Showing papers by "Owen White published in 2007"
J. Craig Venter Institute1, Broad Institute2, Virginia Tech3, Johns Hopkins University4, University of Notre Dame5, Harvard University6, Colorado State University7, Northwestern University8, University of California, Riverside9, University of Oxford10, Purdue University11, Pasteur Institute12, University of São Paulo13, University of Geneva14, University of Massachusetts Amherst15, Instituto Butantan16, University of A Coruña17, University of Göttingen18
TL;DR: A draft sequence of the genome of Aedes aegypti, the primary vector for yellow fever and dengue fever, which at approximately 1376 million base pairs is about 5 times the size of the genomes of the malaria vector Anopheles gambiae was presented in this paper.
Abstract: We present a draft sequence of the genome of Aedes aegypti, the primary vector for yellow fever and dengue fever, which at approximately 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 approximately 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 approximately 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.
1,107 citations
Newcastle University1, J. Craig Venter Institute2, University of Maryland, College Park3, University of Glasgow4, Technical University of Denmark5, University of Calgary6, Natural History Museum7, Ghent University8, University of Dundee9, University of Sassari10, University of California, Los Angeles11, Children's Hospital Oakland Research Institute12, Charles University in Prague13, University of Iowa14, University of Düsseldorf15, University of California, San Francisco16, University of Queensland17, QIMR Berghofer Medical Research Institute18, Chang Gung University19, University of Strathclyde20
TL;DR: The genome sequence of the protist Trichomonas vaginalis predicts previously unknown functions for the hydrogenosome, which support a common evolutionary origin of this unusual organelle with mitochondria.
Abstract: We describe the genome sequence of the protist Trichomonas vaginalis, a sexually transmitted human pathogen. Repeats and transposable elements comprise about two-thirds of the similar to 160-megabase genome, reflecting a recent massive expansion of genetic material. This expansion, in conjunction with the shaping of metabolic pathways that likely transpired through lateral gene transfer from bacteria, and amplification of specific gene families implicated in pathogenesis and phagocytosis of host proteins may exemplify adaptations of the parasite during its transition to a urogenital environment. The genome sequence predicts previously unknown functions for the hydrogenosome, which support a common evolutionary origin of this unusual organelle with mitochondria.
751 citations
University of Pittsburgh1, J. Craig Venter Institute2, Imperial College London3, University of Dundee4, New England Biolabs5, University of Edinburgh6, Lyon College7, Australian National University8, University of Toledo9, University of California, Davis10, Smith College11, Washington University in St. Louis12, New York Blood Center13, National Institutes of Health14, University of Göttingen15, University of Alabama at Birmingham16, Johns Hopkins University17
TL;DR: In this article, the authors sequenced the ∼90 megabase (Mb) genome of the human filarial parasite Brugia malayi and predicted ∼11,500 protein coding genes in 71 Mb of robustly assembled sequence.
Abstract: Parasitic nematodes that cause elephantiasis and river blindness threaten hundreds of millions of people in the developing world. We have sequenced the ∼90 megabase (Mb) genome of the human filarial parasite Brugia malayi and predict ∼11,500 protein coding genes in 71 Mb of robustly assembled sequence. Comparative analysis with the free-living, model nematode Caenorhabditis elegans revealed that, despite these genes having maintained little conservation of local synteny during ∼350 million years of evolution, they largely remain in linkage on chromosomal units. More than 100 conserved operons were identified. Analysis of the predicted proteome provides evidence for adaptations of B. malayi to niches in its human and vector hosts and insights into the molecular basis of a mutualistic relationship with its Wolbachia endosymbiont. These findings offer a foundation for rational drug design.
583 citations
01 Jan 2007
TL;DR: An increase in genes encoding odorant binding, cytochrome P450, and cuticle domains relative to An.
Abstract: Vishvanath Nene,* Jennifer R. Wortman, Daniel Lawson, Brian Haas, Chinnappa Kodira, Zhijian (Jake) Tu, Brendan Loftus, Zhiyong Xi, Karyn Megy, Manfred Grabherr, Quinghu Ren, Evgeny M. Zdobnov, Neil F. Lobo, Kathryn S. Campbell, Susan E. Brown, Maria F. Bonaldo, Jingsong Zhu, Steven P. Sinkins, David G. Hogenkamp, Paolo Amedo, Peter Arensburger, Peter W. Atkinson, Shelby Bidwell, Jim Biedler, Ewan Birney, Robert V. Bruggner, Javier Costas, Monique R. Coy, Jonathan Crabtree, Matt Crawford, Becky deBruyn, David DeCaprio, Karin Eiglmeier, Eric Eisenstadt, Hamza El-Dorry, William M. Gelbart, Suely L. Gomes, Martin Hammond, Linda I. Hannick, James R. Hogan, Michael H. Holmes, David Jaffe, J. Spencer Johnston, Ryan C. Kennedy, Hean Koo, Saul Kravitz, Evgenia V. Kriventseva, David Kulp, Kurt LaButti, Eduardo Lee, Song Li, Diane D. Lovin, Chunhong Mao, Evan Mauceli, Carlos F. M. Menck, Jason R. Miller, Philip Montgomery, Akio Mori, Ana L. Nascimento, Horacio F. Naveira, Chad Nusbaum, Sinead O’Leary, Joshua Orvis, Mihaela Pertea, Hadi Quesneville, Kyanne R. Reidenbach, Yu-Hui Rogers, Charles W. Roth, Jennifer R. Schneider, Michael Schatz, Martin Shumway, Mario Stanke, Eric O. Stinson, Jose M. C. Tubio, Janice P. VanZee, Sergio VerjovskiAlmeida, Doreen Werner, Owen White, Stefan Wyder, Qiandong Zeng, Qi Zhao, Yongmei Zhao, Catherine A. Hill, Alexander S. Raikhel, Marcelo B. Soares, Dennis L. Knudson, Norman H. Lee, James Galagan, Steven L. Salzberg, Ian T. Paulsen, George Dimopoulos, Frank H. Collins, Bruce Birren, Claire M. Fraser-Liggett, David W. Severson*
95 citations
TL;DR: A two-phase protein clustering algorithm, used to generate protein clusters suitable for analysis through Sybil and a method for creating graphical displays of protein or gene clusters that span multiple genomes are described.
Abstract: With the successful completion of genome sequencing projects for a variety of model organisms, the selection of candidate organisms for future sequencing efforts has been guided increasingly by a desire to enable comparative genomics. This trend has both depended on and encouraged the development of software tools that can elucidate and capitalize on the similarities and differences between genomes. "Sybil," one such tool, is a primarily web-based software package whose primary goal is to facilitate the analysis and visualization of comparative genome data, with a particular emphasis on protein and gene cluster data. Herein, a two-phase protein clustering algorithm, used to generate protein clusters suitable for analysis through Sybil and a method for creating graphical displays of protein or gene clusters that span multiple genomes are described. When combined, these two relatively simple techniques provide the user of the Sybil software (The Institute for Genomic Research [TIGR] Bioinformatics Department) with a browsable graphical display of his or her "input" genomes, showing which genes are conserved based on the parameters supplied to the protein clustering algorithm. For any given protein cluster the graphical display consists of a local alignment of the genomes in which the clustered genes are located. The genomes are arranged in a vertical stack, as in a multiple alignment, and shaded areas are used to connect genes in the same cluster, thus displaying conservation at the protein level in the context of the underlying genomic sequences. The authors have found this display-and slight variants thereof-useful for a variety of annotation and comparison tasks, ranging from identifying "missed" gene models or single-exon discrepancies between orthologous genes, to finding large or small regions of conserved gene synteny, and investigating the properties of the breakpoints between such regions.
60 citations
22 May 2007
TL;DR: The Gemina system, developed at TIGR, has been designed as a tool to identify epidemiological factors of disease incidence and to support the design of DNA-based diagnostics such as the development of DNA signature-based assays.
Abstract: The Gemina system (http://gemina.tigr.org) developed at TIGR is a tool for identification of microbial and viral pathogens and their associated genomic sequences based on the associated epidemiological data. Gemina has been designed as a tool to identify epidemiological factors of disease incidence and to support the design of DNA-based diagnostics such as the development of DNA signature-based assays. The Gemina database contains the full complement of microbial and viral pathogens enumerated in the Microbial Rosetta Stone database (MRS) [1]. Initially, curation efforts in Gemina have focused on the NIAID category A, B, and C priority pathogens [2] identified to the level of strains. For the bacterial NIAID category A-C pathogens, for example, we have included 38 species and 769 strains in Gemina. Representative genomic sequences are selected for each pathogen from NCBI’s GenBank by a three tiered filtering system and incorporated into TIGR’s Panda DNA sequence database. A single representative sequence is selected for each pathogen firstly from complete genome sequences (Tier 1), secondly from whole genome shotgun (WGS) data from genome projects (Tier 2), or thirdly from genomic nucleotide sequences from genome projects (Tier3). The list of selected accessions is transferred to Insignia when new pathogens are added to Gemina, allowing Insignia’s Signature Pipeline [3] to be run for each pathogen identified in a Gemina query.
4 citations