[PPT] - Le squenage trs haut dbit: dveloppements et applica4ons dans les PowerPoint Presentation

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Le séquençage à très haut débit:

développements et applica4ons dans les domaines de la Recherche et la Santé

Laurent FARINELLI 17 November 2016

Journées Suisse Romande de forma;on Laboratoire et médecine SILAMED 2016

Lausanne

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Fasteris

Celebra(ng 20 years of DNA clusters:

Probably the longest experience with illumina NGS

Celebra(ng 10 years of illumina NGS:

Fasteris was the first service provider in the world to acquire an illumina instrument

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20

years

f DNA

clusters

10

years illumina NGS

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DNA and PCR?

Who is familiar with DNA and PCR?

3

? !

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Nucleus versus Ball

4 There is 2 meters

f DNA in a cell

Nucleus: 0.003 mm Basket ball: 300 mm There would be 200 km in a basket ball

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Human genome length

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If human DNA was uncoiled and set end-to-end, it

would represent 140 (mes the distance Earth - Sun

150 000 000 km

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DNA vs RNA

6 3’ 5’

O OH P OH RiboNucleic Acid

Base

O OH P DeoxyriboNucleic Acid

Base

5’ 3’ 5’ 3’ 5’ 3’ 5’ 3’

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DNA Replica4on

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DNA polymerase:

1 Unidirectional 5’g3’ 2 Requires a template 3 Requires a primer Tools:

PCR
DNA Sequencing

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Liga4on: « colle » moléculaire

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DNA ligase:

1 Colle des brins 2 A besoin de 5’-phosphate Outils:

Clonage d’ADN

5’ 3’ 5’ 3’

P P P

5’ 3’ 3’ 5’

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Ciseaux moléculaires

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5’ 3’ 5’ 3’

TACCGAATTCTAGG-
ATGGCTTAAGATCC-

Enzyme de Restriction :

1 Séquence reconnue

TACCG AATTCTAGG-
ATGGCTTAA GATCC-

5’ 3’ 5’ 3’

5’ 3’ 3’ 5’ Outils:

Clonage d’ADN

Nucleases non-spécifiques :

Endonucleases Exonucleases

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Ou4ls de Biologie Moléculaire

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Clonage d’ADN Polymerase Chain Reac(on (PCR) Séquençage d’ADN

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Clonage d’ADN

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Polymerase Chain Reac4on (PCR) Amplifica4on de l’ADN

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Polymérase (enzyme)

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Polymerase Chain Reac4on (PCR)

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3’ 5’ 3’ 5’ 3’ 5’ 3’ 5’ 3’ 5’ 3’ 5’ 3’ 5’ 3’ 5’

5’ 5’ 5’ 5’ 5’ 5’ 3’ 3’ 3’ 3’ 3’ 3’

Cycle 1

3’ 5’ 3’ 5’

Cycle 2 n cycles => 2n copies

3’ 5’ 3’ 5’

5’ 5’ 5’ 5’ 5’ 5’ 3’ 3’ 3’ 3’ 3’ 3’ 5’ 5’ 3’ 3’ 5’ 5’ 3’ 3’ 5’ 5’ 3’ 3’ 5’ 5’ 3’ 3’

Cycle 3 …

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Electrophorèse sur gel d’agarose

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DNA sequencing?

Who is familiar with Sanger sequencing?

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? !

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Séquençage d’ADN

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Méthode Sanger

OH DeoxyriboNucleic Acid

O

P

3’ 5’

Base

O O

5’

O O O

3’

é

Di

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Sanger Sequencing

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GCGAATGCGTCCACAACGCTAC GCGAATGCGTCCACAACGC GCGAATGCGTCCACAAC GCGAATGCGTCCAC GCGAATGCGTCC GCGAATGCGTC GCGAATGC GC

ddCTP

GCGAATGCGTCCACAACGCTACA GCGAATGCGTCCACAACGCTA GCGAATGCGTCCACAA GCGAATGCGTCCACA GCGAATGCGTCCA GCGAA GCGA

ddATP

GCGAATGCGTCCACAACGCT GCGAATGCGT GCGAAT

ddTTP

GCGAATGCGTCCACAACG GCGAATGCG GCGAATG GCG G

ddGTP GCGAATGCGTCCACAACGCTACA G T A C

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Sanger Sequencing

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GCGAATGCGTCCACAACGCTAC GCGAATGCGTCCACAACGC GCGAATGCGTCCACAAC GCGAATGCGTCCAC GCGAATGCGTCC GCGAATGCGTC GCGAATGC GC

ddCTP

GCGAATGCGTCCACAACGCTACA GCGAATGCGTCCACAACGCTA GCGAATGCGTCCACAA GCGAATGCGTCCACA GCGAATGCGTCCA GCGAA GCGA

ddATP

GCGAATGCGTCCACAACGCT GCGAATGCGT GCGAAT

ddTTP

GCGAATGCGTCCACAACG GCGAATGCG GCGAATG GCG G

ddGTP GCGAATGCGTCCACAACGCTACA G T A C

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Sanger Sequencing

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GCGAATGCGTCCACAACGCTAC GCGAATGCGTCCACAACGC GCGAATGCGTCCACAAC GCGAATGCGTCCAC GCGAATGCGTCC GCGAATGCGTC GCGAATGC GC

ddCTP

GCGAATGCGTCCACAACGCTACA GCGAATGCGTCCACAACGCTA GCGAATGCGTCCACAA GCGAATGCGTCCACA GCGAATGCGTCCA GCGAA GCGA

ddATP

GCGAATGCGTCCACAACGCT GCGAATGCGT GCGAAT

ddTTP

GCGAATGCGTCCACAACG GCGAATGCG GCGAATG GCG G

ddGTP GCGAATGCGTCCACAACGCTACA G T A C

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Automated Sanger Sequencer

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NGS DNA sequencing?

Who is familiar with NGS?

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? !

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Massively parallel sequencing

Instead of reading one page at a (me We start reading one leaer at a (me,

from each page simultaneously!

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Massively parallel sequencing

Sanger sequencing

One run in 1-2 hours
Read lengths of 800-1100 bases
Up to 96 (384) sequences in parallel

Next-genera(on sequencing

One run in 1-2 hours to more than 6 days !
Read lengths of 50-300 bases or even up to 40 kb
From 1 million to 5 billions sequences in parallel
A lot of diversity depending on the instruments

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Massively parallel sequencing

Single molecules or clonal amplifica(on? Either:

Amplify signal first
Amplify signal at later stage,

during image acquisi(on

A basic rule of physics:

Amplify signal as soon as possible, else you will amplify more and more noise

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Single Molecules

Simpler sample prep Longer reads But also

Higher challenge
Lower accuracy
Challenge of detec(on (requires highly sensi(ve

detectors, which are ofen fragile and/or costly)

Expect lower throughput

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454 Corpora4on

Based on pyrosequencing,

developed in Sweden by Pål Nyhren and Mostafa Ronaghi

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GS - FLX GS - Junior

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454 Corpora4on

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GS - FLX GS - Junior

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Thermo Fisher

Ion S5

2.5 h run for 100 bases, 4h for 400 bases Three chips

Ion 520, 1 - 2 Gb
3-5 million reads
200 or 400 bases reads
Ion 530, 3 - 4 Gb
15-20 million reads
200 or 400 bases reads
Ion 540, 10 - 15 Gb
60-80 million reads
200 bases reads

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Ion S5

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Pacific BioSciences

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Oxford Nanopore

Based on single-molecule sequencing Designed hand-held device MinION

Priced for USD 1000.-
Can sequence 2000 nanopores at a (me
Launched in 2015

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Everything started in 1996 in Geneva..

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With the invention of DNA Colonies.. ..at GlaxoWellcome “Geneva Biomedical Research Ins(tute”

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The DNA Colonies ..

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1996-1997: GlaxoWellcome’s Geneva Biomedical Research Institute Mayer P., Farinelli L. and Kawashima, E., 1997, Patent applica(on WO 98/44151

...now know as DNA Clusters

Key technology for illumina sequencing

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DNA Colonies and in situ Sequencing

33 In situ amplification

1996-1997: GlaxoWellcome’s Geneva Biomedical Research Ins(tute 1998-2000: Serono 2000-2003: Manteia Predic(ve Medicine 2004- :

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DNA Colonies: Random Arraying

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10 microns

Up to 10’000’000 DNA colonies / cm2

1996-1997: GlaxoWellcome’s Geneva Biomedical Research Institute 1998-2000: Serono 2000-2003: Manteia Predictive Medicine 2004- :

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DNA Colonies: Random Arraying

35 DNA Colony Template Common ends Variable part (DNA to be analysed) Common ends Functionalized surface Elongation and denaturation

DNA polymerase 5’-end covalently aaached 3’-end free

1996-1997: GlaxoWellcome’s Geneva Biomedical Research Institute 1998-2000: Serono 2000-2003: Manteia Predictive Medicine 2004- :

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Genera;on of DNA Colonies

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Annealing Elongation Denaturation

1996-1997: GlaxoWellcome’s Geneva Biomedical Research Institute 1998-2000: Serono 2000-2003: Manteia Predictive Medicine 2004- :

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Base-by-base sequencing

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1

1. Incorporation
Polymerase
The 4 nucleotides, labelled and blocked on the 3’-end

Only 1 base is added on each DNA colony

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Base-by-base sequencing

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1

T T

2. Image acquisition
The most time consuming step

=> Real-time base-calling

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Base-by-base sequencing

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T T

3. De-blocking
Remove label
de-block 3’-end

=> Ready for next incorporation

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Base-by-base sequencing

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1 2

T T T G

Cycle 2, the second base is read One cycle takes ~1 hour

(15 min. chemistry, 45 min. scanning the flow-cell)

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Base calling from raw data

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1 2 3 7 8 9 4 5 6

T T T T T T T G T … T G C T A C G A T …

1. Convert images into intensity files (text files)
2. Base calling from each x, y position
3. Filtration of sequences

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Revolu;on in Throughput

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1 page Village 1’000 inhabitants One lane, one sample .. Capillary Sequencer

A library with 75’000 books

f 1000 pages each

3,7 km of books

Illumina HiSeq 10x Earth’s

7’000’000’000 inhabitants

1 gene

Human genome at 25x coverage

75’000’000x

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The Genome Analyzer revolu;on

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Sequencing speed

4 10 300 50 100 150 200 250 300 350 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 Year Bases / sec

7 instruments ABI 377 1 setup ABI 3730xl Solexa 1G

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Tremendous Speed Increase

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Sequencing speed

10000 20000 30000 40000 50000 60000 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Year Bases / sec

7 instruments ABI 377 1 setup ABI 3730xl GA 1G GA II P-E GA IIx Pipeline 1.6 GA II Pipeline 1.4

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HiSeq 2000, 2500 and 1Tb

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Sequencing speed

100000 200000 300000 400000 500000 600000 700000 800000 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Q2, 2010 Q2, 2011 Year Bases / sec

7 instruments ABI 377 1 setup ABI 3730xl GA 1G GA II P-E GA IIx Pipeline 1.4 and 1.6 HiSEQ-2000 June 2010 HiSEQ-2000 June 2011 HiSEQ-2500 1Tb Mid-2014

1.9 mio

bases per second

installed April 2014

165 Gb per day on 1 HiSeq 1Tb

55x coverage human

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HiSeq 4000

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New patterned flow-cells Reads of up to 2 x 150 bp (HiSeq 2500: 2x125) Run of 3.5 days for 2x150 bp (HiSeq 2500: 6 days) 300-350 million pass filter clusters per lane (v3: 250 mio)

90 - 105 Gb per lane

720-840 Gb per flow-cell or over 6 Tb for 2 FC

Over 12 human genomes in a 4 days run Over 100 human exomes or transcriptomes

per run

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NGS instruments at Fasteris

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HiSEQ-2500 1Tb HiSEQ-2500 1Tb HiSEQ 4000

3 HiSeq

MiSeq

1 NextSeq 2 MiSeq

NextSeq MiSeq Ion S5

1 Ion S5 2 Protons

Ion Proton Ion Proton

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2003, founda;on of Fasteris

48 Everything started in a chalet...

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About Fasteris

2003:

Founda(on of Fasteris in Geneva, Switzerland, to provide Sanger DNA sequencing services

2007:

First service provider in the world to acquire a Solexa (now illumina) NGS instrument

Today:

Providing DNA sequencing services for research, industrial and medical laboratories

Most important: our Work, Customers, Team Worldwide reputa(on of quality and excellence

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About Fasteris & Sonic

2013:

Par(cipated to the development and launch of the first Swiss non-invasive prenatal test (NIPT)

Joined the Medisupport Network, crea(ng a unique partnership

f Diagnos(cs – NGS – Bioinforma(cs

2015:

Medisupport joined Sonic Healthcare, now 28’000 employees, No 1 in Europe for Medical Diagnos(cs

Cer(fied ISO 9001 : 2008

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Fasteris team

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Research Nadine VINCENT Magne OSTERAS

Sales & Marketing

Axel STRITTMATTER François ALLER Svetlana SKARUPELOVA

NGS Library Prep

Cécile DELUEN SAGNE Christelle BARRAS Elisabeth DIETERLE ZARE Cristel BUSCA Franz PELEGRIN Sonia PERREIRA Pauline CHARRUAU

Sanger Sequencing

Anne SCHOENDORF Virginie CARNEJAC Christophe BUSER

Bioinformatics & IT

Loïc BAERLOCHER Nicolas GONZALEZ Patricia OTTEN Manuele CASTELNUOVO Gérald BLANC

Development

Marta COTADO

NGS Runs

Cécile DELUEN SAGNE Vianney FRIGARD Fanny JOLY

Administration

Laurent FARINELLI Gilles MATTON Isabelle LOROLE

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Applica;ons performed at Fasteris

Genomes

Re-sequencing
Bacteria, yeast, plant, animals, viruses
Metagenomics
Epigene(cs with bisulfite
Targeted re-sequencing
PCR products, pooled samples
SureSelect, AmpliSeq or illumina target enrichment
De novo sequencing
Bacteria, insect, mammalian, plant
Fasteris mate-pairs

ChIP-SEQ.

Small RNAs

Profiles, comparisons
de novo assembly of viruses

Transcriptomes

Stranded mRNA-SEQ whole transcriptome

Medical analyses Custom applica;ons

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DNA applica;ons and protocols

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Nextera XT kit (low quantity of starting material) Methylome with Bisulfite treatment Truseq Genomic Nano kit Nextera Mate Pair kit 3-5 kb “inserts” Fasteris protocol for de novo sequencing Personalized project Enrichment protocols

Agilent QXT
Illumina Target Enrichment

TruSeq ChiP-SEQ kit

Protein-DNA binding sites de novo assembly Metagenomes Epigenetics Re-sequencing Variant calling

(SNPs, short InDels)

Copy Number Variation

ChIP

Exomes Cancer panels

Total DNA

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2008 ChIP-Seq

Prof. André Fischer, Göpngen, Germany

Mouse with age-related memory loss

Protocol from very low amounts of material

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2008 First bacterial metagenomics paper using illumina NGS 2008 Genomic Research Laboratory University Hospital of Geneva

Bacteria present in oral samples

Sequencing of 16S amplified region

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2008-2009 Amplicons

Laboratory of Virology University Hospital of Geneva

Virus quasi-species

Sequencing of PCR amplified regions

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2009 Whole Exomes

“Liquid Cancer” muta4on detected

Group of Dr. E. TIACCI, University of Perugia, Italy Muta(on found by SureSelect and validated by Sanger in 100% of the

47 pa(ent with same phenotype

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February 2011 The ant genome

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and laboratories in Taiwan, Denmark, USA, Germany, Australia, Finland

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RNA applica;ons and protocols

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Personalized project

Small RNA Total RNA

Fasteris Protocols Illumina protocol improved for de novo sequencing TruSeq Stranded mRNA kit (polyA purification)

Small RNA Size/sequence profiles miRNA expression comparison piRNAs studies virus assembly / identification Transcriptome de novo assembly; transcript annotation and expression comparison Expression comparison Splice variants Variant calling Genome annotation

TruSeq small RNA kit TruSeq Stranded total RNA kit (prokaryote or eukaryote RiboZero treatment) non-coding RNA Illumina protocol improved to remove 2S rRNA

Drosophila small RNA Degraded RNA Non-coding RNA

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Transcriptome in micro spider

Fruisul collabora(ons with a consor(um led by Mike Grbic of the University

f Western Ontario

Original mRNA-SEQ protocol done on Fny amounts of RNA

First spider genome
Expression showed host-related varia(ons

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2009 de novo assembly of virus

Using small RNAs to assemble de novo viral genomes

Sequencing by siRNA: a novel generic tool for virus discovery

Kreuze et al. (2009) Complete viral genome sequence and discovery of novel viruses by deep sequencing

f small RNAs: a generic method for diagnosis, discovery and sequencing of viruses. Virology 388: 1-7

Sequencing by siRNA: complete nucleo(de sequence of SPFMV-Piu3 and ~50% of genome of three novel viruses Data kindly provided by

Dr. Jan KREUZE

Sample prep performed at

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High number of reads per lane Good for large genomes

Several lanes are s(ll needed for

mammalian or large plant genomes

50x coverage in a 2 lanes

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High number of reads per lane Too many for small projects

Too many reads for several applica(ons

=> Need mul4plexing

4, 8 or more samples per channel

(ChIP-SEQ, smallRNAs, bacteria, targeted re-sequencing, etc..)

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Automa;on and Quality Control

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Purified DNA

r

Total RNA Initial Quality Control Quantification & Dilution BioAnalzyer Automated library preparation OPTIONAL: Size Selection Target Enrichment

Green light from customer

HiSeq run in channel QC Bioinformatics pipelines validation and QC Library Quality Control Quantification & Dilution BioAnalzyer Sanger sequencing of index HiSeq titration

NB: Use Qubit, as Nanodrop is often not reliable

20'000 reads 1x50 provided

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Genomic Sample Prepara4on

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Blunt DNA Nebulized DNA Ends repair

T4 DNA pol, Klenow, PNK

Purification Addition of 3’ A

Klenow (exo-)

A A A A Purification Prevents self-ligation A A A A T T T T Ligation of genomic adapters T T Purification One type of double-stranded adapter

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Genomic Sample Prepara;on

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Agarose Gel purification 150-250 bp Example with a single template

5’ 5’ 3’ 3’

PCR amplification

5’ 5’ 3’ 3’ 3’ 3’ 5’ 5’ 3’ 3’ 5’ 5’

2 different reads obtained

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Genomic Sample Prepara;on

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DNA Colonies amplification

2 different reads obtained

Purification Linearization and blocking Primer hybridization Sequencing HiSeq cBot

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Germline cancers: many solu4ons

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Soma4c cancers

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Oncologist Medical report Pathology Oncologist NGS

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Soma4c cancers

ThermoFisher Oncomine solu4ons

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Purified DNA and RNA Ion S5 Oncomine BRCA 1-2 Oncomine Comprehensive Cancer Panel OCP Variants detection

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Soma4c cancers

ThermoFisher Oncomine Comprehensive Cancer Panel (OCP)

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Ion proton and Ion S5 variants detec4on on AmpliSeq Cancer Hotspot v2 workflow

Cancer Hotspot V2 Total Variants Hotspots Variants Sample Name Ion Proton v3 Ion Proton Hi-Q Ion S5 Ion Proton v3 Ion Proton Hi-Q Ion S5 QAC-51 15 15 15 3 3 3 QAC-52 19 20 19 6 6 6 QAC-53 27 27 20 14 14 8 QAC-54 14 14 15 1 1 1 QAC-55 23 22 22 7 7 7 QAC-56 19 18 19 4 4 4 QAC-59 14 14 13 5 5 5 QAC-60 16 15 15 2 2 2 QAC-61 18 17 17 5 5 5 QAC-62 10 11 11 1 1 1 QAC-63 10 11 11 1 1 1 QAC-64 10 11 11 1 1 1 QAC-65 14 15 16 4 5 4 QAC-66 16 16 16 2 2 2 QAC-67 19 18 19 2 2 2 QAC-109 17 15 15 5 5 5 QAC-110 28 28 23 14 14 11 Total 17.00 16.88 16.29 4.53 4.59 4.00 FFPE Samples QAC-68 19 20 11 5 4 4 QAC-70 17 15 16 3 3 3 QAC-71 29 33 16 6 6 6 QAC-108 93 117 27 2 2 Total 39.50 46.25 17.50 4.00 3.75 3.25

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Ion proton and Ion S5 variants detec4on on AmpliSeq BRCA-1-2 workflow

AmpliSeq BRCA-1-2 Total Variants Hotspots Variants Sample Name Ion Proton Ion Proton Hi-Q Ion S5 Ion Proton Ion Proton Hi-Q Ion S5 QAC-72 12 12 10 1 1 1 QAC-73 21 23 20 3 3 3 QAC-74 18 19 19 3 3 3 QAC-75 22 23 22 3 3 3 QAC-76 6 7 6 QAC-77 15 16 13 1 1 1 QAC-78 9 12 9 QAC-79 12 13 12 Total 14.38 15.63 13.88 1.38 1.38 1.38 FFPE Samples QAC-80 83 91 22 4 4 4 QAC-82 14 17 14 4 4 4 QAC-112 24 25 9 1 1 1 QAC-118 128 151 11 1 1 1 Total 62.25 71.00 14.00 2.50 2.50 2.50

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Non-invasive prenatal test (NIPT)

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Non-invasive prenatal test (NIPT)

75 Les 3 chromosomes principaux, Trisomies 21, 18, 13 Sexe sur demande Tous les chromosomes: Les anomalies gonosomiques Les trisomies autosomiques rares Les anomalies de la structure chromosomique www.prendia.ch

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Prendia valida4on study

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Prendia valida4on study

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Prendia valida4on study

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Prendia reports about

ver 6000 consecu4ve cases

79 Pescia et al, Gene(cs in Medicine (2016); doi:10.1038/gim.2016.72.

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Prendia reports about

ver 6000 consecu4ve cases

80 Pescia et al, Gene(cs in Medicine (2016); doi:10.1038/gim.2016.72.

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Prendia reports about

ver 6000 consecu4ve cases

81 Pescia et al, Gene(cs in Medicine (2016); doi:10.1038/gim.2016.72.

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Prendia reports about

ver 6000 consecu4ve cases

82 Pescia et al, Gene(cs in Medicine (2016); doi:10.1038/gim.2016.72.

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Prendia reports about

ver 6000 consecu4ve cases

83 Pescia et al, Gene(cs in Medicine (2016); doi:10.1038/gim.2016.72.

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pipeline at Fasteris

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Monday Tuesday Wednesday

HiSeq Rapid Run Library preparation Base-calling

Illumina HiSeq Rapid Run

Purified DNA Quality Control FaMH - FMH Reports Quality Control

Non-invasive prenatal test

Reimbursed in Switzerland as of 15.7.2015

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85 BIOINFORMATICS GENETICS genesupport NGS EFFINGER-ZENTRUM BERNE Harris Birthright Research Centre in Fetal Medicine King’s College London BERNARD CONRAD, DR PD