts, Kris R. Wunderlich, Bhanu Prakash V.L. Telugu, Gary L. Bennett, Ramatu Ayiesha Gabisi, Ravikiran Donthu, Shalini N. Jhangiani, Rita A. Wright, Mary Qu Yang, Nauman J. Maqbool, W. A. Carvalho, Monique Rijnkels, Yuri Tani Utsunomiya, Charles E. Chappie, John L. Williams, Rob Halgren, Stephen M. J. Searle, A.R.R. Abatepaulo, Thomas Junier, Stephanie D. McKay, Anne G. Rosenwald, David A. Wheeler, Rosemarie Weikard, N. Hastings, Roger T. Stone, Eduardo Eyras, Cerissa Hamilton, Wendy C. Brown, Yan Ding, Ylva Strandberg Lutzow, Matthew Hobbs, Annett Eberlein, Carine Wyss, Jennifer M. Urbanski, Matthew Peter Kent, Lilian P.L. Lau, Dinesh Kumar, Penny K. Riggs, Lawrence B. Schook, Matthew Hitchens, Vandita Joshi, Melissa J. Landrum, Tyler Alioto, Nathan Poslusny, Thomas T. Wheeler, Victor Sapojnikov, Natália F. Martins, San Juana Ruiz, Michael D. MacNeil, Alexandre Rodrigues Caetano, Mario Andres Poli, Catherine Jamis, Masaaki Taniguchi, James E. Womack, William F. Martin, Andrej Razpet, James G. R. Gilbert, Daniel G. Bradley, Readman Chiu, Thomas H. Welsh, Clare A. Gill, Erica Sodergren, Carol G. Chitko-McKown, Hari Prasad Nandakumar, Virpi Ahola, Steve M. Kappes, Jennifer E. Chapin, Sandra Regina Maruyama, John Lopez, Krystin M. Logan, Jonathan A. Green, Laurens G. Wilming, Yue Liu, Antti Iivanainen, Robert A. Holt, Barbara T. Moreno, Marcos De Donato, Christie Kovar, Angela Jolivet Johnson, Carl T. Muntean, Robert Ward, K. James Durbin, Matthew D. Whiteside, Christopher P. Childers, Tad S. Sonstegard, Yin Shin Liu, Bin Zhu, Sameer D. Pant, Ashley J. Waardenberg, André Eggen, D.M. Spurlock, Hsiu Chuan Chen, Le Luo Guan, Sandra L. Rodriguez-Zas, Akiko Takasuga, Daniela D. Moré, Jianqi Yang, Wratko Hlavina, Sheila M. Schmutz, Michael J. Brownstein, Christine G. Elsik, Marvin Diep Dao, Daniel Gerlach, E. Hart, Elsa Chacko, Elizabeth Glass, Libing Shen, Chris P. Verschoor, Eliane P. Cervelatti, Department of Biology, Georgetown University, Department of Animal Science, Texas A&M University [College Station], Livestock Industries, Baylor College of Medicine (BCM), Reymond, Alexandre, Zdobnov, Evgeny, Antonarakis, Stylianos, Ucla, Catherine, Gerlach, Daniel, and Junier, Thomas
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Male ,genome sequence ,[SDV]Life Sciences [q-bio] ,ved/biology.organism_classification_rank.species ,Genome ,Genética y Herencia ,Segmental duplication ,2. Zero hunger ,Genetics ,ddc:616 ,0303 health sciences ,Multidisciplinary ,04 agricultural and veterinary sciences ,Bovine genome ,Animals, Domestic ,Proteins/genetics ,Female ,CIENCIAS NATURALES Y EXACTAS ,Sequence analysis ,Evolution ,Biotecnología Agropecuaria ,Molecular Sequence Data ,Tecnología GM, clonación de ganado, selección asistida, diagnósticos, tecnología de producción de biomasa, etc ,Biology ,Synteny ,Article ,Ciencias Biológicas ,Evolution, Molecular ,03 medical and health sciences ,Species Specificity ,Animals ,Humans ,General ,Gene ,030304 developmental biology ,Whole genome sequencing ,ved/biology ,Taurine cattle ,0402 animal and dairy science ,Genetic Variation ,Sequence Analysis, DNA ,040201 dairy & animal science ,Bos taurus ,Alternative Splicing ,MicroRNAs/genetics ,CIENCIAS AGRÍCOLAS ,cattle ,Cattle ,genetic - Abstract
To understand the biology and evolution of ruminants, the cattle genome was sequenced to about sevenfold coverage. The cattle genome contains a minimum of 22,000 genes, with a core set of 14,345 orthologs shared among seven mammalian species of which 1217 are absent or undetected in noneutherian (marsupial or monotreme) genomes. Cattle-specific evolutionary breakpoint regions in chromosomes have a higher density of segmental duplications, enrichment of repetitive elements, and species-specific variations in genes associated with lactation and immune responsiveness. Genes involved in metabolism are generally highly conserved, although five metabolic genes are deleted or extensively diverged from their human orthologs. The cattle genome sequence thus provides a resource for understanding mammalian evolution and accelerating livestock genetic improvement for milk and meat production. Fil: Bovine Genome Sequencing and Analysis Consortium. Bovine Genome Sequencing And Analysis Consortium; Estados Unidos Fil: Amadio, Ariel Fernando. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Santa Fe. Estación Experimental Agropecuaria Rafaela; Argentina Fil: Poli, Mario Andres. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Genética; Argentina
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- 2009
- Full Text
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42. Evolutionary dynamics of immune-related genes and pathways in disease-vector mosquitoes
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Carolina Barillas-Mury, George Dimopoulos, Sang Woon Shin, Elena A. Levashina, Yuemei Dong, Evgenia V. Kriventseva, Zhiyong Xi, Jianyong Li, Robert M. Waterhouse, Bruce M. Christensen, Kristin Michel, Evgeny M. Zdobnov, Lihui Wang, Liangbiao Zheng, Mike A. Osta, Weiqi Wei, António M. Mendes, Anastasios C. Koutsos, Robert M. MacCallum, Guowu Bian, David W. Severson, George K. Christophides, Michael R. Kanost, Susan M. Paskewitz, Petros Ligoxygakis, George F. Mayhew, Dina Vlachou, Stéphanie Blandin, Fotis C. Kafatos, Zhen Zou, Kanwal S. Alvarez, Haobo Jiang, Lyric C. Bartholomay, Alexander S. Raikhel, and Stephan Meister
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Carrier Proteins/genetics/physiology ,Insect Vectors/ genetics/immunology ,Anopheles gambiae ,Genes, Insect ,Aedes aegypti ,Article ,Evolution, Molecular ,03 medical and health sciences ,Immune system ,Species Specificity ,Aedes ,Anopheles ,Animals ,ddc:576.5 ,Anopheles/ genetics/immunology ,030304 developmental biology ,Melanins ,Genetics ,0303 health sciences ,Antimicrobial Cationic Peptides/physiology ,Multidisciplinary ,Innate immune system ,biology ,Immunity, Innate/ genetics ,Melanins/metabolism ,030302 biochemistry & molecular biology ,fungi ,biology.organism_classification ,Immunity, Innate ,Insect Vectors ,Malaria ,3. Good health ,Aedes/ genetics/immunology ,Drosophila melanogaster ,Vector (epidemiology) ,Multigene Family ,Insect Proteins/genetics/physiology ,Insect Proteins ,Drosophila melanogaster/genetics/immunology ,Malaria/transmission ,Carrier Proteins ,Antimicrobial Cationic Peptides ,Signal Transduction - Abstract
Mosquitoes are vectors of parasitic and viral diseases of immense importance for public health. The acquisition of the genome sequence of the yellow fever and Dengue vector, Aedes aegypti ( Aa ), has enabled a comparative phylogenomic analysis of the insect immune repertoire: in Aa , the malaria vector Anopheles gambiae ( Ag ), and the fruit fly Drosophila melanogaster ( Dm ). Analysis of immune signaling pathways and response modules reveals both conservative and rapidly evolving features associated with different functional gene categories and particular aspects of immune reactions. These dynamics reflect in part continuous readjustment between accommodation and rejection of pathogens and suggest how innate immunity may have evolved.
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- 2007
43. AnoEST: Toward A. gambiae functional genomics
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Evgenia V. Kriventseva, Anastasios C. Koutsos, Evgeny M. Zdobnov, Claudia Blass, Fotis C. Kafatos, and George K. Christophides
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Gene prediction ,Anopheles gambiae ,Genes, Insect ,Biology ,Homology (biology) ,03 medical and health sciences ,0302 clinical medicine ,Complementary DNA ,Anopheles ,Databases, Genetic ,Genetics ,Ensembl ,Animals ,Genetics (clinical) ,030304 developmental biology ,Expressed Sequence Tags ,0303 health sciences ,Expressed sequence tag ,Genome ,Gene Expression Regulation, Developmental ,Gene Annotation ,biology.organism_classification ,Resources ,3. Good health ,Anopheles gambiae/embryology/genetics ,Functional genomics ,030217 neurology & neurosurgery - Abstract
Here, we present an analysis of 215,634 EST and cDNA sequences of a major vector of human malaria Anopheles gambiae structured into the AnoEST database. The expressed sequences are grouped into clusters using genomic sequence as template and associated with inferred functional annotation, including the following: corresponding Ensembl gene prediction, putative orthologous genes in other species, homology to known proteins, protein domains, associated Gene Ontology terms, and corresponding classification into broad GO-slim functional groups. AnoEST is a vital resource for interpretation of expression profiles derived using recently developed A. gambiae cDNA microarrays. Using these cDNA microarrays, we have experimentally confirmed the expression of 7961 clusters during mosquito development. Of these, 3100 are not associated with currently predicted genes. Moreover, we found that clusters with confirmed expression are nonbiased with respect to the current gene annotation or homology to known proteins. Consequently, we expect that many as yet unconfirmed clusters are likely to be actual A. gambiae genes. [AnoEST is publicly available at http://komar.embl.de, and is also accessible as a Distributed Annotation Service (DAS).]
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- 2005
44. Classification of proteins by clustering techniques
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Evgenia V. Kriventseva
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Protein function ,Annotation ,ComputingMethodologies_PATTERNRECOGNITION ,Protein database ,Structural Classification of Proteins database ,Computational biology ,Data mining ,Biology ,Cluster analysis ,computer.software_genre ,Genome ,computer - Abstract
In the past few years, the technology of sequencing has developed to the stage at which the sequencing of a complete genome can be contemplated as a practical and routine possibility. To cope with the exponentially growing data, methodologies for computational classification of biological sequences are required. Recently, several approaches for automatic functional classification of proteins were developed. This review describes the most widely applied clustering algorithms in Bioinformatics and resources developed for protein classification. Keywords: protein classification; protein function; clustering techniques; automatic annotation; protein databases
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- 2005
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45. Alternative splicing: conservation and function
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Evgenia V. Kriventseva and Mikhail S. Gelfand
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Genetics ,Protein isoform ,Exon ,Protein domain ,Gene duplication ,Alternative splicing ,Exonic splicing enhancer ,Human genome ,Biology ,Genome - Abstract
A major role in the analysis of alternative splicing belongs to the large-scale computational examination of available EST and genome data. At least half of human genes are alternatively spliced, and many of them have isoforms not conserved in mouse. Alternative splicing tends to shuffle protein domains and frequently affects signal peptides and functional sites within domains. Thus, alternative splicing is a major mechanism generating functional and evolutional diversity of proteins. On the other hand, unlike simple gene duplication, this mechanism allows for the production of absolutely identical, in some parts, proteins. Keywords: alternative splicing; evolution; isoform; exon–intron structure; protein function; human genome; mouse genome
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- 2004
- Full Text
- View/download PDF
46. Increase of functional diversity by alternative splicing
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Mikhail S. Gelfand, Martin Vingron, Ina Koch, Evgenia V. Kriventseva, Shamil R. Sunyaev, Rolf Apweiler, and Peer Bork
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Gene isoform ,Genetics ,Models, Molecular ,Folded structure ,Positive selection ,Protein domain ,Alternative splicing ,Computational Biology ,Computational biology ,Biology ,Ligands ,Insert (molecular biology) ,Protein Structure, Tertiary ,Functional diversity ,Alternative Splicing ,Animals ,Humans ,Protein Isoforms ,Amino Acid Sequence ,Amino Acids ,Selection, Genetic ,Databases, Protein ,Peptide sequence - Abstract
A large-scale analysis of protein isoforms arising from alternative splicing shows that alternative splicing tends to insert or delete complete protein domains more frequently than expected by chance, whereas disruption of domains and other structural modules is less frequent. If domain regions are disrupted, the functional effect, as predicted from 3D structure, is frequently equivalent to removal of the entire domain. Also, short alternative splicing events within domains, which might preserve folded structure, target functional residues more frequently than expected. Thus, it seems that positive selection has had a major role in the evolution of alternative splicing.
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- 2003
47. The Proteome Analysis database: a tool for the in silico analysis of whole proteomes
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Paul J. Kersey, Youla Karavidopoulou, Florence Servant, Virginie Mittard, Nicola Mulder, Wolfgang Fleischmann, Evgenia V. Kriventseva, Isabelle Phan, Manuela Pruess, Rolf Apweiler, and Alexander Kanapin
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InterPro ,Proteome ,In silico ,Archaeal Proteins ,Biology ,computer.software_genre ,Genome ,03 medical and health sciences ,Mice ,Bacterial Proteins ,Sequence Analysis, Protein ,Genetics ,Human proteome project ,Animals ,Humans ,Databases, Protein ,Eukaryotic cell ,030304 developmental biology ,Protein coding ,0303 health sciences ,Database ,Sequence database ,Sequence Homology, Amino Acid ,030302 biochemistry & molecular biology ,Proteins ,Articles ,Data Interpretation, Statistical ,computer - Abstract
The Proteome Analysis database (http://www.ebi.ac.uk/proteome/) has been developed by the Sequence Database Group at EBI utilizing existing resources and providing comparative analysis of the predicted protein coding sequences of the complete genomes of bacteria, archeae and eukaryotes. Three main projects are used, InterPro, CluSTr and GO Slim, to give an overview on families, domains, sites, and functions of the proteins from each of the complete genomes. Complete proteome analysis is available for a total of 89 proteome sets. A specifically designed application enables InterPro proteome comparisons for any one proteome against any other one or more of the proteomes in the database.
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- 2003
48. Theoretical analysis of alternative splice forms using computational methods
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Evgenia V. Kriventseva, Stéphanie Boué, Ina Koch, and Martin Vingron
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Statistics and Probability ,Models, Molecular ,Protein Conformation ,Sequence alignment ,Computational biology ,Biology ,Biochemistry ,Exon ,Protein structure ,Protein sequencing ,Sequence Analysis, Protein ,Humans ,splice ,Computer Simulation ,Molecular Biology ,Structure (mathematical logic) ,Genetics ,Expressed Sequence Tags ,Models, Genetic ,Sequence Analysis, RNA ,Alternative splicing ,Structural protein ,Exons ,Computer Science Applications ,Computational Mathematics ,Alternative Splicing ,Computational Theory and Mathematics ,Sequence Alignment ,Algorithms ,Transcription Factors - Abstract
Nowadays understanding alternative splicing is one of the greatest challenges in biology, because it is a genetic process much more important than thought at the time of its discovery. In this paper, we explain the approach of using the different available databases and software tools to start a large scale investigation of alternative splice forms. To collect information about alternative splicing we investigated known data in the databases using different computational methods. The investigations proceeded from the genomic sequence data to structural protein data. Then, we interpreted those data to find the relationship between alternative splice forms and protein function and structure. We found some interesting features of alternative splicing which are presented here. We discuss the results of one chosen example. They concern the coverage quality of the protein sequence of a known structure, an EST analysis, the validation of splice variants, the determination of the alternative splice type, and finally the link between alternative splicing and disease. Contact: ina.koch@molgen.mpg.de
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- 2002
49. A collection of well characterised integral membrane proteins
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Rolf Apweiler, Evgenia V. Kriventseva, and Steffen Möller
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Statistics and Probability ,Internet ,Computational Biology ,Membrane Proteins ,Biology ,Biochemistry ,Transmembrane protein ,Computer Science Applications ,Computational Mathematics ,Computational Theory and Mathematics ,Membrane protein ,Test set ,SOSUI ,Statistical analysis ,Abstract Summary ,Molecular Biology ,Algorithm ,Integral membrane protein ,Algorithms ,Software - Abstract
Summary: A collection of transmembrane proteins withannotated transmembrane regions, for which good exper-imental evidence exist, was created as a test or trainingset for algorithms to predict transmembrane regions inproteins. Availability: ftp://ftp.ebi.ac.uk/databases/testsets/transmembrane Contact: moeller@ebi.ac.uk Introduction and motivation A program for the prediction of membrane spanning re-gions in proteins needs reliable data both for its speci-fication and verification. To benchmark the performanceof transmembrane prediction programs, it is necessary touse a test set of sequences with experimentally confirmedtransmembrane regions. Such test sets differ in the selec-tion of proteins and very often in the annotation of trans-membrane segments of identical proteins.This paper describes a test set which unifies, updates andverifies the existing test sets TMHMM (Sonnhammer etal. , 1998), HTP (Rost et al. , 1996), DAS (Cserzo et al. ,1997), CoPreTHi (Promponas et al. , 1998), SOSUI (Hi-rokawa
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- 2001
50. CluSTr: a database of clusters of SWISS-PROT+TrEMBL proteins
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Rolf Apweiler, Evgenia V. Kriventseva, Wolfgang Fleischmann, and Evgeni M. Zdobnov
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InterPro ,Carrier Proteins/genetics ,Protein family ,Databases, Factual ,Protein Data Bank (RCSB PDB) ,Sequence alignment ,PROSITE ,Biology ,computer.software_genre ,Article ,Genetics ,Cluster (physics) ,Animals ,Humans ,Cluster analysis ,Information Services ,Internet ,Database ,Sodium ,Proteins ,Sodium/metabolism ,Proteins/genetics ,UniProt ,Carrier Proteins ,computer ,Sequence Alignment - Abstract
The CluSTr (Clusters of SWISS-PROT and TrEMBL proteins) database offers an automatic classification of SWISS-PROT and TrEMBL proteins into groups of related proteins. The clustering is based on analysis of all pairwise comparisons between protein sequences. Analysis has been carried out for different levels of protein similarity, yielding a hierarchical organisation of clusters. The database provides links to InterPro, which integrates information on protein families, domains and functional sites from PROSITE, PRINTS, Pfam and ProDom. Links to the InterPro graphical interface allow users to see at a glance whether proteins from the cluster share particular functional sites. CluSTr also provides cross-references to HSSP and PDB. The database is available for querying and browsing at http://www.ebi.ac.uk/clustr.
- Published
- 2001
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