PMCC PMCC

Search tips
Search criteria

Advanced
Results 1-12 (12)
 

Clipboard (0)
None

Select a Filter Below

Journals
Year of Publication
1.  Hawkeye and AMOS: visualizing and assessing the quality of genome assemblies 
Briefings in Bioinformatics  2011;14(2):213-224.
Since its launch in 2004, the open-source AMOS project has released several innovative DNA sequence analysis applications including: Hawkeye, a visual analytics tool for inspecting the structure of genome assemblies; the Assembly Forensics and FRCurve pipelines for systematically evaluating the quality of a genome assembly; and AMOScmp, the first comparative genome assembler. These applications have been used to assemble and analyze dozens of genomes ranging in complexity from simple microbial species through mammalian genomes. Recent efforts have been focused on enhancing support for new data characteristics brought on by second- and now third-generation sequencing. This review describes the major components of AMOS in light of these challenges, with an emphasis on methods for assessing assembly quality and the visual analytics capabilities of Hawkeye. These interactive graphical aspects are essential for navigating and understanding the complexities of a genome assembly, from the overall genome structure down to individual bases. Hawkeye and AMOS are available open source at http://amos.sourceforge.net.
doi:10.1093/bib/bbr074
PMCID: PMC3603210  PMID: 22199379
DNA Sequencing; genome assembly; assembly forensics; visual analytics
2.  MetAMOS: a modular and open source metagenomic assembly and analysis pipeline 
Genome Biology  2013;14(1):R2.
We describe MetAMOS, an open source and modular metagenomic assembly and analysis pipeline. MetAMOS represents an important step towards fully automated metagenomic analysis, starting with next-generation sequencing reads and producing genomic scaffolds, open-reading frames and taxonomic or functional annotations. MetAMOS can aid in reducing assembly errors, commonly encountered when assembling metagenomic samples, and improves taxonomic assignment accuracy while also reducing computational cost. MetAMOS can be downloaded from: https://github.com/treangen/MetAMOS.
doi:10.1186/gb-2013-14-1-r2
PMCID: PMC4053804  PMID: 23320958
3.  A framework for human microbiome research 
Methé, Barbara A. | Nelson, Karen E. | Pop, Mihai | Creasy, Heather H. | Giglio, Michelle G. | Huttenhower, Curtis | Gevers, Dirk | Petrosino, Joseph F. | Abubucker, Sahar | Badger, Jonathan H. | Chinwalla, Asif T. | Earl, Ashlee M. | FitzGerald, Michael G. | Fulton, Robert S. | Hallsworth-Pepin, Kymberlie | Lobos, Elizabeth A. | Madupu, Ramana | Magrini, Vincent | Martin, John C. | Mitreva, Makedonka | Muzny, Donna M. | Sodergren, Erica J. | Versalovic, James | Wollam, Aye M. | Worley, Kim C. | Wortman, Jennifer R. | Young, Sarah K. | Zeng, Qiandong | Aagaard, Kjersti M. | Abolude, Olukemi O. | Allen-Vercoe, Emma | Alm, Eric J. | Alvarado, Lucia | Andersen, Gary L. | Anderson, Scott | Appelbaum, Elizabeth | Arachchi, Harindra M. | Armitage, Gary | Arze, Cesar A. | Ayvaz, Tulin | Baker, Carl C. | Begg, Lisa | Belachew, Tsegahiwot | Bhonagiri, Veena | Bihan, Monika | Blaser, Martin J. | Bloom, Toby | Vivien Bonazzi, J. | Brooks, Paul | Buck, Gregory A. | Buhay, Christian J. | Busam, Dana A. | Campbell, Joseph L. | Canon, Shane R. | Cantarel, Brandi L. | Chain, Patrick S. | Chen, I-Min A. | Chen, Lei | Chhibba, Shaila | Chu, Ken | Ciulla, Dawn M. | Clemente, Jose C. | Clifton, Sandra W. | Conlan, Sean | Crabtree, Jonathan | Cutting, Mary A. | Davidovics, Noam J. | Davis, Catherine C. | DeSantis, Todd Z. | Deal, Carolyn | Delehaunty, Kimberley D. | Dewhirst, Floyd E. | Deych, Elena | Ding, Yan | Dooling, David J. | Dugan, Shannon P. | Dunne, Wm. Michael | Durkin, A. Scott | Edgar, Robert C. | Erlich, Rachel L. | Farmer, Candace N. | Farrell, Ruth M. | Faust, Karoline | Feldgarden, Michael | Felix, Victor M. | Fisher, Sheila | Fodor, Anthony A. | Forney, Larry | Foster, Leslie | Di Francesco, Valentina | Friedman, Jonathan | Friedrich, Dennis C. | Fronick, Catrina C. | Fulton, Lucinda L. | Gao, Hongyu | Garcia, Nathalia | Giannoukos, Georgia | Giblin, Christina | Giovanni, Maria Y. | Goldberg, Jonathan M. | Goll, Johannes | Gonzalez, Antonio | Griggs, Allison | Gujja, Sharvari | Haas, Brian J. | Hamilton, Holli A. | Harris, Emily L. | Hepburn, Theresa A. | Herter, Brandi | Hoffmann, Diane E. | Holder, Michael E. | Howarth, Clinton | Huang, Katherine H. | Huse, Susan M. | Izard, Jacques | Jansson, Janet K. | Jiang, Huaiyang | Jordan, Catherine | Joshi, Vandita | Katancik, James A. | Keitel, Wendy A. | Kelley, Scott T. | Kells, Cristyn | Kinder-Haake, Susan | King, Nicholas B. | Knight, Rob | Knights, Dan | Kong, Heidi H. | Koren, Omry | Koren, Sergey | Kota, Karthik C. | Kovar, Christie L. | Kyrpides, Nikos C. | La Rosa, Patricio S. | Lee, Sandra L. | Lemon, Katherine P. | Lennon, Niall | Lewis, Cecil M. | Lewis, Lora | Ley, Ruth E. | Li, Kelvin | Liolios, Konstantinos | Liu, Bo | Liu, Yue | Lo, Chien-Chi | Lozupone, Catherine A. | Lunsford, R. Dwayne | Madden, Tessa | Mahurkar, Anup A. | Mannon, Peter J. | Mardis, Elaine R. | Markowitz, Victor M. | Mavrommatis, Konstantinos | McCorrison, Jamison M. | McDonald, Daniel | McEwen, Jean | McGuire, Amy L. | McInnes, Pamela | Mehta, Teena | Mihindukulasuriya, Kathie A. | Miller, Jason R. | Minx, Patrick J. | Newsham, Irene | Nusbaum, Chad | O’Laughlin, Michelle | Orvis, Joshua | Pagani, Ioanna | Palaniappan, Krishna | Patel, Shital M. | Pearson, Matthew | Peterson, Jane | Podar, Mircea | Pohl, Craig | Pollard, Katherine S. | Priest, Margaret E. | Proctor, Lita M. | Qin, Xiang | Raes, Jeroen | Ravel, Jacques | Reid, Jeffrey G. | Rho, Mina | Rhodes, Rosamond | Riehle, Kevin P. | Rivera, Maria C. | Rodriguez-Mueller, Beltran | Rogers, Yu-Hui | Ross, Matthew C. | Russ, Carsten | Sanka, Ravi K. | Pamela Sankar, J. | Sathirapongsasuti, Fah | Schloss, Jeffery A. | Schloss, Patrick D. | Schmidt, Thomas M. | Scholz, Matthew | Schriml, Lynn | Schubert, Alyxandria M. | Segata, Nicola | Segre, Julia A. | Shannon, William D. | Sharp, Richard R. | Sharpton, Thomas J. | Shenoy, Narmada | Sheth, Nihar U. | Simone, Gina A. | Singh, Indresh | Smillie, Chris S. | Sobel, Jack D. | Sommer, Daniel D. | Spicer, Paul | Sutton, Granger G. | Sykes, Sean M. | Tabbaa, Diana G. | Thiagarajan, Mathangi | Tomlinson, Chad M. | Torralba, Manolito | Treangen, Todd J. | Truty, Rebecca M. | Vishnivetskaya, Tatiana A. | Walker, Jason | Wang, Lu | Wang, Zhengyuan | Ward, Doyle V. | Warren, Wesley | Watson, Mark A. | Wellington, Christopher | Wetterstrand, Kris A. | White, James R. | Wilczek-Boney, Katarzyna | Wu, Yuan Qing | Wylie, Kristine M. | Wylie, Todd | Yandava, Chandri | Ye, Liang | Ye, Yuzhen | Yooseph, Shibu | Youmans, Bonnie P. | Zhang, Lan | Zhou, Yanjiao | Zhu, Yiming | Zoloth, Laurie | Zucker, Jeremy D. | Birren, Bruce W. | Gibbs, Richard A. | Highlander, Sarah K. | Weinstock, George M. | Wilson, Richard K. | White, Owen
Nature  2012;486(7402):215-221.
A variety of microbial communities and their genes (microbiome) exist throughout the human body, playing fundamental roles in human health and disease. The NIH funded Human Microbiome Project (HMP) Consortium has established a population-scale framework which catalyzed significant development of metagenomic protocols resulting in a broad range of quality-controlled resources and data including standardized methods for creating, processing and interpreting distinct types of high-throughput metagenomic data available to the scientific community. Here we present resources from a population of 242 healthy adults sampled at 15 to 18 body sites up to three times, which to date, have generated 5,177 microbial taxonomic profiles from 16S rRNA genes and over 3.5 Tb of metagenomic sequence. In parallel, approximately 800 human-associated reference genomes have been sequenced. Collectively, these data represent the largest resource to date describing the abundance and variety of the human microbiome, while providing a platform for current and future studies.
doi:10.1038/nature11209
PMCID: PMC3377744  PMID: 22699610
4.  Deep Sequencing of the Oral Microbiome Reveals Signatures of Periodontal Disease 
PLoS ONE  2012;7(6):e37919.
The oral microbiome, the complex ecosystem of microbes inhabiting the human mouth, harbors several thousands of bacterial types. The proliferation of pathogenic bacteria within the mouth gives rise to periodontitis, an inflammatory disease known to also constitute a risk factor for cardiovascular disease. While much is known about individual species associated with pathogenesis, the system-level mechanisms underlying the transition from health to disease are still poorly understood. Through the sequencing of the 16S rRNA gene and of whole community DNA we provide a glimpse at the global genetic, metabolic, and ecological changes associated with periodontitis in 15 subgingival plaque samples, four from each of two periodontitis patients, and the remaining samples from three healthy individuals. We also demonstrate the power of whole-metagenome sequencing approaches in characterizing the genomes of key players in the oral microbiome, including an unculturable TM7 organism. We reveal the disease microbiome to be enriched in virulence factors, and adapted to a parasitic lifestyle that takes advantage of the disrupted host homeostasis. Furthermore, diseased samples share a common structure that was not found in completely healthy samples, suggesting that the disease state may occupy a narrow region within the space of possible configurations of the oral microbiome. Our pilot study demonstrates the power of high-throughput sequencing as a tool for understanding the role of the oral microbiome in periodontal disease. Despite a modest level of sequencing (∼2 lanes Illumina 76 bp PE) and high human DNA contamination (up to ∼90%) we were able to partially reconstruct several oral microbes and to preliminarily characterize some systems-level differences between the healthy and diseased oral microbiomes.
doi:10.1371/journal.pone.0037919
PMCID: PMC3366996  PMID: 22675498
6.  Two New Complete Genome Sequences Offer Insight into Host and Tissue Specificity of Plant Pathogenic Xanthomonas spp.▿† 
Journal of Bacteriology  2011;193(19):5450-5464.
Xanthomonas is a large genus of bacteria that collectively cause disease on more than 300 plant species. The broad host range of the genus contrasts with stringent host and tissue specificity for individual species and pathovars. Whole-genome sequences of Xanthomonas campestris pv. raphani strain 756C and X. oryzae pv. oryzicola strain BLS256, pathogens that infect the mesophyll tissue of the leading models for plant biology, Arabidopsis thaliana and rice, respectively, were determined and provided insight into the genetic determinants of host and tissue specificity. Comparisons were made with genomes of closely related strains that infect the vascular tissue of the same hosts and across a larger collection of complete Xanthomonas genomes. The results suggest a model in which complex sets of adaptations at the level of gene content account for host specificity and subtler adaptations at the level of amino acid or noncoding regulatory nucleotide sequence determine tissue specificity.
doi:10.1128/JB.05262-11
PMCID: PMC3187462  PMID: 21784931
7.  Sequence-Based Predictions of Lipooligosaccharide Diversity in the Neisseriaceae and Their Implication in Pathogenicity 
PLoS ONE  2011;6(4):e18923.
Endotoxin [Lipopolysaccharide (LPS)/Lipooligosaccharide (LOS)] is an important virulence determinant in gram negative bacteria. While the genetic basis of endotoxin production and its role in disease in the pathogenic Neisseria has been extensively studied, little research has focused on the genetic basis of LOS biosynthesis in commensal Neisseria. We determined the genomic sequences of a variety of commensal Neisseria strains, and compared these sequences, along with other genomic sequences available from various sequencing centers from commensal and pathogenic strains, to identify genes involved in LOS biosynthesis. This allowed us to make structural predictions as to differences in LOS seen between commensal and pathogenic strains. We determined that all neisserial strains possess a conserved set of genes needed to make a common 3-Deoxy-D-manno-octulosonic acid -heptose core structure. However, significant genomic differences in glycosyl transferase genes support the published literature indicating compositional differences in the terminal oligosaccharides. This was most pronounced in commensal strains that were distally related to the gonococcus and meningococcus. These strains possessed a homolog of heptosyltransferase III, suggesting that they differ from the pathogenic strains by the presence a third heptose. Furthermore, most commensal strains possess homologs of genes needed to synthesize lipopolysaccharide (LPS). N. cinerea, a commensal species that is highly related to the gonococcus has lost the ability to make sialyltransferase. Overall genomic comparisons of various neisserial strains indicate that significant recombination/genetic acquisition/loss has occurred within the genus, and this muddles proper speciation.
doi:10.1371/journal.pone.0018923
PMCID: PMC3078933  PMID: 21533118
8.  Genome Sequence of the Wolbachia Endosymbiont of Culex quinquefasciatus JHB▿  
Journal of Bacteriology  2008;191(5):1725.
Wolbachia species are endosymbionts of a wide range of invertebrates, including mosquitoes, fruit flies, and nematodes. The wPip strains can cause cytoplasmic incompatibility in some strains of the Culex mosquito. Here we describe the genome sequence of a Wolbachia strain that was discovered in the whole-genome sequencing data for the mosquito Culex quinquefasciatus strain JHB.
doi:10.1128/JB.01731-08
PMCID: PMC2648186  PMID: 19114486
9.  Gene-Boosted Assembly of a Novel Bacterial Genome from Very Short Reads 
PLoS Computational Biology  2008;4(9):e1000186.
Recent improvements in technology have made DNA sequencing dramatically faster and more efficient than ever before. The new technologies produce highly accurate sequences, but one drawback is that the most efficient technology produces the shortest read lengths. Short-read sequencing has been applied successfully to resequence the human genome and those of other species but not to whole-genome sequencing of novel organisms. Here we describe the sequencing and assembly of a novel clinical isolate of Pseudomonas aeruginosa, strain PAb1, using very short read technology. From 8,627,900 reads, each 33 nucleotides in length, we assembled the genome into one scaffold of 76 ordered contiguous sequences containing 6,290,005 nucleotides, including one contig spanning 512,638 nucleotides, plus an additional 436 unordered contigs containing 416,897 nucleotides. Our method includes a novel gene-boosting algorithm that uses amino acid sequences from predicted proteins to build a better assembly. This study demonstrates the feasibility of very short read sequencing for the sequencing of bacterial genomes, particularly those for which a related species has been sequenced previously, and expands the potential application of this new technology to most known prokaryotic species.
Author Summary
In this paper we demonstrate that a bacterial genome, Pseudomonas aeruginosa, can be decoded using very short DNA sequences, namely, those produced by the newest generation of DNA sequencers such as the Solexa sequencer from Illumina. Our method includes a novel algorithm that uses the protein sequences from other species to assist the assembly of the new genome. This algorithm breaks up the genome into gene-sized chunks that can be put back together relatively easily, even from sequence fragments as short as 30 bases of DNA. We also take advantage of the genomes of related species, using them as reference strains to assist the assembly. By combining these and other techniques, we were able to assemble 94% of the 6.7 million bases of P. aeruginosa into just 76 large pieces. The remaining 6% is contained in 436 smaller fragments. We have made all of our software available for free under open-source licenses, and we have deposited the newly assembled genome in the public GenBank database.
doi:10.1371/journal.pcbi.1000186
PMCID: PMC2529408  PMID: 18818729
10.  Genome sequence and rapid evolution of the rice pathogen Xanthomonas oryzae pv. oryzae PXO99A 
BMC Genomics  2008;9:204.
Background
Xanthomonas oryzae pv. oryzae causes bacterial blight of rice (Oryza sativa L.), a major disease that constrains production of this staple crop in many parts of the world. We report here on the complete genome sequence of strain PXO99A and its comparison to two previously sequenced strains, KACC10331 and MAFF311018, which are highly similar to one another.
Results
The PXO99A genome is a single circular chromosome of 5,240,075 bp, considerably longer than the genomes of the other strains (4,941,439 bp and 4,940,217 bp, respectively), and it contains 5083 protein-coding genes, including 87 not found in KACC10331 or MAFF311018. PXO99A contains a greater number of virulence-associated transcription activator-like effector genes and has at least ten major chromosomal rearrangements relative to KACC10331 and MAFF311018. PXO99A contains numerous copies of diverse insertion sequence elements, members of which are associated with 7 out of 10 of the major rearrangements. A rapidly-evolving CRISPR (clustered regularly interspersed short palindromic repeats) region contains evidence of dozens of phage infections unique to the PXO99A lineage. PXO99A also contains a unique, near-perfect tandem repeat of 212 kilobases close to the replication terminus.
Conclusion
Our results provide striking evidence of genome plasticity and rapid evolution within Xanthomonas oryzae pv. oryzae. The comparisons point to sources of genomic variation and candidates for strain-specific adaptations of this pathogen that help to explain the extraordinary diversity of Xanthomonas oryzae pv. oryzae genotypes and races that have been isolated from around the world.
doi:10.1186/1471-2164-9-204
PMCID: PMC2432079  PMID: 18452608
11.  Comprehensive DNA Signature Discovery and Validation 
PLoS Computational Biology  2007;3(5):e98.
DNA signatures are nucleotide sequences that can be used to detect the presence of an organism and to distinguish that organism from all other species. Here we describe Insignia, a new, comprehensive system for the rapid identification of signatures in the genomes of bacteria and viruses. With the availability of hundreds of complete bacterial and viral genome sequences, it is now possible to use computational methods to identify signature sequences in all of these species, and to use these signatures as the basis for diagnostic assays to detect and genotype microbes in both environmental and clinical samples. The success of such assays critically depends on the methods used to identify signatures that properly differentiate between the target genomes and the sample background. We have used Insignia to compute accurate signatures for most bacterial genomes and made them available through our Web site. A sample of these signatures has been successfully tested on a set of 46 Vibrio cholerae strains, and the results indicate that the signatures are highly sensitive for detection as well as specific for discrimination between these strains and their near relatives. Our approach, whereby the entire genomic complement of organisms are compared to identify probe targets, is a promising method for diagnostic assay development, and it provides assay designers with the flexibility to choose probes from the most relevant genes or genomic regions. The Insignia system is freely accessible via a Web interface and has been released as open source software at: http://insignia.cbcb.umd.edu.
Author Summary
Now that the genome sequences of hundreds of bacteria and viruses are known, we can design tests that will rapidly detect the presence of these species based solely on their DNA. Such tests have a wide range of applications, from diagnosing infections to detecting harmful microbes in a water supply. These tests can detect a pathogen in a complex mixture of organic material by recognizing short, distinguishing sequences—called DNA signatures—that occur in the pathogen and not in any other species. We present Insignia, a new computational system that identifies DNA signatures of any length in bacterial and viral genomes. Insignia uses highly efficient algorithms to compare sequenced bacterial and viral genomes against each other and to additional background genomes including plants, animals, and human. These comparisons are stored in a database and used to rapidly compute signatures for any particular target species. To maximize its utility for the community, we have made Insignia available as free, open-source software and as a Web application. We have also validated 50 Insignia-designed assays on a panel of 46 strains of Vibrio cholerae, and our results show that the signatures are both sensitive and specific.
doi:10.1371/journal.pcbi.0030098
PMCID: PMC1868776  PMID: 17511514
12.  Minimus: a fast, lightweight genome assembler 
BMC Bioinformatics  2007;8:64.
Background
Genome assemblers have grown very large and complex in response to the need for algorithms to handle the challenges of large whole-genome sequencing projects. Many of the most common uses of assemblers, however, are best served by a simpler type of assembler that requires fewer software components, uses less memory, and is far easier to install and run.
Results
We have developed the Minimus assembler to address these issues, and tested it on a range of assembly problems. We show that Minimus performs well on several small assembly tasks, including the assembly of viral genomes, individual genes, and BAC clones. In addition, we evaluate Minimus' performance in assembling bacterial genomes in order to assess its suitability as a component of a larger assembly pipeline. We show that, unlike other software currently used for these tasks, Minimus produces significantly fewer assembly errors, at the cost of generating a more fragmented assembly.
Conclusion
We find that for small genomes and other small assembly tasks, Minimus is faster and far more flexible than existing tools. Due to its small size and modular design Minimus is perfectly suited to be a component of complex assembly pipelines. Minimus is released as an open-source software project and the code is available as part of the AMOS project at Sourceforge.
doi:10.1186/1471-2105-8-64
PMCID: PMC1821043  PMID: 17324286

Results 1-12 (12)