Emerging Sequencing Technologies TAC Presentation Jay Shendure February 27, 2004

Genome Resequencing Sanger Sequencing (state-of-the-art): –~ 0.1 cents per unfinished base –~ $40,000,000 per 6.5x diploid human genome coverage –~ 2 million bases per machine per day (24 bp/s) (~20,000 instrument-days) But the goals of a ULCS genome requires… –~ cents per unfinished base –~ $1,000 per 6.5x diploid human genome coverage –~ 40 billion bases per instrument-day (~450,000 bp/s) (~1 instrument-day)

Emerging Alternative Technologies Cyclic Array Sequencing –Amplified Pyrosequencing Sequencing By Synthesis with Fluor-dNTPs Sequencing by Cleavage / Ligation (MPSS) –Single Molecule Sequencing By Synthesis with Fluor-dNTPs Nanopore Sequencing (Single Molecule) Sequencing By Hybridization Microelectrophoretic Sequencing

The 24 Hour Genome Throughput:450,000 bp/s Coverage:6.5-fold x 6e9 bases Raw Accuracy:99.7% Read Lengths:20 bp – 60 bp (at least) Final Accuracy: >99.999% Template Prep:~ 1 billion Assumption: cost to own & operate a single instrument will be roughly similar to conventional sequencing (100% uptime -> $1000 / day) Just one of many possible scenarios. Tradeoffs between error and throughput.

Microelectrophoretic Sequencing Throughput:28 bp/s Read Lengths: bp Accuracy: ~99.9% Advanatages: Based on an extraordinarily well-tested technology. Long read-lengths. Disadvantages: Difficult to imagine how 4 orders of magnitude will be achieved without a more radical departure in terms of parallelization.

Sequencing By Hybridization (Perlegen) Throughput:50 to 100 bp/s Read Lengths:25 bp (effective) Error: 3% FP SNPs Advanatages: Well-demonstrated relative to other technologies (14 MB x n = 20). ? Claims to have already sequenced 50 complete haploid genomes? Disadvantages: Large fraction of bases inaccessible (56%!!) Significant sample prep. Would probably need to move from confocal to CCD or decrease pixels / base ratio to achieve necessary speeds.

Nanopore Sequencing Throughput:10 bp/s (–> 30e6 bp/s?) Read Lengths:1 bp Accuracy: ~60% Advanatages: Potential for extraordinarily rapid sequencing Potential for zero-sample prep Disadvantages: No demonstration of single-base-pair resolution at internal base- positions Will likely require significant pore engineering

Cyclic Array Methods Molecules: Single vs. Amplified Acquisition: Real-time vs. Off-line Acquisition Plone Amplification –In Situ Polonies –Emulsion Amplified Beads –Capture Beads –Picowell PCR Enzymatic: Polymerase vs. RE/Ligase

Cyclic Array Methods (1) Homopolymers! (2) Removal of labels (for FL-dNTP methods) (3) Maintainance of synchrony (for amplified methods) (4) High sensitivity of optics (for single molecule methods) (5) Spatial separation of random or ordered array features (6) Method of clonal amplification (7) Feature miniaturization (8) Rate of data acquisition

Multiplex Pyrosequencing (454) Throughput:<100 bp/s ?? Read Lengths:40 – 150 bp Accuracy: >99% ?? Advanatages: Functional technology. Reasonable homopolymer solution. Based almost purely on unmodified nucleotides Disadvantages: Requirement for real-time imaging of sequencing by extension may be a significant bottleneck for improving per-instrument throughput. Diffusion and light scattering creates demand for spatial separation between features; ordered arrays

Polony FISSEQ Throughput:~1 bp/s Read Lengths:5 - 8 bp Accuracy: ~94% Advanatages: Integrates plone generation and sequencing to a single platform. Beat Poisson with polony exclusion principle. Disadvantages: Miniaturization definitely possible, but difficulties in minaturizing sequencable polonies. Polonies visible to confocal scanner but invisible to CCD Observed errors are systematic rather than random.

Massively Parallel Signature Sequencing (Lynx) Throughput:86 bp/s Read Lengths:12 – 16 bp Accuracy: 91%? Advanatages: Demonstrated method for tag sequencing CCD imaging No homopolymer problem. Disadvantages: Observed enzyme efficiencies are poor -> limited read-lengths Long cycle times, long scan times (low signal?).

Single Molecule Sequencing (Webb, Quake, Genovoxx) Throughput:~100 bp/s (333 bp/s?) Read Lengths:~4 bp (45 bp?) Accuracy: 96% (82%?) Advanatages: Can proceed asynchronously. Misincorporation events terminate (maybe). No need for amplification step in sample prep. Disadvantages: Blinking, photobleaching -> missed events. Misincorporation events terminate (maybe). Succesful experiments have involved sequencing non-consecutive bases.

Key Points (1)Very, very high accuracy is critical. (2)Throughput as a function of method of data acquisition is a major bottleneck (CCD!) (3)Real-time methods have much larger constraints in terms of parallelization relative to “off-line” methods.

Key Points (4)Throughput of sequencing must be matched by throughput of library generation and throughput of plone generation. (5)The primary advantages of single-molecule methods are asynchrony and template preparation, not data- density. (6)Combinations of methods for clonal amplification and sequencing give rise to many alternatives.

Key Points (7)A partial homopolymer solution will suffice for many initial goals. (8)For SBS methods, substitution error-rate may be << than indel error-rate. (9)Extending past the point of high accuracy is still informative for matching back to a reference genome.

Cyclic Array vs Nanopore vs Microelectrophoretic vs SBH Single vs Amplifed Real-time vs Off-line Polonies vs Emulsion Beads vs Lynx Beads vs Nanowell PCR vs Rolling Circle Beads Linear Quantitation vs Steric Reversible Terminators vs 3’ Reversible Terminators vs FRET Polymerase vs RE/Ligase Modified vs Unmodified Nucleotides vs Mixtures vs Multistep Direct vs Indirect Labeling Klenow vs BST vs Sequenase CCD vs Confocal Random Arrays vs Ordered Arrays Polymerase Trapping vs Enzyme Reloading TCEP vs BME vs MESNA Technology Agnostism

(1)Generate flanked library with purely in vitro methods. (2)Generate 1-micron “clonal beads” via emulsion PCR (or other method?). (3)Enrich amplified beads from “empty” beads. (4)Sequence acrylamide-immoblized beads in parallel via FISSEQ protocol. Strategy Overview

Clonal PCR Amplification with Emulsions (a)Protocol adopted from Dressman et al. (PNAS 2003) (b)Sub-picoliter aqueous compartments => isolated reaction chambers (c)Compartments also contain paramagnetic beads to which PCR products end up immoblized (via biotin-streptavidin interaction). (d)All copies of amplified DNA on same bead are the same, but amplified DNA on different beads is different (AMPLIFIED CLONALITY, just like polonies!) (e)~100 million beads per PCR tube!!!

Key Advances with Plone FISSEQ (1)In situ Polonies -> Beads => Major reduction in physical size (& greater consistency). Comes at a price. (2)Confocal Scanner - > CCD imaging => ~25x fold increase in data acquisition rate. (3)Operating near the limit of optical resolution. (4)Integration of software for stage operation, data collection, image alignment, bead identification, and base-calling. (5)Iron cores provide sharp resolution of bead centroids in at high bead-densities. (6)Revision to cycling protocols (no trapping or alkylation, TCEP cleavage, unlabeled follow-up) (7)Improvements to emulsion PCR technology to generate sufficient signal for bead- sequencing. (8)Disappearance of systematic errors (unexplained!) (9)6% gels are stable over 30+ cycles -> read-lengths of bases.

FISSEQ (G1 Slide) (C..A..G..T) x 7.5 = 30 quarter-cycles T1CACACACACACACACTCCACCA T2GTGTGTGTGTGTGTGTCCACCA T3AGTGCTCACACACGTGATCCAC T4CAGCCGAACGACCGATCCACCA T5ATGTGAGAGCTGTCGTCCACCA

0.5% of full gel area, 10X, 3 uM beads

Current Protocol 1.Extend with labeled base. 2.Wash 3.Image 4.Cleave label with TCEP 5.Wash 6.Extend with unlabeled base 7.Wash ~30 minute non-imaging cycle time.

Current Analysis Algorithm 1.Align images with allowances for gel warping. 2.Define white-light (WL) pixels as connected objects. 3.Extract data from each Cy5 image and a single Cy3 image at WL pixels only. 4.Calculate Cy5 / Cy3 ratios for each bead (avg value over WL pixels) 5.Rank-order ratios choose cutoff based on a priori knowledge of fraction of beads expected to add. Sub-classify as “Class 1” or “Class 2”. 6.Repeat till “signature” is obtained for each bead in all images. 7.Determine base sequence from signature and knowledge of base-cycle-order. 8.Match signatures to database of known templates (Hamming distance) 9.Classify sequences as perfect matches, matches with one substitution, one single-base insertion, one single-base deletion, or “complex” deviations. 10. Discard “complex” deviations as low-quality reads. 11. Determine error rates for each class as # of errors / total # of bases sequenced

~0.005% of gel area, 3 uM beads, 10x, cycle 1

cy3 cy5

Throughput:~6000 bp/s Read Lengths:14-15 bp Beads analyzed (0 – 1 error)1,627,646 Beads discarded (2+ errors)520,689 # of bases sequenced (total)23,703,953 # bases sequenced (unique)73 Avg fold coverage324,711 Homopolymer solutionNone Pixels used per bead (analysis)~3.6 G1 Slide

cy3 cy5 Class I (blue, 83%) vs. Class II (red, 17%) base-calls

TotalClass I (83%)Class II (17%) Bases23,703,95319,729,8973,974,056 Insertions331,11093,909237,201 Deletions339,242131,340207,902 Substitutions10, ,083 TotalClass IClass II Insertions Deletions Substitutions Error Analysis Not included: PCR error, homopolymer error, difficult contexts Class of substitution error determined by inserted base

6 bp/s 6000 bp/s 60,000 bp/s450,000 bp/s 5-8 bp bp 27 bp60 bp 92% ~99% >99.9%>99.99% million1 billion 0 v 1+ 0 v 1+ 0 v 1 v 2+Full PastPresentFuture 1Future 2 Still a long way to go…

Short-Term Challenges (1)5 templates -> 1 million templates (2)Implementation of FRET homopolymer solution. (3)30 cycles -> 40 cycles (4)6000 bp/s -> 60,000 bp/s. (5)Better base-calling algorithms (source of errors?) (6)Boosting clonal bead-generation throughput. (7)Need method for rapid generation of template libraries. (8)Automation of Cycling & Integration of Cycling / Imaging. (9)How to generate paired reads in this system?

27-mer Library (Tengs & Meyerson) Cut Site = 5’- NNNNNNNNNACNNNNNCTCCNNNNNNN-3’ Enzyme = BsaXI Large jump in complexity (5 -> 1.2 million) Defined sizes and internal fixed bases are a good sanity-checks Human. Sanger traces available for error estimation. Succesfully amplified and proven clonality, but haven’t actually sequenced more the 2 cycles.

Mode 0 = 0 vs 1+ Mode 1 = 0 vs 1 vs 2+ Mode 2 = 0 vs 1 vs 2 vs 3 vs…

Mode 0 = 0 vs 1+ Mode 1 = 0 vs 1 vs 2+ Mode 2 = 0 vs 1 vs 2 vs 3 vs…

FRET as a solution to the resolving homopolymers 2+ populations of reversibly labeled dNTPs Multiple-label strands will FRET, but single-labeled strands will not. Get around quenching. Positive signal on different channel. Internally controlled. Futher multiplexing with more fluors possible. C C G A A C C G T T A C G C Cy3Cy5 C C G A C C G T A C G C Cy3 C C G A A C C G T T A C G C Cy3Cy5 C C G A C C G T A C G C Cy5

Acknowledgements George Greg Porreca Rob Mitra Aaron Lee Church Lab Paul McEwan Kevin McKernan

Summary of altered strategy 5-mer library description Image of current bead-density (SBE) Sample Cy3 vs. Cy5 plot Summary statistics 27-mer library description Aaron’s simulation graphs GP: proof-of-clonality Description of FRET concept Initial FRET data Slide on plethora of sequencing technologies