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1.  The Harvest suite for rapid core-genome alignment and visualization of thousands of intraspecific microbial genomes 
Genome Biology  2014;15(11):524.
Whole-genome sequences are now available for many microbial species and clades, however existing whole-genome alignment methods are limited in their ability to perform sequence comparisons of multiple sequences simultaneously. Here we present the Harvest suite of core-genome alignment and visualization tools for the rapid and simultaneous analysis of thousands of intraspecific microbial strains. Harvest includes Parsnp, a fast core-genome multi-aligner, and Gingr, a dynamic visual platform. Together they provide interactive core-genome alignments, variant calls, recombination detection, and phylogenetic trees. Using simulated and real data we demonstrate that our approach exhibits unrivaled speed while maintaining the accuracy of existing methods. The Harvest suite is open-source and freely available from:
Electronic supplementary material
The online version of this article (doi:10.1186/s13059-014-0524-x) contains supplementary material, which is available to authorized users.
PMCID: PMC4262987  PMID: 25410596
2.  Complete Genome Sequence of the Quality Control Strain Staphylococcus aureus subsp. aureus ATCC 25923 
Genome Announcements  2014;2(6):e01110-14.
Staphylococcus aureus subsp. aureus ATCC 25923 is commonly used as a control strain for susceptibility testing to antibiotics and as a quality control strain for commercial products. We present the completed genome sequence for the strain, consisting of the chromosome and a 27.5-kb plasmid.
PMCID: PMC4223452  PMID: 25377701
3.  Automated ensemble assembly and validation of microbial genomes 
BMC Bioinformatics  2014;15:126.
The continued democratization of DNA sequencing has sparked a new wave of development of genome assembly and assembly validation methods. As individual research labs, rather than centralized centers, begin to sequence the majority of new genomes, it is important to establish best practices for genome assembly. However, recent evaluations such as GAGE and the Assemblathon have concluded that there is no single best approach to genome assembly. Instead, it is preferable to generate multiple assemblies and validate them to determine which is most useful for the desired analysis; this is a labor-intensive process that is often impossible or unfeasible.
To encourage best practices supported by the community, we present iMetAMOS, an automated ensemble assembly pipeline; iMetAMOS encapsulates the process of running, validating, and selecting a single assembly from multiple assemblies. iMetAMOS packages several leading open-source tools into a single binary that automates parameter selection and execution of multiple assemblers, scores the resulting assemblies based on multiple validation metrics, and annotates the assemblies for genes and contaminants. We demonstrate the utility of the ensemble process on 225 previously unassembled Mycobacterium tuberculosis genomes as well as a Rhodobacter sphaeroides benchmark dataset. On these real data, iMetAMOS reliably produces validated assemblies and identifies potential contamination without user intervention. In addition, intelligent parameter selection produces assemblies of R. sphaeroides comparable to or exceeding the quality of those from the GAGE-B evaluation, affecting the relative ranking of some assemblers.
Ensemble assembly with iMetAMOS provides users with multiple, validated assemblies for each genome. Although computationally limited to small or mid-sized genomes, this approach is the most effective and reproducible means for generating high-quality assemblies and enables users to select an assembly best tailored to their specific needs.
PMCID: PMC4030574  PMID: 24884846
4.  Irreconcilable differences: divorcing geographic mutation and recombination rates within a global MRSA clone 
Genome Biology  2012;13(12):181.
A growing resource of methicillin-resistant Staphylococcus aureus (MRSA) genomes uncovers intriguing phylogeographic and recombination patterns and highlights challenges in identifying the source of these phenomena.
PMCID: PMC3580406  PMID: 23270611
5.  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:
PMCID: PMC4053804  PMID: 23320958
6.  Repetitive DNA and next-generation sequencing: computational challenges and solutions 
Nature Reviews. Genetics  2011;13(1):36-46.
Repetitive DNA sequences are abundant in a broad range of species, from bacteria to mammals, and they cover nearly half of the human genome. Repeats have always presented technical challenges for sequence alignment and assembly programs. Next-generation sequencing projects, with their short read lengths and high data volumes, have made these challenges more difficult. From a computational perspective, repeats create ambiguities in alignment and assembly, which, in turn, can produce biases and errors when interpreting results. Simply ignoring repeats is not an option, as this creates problems of its own and may mean that important biological phenomena are missed. We discuss the computational problems surrounding repeats and describe strategies used by current bioinformatics systems to solve them.
PMCID: PMC3324860  PMID: 22124482
7.  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.
PMCID: PMC3377744  PMID: 22699610
8.  Bambus 2: scaffolding metagenomes 
Bioinformatics  2011;27(21):2964-2971.
Motivation: Sequencing projects increasingly target samples from non-clonal sources. In particular, metagenomics has enabled scientists to begin to characterize the structure of microbial communities. The software tools developed for assembling and analyzing sequencing data for clonal organisms are, however, unable to adequately process data derived from non-clonal sources.
Results: We present a new scaffolder, Bambus 2, to address some of the challenges encountered when analyzing metagenomes. Our approach relies on a combination of a novel method for detecting genomic repeats and algorithms that analyze assembly graphs to identify biologically meaningful genomic variants. We compare our software to current assemblers using simulated and real data. We demonstrate that the repeat detection algorithms have higher sensitivity than current approaches without sacrificing specificity. In metagenomic datasets, the scaffolder avoids false joins between distantly related organisms while obtaining long-range contiguity. Bambus 2 represents a first step toward automated metagenomic assembly.
Availability: Bambus 2 is open source and available from
Supplementary Information: Supplementary data are available at Bioinformatics online.
PMCID: PMC3198580  PMID: 21926123
9.  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.
PMCID: PMC3366996  PMID: 22675498
10.  Next Generation Sequence Assembly with AMOS 
A Modular Open-Source Assembler (AMOS) was designed to offer a modular approach to genome assembly. AMOS includes a wide range of tools for assembly, including lightweight de novo assemblers Minimus and Minimo, and Bambus 2, a robust scaffolder able to handle metagenomic and polymorphic data. This protocol describes how to configure and use AMOS for the assembly of Next Generation sequence data. Additionally, we provide three tutorial examples that include bacterial, viral, and metagenomic datasets with specific tips for improving assembly quality.
PMCID: PMC3072823  PMID: 21400694
Next-generation sequencing; genome assembly; Open-Source
12.  Horizontal Transfer, Not Duplication, Drives the Expansion of Protein Families in Prokaryotes 
PLoS Genetics  2011;7(1):e1001284.
Gene duplication followed by neo- or sub-functionalization deeply impacts the evolution of protein families and is regarded as the main source of adaptive functional novelty in eukaryotes. While there is ample evidence of adaptive gene duplication in prokaryotes, it is not clear whether duplication outweighs the contribution of horizontal gene transfer in the expansion of protein families. We analyzed closely related prokaryote strains or species with small genomes (Helicobacter, Neisseria, Streptococcus, Sulfolobus), average-sized genomes (Bacillus, Enterobacteriaceae), and large genomes (Pseudomonas, Bradyrhizobiaceae) to untangle the effects of duplication and horizontal transfer. After removing the effects of transposable elements and phages, we show that the vast majority of expansions of protein families are due to transfer, even among large genomes. Transferred genes—xenologs—persist longer in prokaryotic lineages possibly due to a higher/longer adaptive role. On the other hand, duplicated genes—paralogs—are expressed more, and, when persistent, they evolve slower. This suggests that gene transfer and gene duplication have very different roles in shaping the evolution of biological systems: transfer allows the acquisition of new functions and duplication leads to higher gene dosage. Accordingly, we show that paralogs share most protein–protein interactions and genetic regulators, whereas xenologs share very few of them. Prokaryotes invented most of life's biochemical diversity. Therefore, the study of the evolution of biology systems should explicitly account for the predominant role of horizontal gene transfer in the diversification of protein families.
Author Summary
Prokaryotes can be found in the most diverse and severe ecological niches of the planet. Their rapid adaptation is, in part, the result of the ability to acquire genetic information horizontally. This means that prokaryotes utilize two major paths to expand their repertoire of protein families: they can duplicate a pre-existing gene or acquire it by horizontal transfer. In this study, we track family expansions among closely related strains of prokaryotic species. We find that the majority of gene expansions arrive via transfer not via duplication. Additionally, we find that duplicate genes tend be more transient and evolve slower than transferred ones, highlighting different roles with respect to adaptation and evolution. These results suggest that prevailing theories aimed at understanding the evolution of biological systems grounded on gene duplication might be poorly fit to explain the evolution of prokaryotic systems, which include the vast majority of life's biochemical diversity.
PMCID: PMC3029252  PMID: 21298028
13.  The impact of the neisserial DNA uptake sequences on genome evolution and stability 
Genome Biology  2008;9(3):R60.
A study of the origin and distribution of the abundant short DNA uptake sequence (DUS) in six genomes of Neisseria suggests that transformation and recombination are tightly linked in evolution and that recombination has a key role in the establishment of DUS.
Efficient natural transformation in Neisseria requires the presence of short DNA uptake sequences (DUSs). Doubts remain whether DUSs propagate by pure selfish molecular drive or are selected for 'safe sex' among conspecifics.
Six neisserial genomes were aligned to identify gene conversion fragments, DUS distribution, spacing, and conservation. We found a strong link between recombination and DUS: DUS spacing matches the size of conversion fragments; genomes with shorter conversion fragments have more DUSs and more conserved DUSs; and conversion fragments are enriched in DUSs. Many recent and singly occurring DUSs exhibit too high divergence with homologous sequences in other genomes to have arisen by point mutation, suggesting their appearance by recombination. DUSs are over-represented in the core genome, under-represented in regions under diversification, and absent in both recently acquired genes and recently lost core genes. This suggests that DUSs are implicated in genome stability rather than in generating adaptive variation. DUS elements are most frequent in the permissive locations of the core genome but are themselves highly conserved, undergoing mutation selection balance and/or molecular drive. Similar preliminary results were found for the functionally analogous uptake signal sequence in Pasteurellaceae.
As do many other pathogens, Neisseria and Pasteurellaceae have hyperdynamic genomes that generate deleterious mutations by intrachromosomal recombination and by transient hypermutation. The results presented here suggest that transformation in Neisseria and Pasteurellaceae allows them to counteract the deleterious effects of genome instability in the core genome. Thus, rather than promoting hypervariation, bacterial sex could be regenerative.
PMCID: PMC2397512  PMID: 18366792
14.  M-GCAT: interactively and efficiently constructing large-scale multiple genome comparison frameworks in closely related species 
BMC Bioinformatics  2006;7:433.
Due to recent advances in whole genome shotgun sequencing and assembly technologies, the financial cost of decoding an organism's DNA has been drastically reduced, resulting in a recent explosion of genomic sequencing projects. This increase in related genomic data will allow for in depth studies of evolution in closely related species through multiple whole genome comparisons.
To facilitate such comparisons, we present an interactive multiple genome comparison and alignment tool, M-GCAT, that can efficiently construct multiple genome comparison frameworks in closely related species. M-GCAT is able to compare and identify highly conserved regions in up to 20 closely related bacterial species in minutes on a standard computer, and as many as 90 (containing 75 cloned genomes from a set of 15 published enterobacterial genomes) in an hour. M-GCAT also incorporates a novel comparative genomics data visualization interface allowing the user to globally and locally examine and inspect the conserved regions and gene annotations.
M-GCAT is an interactive comparative genomics tool well suited for quickly generating multiple genome comparisons frameworks and alignments among closely related species. M-GCAT is freely available for download for academic and non-commercial use at: .
PMCID: PMC1629028  PMID: 17022809

Results 1-14 (14)