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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptNIH Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
 
Nature. Author manuscript; available in PMC Sep 15, 2006.
Published in final edited form as:
PMCID: PMC1464427
NIHMSID: NIHMS5166
Genome Sequencing in Open Microfabricated High Density Picoliter Reactors
Marcel Margulies,1* Michael Egholm,1* William E. Altman,1 Said Attiya,1 Joel S. Bader,1 Lisa A. Bemben,1 Jan Berka,1 Michael S. Braverman,1 Yi-Ju Chen,1 Zhoutao Chen,1 Scott B. Dewell,1 Lei Du,1 Joseph M. Fierro,1 Xavier V. Gomes,1 Brian C. Goodwin,1 Wen He,1 Scott Helgesen,1 Chun He Ho,1 Gerard P. Irzyk,1 Szilveszter C. Jando,1 Maria L.I. Alenquer,1 Thomas P. Jarvie,1 Kshama B. Jirage,1 Jong-Bum Kim,1 James R. Knight,1 Janna R. Lanza,1 John H. Leamon,1 Steven M. Lefkowitz,1 Ming Lei,1 Jing Li,1 Kenton L. Lohman,1 Hong Lu,1 Vinod B. Makhijani,1 Keith E. McDade,1 Michael P. McKenna,1 Eugene W. Myers,3 Elizabeth Nickerson,1 John R. Nobile,1 Ramona Plant,1 Bernard P. Puc,1 Michael T. Ronan,1 George T. Roth,1 Gary J. Sarkis,1 Jan Fredrik Simons,1 John W. Simpson,1 Maithreyan Srinivasan,1 Karrie R. Tartaro,1 Alexander Tomasz,4 Kari A. Vogt,1 Greg A. Volkmer,1 Shally H. Wang,1 Yong Wang,1 Michael P. Weiner,2 Pengguang Yu,1 Richard F. Begley,1 and Jonathan M. Rothberg1
1 454 Life Sciences Corp., 20 Commercial St., Branford, CT 06405, USA.
2 The Rothberg Institute For Childhood Diseases, 530 Whitfield St., Guilford, CT 06437, USA.
3 University of California, Berkeley, CA 94720, USA.
4 Laboratory of Microbiology, The Rockefeller University, New York, NY 10021, USA.
Correspondence and requests for materials should be addressed to J. M. Rothberg (jrothberg/at/454.com). Sequences for M. genitalium and S. pneumoniae were deposited at DDBJ/EMBL/GenBank under accession numbers AAGX01000000 and AAGY01000000 respectively.
*These authors contributed equally to the work.
We describe a scalable, highly parallel sequencing system with raw throughput significantly greater than that of state-of-the-art capillary electrophoresis instruments. The apparatus uses a novel 60×60 mm2 fibreoptic slide containing 1,600,000 individual wells and is able to sequence 25 million bases, at 99% or better accuracy (phred 20), in a 4 hour run. To provide sequencing templates, we clonally amplify DNA fragments on beads in the droplets of an emulsion. The template-carrying beads are loaded into the wells to convert each into a picoliter-scale sequencing reactor. We perform sequencing by synthesis using a pyrosequencing protocol optimized for solid support and the small dimension of the open reactors. Here we show the utility, throughput, accuracy and robustness of this system by shotgun sequencing and de novo assembling the Mycoplasma genitalium genome with 96% coverage at 99.96 % accuracy in one run of the machine.
DNA sequencing has dramatically changed the nature of biomedical research and medicine. Reductions in the cost, complexity and time required to sequence large amount of DNA, including improvements in the ability to sequence bacterial and eukaryotic genomes will have significant scientific, economic and cultural impact. Large scale sequencing projects, including whole genome sequencing, have usually required the cloning of DNA fragments into bacterial vectors, amplification and purification of individual templates, followed by Sanger sequencing 1 using fluorescent chain-terminating nucleotide analogues 2 and either slab gel or capillary electrophoresis. Current estimates put the cost of sequencing a human genome between $10 and $25 million 3. Alternative sequencing methods have been described 4, 5, 6, 7, 8 however, no technology has displaced the use of bacterial vectors and Sanger sequencing as the main generators of sequence information.
In this paper we describe an integrated system whose throughput routinely enables applications requiring millions of bases of sequence information, including whole genome sequencing Our focus has been on the co-development of an emulsion-based method 9, 10, 11 to isolate and amplify DNA fragments in vitro, and of a fabricated substrate and instrument that performs pyrophosphate-based sequencing (“pyrosequencing” 5, 12) in picoliter-sized wells.
In a typical run we generate over 25 million bases with a phred 20 or better quality score (predicted to have an accuracy of 99% or higher). While this phred 20 quality throughput is significantly higher than that of Sanger sequencing by capillary electrophoresis, it is currently at the cost of substantially shorter reads and lower average individual read accuracy 13. We further characterize the performance of the system, and demonstrate that it is possible to assemble bacterial genomes de novo from relatively short reads, by sequencing a known bacterial genome, Mycoplasma genitalium (580 kbp), and comparing our shotgun sequencing and de novo assembly with the results originally obtained for this genome 14. The results of shotgun sequencing and de novo assembly of a larger bacterial genome, Streptococcus pneumoniae 15 (2.1 Mbp), are presented in Supplementary Table 4.
Emulsion based sample preparation
We generate random libraries of DNA fragments by shearing an entire genome and isolating single DNA molecules by limiting dilution (Supplementary Methods: Library Preparation). Specifically, we randomly fragment the entire genome, add specialized common adapters to the fragments, capture the individual fragments on their own beads and, within the droplets of an emulsion, clonally amplify the individual fragment (Figure 1A and 1B). Unlike in current sequencing technology, our approach does not require subcloning in bacteria or the handling of individual clones; the templates are handled in bulk within the emulsions 9, 10, 11.
Figure 1
Figure 1
Sample Preparation.
We perform sequencing by synthesis simultaneously in open wells of a fibreoptic slide using a modified pyrosequencing protocol that is designed to take advantage of the small scale of the wells. The fibreoptic slides are manufactured by slicing of a fibreoptic block that is obtained by repeated drawing and fusing of optic fibres. At each iteration, the diameters of the individual fibres decrease as they are hexagonally packed into bundles of increasing cross-sectional sizes. Each fibreoptic core is 44 μm in diameter and surrounded by 2–3 μm of cladding; etching of each core creates reaction wells approximately 55 μm in depth with a centre-to-centre distance of 50 μm (Figure 1C), resulting in a calculated well size of 75 pL and a well density of 480 wells/mm2. The slide, containing approximately 1.6 million wells16, is loaded with beads and mounted in a flow chamber designed to create a 300 μm high channel, above the well openings, through which the sequencing reagents flow (Figure 2, A and B). The unetched base of the slide is in optical contact with a second fibreoptic imaging bundle bonded to a CCD sensor, allowing the capture of emitted photons from the bottom of each individual well (Figure 2, C, and Supplementary Methods: Imaging System).
Figure 2
Figure 2
Sequencing Instrument.
We developed a three-bead system, and optimized the components to achieve high efficiency on solid support. The combination of picoliter-sized wells, enzyme loading uniformity allowed by the small beads and enhanced solid support chemistry enabled us to develop a method that extends the useful read length of sequencing-by-synthesis to 100 bp (Supplementary Methods: Sequencing).
In the flow-chamber cyclically delivered reagents flow perpendicularly to the wells. This configuration allows simultaneous extension reactions on template carrying beads within the open wells and relies on convective and diffusive transport to control the addition or removal of reagents and by-products. The time scale for diffusion into and out of the wells is on the order of 10 seconds in the current configuration and is dependent on well depth and flow channel height. The time scales for the signal-generating enzymatic reactions are on the order of 0.02–1.5 seconds (Supplementary Methods: Interwell Diffusion). The current reaction is dominated by mass transport effects and improvements based on faster delivery of reagents are possible. Well depth was selected based on a number of competing requirements: (i) wells need to be deep enough for the DNA-carrying beads to remain in the wells in the presence of convective transport past the wells, (ii) they must be sufficiently deep to provide adequate isolation against diffusion of by-products from a well in which incorporation is taking place to a well where no incorporation is occurring, and (iii) they must be shallow enough to allow rapid diffusion of nucleotides into the wells, and rapid washing out of remaining nucleotides at the end of each flow cycle to enable high sequencing throughput and reduced reagent use. Following the flow of each nucleotide, a wash containing a nuclease is used to ensure that nucleotides do not remain in any well prior to the next nucleotide being introduced.
Nucleotide incorporation is detected by the associated release of inorganic pyrophosphate (PPi) and the generation of photons 5, 12. Wells containing template-carrying beads are identified by detecting a known four-nucleotide “key” sequence at the beginning of the read (Supplementary Methods: Image Processing). Raw signals are background-subtracted, normalized and corrected. The normalized signal intensity at each nucleotide flow, for a particular well, indicates the number of nucleotides, if any, that were incorporated. This linearity in signal is preserved to at least homopolymers of length 8 (Supplementary Figure 6). In sequencing by synthesis a very small number of templates on each bead lose synchronism (i.e. either get ahead of, or fall behind, all other templates in sequence 17). The effect is primarily due to leftover nucleotides in a well (creating “carry forward”) or to incomplete extension. Typically, we observe a carry forward rate of 1–2% and an incomplete extension rate of 0.1–0.3%. Correction of these shifts is essential because the loss of synchronism is a cumulative effect that degrades the quality of sequencing at longer read lengths. We have developed algorithms, based on detailed models of the underlying physical phenomena, that allow us to determine, and correct for, the amounts of carry forward and incomplete extension occurring in individual wells (Supplementary Methods: Signal Processing). Figure 3 shows the processed result, a 113 bp long read generated in the M. genitalium run discussed below. To assess sequencing performance and the effectiveness of the correction algorithms, independently of artifacts introduced during the emulsion-based sample preparation, we created test fragments with difficult-to-sequence stretches of identical bases of increasing length (homopolymers) (Supplementary Methods: Test Fragments and Supplementary Figure 4). Using these test fragments, we have verified that at the individual read level we achieve base call accuracy of approximately 99.4%, at read lengths in excess of 100 bp (Table 1).
Figure 3
Figure 3
Flowgram of a 113 base read from an M. genitalium run.
Figure 4
Figure 4
M. genitalium Data.
Table 1
Table 1
Summary of sequencing statistics for test fragments
Prior to base calling or aligning reads, we select high quality reads without relying on a priori knowledge of the genome or template being sequenced (Supplementary Methods: High Quality Reads). This selection is based on the observation that poor quality reads have a high proportion of signals that do not allow a clear distinction between a flow during which no nucleotide was incorporated and a flow during which one or more nucleotide was incorporated. When base calling individual reads, errors can occur because of signals that have ambiguous values (Supplementary Figure 5). To improve the usability of our reads, we also developed a metric which allows us to estimate ab initio the quality (or probability of correct base call) of each base of a read, analogous to the phred score 18 used by current Sanger sequencers (Supplementary Methods: Quality Scores and Supplementary Figure 8).
Higher quality sequence can be achieved by taking advantage of the high oversampling that our system affords and building a consensus sequence. Sequences are aligned to one another using the signal strengths at each nucleotide flow, rather than individual base calls, to determine optimal alignment (Supplementary Methods: Flow-space Mapping, Consensus Accuracy and Genome Coverage). The corresponding signals are then averaged, after which base calling is performed. This approach greatly improves the accuracy of the sequence (Supplementary Figure 7), and provides an estimate of the quality of the consensus base. We refer to that quality measure as the Z-score; it is a measure of the spread of signals in all the reads at one location and the distance between the average signal and the closest base calling threshold value. In both re-sequencing and de novo sequencing, as the minimum Z-score is raised the consensus accuracy increases, while coverage decreases; approximately half of the excluded bases, as the Z-score is increased, belong to homopolymers of length 4 and larger. Sanger sequencers usually require a depth of coverage at any base of three or more in order to achieve a consensus accuracy of 99.99%. To achieve a minimum of three fold coverage of 95% of the unique portions of a typical genome requires approximately 7 to 8 fold oversampling. Due to our higher error rate, we have observed that comparable consensus accuracies, over a similar fraction of a genome, are achieved with a depth of coverage of 4 or more, requiring approximately 10–12x oversampling.
Mycoplasma genomic DNA was fragmented and prepared into a sequencing library as described above. (This was accomplished by a single individual in 4 hours.) Following emulsion PCR and bead deposition onto a 60×60 mm2 fibreoptic slide, a process which took one individual 6 hours, 42 cycles of 4 nucleotides were flowed through the sequencing system in an automated 4 hour run of the instrument. The results are summarized in Table 2. In order to measure the quality of individual reads, we aligned each High Quality Read to the reference genome at 70% stringency, using flow-space mapping and criteria similar to those used previously in assessing the accuracy of other base callers 18. When assessing sequencing quality, only reads that mapped to unique locations in the reference genome were included. Since this process excludes repeat regions (parts of the genome whose corresponding flowgrams are 70% similar to one another), the selected reads did not cover the genome completely. Figure 4A illustrates the distribution of read lengths for this run. The average read length was 110 bp, the resulting oversample 40 fold, and 84,011 reads (27.4%) were perfect. Figure 4B summarizes the average error as a function of base position. Coverage of non-repeat regions was consistent with the sample preparation and emulsion not being biased (Supplementary Figure 8). At the individual read level, we observe an insertion and deletion error rate of approximately 3.3%; substitution errors have a much lower rate, on the order of 0.5%. When using these reads without any Z-score restriction, we covered 99.94% of the genome in 10 contiguous regions with a consensus accuracy of 99.97%. The error rate in homopolymers is significantly reduced in the consensus sequence (Supplementary Figure 7). Of the bases not covered by this consensus sequence (366 bp), all belonged to excluded repeat regions. Setting a minimum Z-score equal to 4, coverage was reduced to 98.1% of the genome, while consensus accuracy increased to 99.996%. We further demonstrated the reproducibility of the system by repeating the whole genome sequencing of M. genitalium an additional 8 times, achieving a 40 fold coverage of the genome in each of the 8 separate instrument runs (Supplementary Table 3).
Table 2
Table 2
Summary statistics for M. genitalium
We assembled the M. genitalium reads from a single run into 25 contigs with an average length of 22.4 kbp. One of these contigs was misassembled due to a collapsed tandem repeat region of 60 bp, and was corrected by hand. The original sequencing of M. genitalium resulted in 28 contigs prior to directed sequencing used for finishing the sequence 14. Our assembly covered 96.54% of the genome and attained a consensus accuracy of 99.96%. Non-resolvable repeat regions amount to 3% of the genome: we therefore covered 99.5% of the unique portions of the genome. Sixteen of the breaks between contigs were due to non-resolvable repeat regions, 2 were due to missed overlapping reads (our read filter and trimmer are not perfect and the algorithms we use to perform the pattern matching of flowgrams occasionally misses valid overlaps), and the remainder to thin read coverage. Setting a minimum Z-score of 4, coverage was reduced to 95.27% of the genome (98.2% of the resolvable part of the genome) with the consensus accuracy increasing to 99.994%.
We have demonstrated in this paper the simultaneous acquisition of hundreds of thousands of sequence reads, 80–120 bases long, at 96% average accuracy, in a single run of the instrument using a newly developed in vitro sample preparation methodology, and sequencing technology. With phred 20 as a cutoff, we show that our instrument is able to produce over 47 million bases from test fragments and 25 million bases from genomic libraries. We used test fragments to decouple our sample preparation methodology from our sequencing technology. The decrease in single read accuracy from 99.4% for test fragments to 96% for genomic libraries is primarily due to a lack of clonality in a fraction of the genomic templates in the emulsion, and is not an inherent limitation of the sequencing technology. Most of the remaining errors result from a broadening of signal distributions, particularly for large homopolymers (7 or more), leading to ambiguous base calls. Recent work on the sequencing chemistry and algorithms that correct for crosstalk between wells suggests that the signal distributions will narrow, with an attendant reduction in errors and increase in read lengths. In preliminary experiments with genomic libraries that also includes improvements in the emulsion protocol, we are able to achieve, using 84 cycles, read lengths of 200 bp with accuracies similar to those demonstrated here for 100 bp. On occasion, at 168 cycles, we have generated individual reads which are 100% accurate over greater then 400 bp.
Using M. genitalium, we demonstrate that short fragments a priori do not prohibit the de novo assembly of bacterial genomes. In fact, the larger oversampling afforded by the throughput of our system resulted in a draft sequence having fewer contigs than with Sanger reads, with substantially less effort. By taking advantage of the oversampling, consensus accuracies greater then 99.96% were achieved for this genome. Further quality filtering the assembly, a consensus sequence can be selected with accuracy exceeding 99.99%, while incurring only a minor loss of genome coverage. Comparable results were seen when we shotgun sequenced and de novo assembled the 2.1 Mbp genome of Streptococcus pneumoniae 15 (Supplementary Table 4). The de novo assembly of genomes more complex than bacteria, including mammalian genomes, may require the development of methods, similar to those developed for Sanger sequencing, to prepare and sequence paired end libraries that can span repeats in these genome. To facilitate the use of paired end libraries we have developed methods to sequence, in an individual well, from both ends of genomic template, and plan to add paired end read capabilities to our assembler (Supplementary Methods: Double Ended Sequencing).
Future increases in throughput, and a concomitant reductions in cost per base, may come from the continued miniaturization of the fibreoptic reactors, allowing more sequence to be produced per unit area – a scaling characteristic similar to that which enabled the prediction of significant improvements in the integrated circuit at the start of its development cycle 19.
Emulsion based clonal amplification.
The simultaneous amplification of fragments is achieved by isolating individual DNA-carrying beads in separate ~100 μm aqueous droplets (on the order of 2×106/mL) made through the creation of a PCR-reaction-mixture-in-oil emulsion. (Figure 1B and Supplementary Methods: Preparation of DNA Capture Beads, Binding Template Species to DNA Capture Beads, PCR Reaction Mix Preparation and Formulation, Emulsification and Amplification). The droplets act as separate microreactors in which parallel DNA amplifications are performed, yielding approximately 107 copies of a template per bead; 800 μL of emulsion containing 1.5 million beads are prepared in a standard 2 mL tube. Each emulsion is aliquoted into 8 PCR tubes for amplification. After PCR, the emulsion is broken to release the beads, which include beads with amplified, immobilized DNA template, and empty beads (Supplementary Methods: Breaking the Emulsion and Recovery of Beads). We then enrich for template-carrying beads (Supplementary Methods: Enrichment of Beads). Typically, about 30% percent of the beads will have DNA, producing 450,000 template-carrying beads per emulsion reaction. The number of emulsions prepared depends on the size of the genome and the expected number of runs required to achieve adequate oversampling. The 580 kbp M. genitalium genome, sequenced on one 60×60 mm2 fibreoptic slide, required 1.6 mL of emulsion. A human genome, oversampled 10 times, would require approximately 3000 mL of emulsion.
Bead loading into Picoliter Wells.
The enriched template-carrying beads are deposited by centrifugation into open wells (Figure 1C), arranged along one face of a 60×60 mm2 fibreoptic slide. The beads (diameter ~ 28 μm) are sized to ensure that no more than one bead fits in most wells (we observed that 2–5% of filled wells contain more than one bead). Loading 450,000 beads (from one emulsion preparation) onto each half of a 60×60 mm2 plate was experimentally found to limit bead occupancy to approximately 35% of all wells, thereby reducing chemical and optical crosstalk between wells. A mixture of smaller beads that carry immobilized ATP sulfurylase and luciferase necessary to generate light from free pyrophosphate are also loaded into the wells to create the individual sequencing reactors (Supplementary Methods: Bead Deposition, Preparation of Enzyme Beads and Micro-particle Fillers).
Image Capture.
A bead carrying 10 million copies of a template yields approximately 10,000 photons at the CCD sensor, per incorporated nucleotide. The generated light is transmitted through the base of the fibreoptic slide and detected by a large format CCD (4095×4096 pixels). The images are processed to yield sequence information simultaneously for all bead-template carrying wells. The imaging system was designed to accommodate a large number of small wells and the large number of optical signals being generated from individual wells during each nucleotide flow. Once mounted, the fibreoptic slide’s position does not shift; this makes it possible for the image analysis software to determine the location of each well (whether or not it contains a DNA-carrying bead), based on light generation during the flow of a pyrophosphate solution which precedes each sequencing run. A single well is imaged by approximately nine 15 μm pixels. For each nucleotide flow, the light intensities collected by the pixels covering a particular well are summed to generate a signal for that particular well at that particular nucleotide flow. Each image captured by the CCD produces 32 megabytes of data. In order to perform all the necessary signal processing in real time, the control computer is fitted with an accessory board (Supplementary Methods: Field Programmable Arrays), hosting a 6 million gate FPGA 20, 21.
De novo Shotgun Sequence Assembler.
A de novo flow-space assembler was developed to capture all of the information contained in the original flow-based signal trace. It also addresses the fact that existing assemblers are not optimized for 80 to120 bp reads, particularly with respect to memory management due to the increased number of sequencing reads needed to achieve equivalent genome coverage. (A completely random genome covered with 100 bp reads requires approximately 50% more reads to yield the same number of contiguous regions (contigs) as achieved with 700 bp reads, assuming the need for a 30 bp overlap between reads.) 22. This assembler consists of a series of modules: the Overlapper, which finds and creates overlaps between reads, the Unitigger, which constructs larger contigs of overlapping sequence reads, and the Multialigner, which generates consensus calls and quality scores for the bases within each contig (Supplementary Methods: De novo Sequence Assembler). (The names of the software modules are based on those performing related functions in other assemblers developed by Myers 23.)
Supplementary Material
SI figs
SI guide
methods
tables
Acknowledgments
We acknowledge Peter Dacey and the support of the Operations groups of 454 Life Sciences. This research was supported in part by the US Department of Health and Human Services under NIH grants.
Footnotes
Supplementary Information accompanies the paper on www.nature.com/nature.
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