Overview of Next Generation Sequencing platform technologies

Next Generation Sequencing Core Facility

Next Generation Sequencing Core Facility

Max Planck Institute for Molecular Genetics Max Planck Institute for Molecular Genetics Berlin, Germany

Berlin, Germany

Dr.

Bernd

Timmermann

Overview

of

Next

Generation

Sequencing

platform

technologies

1. Technologies



Illumina



Roche / 454

2. Projects and Applications



whole Genome Re-sequencing



Sequence Capture



Amplicon Sequencing

3. Outlook

Outline

Max Planck Society

Max Planck Institute for molecular Genetics

80

institutes

and

research

facilities

20,435

people

Budget

1,400

million

euro

in

2010

1980 1985 1990 1995 2000 2005 2010 1000,000,000 100,000,000 10,000,000 1,000,000 100,0000 10,000 1000 100 10 Gel-based Systems Capillary Sequencing Next Generation Sequencing First Generation Capillary Sequencer Second Generation Capillary Sequencer Microwell Pyrosequencing Short-Read Sequencer Throughput pe r s y s te m [k ilobas e s /da y ] Year

Modified after MR Stratton et al. Nature458, 719‐724 (2009)

Development of Sequencing Throughput

Development of Sequencing Technologies

• 96 sequences in parallel

• 3.2 billions of sequences

per run

Human Genome Project

1000 Genomes Project

7 x Illumina

3 x SOLiD

5 x Roche GS

Sequencing Capacities

at the MPI-MG

3 x Capillary Systems

IT Infrastructure

25 x 32 (64) Compute Server with 128 (512 GB) RAM 4 peta byte Storage Capacity

1. Technologies



Illumina



Roche / 454

2. Projects and Applications



whole Genome Re-sequencing



Sequence Capture



Amplicon Sequencing

3. Outlook

Technologies

Genome Sequencer FLX

HiSeq 2000/

SOLiD

• Sequencing of target regions

• Whole genome resequencing

• de novo Sequencing

• Metagenome Analyses

• Amplicon Sequencing

• Full length Transcriptome Analyses

• Sequencing of target regions

Principle Illumina Sequencing

Library

Preparation

Attachement of single molecules to surface

Amplification to form clusters

Cluster

Generation

5’ G T C A G T C A G T C A G T 3’ 5’ C A G T C A T C A C C T A G C G T A

First base incorporated Cycle 1: Add sequencing reagents

Remove unincorporated bases Detect signal

Cycle 2-n: Add sequencing reagents and repeat

Sequencing by Synthesis (SBS)

Referenzsequenz ....CGAGCGAATGAAGTCGGGAGTCGTAATGAGCCCGTAATCCCGTTAGTA.... CGAGCGAATGAAGTCGGGAGTCCTAATGAGCCCGTA GAGCGAATGAAGTCGGGAGTCCTAATGAGCCCGTAA CGAATGAAGTCGGGAGTCCTAATGAGCCCGTAATCC TGAAGTCGGGAGTCCTAATGAGCCCGTAATCCCGTT TCGGGAGTCCTAATGAGCCCGTAATCCCGTTAGTA Sequence Reads

Conversion of image data to DNA sequences

Input Material:

~ 1-3 µg DNA shotgun Sequencing

~ 10 ng

ChipSeq

Sequencing

Library Preparation:

~ 1.5 days

Cluster Generation:

~ 1 day

Run Time/

Single read ~ 2 days (36 b)

Read Length:

Paired End ~ 10 days (2 x 100 b)

Data Processing:

~ 1 day

Output:

Paired End ~ 500 Gb

Reads:

up to 4800 Mio

Facts Illumina Sequencing (HiSeq 2000)

1. Genome is loaded into a PicoTiter™ plate 3. Load Reagents in a single rack 4. Sequencing 2. Load PicoTiter

plate into instrument

454 Sequencing Instrument

Principle 454 Sequencing

Library Preparation

Emulsion PCR

Depositing DNA Beads into the PicoTiter™Plate Pyrosequencing

Emulsion Breaking

Input Material:

~ 0.5 µg DNA

Library Preparation :

~ 4 hours

Emulsion PCR:

~ 1 day

Run Time:

20 hours

Data Processing:

~ 10 hours

Output:

Titanium+ 700 -

1000 MB

Reads:

Titanium+ 1.000.000 -

1.600.000

Read length:

700 -

800 bases

Facts 454 Sequencing

Sequencing Pipeline

1. Technologies



Illumina



Roche / 454

2. Projects and Applications



whole Genome Re-sequencing



Sequence Capture



Amplicon Sequencing

3. Outlook

Projects and Applications

Goals

• A public database of essentially all SNPs and detectable CNVs with allele frequency >1% in each of multiple human population samples

• Pioneer and evaluate methods for:

• Generating data from next-generation sequencing platforms

• Exchanging and combining data and analytical methods

• Discovering and genotyping SNPs and CNVs from nextgen data

• Imputation with and from next generation sequencing data

• 454, Illumina and AB SOLiD platforms

• Academic genome centers in US, UK, Germany, China and platform companies

(Nature 2010, Science 2010 and Nature 2011)

OncoTrack, “Methods for systematic 

next generation oncology biomarker 

development”, 

is an international consortium of over 

60 scientists, that has launched one of 

Europe’s largest collaborative academic‐

industry research projects to develop 

and assess novel approaches for 

identification of new markers for colon 

cancer. 

DNA

RNA

Protein

Methylation

Mutations

mRNA

miRNA

Cell

lines

Tissues

Sequencing

Bioinformatics

RNAseq

expression profiling total RNA Isolation

quality control small RNA Depletion

dsDNA generation using random hexamers

Illumina library preparation

massive parallel sequencing

Mapping

GWAS

Candidate

Genes

Whole

Exome

0.5 –

5 MB

35 MB

385 k Array, Nimblegen

In-solution

Enrichment

2.1 Mio Array, Nimblegen

In-solution

Enrichment

Sequence Capture

Targeted Resequencing:

Project outline

Identification patients Sequence capture

Next-Gen sequencing “Bioinformatics” Follow-up sequencing Functional characterization

Work-flow

Principle of sequence capture

DNA Preparation Enrichment of target regions Sequencing

A1 SP1 A2 genomic DNA Fragments (200‐500bp) Ligation of adapters Hybridization  Selection with  streptavidin beads Amplification and  Quantification May 23rd 2012, Budapest

Cleft lip with or without cleft palate (CL/P)

Cooperation with M. Nöthen and E. Mangold

•

Prevalence among live births

~ 1 : 1.000

•

Risk for siblings 1 : 20 –

1 : 25

•

λ

40 -

50

Epidemiology of

Epidemiology of

nonsyndromic CL/P

nonsyndromic CL/P

Mangold E. et al. (2010), Nature Genetics

•

3 Loci on chr 8 (640Kb), 10 (161Kb) and 17 (340Kb)

in 20 affected individuals

•

MID tagging and pooling of 10 samples

•

Enrichment using the 2.1M NimbleGen array

•

Sequencing on a Roche GS FLX system

Cleft lip with or without cleft palate (CL/P)

Resequencing as follow up of GWAS

Mapping

•

•

6.726 unique variants (>10 x Coverage)

•

•

3.783 variants not listed in dbSNP (hg19)

•

•

4 coding Variants

•

•

Detection of structural Variations not yet finished

Cleft lip with or without cleft palate (CL/P)

Preliminary Results

Mutation detection pipeline quality

Concordance with Affymetrix Array "genome-wide human SNP array 6.0"

Aim

Detection and quantification of new and known variants

METHOD

Amplification and sequencing of target regions

Multiple alignments of sequences against a reference

reference

patient sequences

Amplicon Sequencing

Amplicon Sequencing

emPCR Amplificationand sequencing

•

Long

reads

required

to

sequence

through

the

locus

specific

primer,

enable

haplotyping

over

longer

distances

•

100s

to

1000s

of

amplicon

clones

sequenced

simultaneously

Amplicon Sequencing

IRON Study

I

nterlaboratory

Ro

bustness of

N

GS

Amplicon Sequencing

IRON Study

Hematology Focus Group

Amplicon Sequencing

IRON Study

Results

• per each amplicon, the median coverage eached was 713-fold, ranging from 553-fold to 878-fold

• a total of 92 variants (44 distinct mutations and 10 SNPs) were observed

• in comparison to data available from Sanger sequencing, 454 amplicon deep-sequencing detected all mutations and SNPs that were previously known

• we here confirm in a multicenter analysis that amplicon-based deep-sequencing is technically feasible, achieves a high concordance across multiple laboratories, and

therefore allows a broad and in-depth molecular characterization of hematological malignancies.

Kohlmann et al. (2011), Leukemia

Sensitivity

of

mutation

detection

as

a

function

of

tumor

cell

content

Querings et al. (2011), PlosOne

Establishment of small scale NGS systems

Analysis of complete genomes

Personalized medicine

Outlook

Acknowledgments

Hans Lehrach

Bernhard Herrmann

Hilger Ropers

Martin Vingron

Michal Schweiger

Martin Kerick

Markus Ralser

Sequencing Facility:

Ilona Hauenschild

Sonia Paturej

Tina Moser

Ina Lehmann

Norbert Merges

Daniela Roth

Sabrina Rau

Heiner Kuhl

Sven Klages

Martin Werber

Thanks