Sequencing Technology and Applica�Ons

Next Genera�on Sequencing technology and applica�ons

Leonardo A. Meza-‐Zepeda, Ph.D. Genomics Core Facility Helse Sør-‐Øst/University of Oslo

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Topics

7 Introduc�on 7 Technologies 7 Applica�ons

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1 Human Genome Project 3 billion bases

Cost approx. 3 Billion Dollars

Public HGP Celera Genomics 1990-‐2003

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Development of Sequencing Technologies

Massively parallel sequencing

Human Genome Project Stra�on MR et al, Nature 2009

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2 Development of Sequencing Technologies last 10 years

ER Mardis. Nature 470, 198-203 (2011)

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Cost per Megabase

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3 Costs for a Human Genome

Capillary Sequencing Next Genera�on Sequencing Applied Biosytems 3730xl HiSeq 2500 (2004) (Today) U$ 15,000,000 U$ 6,000

The Norwegian oslo.genomics.no Radium Hospital

Sequencing Costs per Genome

Costs Genomes

$100M Venter 1M

$10M 100k Watson

$1M 10k African, Asian, Cancer pair

$100k 169 in Genbank 1,000 Individual Genome Cost per Human Genome Human per Cost $10k Sequencing 100

2007 2008 2009 2010 2011 2012 Time

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4 Sequencing Technologies

7 Solexa (Illumina) 7 Sequencing by synthesis 7 454 (Roche) 7 Pyrosequencing 7 SOLiD (Life Technologies) 7 Sequencing by liga�on

7 Non op�cal 7 Ion Torrent/ Ion Proton

7 Single molecule sequencing 7 Helicos, Paciﬁc Biosciences, Nanopores Oxford

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Common a�ributes of commercial sequencers

7 Random fragmenta�on of DNA 7 Liga�on of adapter, crea�on of a library (genome/transcriptome) 7 Library ampliﬁca�on on a solid surface 7 Direct sequencing for single molecule pla�orms 7 Direct step by step detec�on of nucleo�de incorpora�on 7 Shorter read length thank tradi�onal sequencers 7 Digital read type, enables direct quan�ta�ve comparisons 7 Possible to read both ends of a DNA fragment 7 Single read or Paired-‐end reads

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5 Single and Paired Ends Libraries

Single Read

Single Read Library (Up to 100bp) i.e. ChIP-‐Seq, miRNA-‐Seq

Read 1 Read 2

Short Insert Paired-‐Ends Library

200bp → 500bp i.e. RNA-‐Seq, Genomic-‐Seq

Read 1 Read 2

2Kb → Paired-‐end 10Kb read oﬀer advantages for Long Insert Mate Pair Library sequencing larger and complex genomes. i.e. Genomic-‐Seq Facilitates accurate posi�oning (mapping) of the reads compared to single reads

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Paired-‐end Sequencing and Alignment

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6 Mate-‐pair Sequencing and Alignment

Combina�on of short-‐read and mate-‐pair sequence reads for de novo sequencing

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Barcoding Libraries

Library Sequence Separate prepara�on pool sequences

Sequencing of insert and index

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7 Sequencing Technologies

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DNA Fragmenta�on

Adap�ve Focused Acous�cs, COVARIS 7 Acous�c energy wave that converges and focuses to a small-‐localized area 7 Shearing of DNA, RNA, Chroma�n, +++ 7 Random fragmenta�on

Plates

Single Sample

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8 Library Construc�on

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Nextera Library Construc�on, Illumina

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9 Targeted Ampliﬁca�on

HaloPlex (Agilent)

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Targeted Ampliﬁca�on

TruSeq Custom Amplicon (Illumina)

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10 Targeted Ampliﬁca�on

AmpliSeq (Ion Torrent) 12 to 3072-‐plex

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Targeted Ampliﬁca�on

Single Molecule Molecular Inversion Probes

O’Roak BJ, et al Science 2012 Hia� JB, et al Genome Res 2013

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11 Library Ampliﬁca�on, Emulsion PCR

Roche/454 and Ion Torrent/Proton

Metzker, Nature Reviews Gene�cs 2010

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Roche 454, Pyrosequencing

Problems with homopolymers

Metzker, Nature Reviews Gene�cs 2010

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12 Roche/454 Technology

Instrument Run �me (hr) Read Length Yield Error Type Error Rate (%) (bp) (Mb/run) GS FLX 23 1000 700 Mb Indel 1 Titanium XL+ Mean: 700 GS FLX 10 600 450 Mb Indel 1 Titanium XLR70 Mean: 450 GS Junior 10 400 35 Mb Indels 1

7 Mate pair paired-‐end reads of 3 kb, 8kb and 20kb 7 Cost per run makes sequencing an en�re human prohibi�ve 7 Great pla�orm for targeted valida�on 7 Good for de novo sequencing in combina�on with short reads

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SOLiD, Life Technologies

Beads are placed in the surface of the ﬂow cell

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13 SOLiD, Life Technologies

Tucker, Am J Hum Gen 2009 Metzker, Nature Reviews Gene�cs 2010

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SOLiD Technology

Instrument Run �me Read Length Yield Error Type Error Rate (%) (days) (bp) (Gb/run) 5550 W 2 -‐ 8 1 x 50 80 Gb A-‐T bias 0.01 1 x 75 120 Gb 2 x 50 160 Gb 5500xl W 2 -‐ 8 1 x 50 160 Gb A-‐T bias 0.01 1 x 75 240 Gb 2 x 50 320 Gb

7 6-‐lane ﬂow chip with independent lanes 7 Very high accuracy data due to two base encoding 7 Conversion of color space to base space 7 Paired-‐end chemistry enabled 7 Wild-‐ﬁre chemistry being implemented (replaces ePCR)

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14 Ion Torrent/Proton, Life Technologies

Library Construc�on and Emulsion PCR

Semiconductor Chip

Problems with homopolymers

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Diﬀerent Chip Sizes

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15 Instruments

Ion Proton to sequence one human genome per day for U$ 1000

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Illumina Sample Prepara�on

1 Library prepara�on Fragment DNA

Repair ends / Add A overhang

Ligate adapters

Select ligated DNA

2 Automated Cluster Genera�on Hybridize to ﬂow cell

1-‐8 samples Extend hybridized oligos

Perform bridge ampliﬁca�on

3 Sequencing Perform sequencing on forward strand

1-‐16 samples Re-‐generate reverse strand

Perform sequencing on reverse strand

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16 Illumina Library Prepara�on

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Nextera Library Construc�on, Illumina

7 Low DNA input 50 ng 7 Fast Library Prep. 90 minutes 7 Automa�on friendly 7 Larger insert size 7 GC bias (inser�on site)

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17 Illumina Cluster Genera�on

Seq. Library 100 μm (8 pmols)

Single molecule array 3 Billion clusters Library Cluster Growth Cluster Density Prepara�on Ampliﬁca�on

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Sequencing-‐by-‐Synthesis

Terminator and 3 Billion clusters Incorporated x 2x100bp = 600 Gigabases per run Add 4 Fl-‐ ﬂuorescent dye are Fl-‐NTP is NTP’s + cleaved from the Fl-‐ imaged Polymerase 100 exomes 30x NTP 5 human X 36 genomes -‐ 150 30x coverage

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18 Illumina Instruments

2010: HiSeq 2000 • Two flow cells per run, 100 Gbp/FC or one human genome • New scanning mechanics -‐ scans both surfaces of FC lanes 2011: HiSeq 2000 • Improved chemistry: increased yield and accuracy • Approx. 600 GB, 5-‐6 human genomes 2011: MiSeq Personal Sequencer • One flow cells per run • 2x150 bp, approx. 4-‐5 Gb • Fast sequencing, 4-‐27 hrs per run 2012: MiSeq v.2 chemistry • Scans both surfaces of FC, Double the capacity • 2x250 bp, approx. 8-‐10 Gb 2013: HiSeq 2500 • One flow cell per run • RAPID mode, 27hrs sequencing run • One human genome per flow cell 2013: MiSeq v.3 chemistry • Scans both surfaces of FC, Double the capacity • 2x300 bp, approx. 15 Gb

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Illumina

Instrument Run �me Read Length Yield Error Type Error Rate (%) (days) (bp) (Gb/run) HiSeq 2500 2 1 x 36 108 Gb Sub 0.1 High output 5 2 x 50 300 Gb mode 11 2 x 100 600 Gb HiSeq 2500 7 1 x 36 22 Gb Sub 0.1 Rapid mode 27 2 x 100 120 Gb 40 2 x 150 360 Gb MiSeq 4 1 x 50 1.3 Gb Sub 0.1 24 2 x 150 7.5 Gb 65 2 x 300 15 Gb

New development: Ordered array of clusters

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19 Moleculo, Long-‐Read Sequencing

Voskoboynik A, et al eLife 2013

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Single Molecule Sequencing

7 Helicos 7 Paciﬁc Biosciences 7 Oxford Nanopores

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20 Helicos

Top: CTAGTC Bo�om: CAGCTA

Metzker, Nature Reviews Gene�cs 2010

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Paciﬁc Biosciences

7 Single Molecule Real Time (SMRT) sequencing technology 7 No amplification 7 Single pass read accuracy 85% 7 150,000 zero-mode waveguides per SMRT cell 7 Approx. 3-5,000 bp sequence length Metzker, Nature Reviews Gene�cs 2010

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21 Nanopore Technology

Nanopore is, essen�ally, a nano-‐scale hole. 7 Biological: pore-‐forming protein in a membrane (lipid bilayer) 7 Solid-‐state: formed by synthe�c materials, (silicon nitride) 7 Hybrid: pore-‐forming protein set in a synthe�c material

To come

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Data analysis

Fluorescent signal Number Base call Alignment Biological pH change de novo Interpreta�on Conduc�vity

Large IT infrastructure

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22 NGS Applica�ons

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NGS applica�ons

7 Genomes: re-‐sequencing or de novo 7 Point muta�on/indel/structural varia�on discovery 7 Protein:DNA binding 7 Chroma�n IP/histone binding 7 Nucleosome/transcrip�on factor binding, etc. 7 ncRNA discovery/sequencing/variants 7 Transcriptome sequencing (RNA-‐seq) 7 Genome-‐wide methyla�on of DNA (Methyl-‐seq) 7 Clinical sequencing for therapeu�c decisions

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23 de novo Genome Sequencing

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Resequencing

Meyerson et al, Nature Reviews Gene�cs 2010

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24 ICGC

Descrip�on of genomic, transcriptomic and epigenomic changes 7 Data available to the en�re research community 50 diﬀerent tumour types and/or subtypes 7 Clinical and societal importance across the globe 7 Pa�ent-‐matched control samples (500 of each) 7 ~ $ 25 million each project Osteosarcomas (Myklebost/Meza-‐Zepeda) 7 Wellcome Trust Sanger Ins�tute (Michael Stra�on)

Similar US ini�a�ve, The Cancer Genome Atlas (TCGA)

Interna�onal network of cancer genome projects. Nature 2010

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Sequence Capture

-‐ Candidate region -‐ Exome (1/40 genome) Sequencing disease and control Meyerson et al, Nature Reviews Gene�cs 2010 -‐ Private SNPs Mardis ER, Nat Rev Gastroenterology & Hepatology 2012

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25 Metagenomics

Main metagenomics applications, from the metagenomic libraries construction and screening, until next generation sequencing, gene count and genome reconstruction.

Lepage P et al. Gut 2011

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RNA-‐Seq

Single reads Paired-‐End

The Norwegian Radium oslo.genomics.no

26 RNA-‐Seq (Quan�ﬁca�on)

IOR/MOS (Osteosarcoma cell line) Lorenz, et al

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Transcript Variants

RUNX2

Håkelien et al

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27 Alterna�ve isoform regula�on in human �ssues

Exon usage

Wang, Sandberg et al. Nature 2008

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Small RNA Sequencing

Size selec�on

Quan�ﬁca�on Discovery

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28 miRNAs Colorectal Cancer

Schee, et PLoSOne al 2013

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ChIP-‐Seq

Sequencing

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29 Epigene�c Regula�on

The Norwegian oslo.genomics.no Radium

Epigene�c landscapes

H3K4me3 Undiﬀ.

Diﬀ. H3K27Ac Undiﬀ.

Diﬀ. H3K27me3 Undiﬀ.

Diﬀ. H3K36me3 Undiﬀ.

Diﬀ. H3K9AC Undiﬀ.

Diﬀ. H3 Undiﬀ.

Diﬀ.

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30 Gene Expression and Histone Modiﬁca�ons

Håkelien et al

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RNA Sequencing, Fusion Transcript

Gene A Gene B

Fused mRNA

Gene junc�on

Paired-‐end

Adapter1 Adapter2 ACGTTTTCGGATT ACGTTTTCGGATTG Seq-‐primer1 Seq-‐primer2 Read 1 (75 bp) Read 2 (75 bp)

mRNA fragment ~240 -‐280 bp

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31 Fusion Transcript Analysis

mRNA fragment ~240 -‐280 bp

ACGTTTTCGGATTGGC ACGTTTTCGGATTGGC Read 1 (75 bp ) Read 1 (75 bp ) 70 Millions reads Mapping to transcriptome and genome

Candidate fusion genes: not correctly mapped reads

Spanning reads

Gene A ACGTACTCGGATTGGC ACGTTAACGGATTGGC Gene B Breakpoint Fusion transcript CGGATTGGCTGGCTCA ACGTTCTCGGATTGGC ACGTTTTCGGATTGGA ACGTTTTCGCGGATTG

Breakpoint reads

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Filtering Candidate Fusions

Sample Fusions Star�ng with 2597 reported fusions IOR-‐MOS 34 IOR-‐OS15 404 Pipeline IOR-‐OS18 547

MHM 56 Filter fusions Filter found in Filter read-‐ repete�ve/low Filter ribosomal OSA 191 normal control through events complex. seq. protein �ssues breakpoint ZK58 391

KPD 248 -‐ 491 -‐ 65 -‐ 27 -‐ 590

MG-‐63 324

SAOS-‐2 175

IOR-‐OS10 38 … s�ll 1424 fusions, 1100 unique

SARG 189 Total 2597 Lorenz et al

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32 Breakpoint at Genomic Level

IOR-‐OS15

PMP22 ELOVL5

K. Szuhai, Leiden

RNAseq only + DNAseq

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Circula�ng Tumour DNA

Leary et, Sci Transl Med 2012

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33 Biomarkers

Leary R J et al. Sci Transl Med 2010

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Non-‐invasive prenatal test

Bianchi DW, Nature Medicine 2012

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34 DNA Methyla�on

Gene silencing

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Bisulﬁte Sequencing

Bisulﬁte conversion

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35 Aﬃnity-‐based Methods (enrichment)

MeDIP-‐Seq MBD-‐Seq

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Reduced Representa�ons

Reduced Representa�on Bisulﬁte Seq. 7 0.01-‐ 0.3 ug of DNA 7 Base pair resolu�on 7 Theore�cal genomic coverage 10% 7 CpG rich regions

Deep Sequencing

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36 Detec�ng DNA Base Modiﬁca�ons

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WGBS of a newborn (NB) and a centenarian (Y103) individual

Genome-wide DNA methylation levels in the NB, Y26, and Y103 individuals

Heyn H et al. PNAS 2012

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37 Personalised Medicine

Making the treatment as individualized as the disease, by iden�fying gene�c, genomic, and clinical informa�on that allows accurate predic�ons to be made about a person's suscep�bility of developing disease, the course of disease, and its response to treatment.

Advantages of personalised medicine 7 Ability to make more informed medical decisions 7 Higher probability of desired outcomes thanks to be�er-‐targeted therapies 7 Reduced probability of nega�ve side eﬀects 7 Earlier disease interven�on 7 Reduced healthcare costs

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Cancer classiﬁca�on based on genomic proﬁle

Gene Reflec�ng profile A mechanism that driver tumour growth, possible sensi�vity to specific targeted therapy

Gene proﬁle C Gene proﬁle B

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38 Treatments based on genetic profiles

Treatment lung cancer Treatment colon cancer

Sequencing

Colon treatment Sarcoma treatment for lung cancer? for colon cancer?

New medicine?

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Targeted Resequencing of Cancer Genes

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39 Lung cancer incidence

20 Women Men 15

10 Per 100 000 person-years Per

0 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007

Men :29% increase (absolute numbers) Women: 163% increase (absolute numbers) Age-‐adjusted incidence : 36/100000 (men) (1,4% annual increase) 28/100000 (women) (4,9% annual increase)

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A deadly Disease

Males Females

Cancer incidence in Norway 2005-‐2009

Cancer Register of Norway

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40 Poor Prognosis

Localized disease 5 –year survival: Males 44 %, Females 55 % Need for new therapeu�c op�ons

Cancer Register of Norway

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Personalised Cancer Medicine

Aims: To map muta�on frequencies in lung cancer Iden�fy novel therapeu�c targets

7 Large lung cancer biobank ( Drs. Helland and Brustugun) 7 430 clinical surgical biopsies, NSCLC 7 Early stage 7 Untreated samples 7 100 cases, tumour/normal pair 7 Targeted resequencing 7 All kinase genes + 100 cancer genes 7 All exons and UTRs 7 Cancer Clinic, Bioinforma�cs and Genomics CF

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41 Kinases Regulate Cell Signaling

Kinases Targeted in Clinical Trials

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Agilent Kinome Set

Inositol ADDITIONAL PROTEIN KINASE PI3K DOMAIN DIGLYCERIDE PIK3 REGULATORY polyphosphate PIP4/PIP5 CANCER GENES BREAST CANCER MORE CANCER GENES (517) PROTEINS (12) KINASES (13) COMPONENTS (6) kinases (9) kinases (9) (20) GENES (16) GENES (11) AAK1 PIK3C2A AGK PIK3R1 IP6K1 PIKFYVE CDC6 COL1A1 CCND1 AATK PIK3C2B CERK PIK3R2 IP6K2 PIP4K2A CHD3 GAB1 CCND2 ABL1 PIK3C2G DGKA PIK3R3 IP6K3 PIP4K2B HRAS HAUS3 CCND3 ABL2  PIK3C3 DGKB PIK3R4 IPMK PIP4K2C KRAS IRS2 ESR1 ACTR2 PIK3CA DGKD PIK3R5 IPPK PIP5K1A NRAS IRS4 ESR2 ACVR1 ATM PIK3CB DGKE PIK3R6 ITPK1 PIP5K1B PTEN KIAA1468 FBXW7 ACVR1B AXL PIK3CD DGKG ITPKA PIP5K1C CDH1 KLHL4 IDH1 ACVR1C CDKs PIK3CG DGKH ITPKB PIP5KL1 TP53 NFKB1 IDH2 ACVR2A PI4KA DGKI ITPKC PIPSL CDKN2A NFKBIA MLH1 EGFR ACVR2B PI4KB DGKQ CDKN2B NFKBIE TERT ACVRL1 FGFRs PI4K2B DGKZ APC PALB2 ADCK1 FLTs PI4K2A SPHK1 RB1 RHEB ADCK4 SPHK2 CTNNB1 RNF220 IGF1R ADCK5 BRCA1 SNX4 ADRBK1 JAK1 BRCA2 SP1 ADRBK2 KIT NF1 USP28 AKT1 MAPKs NF2 AKT2 GATA3 MET AKT3 MYC ALK MTOR INPP4A PDGFRs RAF1 TGFBRs 612 genes, total 3.2 Mbp

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42 Analysis Pipieline

Calling DNA copy Genomic Mapped Calling soma�c number Indels rearrange-‐ Annota�on reads varia�ons muta-‐ changes ments �ons

Soma�c Muta�on Detec�on Pipeline

Collabora�on with UiO HSØ/ Bioinforma�cs Core Facility

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Single Nucleo�de Variants

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43 Soma�c Muta�on Distribu�on

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Func�onal and Clinical Annota�on Pipeline

Sigve Nakken et al

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44 EGFR Muta�on

CTG>CGG Leu>Arg Missense Muta�on Lorenz, Nakken, Vodak , Madoui, et al

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EGFR mutations in lung cancer

EGF ligand binding Tyrosine kinase Autophos

TM K DFG Y Y Y Y

718 745 776 835 858 Y869 947 964

GXGXXG K R H DFG R Y M LREA

Most TKI responders have EGFR muta�ons i.e. Iressa and Tarceva

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45 EGFR in lung cancer

Ligand 7 Epidermal Growth Factor Receptor L-‐domain 7 Muta�ons increase ac�vity of EGFR Furine-‐like domain 7 Increased cell survival and prolifera�on L-‐domain 7 Drives tumour growth Extracellular domain 7 EGFR inhibitor Transmembrane domain Intraracellular domain 7 Pa�ents treated with EGFR inhibitors EGFR Lung cancer before treatment Lung cancer a�er treatment Tyrosine kinase domain

Survival Prolifera�on 10-‐15% of pa�ents with EGFR muta�ons

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Pao & Chmielecki, Nat Rev Cancer 2010

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46 Norwegian Cancer Genomics Consor�um www.cancergenomics.no

Oslo, Bergen, Trondheim and Tromsø Key inves�gators 7 Ola Myklebost, PI, OUS 7 Ragnhild Lothe, OUS 7 Harald Holte, OUS Transla�onal medicine group 7 Per Eystein Lønning, Haukeland 7 Anders Waage , St Olavs 7 Giske Ursin, Norwegian Cancer Registry 7 Leonardo A. Meza-‐Zepeda, OUS, Sequencing Technology 7 Eivind Hovig, OUS, Bioinforma�cs

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NCGC Project Sequencing 4000 tumour/blood pairs Exome and custom targeted resequencing Different cancer types 7 Breast cancer, Lymphoma, Leukemia, Colorectal cancer, Malignant melanoma, Sarcoma, Mul�ple 7 Provide myeloma, a na�onal Gynecological network for cancers, implementa�on Prostate of personalised cancer cancer medicine in Norway 7 Provide and disseminate methodology for sequencing of tumour material and iden�fica�on of soma�c muta�ons 7 Ini�ate a number of research projects to determine the applicability of muta�on profiles from the individual tumour for therapeu�c decisions

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47 NCGC data logis�cs

Myeloma Bioinforma�cs Sequence Lymphoma

Leukemia OUS

Colon Na�onal

Melanoma muta�on database Haukeland

Prostate

Breast Cancer registry St Olavs Sarcoma

Clinical data Accumulated Others? na�onal data oslo.genomics.no

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48 DNase-‐Seq

Iden�fy open chroma�n associated with ac�ve DNA elements Foot print of transcrip�on factors Zeng et al, Nature Immunology 2012

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Chromosome Conforma�on Capture

Similar for 4C, ChIA Hi-‐C, -‐PET Stadhouders, et al Nature Protocols 2013

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49 Ribosome Proﬁling

Ingolia, et al Nature Protocols 2012

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