Roche Sequencing Story - PDF Free Download

Roche Sequencing Story Driving toward personalized medicine 9 November 2017 page 1 Roche For Research Use Only

IMPORTANT NOTICE Intended Use Unless explicitly stated otherwise, all Roche products and services referenced in this presentation/document are intended for the following use: For life science research only Not for use in diagnostic procedures All data on File For Roche Internal Use Only Do Not Distribute 9 November 2017 page 2 Roche

OUR GOAL Become the partner of choice for sequencing by making it simple and accessible enough for routine clinical use. Sample in. Result out. 9 November 2017 page 3 Roche For Research Use Only

Roche Sequencing Strategy PHASE I Invest in best-in-class technology across the NGS workflow PHASE II (TODAY) Create flexible, modular tools that simplify NGS workflow PHASE III Develop an end-to-end solution to enable diverse, routine clinical applications A phased approach to creating an end-to-end solution 9 November 2017 page 4 Roche For Research Use Only

The Roche Sequencing Vision An integrated NGS workflow SAMPLE PREPARATION SEQUENCING DATA, ANALYTICS AND REPORTING 9 November 2017 page 5 Roche For Research Use Only

Sequencing Vision Complete end to end solution: Sample in result out HEAT-Seq Sample Prep DNA Isolation Target Enrichment 2 nd and 3 rd Analysis Content: Oncology, Genetic Testing Roche Developed, Acquired or partnerships Library Preparation Sequencing Reporting 9 November 2017 page 6 Roche For Research Use Only

Sequencing solution investments Sample Prep Aug 2015 Kapa technology provides components essential to our fully integrated NGS solution. Kapa enzymes have the potential to improve the performance of the entire sequencing workflow and complement our existing technologies and expertise. MilliSect Nov 2014 High performance micro-dissection instrumentation, software and consumables promise to expand our diagnostic tool kit and bridge anatomic pathology (H&E staining) with genomic sequencing analysis through high quality sample preparation. AbVitro and Lumora Sep 2014 and July 2015 AbVitro s primer extension-based target enrichment technology offers the potential to support NGS directly from blood or other biological samples. Lumora s Heat Elution technology recovers DNA from FFPE and other challenging clinical samples in minutes, rather than the hours required for current technologies. For Roche Internal Use Only Do Not Distribute 9 November 2017 page 7 Roche

KAPA Library Preparation Kits and Enzymes Directed Evolution yields improved enzymes Core Technology Directed Evolution: A method of protein engineering that simulates natural selection in the lab Result Generates higher fidelity enzymes that reduce error and bias: Next-Gen Sequencing Library Preparation PCR/qPCR For Roche Internal Use Only Do Not Distribute 9 November 2017 page 9 Roche

Kit Selection by Application Application/ Sample Type Whole-genome Sequencing (human) Whole-genome Sequencing (small genomes) Exome Sequencing Amplicon Sequencing ChIP-Seq Methyl-Seq FFPE DNA Cell-free DNA Whole Transcriptome mrna-seq Non-coding RNA FFPE RNA Targeted RNA-Seq Ion Torrent Sequencing For further information on these applications, please refer to the individual sections or contact Global Customer Support at global.gcs_rss-sampleprep@roche.com. For Research Use Only. Not for use in diagnostic procedures. Data on file page 10 Roche

RNA LIBRARY PREPARATION SOLUTIONS

KAPA Library Prep Kits for RNA-Seq No RNA Enrichment HyperPrep HyperPlus cdna Library Prep Workflow Standard Streamlined Standard Streamlined Standard Streamlined KAPA Product KAPA Stranded RNA-Seq Kits KAPA RNA HyperPrep Kits KAPA Stranded mrna-seq Kits KAPA mrna HyperPrep Kits KAPA Stranded RNA-Seq Kits with RiboErase KAPA RNA HyperPrep Kits with RiboErase Library Prep Workflow time 6 8 hr 4 hr 8 10 hr 5.5 hr 10 12 hr 6.5 hr Input Amount 10 400 ng into library prep 1 100 ng into library prep 100 ng 4 μg into mrna capture 50 ng 1 μg into mrna capture 100 ng 1 μg into rrna depletion 25 ng 1 μg into rrna depletion Sample Type High-quality Total RNA Degraded or FFPE Total RNA Enriched RNA High-quality Total RNA High-quality Total RNA Degraded or FFPE Total RNA Species Eukaryotic (Animal, Plant, etc.) Prokaryotic (Bacterial, etc.) Eukaryotic (Animal, Plant, etc.) Human, Mouse, and Rat Differentiating Applications Targeted RNA-Seq Whole Transcriptome mrna-seq Non-coding RNA Whole Transcriptome Shared Applications Strand-specific Automation-friendly Gene Expression Analysis; Detection of Gene Fusions, Isoforms, and other Structural Variants; Novel Transcript Identification; SNV Discovery Yes Yes For Research Use Only. Not for use in diagnostic procedures. page 12 Roche

The Evolution of KAPA Library Prep for RNA-Seq PERFORMANCE and WORKFLOW KAPA RNA HyperPrep Input (RiboErase) = 25 ng 1 µg Input (mrna capture) = 50 ng 1 µg Input (no enrichment) = 1 ng 100 ng KAPA Stranded RNA-Seq with RiboErase (HMR) Input = 100 ng 1 µg KAPA Stranded (m)rna-seq Input = 400 ng 1 µg for mrna capture, or 10 400 ng for no capture 2013 2015 October 2016 Gene expression analysis Detection of gene fusions, isoforms, and other structural variants Novel transcript identification SNV discovery

RNA-Seq Workflow Streamlining KAPA Stranded RNA Library Prep KAPA RNA HyperPrep mrna capture rrna depletion mrna capture rrna depletion Frag + Prime RNA Frag + Prime RNA 1st Strand Synthesis 1st Strand Synthesis 2nd Strand Synthesis Cleanup A-Tail Adapter Ligation Cleanup Cleanup 2.5 h 2nd Strand Synthesis & A-Tailing Adapter Ligation Cleanup Cleanup Amplification with PCR Mix 40 m Amplification with PCR Mix Cleanup Cleanup

RNA-Seq data expectations RiboErase Intergenic Intronic Exonic Ribosomal High quality Total RNA-seq Total RNA-seq depleted in silico mrna capture rrna depletion Low quality For Roche Internal Use Only Do Not Distribute 9 November 2017 page 17 Roche

KAPA mrna Hyper Sequencing of mrna-enriched samples provides a focused view of the exonic regions in the transcriptome Benefits include: Focused sequencing of protein-coding transcripts Improved coverage of gc-rich and low abundance transcripts Identification of an increased number of transcripts and genes Starting input 50 ng 1 ug For Research Use Only. Not for use in diagnostic procedures. Data on file 9 November 2017 page 18 Roche

Performance: Sequencing metrics Better utilize sequencing capacity. Libraries were generated in quadruplicate with 50 ng of high-quality Universal Human Reference (UHR) RNA using the manufacturers standard recommendations per workflow, where possible. For Roche Internal Use Only Do Not Distribute 9 November 2017 page 19 Roche

Performance: GC-rich coverage KAPA mrna HyperPrep TruSeq Stranded mrna NEBNext Ultra Directional with mrna Capture Improved coverage. IGV coverage and splice junction tracks of the GC-rich GC-rich SLC2A4RG gene. Libraries were generated with 50 ng of high-quality UHR RNA using the manufacturers standard recommendations per workflow, where possible. For Roche Internal Use Only Do Not Distribute 9 November 2017 page 20 Roche

KAPA RNA Hyper with RiboErase Sequencing of total RNA samples that have been ribosomal RNA (rrna) depleted provides a more comprehensive representation of the transcriptome Benefits include: Up to 99.98% rrna depletion from various sample types Compatible with degraded inputs, including FFPE Detection of noncoding and precursor transcripts Improved coverage of GC-rich and low abundance transcripts Qualified automation method For Research Use Only. Not for use in diagnostic procedures. Data on file 9 November 2017 page 21 Roche

Impact of sample quality on library construction Sample quality dramatically affects library preparation Useful metrics to assess RNA quality include RNA Integrity Number (RIN) DV200 High-quality UHR FFPE 1: HQ FFPE FFPE 2: LQ FFPE Quality assessment of input RNA. Electropherograms were generated using an Agilent RNA 6000 Pico Kit. Blue shading highlights RNA fragments >200 nt. For Roche Internal Use Only Do Not Distribute 9 November 2017 page 22 Roche

Impact of sample quality on library construction 100 Post-Ligation yield (pm) Adapter dimer (%) 80 60 40 20 0 6 10 20 22 29 37 42 47 52 95 DV200 (%) High-quality UHR FFPE 1: HQ FFPE FFPE 2: LQ FFPE Sample quality affects RNA-seq library construction. Libraries were constructed using 100 ng of RNA from FFPE tissues (DV200 range 6 52%) and a high-quality UHR control (DV200 95%). Post-ligation yield was measured by qpcr and adapter dimer rates were calculated from electrophoretic assessment of final libraries. For Roche Internal Use Only Do Not Distribute 9 November 2017 page 23 Roche

Impact of sample quality on library construction 100 Post-Ligation yield (pm) Adapter dimer (%) 80 60 40 20 0 6 10 20 22 29 37 42 47 52 95 DV200 (%) Sample quality affects RNA-seq library construction. Libraries were constructed using 100 ng of RNA from FFPE tissues (DV200 range 6 52%) and a high-quality UHR control (DV200 95%). Post-ligation yield was measured by qpcr and adapter dimer rates were calculated from electrophoretic assessment of final libraries. For Roche Internal Use Only Do Not Distribute 9 November 2017 page 24 Roche

Impact of sample quality on library construction 100 Post-Ligation yield (pm) Adapter dimer (%) 80 60 40 20 LQ FFPE HQ FFPE 0 6 10 20 22 29 37 42 47 52 95 DV200 (%) LQ FFPE HQ FFPE Sample quality affects RNA-seq library construction. Libraries were constructed using 100 ng of RNA from FFPE tissues (DV200 range 6 52%) and a high-quality UHR control (DV200 95%). Post-ligation yield was measured by qpcr and adapter dimer rates were calculated from electrophoretic assessment of final libraries. For Roche Internal Use Only Do Not Distribute 9 November 2017 page 25 Roche

Impact of sample quality on sequencing metrics Sample quality affects some sequencing metrics. Libraries were constructed using 25 or 100 ng of UHR or FFPE RNA using RNA HyperPrep with RiboErase. Duplicate libraries were sequenced and subsampled to 14M reads. For Roche Internal Use Only Do Not Distribute 9 November 2017 page 26 Roche

DNA LIBRARY PREPARATION SOLUTIONS

KAPA DNA Library Prep Kits HTP/LTP HyperPrep HyperPlus Applications Primary applications WGS, WES, Custom Panels, ChIP-Seq, Methyl-Seq WGS, WES, Custom Panels, ChIP-Seq, Methyl-Seq WGS. WES, Custom Panels Input 10 ng 5 μg 1 ng 1 μg 1 ng 1 μg High-quality DNA Recommended Recommended Recommended Sample Type FFPE DNA Compatible Recommended Recommended Cell-free DNA Compatible Recommended N/A ChIP DNA Compatible Recommended Compatible Performance Maximum Conversion Rate (Library Prep Efficiency) 40% 60% 100% DNA Polymerase KAPA HiFi KAPA HiFi KAPA HiFi Amplification Low-bias Amplification Yes Yes Yes PCR-free Workflows Compatible Recommended Recommended Fragmentation Mechanical Mechanical Integrated enzymatic Workflow Library Prep Time 4.5 6 hr 2 3 hr 1.5 3 hr (incl. fragmentation) Automation Friendly Yes Yes Yes For Research Use Only. Not for use in diagnostic procedures. page 28 Roche

Evolution of conversion rates Maximum conversion rate for 1 µg high quality input 60-100% Baseline KAPA Library Preparation Kit KAPA with bead Library Prep Kit 9 November 2017 page 29 Roche For Research Use Only KAPA Hyper Prep Data on file. For Research Use Only. Not for use in diagnostic procedures. KAPA HyperPlus With Fragmentation

KAPA HyperPlus: Fast & fully automatable KAPA with-bead Library Preparation KAPA Hyper Prep KAPA HyperPlus 10 45 min 30 min 15 min 30 min 30 min 30 min 2 3 h 1.5 3 h 4.5 6 h Data on file. For Research Use Only. Not for use in diagnostic procedures. 9 November 2017 page 30 Roche For Research Use Only

Bringing Together Best-in-Class Technologies to Craft an End-to-End Solution A global effort, headquartered in Pleasanton, California SAMPLE PREPARATION SEQUENCING ANALYTICS MEDICAL CONTENT AvanSci Bio: Tissue Dissection Lumora: Heat Elution Kapa Biosystems: Library Prep NimbleGen: Target Enrichment AbVitro: PETE Genia: Single Molecule Nanopore Technology Stratos (research collaboration): Sequencing by Expansion Bina: Bioinformatics For Research Use Only. Not for use in diagnostic procedures. Ariosa (NIPT) Signature (Oncology) CAPP Medical (Oncology)

What is HyperCap? Integrated workflow of NGS Library Prep and Enrichment Solutions For Research Use Only. Not for use in diagnostic procedures.

Why use HyperCap? Streamlined workflow offering improved performance, flexibility, and automation-friendly Fast protocol Library prep in less than half a day Flexibility to perform shorter hybe supported High - efficiency library construction High conversion rates (yields) increase molecular complexity prior to capture Low fragmentation and amplification bias Versatile performance Improved enrichment metrics with across designs Comparable metrics between O/N and 4-hour hybridization Automation-friendly Steps that require user intervention or off-deck equipment can be eliminated For Research Use Only. Not for use in diagnostic procedures.

SeqCap EZ HyperCap Workflow v1.0 Reduce library prep time with Hyper Prep & HyperPlus kits KAPA Standard KAPA Hyper Prep KAPA HyperPlus Covaris Shearing * Covaris Shearing * Enzymatic Fragmentation End Repair SPRI Cleanup Single Tube End Repair & A-Tailing Adapter Ligation Single Tube End Repair & A-Tailing Adapter Ligation A-Tailing SPRI Cleanup SPRI Cleanup SPRI Cleanup Size Selection Size Selection Adapter Ligation PCR PCR SPRI Cleanup SPRI Cleanup SPRI Cleanup Size Selection PCR SPRI Cleanup ~3 hours* ~3 hours * Covaris shearing TAT is dependent on instrument, make, model and batch size. Time estimates for Standard and Hyper do not include covaris shearing. Enzymatic fragmentation allows for efficient and effective fragmentation for automated / high-throughput customers ~6 hours* For Roche Internal Use Do Distribute 9 November 2017 page 34 Roche For Research Use Only. Not for use in diagnostic procedures.

Target Enrichment Systems

Why perform targeted sequencing? Enable selective studying from relevant regions For Roche Internal Use Only Do Not Distribute 9 November 2017 page 36 Roche

SeqCap EZ Probe Library superior design More probes, uniform coverage, better capture Simple Tiling Design Target Region 120mer probes/baits tiled across the region. NimbleGen s Sequence Capture Design Target Region Up to 2,100,000 (50-105mer) probes selected for the region using special algorithm. Significantly more probes. Benefits: Higher density tiling Redundancy to reduce risk of unbalanced coverage or missed regions Ability to move probes for better uniformity For Roche Internal Use Only Do Not Distribute 9 November 2017 page 37 Roche

SeqCap EZ Choice Probe Design More probes significantly reduce risk of missing regions Simple Tiling Design Small insertion X Target Region Missing Region Target Region Missing Region X Missing or non-performing Probe NimbleGen Sequence Capture Design Small insertion Target Region X Target Region X Flanking probes can capture novel variants Redundant probes reduce risks For Roche Internal Use Only Do Not Distribute 9 November 2017 page 38 Roche

SeqCap EZ Library Workflow Capture targets up to 200 Mb with 2.1 M oligos in solution Target Regions Prepare with Next- Gen Sequencing Adaptors SeqCap EZ Probes (Solution Capture) Amplify DNA and Enrichment QC Sequence DNA on a Next-Gen Sequencer Genomic DNA Library Preparation Hybridization Capture and Washing Amplification and QC Sequencing For Roche Internal Use Only Do Not Distribute 9 November 2017 page 39 Roche

Comprehensive Variant Detection enabled by NimbleGen target enrichment technology gdna Seq SeqCap EZ Epigenetic variation detection (methyl seq) SeqCap Epi Sensitive, accurate and reproducible detection of variants RNA Seq SeqCap RNA For Roche Internal Use Only Do Not Distribute 9 November 2017 page 40 Roche

DNA Methylation Fields of Study From development to disease DNA Methylation is an essential field of genomics research with growing importance in human health and agriculture research. N NH 2 DNMTs N NH 2 CH 3 Cancer and carcinogenesis Autoimmune disease Mammalian embryonic development Neurological disorders O N AdoMet cytosine O AdoHcy N 5-methylcytosine For Roche Internal Use Only Do Not Distribute 9 November 2017 page 41 Roche

5mC monitoring technology Bisulfite mediated deamination of Cytosine Unmethylated : Methylated: Bisulfite is the gold standard technology for single-base resolution Uracil is replaced with thymine by DNA polymerase during amplification (T read as unmethylated C) BOTH 5mC and 5hmC are substantially resistant to the mutagenesis conditioned by HSO 3 - C read as either 5mC or 5hmC Destroys ~96% of the sample via acid-hydrolysis (nicks DNA) Clark SJ et al., Nucl. Acids Res. 1994. 22 (15): 2990-2997. doi: 10.1093/nar/22.15.2990 For Roche Internal Use Only Do Not Distribute 9 November 2017 page 42 Roche

Existing Technologies in DNA Methylation Studies One technology from discovery to validation 1-10 1,000,000 s # of Samples Possible WGBS RRBS Microarrays SeqCap MassArray Amplicons Epi # of CpG s interrogated 1000 s qpcr 1-10 For Roche Internal Use Only Do Not Distribute 9 November 2017 page 43 Roche

SeqCap Epi Enrichment System Workflow Bisulfite treatment and then capture Target Regions Prepare a SeqCap Epi Library Bisulfite Conversion SeqCap Epi - Solution Capture (probes target CG, CHG, CHH) Amplify DNA Sequence HiSeq CpG Island CpG Island CpG Island Genomic DNA Library Preparation Chemical Mutagenesis Hybridization Capture and Washing Amplification and QC Sequencing With methylated adapters (C>T conversion) and amplification with uracil tolerant polymerase Focus bisulfite sequencing to ANY C of interest (Convert then Capture) For Roche Internal Use Only Do Not Distribute 9 November 2017 page 44 Roche

Workflows Considered for SeqCap Epi SeqCap Epi Alternative MethylSeq Library Prep Bisulfite Conversion Pre-Capture Amplify Library Capture Post-Capture Amplify Library Sequence MethylSeq Library Prep Capture Bisulfite Conversion Post-Capture Amplify Library Sequence 9 November 2017 page 45 Roche For Research Use Only

TRM1 TRM2 Capture Before Bisulfite Conversion Leads to More Severe Bottlenecking of Genomic Information 100% input complexity - SeqCap Epi Alternative 100% input complexity - - ± - ± MethylSeq Library Prep Bisulfite Conversion Pre-Capture Amplify Library Capture MethylSeq Library Prep Capture Bisulfite Conversion - - ± tighter bottleneck Post-Capture Amplify Library Sequence Post-Capture Amplify Library Sequence 9 November 2017 page 46 Roche For Research Use Only

Slide 46 TRM1 TRM2 changed the Seqcap epi to blue and the "before" in the title to orange Teri Rambo Mueller, 5/12/2016 changed the Seqcap epi to blue and the "before" in the title to orange Teri Rambo Mueller, 5/12/2016

TRM3 Capture Before Bisulfite Conversion Leads to More Severe Bottlenecking of Genomic Information SeqCap Epi Alternative + Higher output complexity Bisulfite Conversion + Lower sample input required Pre-Capture Amplify Library + Higher reproducibility - Higher probe density required - Lower output complexity - Higher sample input required Capture - Lower reproducibility Bisulfite Conversion + Lower probe density required 9 November 2017 page 47 Roche For Research Use Only

Slide 47 TRM3 changed the Seqcap epi to blue and the "before" in the title to orange Teri Rambo Mueller, 5/12/2016

Innovative Probe Design and Manufacture High probe density facilitates the capture of complex intermediate methylation patterns All possible methylation patterns represented in the bisulfite mutagenized sequencing library do not have to be specifically targeted by perfectly complementary probes: Sufficient misalignments are tolerated to allow capture by similar probes in a pool of millions Epi is designed to be used with ~200bp insert libraries, so targets with intermediate methylation can also be captured by adjacent capture probes up to 150 bp away High tiling density means that each CpG can be targeted by multiple probes For Roche Internal Use Only Do Not Distribute 9 November 2017 page 48 Roche

Existing Technologies in DNA Methylation Studies Limitations and gaps Whole Genome Whole Genome Bisulfite sequencing (WGBS) Microarrays Content Performance Cost Content Performance Limitations Poor depth of coverage Difficult data analysis Cost-prohibitive Indirect measurement Limited SNP calling on CpG Closed data analysis system Target Enrichment Agilent SureSelect Methyl-Seq Reduced Representation Bisfulite Sequencing (RRBS) Content Performance Content Convenience Cost Limited molecular complexity High PCR duplication Very high sample input Targets only one strand No custom content Fixed content limited by enzyme sites Missing data For Roche Internal Use Only Do Not Distribute 9 November 2017 page 49 Roche

Compare with Whole Genome Bisulfite Sequencing High Correlation with WGBS Data R = 0.929 Left-right symmetry indicates little systematic bias in % methylation measurements

Product Details SeqCap Epi Enrichment System Fixed Content SeqCap Epi CpGiant Enrichment Kit Epigenome-wide fixed design containing Illumina s Infinium Human Methylation450 BeadChip sites with smart padding Covers >5.5 million CpG sites in human genome Custom Content SeqCap Epi Choice Enrichment Kits Human Designs Small <30Mb, Medium 30-60Mb, and Large 60-90Mb designs SeqCap Epi Developer Enrichment Kits Non-Human and Large Human Designs Small <30Mb, Medium 30-60Mb, and Large 60-90Mb, and XL 90-210Mb designs For Roche Internal Use Only Do Not Distribute 9 November 2017 page 52 Roche

Existing Technologies in DNA Methylation Studies Limitations and gaps Whole Genome Whole Genome Bisulfite sequencing (WGBS) Microarrays Content Performance Cost Content Performance Limitations Poor depth of coverage Difficult data analysis Cost-prohibitive Indirect measurement Limited SNP calling on CpG Closed data analysis system Target Enrichment Agilent SureSelect Methyl-Seq Reduced Representation Bisulfite Sequencing (RRBS) Content Performance Content Convenience Cost Limited molecular complexity High PCR duplication Very high sample input Targets only one strand No custom content Fixed content limited by enzyme sites Missing data For Roche Internal Use Only Do Not Distribute 9 November 2017 page 53 Roche

SeqCap Epi CpGiant Enrichment Kits Upgrade your research from microarrays Epigenome-wide fixed design containing Illumina s Infinium Human Methylation450 BeadChip sites with smart padding to maximize CpG For Roche Internal Use Only Do Not Distribute 9 November 2017 page 54 Roche

The Importance of Targeting Watson and Crick SNPs are still important in the bisulfite world

Existing Technologies in DNA Methylation Studies Limitations and gaps Whole Genome Whole Genome Bisulfite sequencing (WGBS) Microarrays Content Performance Cost Content Performance Limitations Poor depth of coverage Difficult data analysis Cost-prohibitive Indirect measurement Limited SNP calling on CpG Closed data analysis system Target Enrichment Agilent SureSelect Methyl-Seq Reduced Representation Bisulfite Sequencing (RRBS) Content Performance Content Convenience Cost Limited molecular complexity High PCR duplication Very high sample input Targets only one strand No custom content Fixed content limited by enzyme sites Missing data For Roche Internal Use Only Do Not Distribute 9 November 2017 page 61 Roche

Direct Comparison The Importance of Targeting Watson and Crick Targeted Region Coverag e Targeted Region Coverage

SeqCap Epi Performance Benchmarking Head to head comparison with SureSelect Methyl-Seq workflow Red = Poor, Green = Good SAMPLE %DUP READS %ON TARGET READS MEAN DEPTH COV MEDIA N DEPTH COV PCT >1X PCT >10X PCT >20X PCT >50X PCT >100X FOLD 80 PENALT Y CpG POS COV 1X BOTH CpG POS COV 10X BOTH AVG STRAN D BIAS Roche Agilent-mimic design / 83.9 Mbp primary / Roche workflow Sample d to 55M reads Sample d to 55M reads IMR90_1 15.2 70.7 29.7 28 99.22 89.97 69.33 12.39 0.08 1.99 3449321 557194 0.50 IMR90_2 10.7 66.8 29.5 28 99.25 90.73 70.20 11.22 0.09 1.98 3491702 623665 0.50 NA12762_ 1 6.6 71.3 32.7 29 99.29 90.59 71.71 15.65 0.22 2.03 3443276 752756 0.50 NA12762_ 2 5.9 67.1 30.9 28 99.25 89.19 68.74 12.83 0.16 2.19 3403874 637597 0.50 NA12878_ 1 5.9 71.0 32.2 30 99.31 92.31 74.23 15.97 0.19 1.91 3604343 854644 0.50 NA12878_ 2 5.1 72.5 33.3 32 99.32 93.46 76.97 17.02 0.22 1.86 3618971 968540 0.50 Agilent design / 84.5 Mbp primary / Agilent workflow IMR90_1 34.8 88.7 28.7 24 98.09 81.94 59.48 14.88 1.05 2.64 302328 9298 0.02 IMR90_2 29.9 87.7 30.4 26 98.26 83.61 62.42 17.09 1.29 2.56 332046 10725 0.02 NA12762_ 1 29.5 87.6 30.4 25 98.35 83.14 61.89 17.34 1.34 2.80 385678 9978 0.02 NA12762_ 2 33.7 86.8 28.1 23 98.22 81.30 58.27 14.24 0.93 2.84 368159 9305 0.02 NA12878_ 1 29.6 87.8 30.5 25 98.22 83.17 62.03 17.33 1.35 2.80 397506 10069 0.02 NA12878_ 2 33.5 87.8 28.8 24 98.09 81.67 59.39 15.22 1.07 2.65 344970 9070 0.02 9 November 2017 page 63 Roche For Research Use Only

SeqCap Epi Performance Benchmarking Don t be concerned about lower probe specificity by targeting converted DNA Red = Poor, Green = Good %ON TARGET READS 70.7 66.8 71.3 67.1 71 72.5 88.7 87.7 87.6 86.8 87.8 87.8 9 November 2017 page 64 Roche For Research Use Only

SeqCap Epi Performance Benchmarking ~25% Lower duplicate read rate Red = Poor, Green = Good %DUP READS 15.2 10.7 6.6 5.9 5.9 5.1 34.8 29.9 29.5 33.7 29.6 33.5 9 November 2017 page 65 Roche For Research Use Only

SeqCap Epi Performance Benchmarking ~25 Fold better strand representation, infinitely better 5mC SNP error correction Red = Poor, Green = Good CpG POS COV 1X BOTH CpG POS COV 10X BOTH AVG STRAND BIAS 3449321 557194 0.5 3491702 623665 0.5 3443276 752756 0.5 3403874 637597 0.5 3604343 854644 0.5 3618971 968540 0.5 302328 9298 0.02 332046 10725 0.02 385678 9978 0.02 368159 9305 0.02 397506 10069 0.02 344970 9070 0.02 9 November 2017 page 66 Roche For Research Use Only

TRM5 SeqCap Epi Brings Unique Advantages Coverage of both strands provides more SNP information Roche Nimblegen 44k Shared in Common 38k Agilent Design 11k SeqCap EPI call 65% more SNPs 9 November 2017 page 67 Roche For Research Use Only

Slide 67 TRM5 changed the colors Teri Rambo Mueller, 5/12/2016

Existing Technologies in DNA Methylation Studies Limitations and gaps Whole Genome Whole Genome Bisulfite sequencing (WGBS) Microarrays Content Performance Cost Content Performance Limitations Poor depth of coverage Difficult data analysis Cost-prohibitive Indirect measurement Limited SNP calling on CpG Closed data analysis system Target Enrichment Agilent SureSelect Methyl-Seq Reduced Representation Bisulfite Sequencing (RRBS) Content Performance Content Convenience Cost Limited molecular complexity High PCR duplication Very high sample input Targets only one strand No custom content Fixed content limited by enzyme sites Missing data For Roche Internal Use Only Do Not Distribute 9 November 2017 page 68 Roche

Capture Your DMRs of Interest Custom designs allow for monitoring unique DMRs 3.2Mbp capture design targeting 500 genes promoters (Developed with John Greally at Albert Einstein School of Medicine) For Roche Internal Use Only Do Not Distribute 9 November 2017 page 69 Roche

SeqCap Epi Enrichment System Leveraging NimbleGen s probe design and manufacture The Challenge High Complexity Capture Targets: Bisulfite treatment effectively doubles genome size; many probes needed to enable capture after bisulfite Loss of Information: Bisulfite treatment and inefficient enrichment can result in loss of genomic information Ineffective and Unaffordable Solutions: Previous commercial offerings failed to offer performance, cost, effectiveness and customizability The Solution: SeqCap Epi Innovative Probe Design: Roche NimbleGen technology enables efficient production of millions of probes to capture epigenome complexity Unique Workflow: Bisulfite before capture and targeting both strands for enrichment conserves molecular complexity Custom & Fixed Content Available: First to offer both catalog and custom designs to significantly advance the research depth and throughput For Roche Internal Use Only Do Not Distribute 9 November 2017 page 70 Roche

Capture Your Regions of Interest SeqCap Epi Enrichment Kits Products Design Size SeqCap Epi CpGiant Enrichment Kit 84 Mb SeqCap Epi Choice Enrichment Kit Small (<30Mb) Medium (30-60Mb) Large (60-90Mb) SeqCap Epi Developer Enrichment Kit Small (<30Mb) Medium (30-60Mb) Large (60-90Mb) XL (90-210Mb) Up to 90 Mb Up to 210 Mb For Roche Internal Use Only Do Not Distribute 9 November 2017 page 71 Roche

SeqCap Epi CpGiant Demo Data Review design Regions of interest selection An epigenome-wide fixed content design was created containing all of the Illumina Infinium HumanMethylation 450 BeadChip sites with smart padding to maximize the number of CpG s that will be assayed (5.5 million). 80Mb design Innovative probe design and manufacture allows for the capture of both strands enabling the detection of complex or rare methylation events. 9 November 2017 page 72 Roche For Research Use Only

SeqCap Epi CpGiant Demo Data Review experimental design 1 ug NA12891 and NA19240 sample DNA with LTP/HTP Kapa Library Prep Kit SeqCap Epi User's Guide v1.2 1 samples pre-captured multiplexed 72 hour hybridization Illumina HiSeq 2000 in high output mode, v3 chemistry and 2x101bp reads 9 November 2017 page 73 Roche For Research Use Only

SeqCap Epi CpGiant Demo Data Review analysis Sequencing reads in fastq files Examine Sequence Read Quality FastQC Adapter and Quality Trimming Trimmomatic Map Reads to Reference Genome BS Map Split Reads by Strand, Remove Duplicates and Merge Split Files Bamtools, SamTools, Picard Mark Duplicates SeqCap Epi Data Analysis Tech Note Filter For Properly Paired Reads and Clip Overlapping Reads Methylation Analysis BSMAP, BisSNP 9 November 2017 page 74 Roche For Research Use Only

SeqCap Epi CpGiant Demo Data Review performance 100 80 60 40 20 0 % dup rate % on-target Mean Depth of Coverage % bases >= 1 % bases >= 10 NA12878-1 NA12878-2 NA19240-1 NA19240-2 Fold 80 base penalty(1/nc80) = 2.27(average for the 4 samples) The amount of additional sequencing needed to bring 80% of bases to the mean coverage. 9 November 2017 page 75 Roche For Research Use Only

Demo Data Packages available now! Product rawdata bamfiles README Gene List Tech note metrics bedfiles SeqCap Epi CP Giant x x x NA x x x Provides you with an easy, low resource way to evaluate our products. Gives you a preview into our performance and our method of data analysis. Helps you make a good decision on which exome or workflow to choose. Gets your Bioinformaticist involved early. 9 November 2017 page 76 Roche For Research Use Only

Other Demo Data Packages DPOP Package SeqCap EZ Exome V3-1 day hybe SeqCap EZ Exome V3-3 day hybe SeqCap EZ Exome V3 + UTR SeqCap EZ MedExome and MedExome + Mito SeqCap EZ Mitome SeqCap EZ MedExome - post-capture multiplexed SeqCap EZ MedExome - Hyper v1.0 SeqCap EZ MedExome - HyperPlus v1.0 SeqCap EZ MedExome - Whole Blood HyperPlus v1.0 SeqCap EZ Inherited Disease Panel SeqCap RNA - lnc RNA SeqCap RNA - Choice VCRome - 1 day hybe VCRome - 3 day hybe SeqCap Epi CP Giant SeqCap EZ Comprehensive Cancer Panel - 1 day hybe SeqCap EZ Comprehensive Cancer Panel - 3 day hybe SeqCap EZ Comprehensive Cancer Panel - FFPE HyperPlus 4 hour v1.0 SeqCap EZ Comprehensive Cancer Panel - HyperPlus v1.0 SeqCap EZ Comprehensive Cancer Panel - Hyper v1.0 SeqCap EZ Comprehensive Cancer Panel - HyperPlus Automation v1.0 HEAT-Seq Oncology Panel HEAT-Seq Choice - CFTR HEAT-Seq Ultra Oncology Hot Spot Panel - NA12878 HEAT-Seq Ultra Oncology Hot Spot Panel - TruQ4 HEAT-Seq Ultra Choice - XXL - Pediatric Tumor SeqCap EZ Exome Design - Neurology SeqCap EZ Exome Design - Soy SeqCap EZ Exome Design - UTR only SeqCap EZ Exome V2 BED Files ONLY SeqCap Epi Design - Human Disease Methylome SeqCap EZ Exome Design - Barley SeqCap EZ Exome Design - Human MHC SeqCap EZ Exome Design - Maize SeqCap EZ Exome Design - Mouse SeqCap EZ Exome Design - Pig SeqCap EZ Exome Design - Switchgrass SeqCap EZ Exome Design - Wheat SeqCap EZ Exome V1 SeqCap EZ Exome Design - Canine DPOP Package includes: Raw data, BAM files (for most), Gene Lists, Metrics, BED files, README and Data Analysis Technical Note 9 November 2017 page 77 Roche For Research Use Only

Discover More, Sequence Less Comprehensive solutions with exome & custom designs SeqCap EZ System Products Design Size SeqCap Epi System Products Design Size EXOME SeqCap Epi CPGiant 84 Mb SeqCap EZ Medexome 47 Mb SeqCap Epi Choice up to 90 Mb SeqCap EZ Medexome Plus up to 200 Mb SeqCap Epi Developer up to 210 Mb SeqCap EZ Exome Library 2.0 44 Mb Human Disease Methylome Design 156 Mb SeqCap EZ Exome Library 3.0 64 Mb SeqCap EZ Exome + UTR 96 Mb SeqCap RNA System Products Design Size SeqCap EZ Exome Plus up to 200 Mb SeqCap RNA Human lncrna 17 Mb HGSC VCRome 45.2 Mb SeqCap RNA Choice up to 7 Mb CUSTOM SeqCap RNA Choice XL 7-100 Mb SeqCap EZ Choice up to 7 Mb SeqCap RNA Developer up to 200 Mb SeqCap EZ Choice XL up to 200 Mb SeqCap EZ Developer up to 200 Mb HEAT-Seq System Products Design Size DESIGNS HEAT-Seq Oncology Panel 60 genes Human Oncology Panel 2.75 Mb (981 genes) HEAT-Seq Ultra Oncology Hotspot Panel 53 genes Comprehensive Cancer 4 Mb (578 genes) HEAT-Seq Choice >5000 genes Neurology Panel 1.5 Mb (256 genes) HEAT-Seq Ultra Choice up to 60 genes Human 50 Mb UTR Human MHC Mitochondria Genome Mouse Exome Pig Exome Soy Exome Maize Exome Wheat Exome Barley Exome Canine Exome Switchgrass Exome 50 Mb 4.97 Mb 16 Kb 54.3 Mb 58.1 Mb 85.3 Mb 110 Mb 106.9 Mb 88.6 Mb 152 Mb 50 Mb For Roche Internal Use Only Do Not Distribute 9 November 2017 page 78 Roche

SEQUENCING Nanopore Technology A semiconductor-based sequencing platform with potential to address the diversity of clinical NGS requirements IMPORTANCE Potential for disruptive technology with high accuracy and fast turnaround Single molecule sequencing (SMS) for increased sensitivity and enhanced structural variant detection Compact format integrates easily into laboratory space Product in development and not commercially available 9 November 2017 page 79 Roche For Research Use Only

Sequencing solution investments Menu & data solutions, contd. Ariosa Diagnostics Dec 2014 Testing service provides highly targeted and accurate Harmony non-invasive prenatal test* (NIPT) in a CLIAcertified laboratory using cell-free DNA technology. The technology has the potential to provide early actionable information in pregnancy, cancer and transplantation, aligning with our personalized healthcare strategy. Bina Technologies Dec 2014 Informatics and data management are critical components of a seamless, end-to-end sequencing solution. Bina offers solutions to improve the efficiency and value of genomic analysis and continues to develop new methodologies and algorithms that link NGS data to disease-relevant genetic markers. * The Harmony Prenatal Test is developed by Ariosa Diagnostics. Ariosa Diagnostics is a laboratory certified under the Clinical Laboratory Improvement Amendments (CLIA). As with other laboratory-developed tests, this test has not been cleared or approved by the US FDA. For Roche Internal Use Only Do Not Distribute 9 November 2017 page 80 Roche

Sequencing solution investments Menu & data solutions CAPP Medical Apr 2015 Focused, next-generation tumor sequencing assays using simple blood draws and cell free DNA (cfdna) technology have the potential to significantly shorten the time to cancer diagnosis and change routine cancer diagnostic monitoring. Signature Genomics Feb 2015 Translational oncology and genomics company offers large blood and tissue biobanks for multiple cancer types, constructed from multicenter prospective clinical studies. Samples are used to validate circulating cell free DNA (cfdna) NGS tests like that of CAPP Medical with retrospective clinical testing. For Roche Internal Use Only Do Not Distribute 9 November 2017 page 81 Roche

Sample Preparation Goals Become the leader in blood-based sequencing, including cell-free DNA Automate and optimize direct-from-sample sequencing Sequencing Goals Continue to seek and support innovation Informatics Goals DATA, ANALYTICS AND REPORTING Committed to Ensuring Success by Developing Disruptive Technology Develop, partner and acquire proprietary end-to-end data management, analytics and reporting 9 November 2017 page 82 Roche For Research Use Only

Bringing Together Best-in-Class Technologies to Craft an End-to-End Solution A global effort, headquartered in Pleasanton, Calif. SAMPLE PREPARATION SEQUENCING ANALYTICS MEDICAL CONTENT For presentation purposes only Not for distribution 9 November 2017 page 83 2017 Roche

Product Overview Circulating Tumor DNA (ctdna) Crowley, E. et al. (2013) Liquid biopsy: monitoring cancer-genetics in the blood Nat. Rev. Clin. Oncol. doi:10.1038/nrclinonc.2013.110 9 November 2017 page 84 Roche For Research Use Only

Product Overview End-to-end Workflow * *The NextSeq 500/550 instruments and associated sequencing reagents are manufactured and sold by lllumina and are not supplied by Roche. 9 November 2017 page 85 Roche For Research Use Only

Product Overview Panel Options Analyze genes in NCCN 1 Guidelines Analyze genes targeted in clinical trials Analyze genes in longitudinal studies # of Genes Size Mutation Classes Targeted Panel Expanded Panel Surveillance Panel 17 77 197 genes 81kb 192kb 198kb SNVs, CNVs, Indels, Fusions NCCN = National Comprehensive Cancer Network 1 National Comprehensive Cancer Network, http:/www.nccn.org October 15, 2016 Data on file. 9 November 2017 page 86 Roche For Research Use Only

Product Overview AVENIO ctdna Targeted Kit SNVs Indels* Fusions** CNVs** Amplifications ALK KRAS ALK ALK EGFR APC MET APC RET ERBB2 BRAF NRAS BRAF ROS1 MET BRCA1 PDGFRA EGFR BRCA2 RET ERBB2 DPYD ROS1 KIT EGFR TP53 MET ERBB2 UGT1A1 KIT Genes with whole exon coverage in bold *Indels are limited to variants in a pre-specified list of positions, referred to as "Loci of Interest", except for EGFR exon 19 long deletions, EGFR exon 20 long insertions and MET long insertions, which are not restricted to a pre-defined set of Indels **Detection of Fusions and CNVs are limited to variants in a pre-specified list of positions, referred to as "Loci of Interest" in the AVENIO ctdna Analysis Software Includes select introns for fusion detection Example: Lung Cancer National Comprehensive Cancer Network EGFR ALK Future Targets KRAS MET BRAF ROS1 ERBB2 Source: ClinicalTrials.gov, NCCN.org, Data on file Includes genes in NCCN Guidelines 9 November 2017 page 87 Roche For Research Use Only

Analysis and Results Variant information Variant information 9 November 2017 page 88 Roche For Research Use Only

Recap Summary Analyze up to 16 samples at a time, using either fastq or bcl format 2 user profiles, 3 gene panels, 4 mutation classes Customizable workflows and annotations Separate reports for sample metrics and sample attributes Summary 9 November 2017 page 89 Roche For Research Use Only

Roche Diagnostics and Pharmaceutical Synergy Positioned for leadership in personalized healthcare DIAGNOSTICS PHARMACEUTICALS Combined strengths of Pharmaceuticals and Diagnostics Synergies in research, development and marketing Unique global network of alliances Best positioned to deliver on the promise of personalized healthcare Confidential. Do Not Distribute.

Roche Sequencing Enabling personalized medicine on a global scale

Doing now what patients need next For Roche Internal Use Only Do Not Distribute 9 November 2017 page 93 Roche