Human Genome Sequencing Using Unchained Base Reads on Self-Assembling DNA Nanoarrays

Drmanac, Radoje; Sparks, Andrew B.; Callow, Matthew J.; Halpern, Aaron L.; Burns, Norman; Kermani, Bahram G.; Carnevali, P.; Nazarenko, Igor; Nilsen, Geoffrey B.; Yeung, George; Dahl, Fredrik A.; Fernandez, Andres; Staker, Bryan; Pant, Krishna Prasad; Baccash, Jonathan; Borcherding, Adam; Brownley, Anushka; Cedeno, Ryan J.; Chen, Linsu; Chernikoff, Dan; Cheung, Alex; Chirita, Razvan; Curson, Benjamin; Ebert, Jessica; Hacker, Coleen R.; Hartlage, Robert; Hauser, Brian; Huang, Shun; Jiang, Yuan; Karpinchyk, Vitali; Koenig, Mark; Kong, Calvin; Landers, Tom; Le, Catherine T.; Liu, Jia; McBride, Celeste; Morenzoni, Matt; Morey, Robert; Mutch, Karl; Perazich, Helena; Perry, Kimberly J.; Peters, Brock A.; Peterson, Joe; Pethiyagoda, Charit L.; Pothuraju, Kaliprasad; Richter, Claudia; Rosenbaum, Abraham M.; Roy, Shaunak; Shafto, Jay; Sharanhovich, Uladzislau; Shannon, Karen W.; Sheppy, Conrad G.; Sun, Michel M.; Thakuria, Joseph V.; Tran, Anne B.; Vu, Dylan; Zaranek, Alexander Wait; Wu, Xiaodi; Drmanac, Snezana; Oliphant, Arnold; Banyai, W. C.; Martin, Bruce; Ballinger, Dennis G.; Church, George M.; Reid, Clifford A.

doi:10.1126/science.1181498

Cited by 1,091 publications

(1,011 citation statements)

References 34 publications

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“…Genomic DNA was isolated from buffy coats of human blood samples using validated processes according to the requirements of Complete Genomics (CG). Whole-genome sequencing (WGS) was performed by CG using their proprietary paired-end nanoarray-based sequencingby-ligation technology 83 . All sequencing data quality control, mapping and variant calling were carried out by CG as part of their sequencing service using the Standard Sequencing Service pipeline version 2.4.…”

Section: Methodsmentioning

confidence: 99%

Integrated multi-omics of the human gut microbiome in a case study of familial type 1 diabetes

et al. 2016

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The gastrointestinal microbiome is a complex ecosystem with functions that shape human health. Studying the relationship between taxonomic alterations and functional repercussions linked to disease remains challenging. Here, we present an integrative approach to resolve the taxonomic and functional attributes of gastrointestinal microbiota at the metagenomic, metatranscriptomic and metaproteomic levels. We apply our methods to samples from four families with multiple cases of type 1 diabetes mellitus (T1DM). Analysis of intra-and inter-individual variation demonstrates that family membership has a pronounced effect on the structural and functional composition of the gastrointestinal microbiome. In the context of T1DM, consistent taxonomic differences were absent across families, but certain human exocrine pancreatic proteins were found at lower levels. The associated microbial functional signatures were linked to metabolic traits in distinct taxa. The methodologies and results provide a foundation for future large-scale integrated multi-omic analyses of the gastrointestinal microbiome in the context of host-microbe interactions in human health and disease.

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Section: Methodsmentioning

confidence: 99%

Integrated multi-omics of the human gut microbiome in a case study of familial type 1 diabetes

et al. 2016

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“…Two peripheral blood leukocyte-derived DNA samples derived from monozygotic twins discordant for schizophrenia were sequenced at high coverage using the short-read sequencing-by-ligation technology from Complete Genomics (CG) and assembled using their Complete Genomics Analysis tools (CGA) (Supplementary Note 1) 13 .…”

Section: Development Of Filters Using Monozygotic Twin Genomesmentioning

confidence: 99%

“…Another commonly used approach is to apply quality filters that are aimed at selectively removing errors. Every whole-genome sequence reported so far has used filtering to some extent: the most commonly used filters being those that remove sequences with a too-low coverage depth, discard variants with a low-confidence score or eliminate variants located within a cluster of variants 3,7,[10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25] . Surprisingly, there is little consensus with respect to which filters should be used and at which threshold they should be applied.…”

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confidence: 99%

Optimized filtering reduces the error rate in detecting genomic variants by short-read sequencing

et al. 2011

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“…The principles behind these four systems are schematically depicted in Figure 3. Additional platforms exist, such as the Polonator[62], the Helicos Single Molecule Sequencer[63], and an in-house only nanoarray-based sequencing-by-ligation technology developed by Complete Genomics[64]. These latter systems remain quite limited in their use and will not be discussed.…”

Section: Massively Parallel Sequencingmentioning

confidence: 99%

Direct mutation analysis by high-throughput sequencing: From germline to low-abundant, somatic variants

Gundry

Vijg

2012

Mutation Research/Fundamental and Molecular Mechanisms of Mutag

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DNA mutations are the source of genetic variation within populations. The majority of mutations with observable effects are deleterious. In humans mutations in the germ line can cause genetic disease. In somatic cells multiple rounds of mutations and selection lead to cancer. The study of genetic variation has progressed rapidly since the completion of the draft sequence of the human genome. Recent advances in sequencing technology, most importantly the introduction of massively parallel sequencing (MPS), have resulted in more than a hundred-fold reduction in the time and cost required for sequencing nucleic acids. These improvements have greatly expanded the use of sequencing as a practical tool for mutation analysis. While in the past the high cost of sequencing limited mutation analysis to selectable markers or small forward mutation targets assumed to be representative for the genome overall, current platforms allow whole genome sequencing for less than $5,000. This has already given rise to direct estimates of germline mutation rates in multiple organisms including humans by comparing whole genome sequences between parents and offspring. Here we present a brief history of the field of mutation research, with a focus on classical tools for the measurement of mutation rates. We then review MPS, how it is currently applied and the new insight into human and animal mutation frequencies and spectra that has been obtained from whole genome sequencing. While great progress has been made, we note that the single most important limitation of current MPS approaches for mutation analysis is the inability to address low-abundance mutations that turn somatic tissues into mosaics of cells. Such mutations are at the basis of intra-tumor heterogeneity, with important implications for clinical diagnosis, and could also contribute to somatic diseases other than cancer, including aging. Some possible approaches to gain access to low-abundance mutations are discussed, with a brief overview of new sequencing platforms that are currently waiting in the wings to advance this exploding field even further.

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Human Genome Sequencing Using Unchained Base Reads on Self-Assembling DNA Nanoarrays

Cited by 1,091 publications

References 34 publications

Integrated multi-omics of the human gut microbiome in a case study of familial type 1 diabetes

Integrated multi-omics of the human gut microbiome in a case study of familial type 1 diabetes

Optimized filtering reduces the error rate in detecting genomic variants by short-read sequencing

Direct mutation analysis by high-throughput sequencing: From germline to low-abundant, somatic variants

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