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1.  Genome sequence of the human malaria parasite Plasmodium falciparum 
Nature  2002;419(6906):10.1038/nature01097.
The parasite Plasmodium falciparum is responsible for hundreds of millions of cases of malaria, and kills more than one million African children annually. Here we report an analysis of the genome sequence of P. falciparum clone 3D7. The 23-megabase nuclear genome consists of 14 chromosomes, encodes about 5,300 genes, and is the most (A + T)-rich genome sequenced to date. Genes involved in antigenic variation are concentrated in the subtelomeric regions of the chromosomes. Compared to the genomes of free-living eukaryotic microbes, the genome of this intracellular parasite encodes fewer enzymes and transporters, but a large proportion of genes are devoted to immune evasion and host–parasite interactions. Many nuclear-encoded proteins are targeted to the apicoplast, an organelle involved in fatty-acid and isoprenoid metabolism. The genome sequence provides the foundation for future studies of this organism, and is being exploited in the search for new drugs and vaccines to fight malaria.
doi:10.1038/nature01097
PMCID: PMC3836256  PMID: 12368864
2.  MetaRef: a pan-genomic database for comparative and community microbial genomics 
Nucleic Acids Research  2013;42(D1):D617-D624.
Microbial genome sequencing is one of the longest-standing areas of biological database development, but high-throughput, low-cost technologies have increased its throughput to an unprecedented number of new genomes per year. Several thousand microbial genomes are now available, necessitating new approaches to organizing information on gene function, phylogeny and microbial taxonomy to facilitate downstream biological interpretation. MetaRef, available at http://metaref.org, is a novel online resource systematically cataloguing a comprehensive pan-genome of all microbial clades with sequenced isolates. It organizes currently available draft and finished bacterial and archaeal genomes into quality-controlled clades, reports all core and pan gene families at multiple levels in the resulting taxonomy, and it annotates families’ conservation, phylogeny and consensus functional information. MetaRef also provides a comprehensive non-redundant reference gene catalogue for metagenomic studies, including the abundance and prevalence of all gene families in the >700 shotgun metagenomic samples of the Human Microbiome Project. This constitutes a systematic mapping of clade-specific microbial functions within the healthy human microbiome across multiple body sites and can be used as reference for identifying potential functional biomarkers in disease-associate microbiomes. MetaRef provides all information both as an online browsable resource and as downloadable sequences and tabular data files that can be used for subsequent offline studies.
doi:10.1093/nar/gkt1078
PMCID: PMC3964974  PMID: 24203705
3.  Sequencing of Culex quinquefasciatus establishes a platform for mosquito comparative genomics 
Arensburger, Peter | Megy, Karine | Waterhouse, Robert M. | Abrudan, Jenica | Amedeo, Paolo | Antelo, Beatriz | Bartholomay, Lyric | Bidwell, Shelby | Caler, Elisabet | Camara, Francisco | Campbell, Corey L. | Campbell, Kathryn S. | Casola, Claudio | Castro, Marta T. | Chandramouliswaran, Ishwar | Chapman, Sinéad B. | Christley, Scott | Costas, Javier | Eisenstadt, Eric | Feshotte, Cedric | Fraser-Liggett, Claire | Guigo, Roderic | Haas, Brian | Hammond, Martin | Hansson, Bill S. | Hemingway, Janet | Hill, Sharon | Howarth, Clint | Ignell, Rickard | Kennedy, Ryan C. | Kodira, Chinnappa D. | Lobo, Neil F. | Mao, Chunhong | Mayhew, George | Michel, Kristin | Mori, Akio | Liu, Nannan | Naveira, Horacio | Nene, Vishvanath | Nguyen, Nam | Pearson, Matthew D. | Pritham, Ellen J. | Puiu, Daniela | Qi, Yumin | Ranson, Hilary | Ribeiro, Jose M. C. | Roberston, Hugh M. | Severson, David W. | Shumway, Martin | Stanke, Mario | Strausberg, Robert | Sun, Cheng | Sutton, Granger | Tu, Zhijian (Jake) | Tubio, Jose Manuel C. | Unger, Maria F. | Vanlandingham, Dana L. | Vilella, Albert J. | White, Owen | White, Jared R. | Wondji, Charles S. | Wortman, Jennifer | Zdobnov, Evgeny M. | Birren, Bruce | Christensen, Bruce M. | Collins, Frank H. | Cornel, Anthony | Dimopoulos, George | Hannick, Linda I. | Higgs, Stephen | Lanzaro, Gregory C. | Lawson, Daniel | Lee, Norman H. | Muskavitch, Marc A. T. | Raikhel, Alexander S. | Atkinson, Peter W.
Science (New York, N.Y.)  2010;330(6000):86-88.
Culex quinquefasciatus (the Southern house mosquito) is an important mosquito vector of viruses such as West Nile virus and St. Louis encephalitis virus as well of nematodes that cause lymphatic filariasis. It is one species within the Culex pipiens species complex and enjoys a distribution throughout tropical and temperate climates of the world. The ability of C. quinquefasciatus to take blood meals from birds, livestock and humans contributes to its ability to vector pathogens between species. We describe the genomic sequence of C. quinquefasciatus, its repertoire of 18,883 protein-coding genes is 22% larger than Ae. aegypti and 52% larger than An. gambiae with multiple gene family expansions including olfactory and gustatory receptors, salivary gland genes, and genes associated with xenobiotic detoxification.
doi:10.1126/science.1191864
PMCID: PMC3740384  PMID: 20929810
4.  CloVR-ITS: Automated internal transcribed spacer amplicon sequence analysis pipeline for the characterization of fungal microbiota 
Microbiome  2013;1:6.
Background
Besides the development of comprehensive tools for high-throughput 16S ribosomal RNA amplicon sequence analysis, there exists a growing need for protocols emphasizing alternative phylogenetic markers such as those representing eukaryotic organisms.
Results
Here we introduce CloVR-ITS, an automated pipeline for comparative analysis of internal transcribed spacer (ITS) pyrosequences amplified from metagenomic DNA isolates and representing fungal species. This pipeline performs a variety of steps similar to those commonly used for 16S rRNA amplicon sequence analysis, including preprocessing for quality, chimera detection, clustering of sequences into operational taxonomic units (OTUs), taxonomic assignment (at class, order, family, genus, and species levels) and statistical analysis of sample groups of interest based on user-provided information. Using ITS amplicon pyrosequencing data from a previous human gastric fluid study, we demonstrate the utility of CloVR-ITS for fungal microbiota analysis and provide runtime and cost examples, including analysis of extremely large datasets on the cloud. We show that the largest fractions of reads from the stomach fluid samples were assigned to Dothideomycetes, Saccharomycetes, Agaricomycetes and Sordariomycetes but that all samples were dominated by sequences that could not be taxonomically classified. Representatives of the Candida genus were identified in all samples, most notably C. quercitrusa, while sequence reads assigned to the Aspergillus genus were only identified in a subset of samples. CloVR-ITS is made available as a pre-installed, automated, and portable software pipeline for cloud-friendly execution as part of the CloVR virtual machine package (http://clovr.org).
Conclusion
The CloVR-ITS pipeline provides fungal microbiota analysis that can be complementary to bacterial 16S rRNA and total metagenome sequence analysis allowing for more comprehensive studies of environmental and host-associated microbial communities.
doi:10.1186/2049-2618-1-6
PMCID: PMC3869194  PMID: 24451270
Internal transcribed spacer (ITS); Fungal microbiota; Automated sequence analysis pipeline; Cloud computing
5.  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
6.  The Human Microbiome Project: A Community Resource for the Healthy Human Microbiome 
PLoS Biology  2012;10(8):e1001377.
This manuscript describes the NIH Human Microbiome Project, including a brief review of human microbiome research, a history of the project, and a comprehensive overview of the consortium's recent collection of publications analyzing the human microbiome.
doi:10.1371/journal.pbio.1001377
PMCID: PMC3419203  PMID: 22904687
7.  The Metadata Coverage Index (MCI): A standardized metric for quantifying database metadata richness 
Standards in Genomic Sciences  2012;6(3):438-447.
Variability in the extent of the descriptions of data (‘metadata’) held in public repositories forces users to assess the quality of records individually, which rapidly becomes impractical. The scoring of records on the richness of their description provides a simple, objective proxy measure for quality that enables filtering that supports downstream analysis. Pivotally, such descriptions should spur on improvements. Here, we introduce such a measure - the ‘Metadata Coverage Index’ (MCI): the percentage of available fields actually filled in a record or description. MCI scores can be calculated across a database, for individual records or for their component parts (e.g., fields of interest). There are many potential uses for this simple metric: for example; to filter, rank or search for records; to assess the metadata availability of an ad hoc collection; to determine the frequency with which fields in a particular record type are filled, especially with respect to standards compliance; to assess the utility of specific tools and resources, and of data capture practice more generally; to prioritize records for further curation; to serve as performance metrics of funded projects; or to quantify the value added by curation. Here we demonstrate the utility of MCI scores using metadata from the Genomes Online Database (GOLD), including records compliant with the ‘Minimum Information about a Genome Sequence’ (MIGS) standard developed by the Genomic Standards Consortium. We discuss challenges and address the further application of MCI scores; to show improvements in annotation quality over time, to inform the work of standards bodies and repository providers on the usability and popularity of their products, and to assess and credit the work of curators. Such an index provides a step towards putting metadata capture practices and in the future, standards compliance, into a quantitative and objective framework.
doi:10.4056/sigs.2675953
PMCID: PMC3558968  PMID: 23409217
8.  Metabolic Reconstruction for Metagenomic Data and Its Application to the Human Microbiome 
PLoS Computational Biology  2012;8(6):e1002358.
Microbial communities carry out the majority of the biochemical activity on the planet, and they play integral roles in processes including metabolism and immune homeostasis in the human microbiome. Shotgun sequencing of such communities' metagenomes provides information complementary to organismal abundances from taxonomic markers, but the resulting data typically comprise short reads from hundreds of different organisms and are at best challenging to assemble comparably to single-organism genomes. Here, we describe an alternative approach to infer the functional and metabolic potential of a microbial community metagenome. We determined the gene families and pathways present or absent within a community, as well as their relative abundances, directly from short sequence reads. We validated this methodology using a collection of synthetic metagenomes, recovering the presence and abundance both of large pathways and of small functional modules with high accuracy. We subsequently applied this method, HUMAnN, to the microbial communities of 649 metagenomes drawn from seven primary body sites on 102 individuals as part of the Human Microbiome Project (HMP). This provided a means to compare functional diversity and organismal ecology in the human microbiome, and we determined a core of 24 ubiquitously present modules. Core pathways were often implemented by different enzyme families within different body sites, and 168 functional modules and 196 metabolic pathways varied in metagenomic abundance specifically to one or more niches within the microbiome. These included glycosaminoglycan degradation in the gut, as well as phosphate and amino acid transport linked to host phenotype (vaginal pH) in the posterior fornix. An implementation of our methodology is available at http://huttenhower.sph.harvard.edu/humann. This provides a means to accurately and efficiently characterize microbial metabolic pathways and functional modules directly from high-throughput sequencing reads, enabling the determination of community roles in the HMP cohort and in future metagenomic studies.
Author Summary
The human body is inhabited by trillions of bacteria and other microbes, which have recently been studied in many different habitats (including gut, mouth, skin, and urogenital) by the Human Microbiome Project (HMP). These microbial communities were assayed using high-throughput DNA sequencing, but it can be challenging to determine their biological functions based solely on the resulting short sequences. To reconstruct the metabolic activities of such communities, we have developed HUMAnN, a method to accurately infer community function directly from short DNA reads. The method's accuracy was validated using a collection of synthetic microbial communities. Applying HUMAnN to data from the HMP, we showed that, unlike individual microbial species, many metabolic processes were present among all body habitats. However, the frequencies of these processes varied dramatically, and some were highly enriched within individual habitats to provide niche specialization (e.g. in the gut, which is abundant in food matter but low in oxygen). Other community functions were linked specifically to properties of the human host, such as biochemical processes only present in vaginal habitats with particularly high or low pH. Studying additional environmental or disease-associated communities using HUMAnN will further improve our understanding of how the microbial organisms in a community are linked to the biological processes they carry out.
doi:10.1371/journal.pcbi.1002358
PMCID: PMC3374609  PMID: 22719234
9.  Minimum information about a marker gene sequence (MIMARKS) and minimum information about any (x) sequence (MIxS) specifications 
Yilmaz, Pelin | Kottmann, Renzo | Field, Dawn | Knight, Rob | Cole, James R | Amaral-Zettler, Linda | Gilbert, Jack A | Karsch-Mizrachi, Ilene | Johnston, Anjanette | Cochrane, Guy | Vaughan, Robert | Hunter, Christopher | Park, Joonhong | Morrison, Norman | Rocca-Serra, Philippe | Sterk, Peter | Arumugam, Manimozhiyan | Bailey, Mark | Baumgartner, Laura | Birren, Bruce W | Blaser, Martin J | Bonazzi, Vivien | Booth, Tim | Bork, Peer | Bushman, Frederic D | Buttigieg, Pier Luigi | Chain, Patrick S G | Charlson, Emily | Costello, Elizabeth K | Huot-Creasy, Heather | Dawyndt, Peter | DeSantis, Todd | Fierer, Noah | Fuhrman, Jed A | Gallery, Rachel E | Gevers, Dirk | Gibbs, Richard A | Gil, Inigo San | Gonzalez, Antonio | Gordon, Jeffrey I | Guralnick, Robert | Hankeln, Wolfgang | Highlander, Sarah | Hugenholtz, Philip | Jansson, Janet | Kau, Andrew L | Kelley, Scott T | Kennedy, Jerry | Knights, Dan | Koren, Omry | Kuczynski, Justin | Kyrpides, Nikos | Larsen, Robert | Lauber, Christian L | Legg, Teresa | Ley, Ruth E | Lozupone, Catherine A | Ludwig, Wolfgang | Lyons, Donna | Maguire, Eamonn | Methé, Barbara A | Meyer, Folker | Muegge, Brian | Nakielny, Sara | Nelson, Karen E | Nemergut, Diana | Neufeld, Josh D | Newbold, Lindsay K | Oliver, Anna E | Pace, Norman R | Palanisamy, Giriprakash | Peplies, Jörg | Petrosino, Joseph | Proctor, Lita | Pruesse, Elmar | Quast, Christian | Raes, Jeroen | Ratnasingham, Sujeevan | Ravel, Jacques | Relman, David A | Assunta-Sansone, Susanna | Schloss, Patrick D | Schriml, Lynn | Sinha, Rohini | Smith, Michelle I | Sodergren, Erica | Spor, Aymé | Stombaugh, Jesse | Tiedje, James M | Ward, Doyle V | Weinstock, George M | Wendel, Doug | White, Owen | Whiteley, Andrew | Wilke, Andreas | Wortman, Jennifer R | Yatsunenko, Tanya | Glöckner, Frank Oliver
Nature Biotechnology  2011;29(5):415-420.
Here we present a standard developed by the Genomic Standards Consortium (GSC) for reporting marker gene sequences—the minimum information about a marker gene sequence (MIMARKS). We also introduce a system for describing the environment from which a biological sample originates. The ‘environmental packages’ apply to any genome sequence of known origin and can be used in combination with MIMARKS and other GSC checklists. Finally, to establish a unified standard for describing sequence data and to provide a single point of entry for the scientific community to access and learn about GSC checklists, we present the minimum information about any (x) sequence (MIxS). Adoption of MIxS will enhance our ability to analyze natural genetic diversity documented by massive DNA sequencing efforts from myriad ecosystems in our ever-changing biosphere.
doi:10.1038/nbt.1823
PMCID: PMC3367316  PMID: 21552244
10.  Conceptualizing a Genomics Software Institute (GSI) 
Standards in Genomic Sciences  2012;6(1):136-144.
Microbial ecology has been enhanced greatly by the ongoing ‘omics revolution, bringing half the world's biomass and most of its biodiversity into analytical view for the first time; indeed, it feels almost like the invention of the microscope and the discovery of the new world at the same time. With major microbial ecology research efforts accumulating prodigious quantities of sequence, protein, and metabolite data, we are now poised to address environmental microbial research at macro scales, and to begin to characterize and understand the dimensions of microbial biodiversity on the planet. What is currently impeding progress is the need for a framework within which the research community can develop, exchange and discuss predictive ecosystem models that describe the biodiversity and functional interactions. Such a framework must encompass data and metadata transparency and interoperation; data and results validation, curation, and search; application programming interfaces for modeling and analysis tools; and human and technical processes and services necessary to ensure broad adoption. Here we discuss the need for focused community interaction to augment and deepen established community efforts, beginning with the Genomic Standards Consortium (GSC), to create a science-driven strategic plan for a Genomic Software Institute (GSI).
doi:10.4056/sigs.2485911
PMCID: PMC3359878  PMID: 22675605
11.  Longitudinal Assessment of Antisaccades in Patients with Multiple Sclerosis 
PLoS ONE  2012;7(2):e30475.
We have previously demonstrated that assessment of antisaccades (AS) provides not only measures of motor function in multiple sclerosis (MS), but measures of cognitive control processes in particular, attention and working memory. This study sought to demonstrate the potential for AS measures to sensitively reflect change in functional status in MS. Twenty-four patients with relapsing-remitting MS and 12 age-matched controls were evaluated longitudinally using an AS saccade task. Compared to control subjects, a number of saccade parameters changed significantly over a two year period for MS patients. These included saccade error rates, latencies, and accuracy measures. Further, for MS patients, correlations were retained between OM measures and scores on the PASAT, which is considered the reference task for the cognitive evaluation of MS patients. Notably, EDSS scores for these patients did not change significantly over this period. These results demonstrate that OM measures may reflect disease evolution in MS, in the absence of clinically evident changes as measured using conventional techniques. With replication, these markers could ultimately be developed into a cost-effective, non-invasive, and well tolerated assessment tool to assist in confirming progression early in the disease process, and in measuring and predicting response to therapy.
doi:10.1371/journal.pone.0030475
PMCID: PMC3271102  PMID: 22319570
12.  A closer look at visually guided saccades in autism and Asperger’s disorder 
Motor impairments have been found to be a significant clinical feature associated with autism and Asperger’s disorder (AD) in addition to core symptoms of communication and social cognition deficits. Motor deficits in high-functioning autism (HFA) and AD may differentiate these disorders, particularly with respect to the role of the cerebellum in motor functioning. Current neuroimaging and behavioral evidence suggests greater disruption of the cerebellum in HFA than AD. Investigations of ocular motor functioning have previously been used in clinical populations to assess the integrity of the cerebellar networks, through examination of saccade accuracy and the integrity of saccade dynamics. Previous investigations of visually guided saccades in HFA and AD have only assessed basic saccade metrics, such as latency, amplitude, and gain, as well as peak velocity. We used a simple visually guided saccade paradigm to further characterize the profile of visually guided saccade metrics and dynamics in HFA and AD. It was found that children with HFA, but not AD, were more inaccurate across both small (5°) and large (10°) target amplitudes, and final eye position was hypometric at 10°. These findings suggest greater functional disturbance of the cerebellum in HFA than AD, and suggest fundamental difficulties with visual error monitoring in HFA.
doi:10.3389/fnint.2012.00099
PMCID: PMC3491344  PMID: 23162442
autism; Asperger’s disorder; saccades; eye movements; Verbal Comprehension Index
13.  Resources and Costs for Microbial Sequence Analysis Evaluated Using Virtual Machines and Cloud Computing 
PLoS ONE  2011;6(10):e26624.
Background
The widespread popularity of genomic applications is threatened by the “bioinformatics bottleneck” resulting from uncertainty about the cost and infrastructure needed to meet increasing demands for next-generation sequence analysis. Cloud computing services have been discussed as potential new bioinformatics support systems but have not been evaluated thoroughly.
Results
We present benchmark costs and runtimes for common microbial genomics applications, including 16S rRNA analysis, microbial whole-genome shotgun (WGS) sequence assembly and annotation, WGS metagenomics and large-scale BLAST. Sequence dataset types and sizes were selected to correspond to outputs typically generated by small- to midsize facilities equipped with 454 and Illumina platforms, except for WGS metagenomics where sampling of Illumina data was used. Automated analysis pipelines, as implemented in the CloVR virtual machine, were used in order to guarantee transparency, reproducibility and portability across different operating systems, including the commercial Amazon Elastic Compute Cloud (EC2), which was used to attach real dollar costs to each analysis type. We found considerable differences in computational requirements, runtimes and costs associated with different microbial genomics applications. While all 16S analyses completed on a single-CPU desktop in under three hours, microbial genome and metagenome analyses utilized multi-CPU support of up to 120 CPUs on Amazon EC2, where each analysis completed in under 24 hours for less than $60. Representative datasets were used to estimate maximum data throughput on different cluster sizes and to compare costs between EC2 and comparable local grid servers.
Conclusions
Although bioinformatics requirements for microbial genomics depend on dataset characteristics and the analysis protocols applied, our results suggests that smaller sequencing facilities (up to three Roche/454 or one Illumina GAIIx sequencer) invested in 16S rRNA amplicon sequencing, microbial single-genome and metagenomics WGS projects can achieve cost-efficient bioinformatics support using CloVR in combination with Amazon EC2 as an alternative to local computing centers.
doi:10.1371/journal.pone.0026624
PMCID: PMC3197577  PMID: 22028928
14.  Solving the Problem: Genome Annotation Standards before the Data Deluge 
Standards in Genomic Sciences  2011;5(1):168-193.
The promise of genome sequencing was that the vast undiscovered country would be mapped out by comparison of the multitude of sequences available and would aid researchers in deciphering the role of each gene in every organism. Researchers recognize that there is a need for high quality data. However, different annotation procedures, numerous databases, and a diminishing percentage of experimentally determined gene functions have resulted in a spectrum of annotation quality. NCBI in collaboration with sequencing centers, archival databases, and researchers, has developed the first international annotation standards, a fundamental step in ensuring that high quality complete prokaryotic genomes are available as gold standard references. Highlights include the development of annotation assessment tools, community acceptance of protein naming standards, comparison of annotation resources to provide consistent annotation, and improved tracking of the evidence used to generate a particular annotation. The development of a set of minimal standards, including the requirement for annotated complete prokaryotic genomes to contain a full set of ribosomal RNAs, transfer RNAs, and proteins encoding core conserved functions, is an historic milestone. The use of these standards in existing genomes and future submissions will increase the quality of databases, enabling researchers to make accurate biological discoveries.
doi:10.4056/sigs.2084864
PMCID: PMC3236044  PMID: 22180819
16.  CloVR: A virtual machine for automated and portable sequence analysis from the desktop using cloud computing 
BMC Bioinformatics  2011;12:356.
Background
Next-generation sequencing technologies have decentralized sequence acquisition, increasing the demand for new bioinformatics tools that are easy to use, portable across multiple platforms, and scalable for high-throughput applications. Cloud computing platforms provide on-demand access to computing infrastructure over the Internet and can be used in combination with custom built virtual machines to distribute pre-packaged with pre-configured software.
Results
We describe the Cloud Virtual Resource, CloVR, a new desktop application for push-button automated sequence analysis that can utilize cloud computing resources. CloVR is implemented as a single portable virtual machine (VM) that provides several automated analysis pipelines for microbial genomics, including 16S, whole genome and metagenome sequence analysis. The CloVR VM runs on a personal computer, utilizes local computer resources and requires minimal installation, addressing key challenges in deploying bioinformatics workflows. In addition CloVR supports use of remote cloud computing resources to improve performance for large-scale sequence processing. In a case study, we demonstrate the use of CloVR to automatically process next-generation sequencing data on multiple cloud computing platforms.
Conclusion
The CloVR VM and associated architecture lowers the barrier of entry for utilizing complex analysis protocols on both local single- and multi-core computers and cloud systems for high throughput data processing.
doi:10.1186/1471-2105-12-356
PMCID: PMC3228541  PMID: 21878105
17.  The Genomic Standards Consortium 
PLoS Biology  2011;9(6):e1001088.
A vast and rich body of information has grown up as a result of the world's enthusiasm for 'omics technologies. Finding ways to describe and make available this information that maximise its usefulness has become a major effort across the 'omics world. At the heart of this effort is the Genomic Standards Consortium (GSC), an open-membership organization that drives community-based standardization activities, Here we provide a short history of the GSC, provide an overview of its range of current activities, and make a call for the scientific community to join forces to improve the quality and quantity of contextual information about our public collections of genomes, metagenomes, and marker gene sequences.
doi:10.1371/journal.pbio.1001088
PMCID: PMC3119656  PMID: 21713030
18.  The IGS Standard Operating Procedure for Automated Prokaryotic Annotation 
Standards in Genomic Sciences  2011;4(2):244-251.
The Institute for Genome Sciences (IGS) has developed a prokaryotic annotation pipeline that is used for coding gene/RNA prediction and functional annotation of Bacteria and Archaea. The fully automated pipeline accepts one or many genomic sequences as input and produces output in a variety of standard formats. Functional annotation is primarily based on similarity searches and motif finding combined with a hierarchical rule based annotation system. The output annotations can also be loaded into a relational database and accessed through visualization tools.
doi:10.4056/sigs.1223234
PMCID: PMC3111993  PMID: 21677861
Institute for Genome Sciences; functional annotation; structural annotation; microbial genomics; prokaryotic genomics; annotation pipeline; pFunc; Glimmer; HMM; BER; Ergatis; Manatee; IGS Annotation Engine
19.  Towards BioDBcore: a community-defined information specification for biological databases 
The present article proposes the adoption of a community-defined, uniform, generic description of the core attributes of biological databases, BioDBCore. The goals of these attributes are to provide a general overview of the database landscape, to encourage consistency and interoperability between resources; and to promote the use of semantic and syntactic standards. BioDBCore will make it easier for users to evaluate the scope and relevance of available resources. This new resource will increase the collective impact of the information present in biological databases.
doi:10.1093/database/baq027
PMCID: PMC3017395  PMID: 21205783
20.  Meeting Report from the Genomic Standards Consortium (GSC) Workshop 10 
Standards in Genomic Sciences  2010;3(3):225-231.
This report summarizes the proceedings of the 10th workshop of the Genomic Standards Consortium (GSC), held at Argonne National Laboratory, IL, USA. It was the second GSC workshop to have open registration and attracted over 60 participants who worked together to progress the full range of projects ongoing within the GSC. Overall, the primary focus of the workshop was on advancing the M5 platform for next-generation collaborative computational infrastructures. Other key outcomes included the formation of a GSC working group focused on MIGS/MIMS/MIENS compliance using the ISA software suite and the formal launch of the GSC Developer Working Group. Further information about the GSC and its range of activities can be found at http://gensc.org/.
doi:10.4056/sigs.1423520
PMCID: PMC3035307  PMID: 21304723
21.  Meeting Report: Metagenomics, Metadata and MetaAnalysis (M3) at ISMB 2010 
Standards in Genomic Sciences  2010;3(3):232-234.
This report summarizes the proceedings of the first day of the Metagenomics, Metadata and MetaAnalysis (M3) workshop held at the Intelligent Systems for Molecular Biology 2010 conference. The second day, which was dedicated to the inaugural meeting of the BioSharing initiative is presented in a separate report. The Genomic Standards Consortium (GSC) hosted the first day of this Special Interest Group (SIG) at ISMB to continue exploring the bottlenecks and emerging solutions for obtaining biological insights through large-scale comparative analysis of metagenomic datasets. The M3 SIG included invited and selected talks and a panel discussion at the end of the day involving the plenary speakers. Further information about the GSC and its range of activities can be found at http://gensc.org. Information about the newly established BioSharing effort can be found at http://biosharing.org/.
doi:10.4056/sigs.1383476
PMCID: PMC3035302  PMID: 21304724
22.  Meeting Report: BioSharing at ISMB 2010 
Standards in Genomic Sciences  2010;3(3):254-258.
This report summarizes the proceedings of the one day BioSharing meeting held at the Intelligent Systems for Molecular Biology (ISMB) 2010 conference in Boston, MA, USA This inaugural BioSharing event was hosted by the Genomic Standards Consortium as part of its M3 & BioSharing special interest group (SIG) workshop. The BioSharing event included invited talks from a range of community leaders and a panel discussion at the end of the day. The panel session led to the formal agreement among community leaders to join together to promote cross-community knowledge exchange and collaborations. A key focus of the newly formed Biosharing community will be linking up resources to promote real-world data sharing (virtuous cycle of data) and supporting compliance with data policies through the creation of a one-stop-portal of information. Further information about the newly established BioSharing effort can be found at http://biosharing.org.
doi:10.4056/sigs/1403501
PMCID: PMC3035313  PMID: 21304729
23.  Meeting Report: Towards a Critical Assessment of Functional Annotation Experiment (CAFAE) for bacterial genome annotation 
Standards in Genomic Sciences  2010;3(3):240-242.
It is widely recognized that, with the advent of very high throughput, short read, and highly parallelized sequencing technologies, the generation of new DNA sequences from microbes, plants, metagenomes is outpacing the ability to assign functions to (“annotate”) all this data. To begin to try to address this, on May 18 and 19, 2010, a team of roughly fifty people met to define and scope the possibility of a first Critical Assessment of Functional Annotation Experiment (CAFAE) for bacterial genome annotation in Crystal City, Virginia. Due to the fundamental importance of genomic data to its mission, the Department of Energy (DOE) BER program hosted this workshop, funding the attendance of all invitees. The workshop was co-organized by Dan Drell and Susan Gregurick (DOE), Owen White and Nikos Kyripides.
doi:10.4056/sigs.1323436
PMCID: PMC3035297  PMID: 21304726
24.  Towards BioDBcore: a community-defined information specification for biological databases 
Nucleic Acids Research  2010;39(Database issue):D7-D10.
The present article proposes the adoption of a community-defined, uniform, generic description of the core attributes of biological databases, BioDBCore. The goals of these attributes are to provide a general overview of the database landscape, to encourage consistency and interoperability between resources and to promote the use of semantic and syntactic standards. BioDBCore will make it easier for users to evaluate the scope and relevance of available resources. This new resource will increase the collective impact of the information present in biological databases.
doi:10.1093/nar/gkq1173
PMCID: PMC3013734  PMID: 21097465

Results 1-25 (60)