Karin A. Remington

The Sorcerer II Global Ocean Sampling Expedition: Northwest Atlantic through Eastern Tropical Pacific

The worlds oceans contain a complex mixture of micro-organisms that are for the most part, uncharacterized both genetically and biochemically. We report here a metagenomic study of the marine planktonic microbiota in which surface (mostly marine) water samples were analyzed as part of the Sorcerer II Global Ocean Sampling expedition. These samples, collected across a several-thousand km transect from the North Atlantic through the Panama Canal and ending in the South Pacific yielded an extensive dataset consisting of 7.7 million sequencing reads (6.3 billion bp). Though a few major microbial clades dominate the planktonic marine niche, the dataset contains great diversity with 85% of the assembled sequence and 57% of the unassembled data being unique at a 98% sequence identity cutoff. Using the metadata associated with each sample and sequencing library, we developed new comparative genomic and assembly methods. One comparative genomic method, termed “fragment recruitment,” addressed questions of genome structure, evolution, and taxonomic or phylogenetic diversity, as well as the biochemical diversity of genes and gene families. A second method, termed “extreme assembly,” made possible the assembly and reconstruction of large segments of abundant but clearly nonclonal organisms. Within all abundant populations analyzed, we found extensive intra-ribotype diversity in several forms: (1) extensive sequence variation within orthologous regions throughout a given genome; despite coverage of individual ribotypes approaching 500-fold, most individual sequencing reads are unique; (2) numerous changes in gene content some with direct adaptive implications; and (3) hypervariable genomic islands that are too variable to assemble. The intra-ribotype diversity is organized into genetically isolated populations that have overlapping but independent distributions, implying distinct environmental preference. We present novel methods for measuring the genomic similarity between metagenomic samples and show how they may be grouped into several community types. Specific functional adaptations can be identified both within individual ribotypes and across the entire community, including proteorhodopsin spectral tuning and the presence or absence of the phosphate-binding gene PstS.

The Diploid Genome Sequence of an Individual Human

Presented here is a genome sequence of an individual human. It was produced from ∼32 million random DNA fragments, sequenced by Sanger dideoxy technology and assembled into 4,528 scaffolds, comprising 2,810 million bases (Mb) of contiguous sequence with approximately 7.5-fold coverage for any given region. We developed a modified version of the Celera assembler to facilitate the identification and comparison of alternate alleles within this individual diploid genome. Comparison of this genome and the National Center for Biotechnology Information human reference assembly revealed more than 4.1 million DNA variants, encompassing 12.3 Mb. These variants (of which 1,288,319 were novel) included 3,213,401 single nucleotide polymorphisms (SNPs), 53,823 block substitutions (2–206 bp), 292,102 heterozygous insertion/deletion events (indels)(1–571 bp), 559,473 homozygous indels (1–82,711 bp), 90 inversions, as well as numerous segmental duplications and copy number variation regions. Non-SNP DNA variation accounts for 22% of all events identified in the donor, however they involve 74% of all variant bases. This suggests an important role for non-SNP genetic alterations in defining the diploid genome structure. Moreover, 44% of genes were heterozygous for one or more variants. Using a novel haplotype assembly strategy, we were able to span 1.5 Gb of genome sequence in segments >200 kb, providing further precision to the diploid nature of the genome. These data depict a definitive molecular portrait of a diploid human genome that provides a starting point for future genome comparisons and enables an era of individualized genomic information.

The Sorcerer II Global Ocean Sampling Expedition: Expanding the Universe of Protein Families

Metagenomics projects based on shotgun sequencing of populations of micro-organisms yield insight into protein families. We used sequence similarity clustering to explore proteins with a comprehensive dataset consisting of sequences from available databases together with 6.12 million proteins predicted from an assembly of 7.7 million Global Ocean Sampling (GOS) sequences. The GOS dataset covers nearly all known prokaryotic protein families. A total of 3,995 medium- and large-sized clusters consisting of only GOS sequences are identified, out of which 1,700 have no detectable homology to known families. The GOS-only clusters contain a higher than expected proportion of sequences of viral origin, thus reflecting a poor sampling of viral diversity until now. Protein domain distributions in the GOS dataset and current protein databases show distinct biases. Several protein domains that were previously categorized as kingdom specific are shown to have GOS examples in other kingdoms. About 6,000 sequences (ORFans) from the literature that heretofore lacked similarity to known proteins have matches in the GOS data. The GOS dataset is also used to improve remote homology detection. Overall, besides nearly doubling the number of current proteins, the predicted GOS proteins also add a great deal of diversity to known protein families and shed light on their evolution. These observations are illustrated using several protein families, including phosphatases, proteases, ultraviolet-irradiation DNA damage repair enzymes, glutamine synthetase, and RuBisCO. The diversity added by GOS data has implications for choosing targets for experimental structure characterization as part of structural genomics efforts. Our analysis indicates that new families are being discovered at a rate that is linear or almost linear with the addition of new sequences, implying that we are still far from discovering all protein families in nature.

Whole-genome shotgun assembly and comparison of human genome assemblies

We report a whole-genome shotgun assembly (called WGSA) of the human genome generated at Celera in 2001. The Celera-generated shotgun data set consisted of 27 million sequencing reads organized in pairs by virtue of end-sequencing 2-kbp, 10-kbp, and 50-kbp inserts from shotgun clone libraries. The quality-trimmed reads covered the genome 5.3 times, and the inserts from which pairs of reads were obtained covered the genome 39 times. With the nearly complete human DNA sequence [National Center for Biotechnology Information (NCBI) Build 34] now available, it is possible to directly assess the quality, accuracy, and completeness of WGSA and of the first reconstructions of the human genome reported in two landmark papers in February 2001 [Venter, J. C., Adams, M. D., Myers, E. W., Li, P. W., Mural, R. J., Sutton, G. G., Smith, H. O., Yandell, M., Evans, C. A., Holt, R. A., et al. (2001) Science 291, 1304–1351; International Human Genome Sequencing Consortium (2001) Nature 409, 860–921]. The analysis of WGSA shows 97% order and orientation agreement with NCBI Build 34, where most of the 3% of sequence out of order is due to scaffold placement problems as opposed to assembly errors within the scaffolds themselves. In addition, WGSA fills some of the remaining gaps in NCBI Build 34. The early genome sequences all covered about the same amount of the genome, but they did so in different ways. The Celera results provide more order and orientation, and the consortium sequence provides better coverage of exact and nearly exact repeats.

Massive parallelism, randomness and genomic advances

In reviewing the past decade, it is clear that genomics was, and still is, driven by innovative technologies, perhaps more so than any other scientific area in recent memory. From the outset, computing, mathematics and new automated laboratory techniques have been key components in allowing the field to move forward rapidly. We highlight some key innovations that have come together to nurture the explosive growth that makes a new era of genomics a reality. We also document how these new approaches have fueled further innovations and discoveries.

Visualization challenges for a new cyber-pharmaceutical computing paradigm

Celera has encountered a number of visualization problems in the course of developing tools for bioinformatics research, applying them to our data generation efforts, and making that data available to our customers. This paper presents several examples from Celeras experience. In the area of genomics, challenging visualization problems have come up in assembling genomes, studying variations between individuals, and comparing different genomes to one another. The emerging area of proteomics has created new visualization challenges in interpreting protein expression data, studying protein regulatory networks, and examining protein structure. These examples illustrate how the field of bioinformatics is posing new challenges concerning the communication of data that are often very different from those that have heretofore dominated scientific computing. Addressing the level of detail, the degree of complexity, and the interdisciplinary barriers that characterize bioinformatic problems can be expected to be a sizable but rewarding task for the field of scientific visualization.

EXPLORING THE OCEAN'S MICROBES: SEQUENCING THE SEVEN SEAS

Marvin E. Frazier,Douglas B. Rusch, Aaron L. Halpern, Karla B. Heidelberg, Granger Sutton, Shannon Williamson, Shibu Yooseph, Dongying Wu, Jonathan A. Eisen, Jeff Hoffman, Charles H. Howard, Cyrus Foote, Brooke A. Dill, Karin Remington, Karen Beeson, Bao Tran, Hamilton Smith, Holly Baden-Tillson, Clare Stewart, Joyce Thorpe, Jason Freemen, Cindy Pfannkoch, Joseph E. Venter, John Heidelberg, Terry Utterback, Yu-Hui Rogers, Shaojie Zhang, Vineet Bafna, Luisa Falcon, Valeria Souza,German Bonilla, Luis E. Eguiarte , David M. Karl, Ken Nealson, Shubha Sathyendranath, Trevor Platt, Eldredge Bermingham, Victor Gallardo, Giselle Tamayo, Robert Friedman, Robert Strausberg, J. Craig Venter 1 J. Craig Venter Institute, Rockville, Maryland, United States Of America 2 The Institute For Genomic Research, Rockville, Maryland, United States Of America 3 Department of Computer Science, University of California San Diego 4 Instituto de Ecologia Dept. Ecologia Evolutiva, National Autonomous University of Mexico Mexico City, 04510 Distrito Federal, Mexico 5 University of Hawaii, Honolulu, United States of America 6 Dept. of Earth Sciences, University of Southern California, Los Angeles, California, United States of America 7 Dalhousie University, Halifax, Nova Scotia, Canada 8 Smithsonian Tropical Research Institute, Balboa, Ancon, Republic of Panama 9 University of Concepcion, Concepcion, Chile 10 University of Costa Rica, San Pedro, San Jose, Republic of Costa Rica