Next Generation Sequencing Exome Sequencing

Marcela Davila

Genomics Core Facility

NGS methods

First generation (great cost, intense human effort) 1954 – Sequencing by degradation (Whitfeld PR) 1975 – Chain termination method (Sanger & Coulson) 1977 – Chemical modification (Maxam and Gilbert) Second generation (sincronyzed washing/scanning) SBS – Illumina Pyrosequencing – Roche SBL – AB SOLiD Third generation (increase sequencing speed, high throughput, no optics) Semiconductor: Ion Torrent SBS-single molecule: Helicos SBS-single molecule-real time: Pacific Biosciences SBH/SBL- Complete Genomics FRET: VisiGen Protein nanopores: Oxford Nanopore TEM: Halcyon Molecular and ZS Genetics Transistor mediated: IBM STM: Reveo

Sanger method

Dye-labeled terminator

DNA template

Laser beam

Chromatogram

Capillar electrophoresis

Next generation sequencing

For cyclic array sequencing

1. DNA library preparation (ligation of adapters) 2. Amplification (ePCR, bridge PCR) 3. Sequencing reaction 4. Imaging 5. Decoding

1. DNA library preparation (ligation of adapters) 2. Amplification (ePCR, bridge PCR) 3. Sequencing reaction 4. Imaging 5. Decoding

Next generation sequencing

For cyclic array sequencing

1. DNA library preparation (ligation of adapters) 2. Amplification (ePCR, bridge PCR) 3. Sequencing reaction 4. Imaging 5. Decoding

Next generation sequencing

For cyclic array sequencing

SeqBySynthesis - Illumina

Pyrosequencing - Roche

Pyrogram

SeqByLigation – AB/SOLiD

First round

Second round

SeqByLigation – AB/SOLiD

SeqByLigation – AB/SOLiD

IonSensitiveFieldEffectTransistors – Ion Torrent

1 2 3

A A

C C C

G G G G

T T

A A

C C

G G

T T

SeqBySynthesis - single molecule - Helicos

Single Molecule Real Time – Pacific Biosciences

combinatorialProbeAnchorLigation – Complete Genomics

FluorescenceResonanceEnergyTransfer – VisiGen

Protein nanopores – Oxford Nanopore Tech

Exonuclease

Transmission Electron Microscopy – Halcyon Molecular/ZS Genetics

Electronic fingerprint

STM - Transistor mediated – IBM

metal

Dielectric layers

ScanningTunnelingMicroscope– Reveo

Niedringhaus TP, et al (2011) Metzker ML (2010) Schadt EE, et al (2010) Tanaka H and Kawai T (2009) Drmanac R, et al (2009) Mardis ER. (2008) http://www.illumina.com/Media/flash_player.ilmn?dirname=systems&swfname=GA_workflow_vid&width=780&height=485&iframe http://my454.com/products/technology.asp http://appliedbiosystems.cnpg.com/Video/flatFiles/699/index.aspx http://www.helicosbio.com/Technology/TrueSingleMoleculeSequencing/tSMStradeHowItWorks/tabid/162/Default.aspx http://www.pacificbiosciences.com/aboutus/video-gallery?videoImage=pac_bio_lg.jpg http://www.nanoporetech.com/news/movies#movie-24-nanopore-dna-sequencing http://www.invitrogen.com/site/us/en/home/Products-and-Services/Applications/Sequencing/Semiconductor-Sequencing/Semiconductor-Sequencing-Technology/Ion-Torrent-Technology-How-Does-It-Work.html http://www.abrf.org/Other/ABRFMeetings/ABRF2005/Hardin.pdf http://researcher.ibm.com/view_project.php?id=1120

References

Quality Check Quality Filter

Mapping to reference genome Realignment and recalibration

SNV detection Peak detection Transcript abundance estimation

Resequencing RNA-seq ChIP-Seq

Different applications, different pipelines

AAGCCTA

AAGCTTA

Human genome 3 billion bps

3 million differences

(0.1%)

AAGCTA

AAG-TA

AAG-TA

AAGCTA

UAG GGU ACU

* G T

Splice sites/branch site UTRs Coding regions

SNPs

Biotin probes

Streptavidin beads

DNA library

Hybridization

Capture

Targeted resequencing

Single end (SE)

Paired-end (PE)

Mate-pair (MP)

200-500 bp

2-5 Kb

R1

R1

R1

R2

R2

Different recipies

@HWI-H200:53:D08U2ACXX:5:1101:1231:2012 1:N:0:

GCATTTTAGTAGAACCAGNCATTTCCCCCNACNTCNNTNCGNNANNNNTAA

+

@CCFFFFFHFFHHJJJJJ#3<FGIJJJJJ#1?###################

@HWI-H200:53:D08U2ACXX:5:1101:1184:2013 1:N:0:

TATATTTAATGTACTTTCNTATTTTATATNCANTATNTNATANANNNNTTG

+

CC@FFFFFHHHFFFFHIG#3AFGIIIHIJ#2A#1:C###############

@HWI-H200:53:D08U2ACXX:5:1101:1151:2035 1:N:0:

TTTTGCCTTGTTGCCCAGGTTGGTCTCGAACTCCTGGGCTCAAGGGATATG

+

@CCFFFFFHHHHHJJJGIGJJIIBHHHHIIGBGHGCHIIIHHGIGIJGHIF

@HWI-H200:53:D08U2ACXX:5:1101:1248:2055 1:N:0:

CAGGAACAGAATGAATGAGCGAAACAAATTCCCCTTGAGCTTCACTTGTTG

+

CCCFFFFFHHHHHIJJJJJJJJJJIJJIJJIJJJJJIJJIJJJJJJJIIIH

@HWI-H200:53:D08U2ACXX:5:1101:1235:2080 1:N:0:

ATGGTCTATTAAGTATGCAATAGTATTTTGTCTAAAACAATAATGTACATA

+

@@@FADDFHHHGHFHHGEIHIJGAIFHIIIIJIHIIJHIJIJJJHFHDHII

@HWI-H200:53:D08U2ACXX:5:1101:1165:2081 1:N:0:

ATAACAATGACAATAGAATTTGGGGACTCAGGAGGAAAGGGAGGGAAGCGG

+

CCCFFFFFGHHHHJGHIIIJJJJJJJJIIIJJIGGIJJJJGIIGIIIIIJJ

@HWI-H200:53:D08U2ACXX:5:1101:1231:2012 2:N:0:

TACTNNTANNTNCAGANCAGTTTAAATAAATAAAACATNCACCAGTATGTA

+

@BCF##22##2#2<CG#2AEFGIHJIIJJJFIJJJJJJ#0?GGGBFHIJGH

@HWI-H200:53:D08U2ACXX:5:1101:1184:2013 2:N:0:

ACATNNAANNTNAAAGNTCACAAACTATATATTATATANTGTACATAAAAT

+

B@@F##22##2#3<CG#3AFHIJJJGJJJJJJJJIJJJ#0?FGHJJJJGJG

@HWI-H200:53:D08U2ACXX:5:1101:1151:2035 2:N:0:

CAAACTAACCANGCGGACTTCATTGCTTTTAGAGGACACAATTAATTCTCT

+

CCCFFFFFHHH#2<CGIJBHJJIJJGIGJIIFGGIJJJIIJHIJIGIJIJI

@HWI-H200:53:D08U2ACXX:5:1101:1248:2055 2:N:0:

TATACAATCAANGCACAATCTATTAGAATGGGAAGAGACCCTGGAGATAAT

+

CCCFFFFFHHH#2AFHIJIHHHJJJJJJIJJJJJJJJJJJJIJJHEGHGG<

@HWI-H200:53:D08U2ACXX:5:1101:1235:2080 2:N:0:

AATCCCAACACTTTGGGAGGCTGAGGTGGGTGGATCACTTGGGGTCAGGAG

+

B@?DFBFFHHHHHIJJIJIJJJJIGI:DGI?F@GBFGIIGAGIIBF>HGIH

@HWI-H200:53:D08U2ACXX:5:1101:1165:2081 2:N:0:

GCTGTGTTAGCTTCTTTGTCCTATTGAAATGCAAAGATAGGCTGACTAACT

+

CC@FFFFFHHHHHJJJJI?CHFHGJJJJJIIJJJJIIJJGFHIJJJJJJJE

R1 R2

@HWI-H200:53:D08U2ACXX:5:1101:1231:2012 1:N:0:

GCATTTTAGTAGAACCAGNCATTTCCCCCNACNTCNNTNCGNNANNNNTAA

+

@CCFFFFFHFFHHJJJJJ#3<FGIJJJJJ#1?###################

31 37 39 18 16 2

Fastq format

LIMS

Phred = 50

Probability that the base has been erroneously called

Phred score

P(called wrong)

Accuracy base call

10 1 in 10 90%

20 1 in 100 99%

30 1 in 1000 99,9%

40 1 in 10000 99,99%

50 1 in 100000 99,999%

Phred = 10

Phred quality score

Peak detection Transcript abundance estimation

RNA-seq ChIP-Seq

Quality Check Quality Filter

Mapping to reference genome Realignment and recalibration

SNV detection

Resequencing

Variant calling Annotation Custom filtering of variants

Exome pipeline

Quality check - FastQC

Quality check - FastQC

@HWI-H200:53:D08U2ACXX:5:1101:1231:2012 1:N:0:

GCATTTTAGTAGAACCAGNCATTTCCCCCNACNTCNNTNCGNNANNNNTAA

+

@CCFFFFFHFFHHJJJJJ#3<FGIJJJJJ#1?###################

X nts

Low quality

Ambiguous bases

Quality filter- FastX

CTACGATCGATCGA AGACGCAGCTACTACACG

CTACGATCGATCTACGCAGCTACTACACGTGCTGGGACGC REF

ACCACACGTGCAGG TCGATCGACG

CTACG ATCGACGCAGCTACCA AGGGACGT

READS

WHERE to place the reads? a) Unique reads b) Everywhere possible c) Choose one randomly d) Use pair-end data

HOW to place the reads? a) Ungapped b) Gapped

ACTACACGTGCAGGGACGT

Mapping

Local realignment around indels

HWI-H200:53:D08U2ACXX:6:1108:18555:16623 99 chr1 10001 0 45M6S = 10174 224

TAACCCTAACCCTAACCCTAACCCTAACCCTAACCCT

AACCCTAAAGATCG @?@DDDBDAH??FHDGFFFHIIIGDGEHHI<ABHICHIEHCDD3BDEDGEC MD:Z:45 RG:Z:1 XG:i:0 AM:i:0 NM:i:0

SM:i:0 XM:i:0 XO:i:0 XT:A:M

HWI-H200:53:D08U2ACXX:6:1101:9568:123823 99 chr1 10003 11 1S46M1S = 10204 252

GACCCTGACCCTGACCCTAACCCTAACCCTAACCCTA

ACCCCAAACCC @@CFBDFFDFHHFGIIEHGGGD@GGHDGGFHGGEHEGCGHGGHGEHGC MD:Z:5A5A28T2C2 RG:Z:1 XG:i:0

AM:i:11 NM:i:4 SM:i:11 XM:i:4 XO:i:0 XT:A:

M

HWI-H200:53:D08U2ACXX:6:1302:17187:33007 97 chr1 10003 0 51M chrM 430 0

ACCCTAACCCTAACCCTAACCCTAACCCTAACCCTAA

CCCTAACCCTAACC CCCFFFFFHHHHHJJJJJJIIIIJJJJJIIJJJJJJJJJJJJJJJJJIIGI X0:i:513 MD:Z:51 RG:Z:1 XG:i:0

AM:i:0 NM:i:0 SM:i:0 XM:i:0 XO:i:

0 XT:A:R

HWI-H200:53:D08U2ACXX:6:1104:2930:78353 177 chr1 10004 0 51M chr22 38431286 0

CCCTAACCCTAACCCTAACCCTAACCCTAACCCTAAC

CCTAACCCTAACCC IIGAF?JJIGADJIGGD?GHGEEEIHGCCGIIHIHHIHFDHDHDDDDB@@B X0:i:515 MD:Z:51 RG:Z:1 XG:i:0

AM:i:0 NM:i:0 SM:i:0 XM:i:0 XO:i:

0 XT:A:R

HWI-H200:53:D08U2ACXX:6:1205:3665:10423 99 chr1 10054 0 51M = 10366 363

CTAACCCTAACCCTAACCCTAACCCTAACCCTAACCCTAACCCTA

ACCCTA CCCFFFFFDBHHHIGEGEHEHIJJIHIFGIIGEHIGH9FGHHIIJJGGI=C X0:i:502 MD:Z:51 RG:Z:1 XG:i:0 AM:i:0

NM:i:0 SM:i:0 XM:i:0 XO:i:0 XT:A:

R

HWI-H200:53:D08U2ACXX:6:1101:4778:107011 163 chr1 10056 0 51M = 10355 350

AACCCTAACCCTAACCCTAACCCTAACCCTAACCCTA

ACCCTAACCCTAAC CCCFFFFFHHHHGJJJJJJJJJJIJJIJJIIHGIJECEHIJ;FGEIIEHCA X0:i:508 MD:Z:51 RG:Z:1 XG:i:0

AM:i:0 NM:i:0 SM:i:0 XM:i:0 XO:i:

0 XT:A:R

SAM (Sequence Alignment/Map) BAM

Query name HWI-H200:53:D08U2ACXX:6:1101:1233:2037

Flat 83

Reference name chr15

Leftmost position 47933389

Mapping quality 29

CIGAR string 51M

Mate reference =

Mate position 47933089

Insert size 351

Query sequence AATGAATGNCCATGGNCAGCAGCAGGACAGCAGGAACCACGTCT

Quality 00#9DG?:1#FB@>E@BGHHCGCFABIIHEIGFHFDC7;ADB@?@

Optional fields XT:A:U NM:i:2 SM:i:29 AM:i:29 X0:i:1 X1:i:0

BAM format

ACTACACGTGCAGGGACGT CTACGATCGATCGA AGACGCAGCTACTACACG

CTACGATCGATCTACGCAGCTACTACACGTGCTGGGACGC REF

ACCACACGTGCAGG TCGATCGACG

CTACG ATCGACGCAGCTACCA AGGGACGT

READS

Is it a variant allele?

P(CC|D) = 0.06 P(CT|D) = 0.94 P(TT|D) = 3 × 10−11

What is the most likely

genotype?

Variant calling - GATK

VCF format

In which gene is it located? Name, Description,

OMIM, Pathway, GO,

Expression profiles . . .

Where in the gene is it located? Intron, exon, UTR,

intergenic region, splice site Is there any AA change? GAA -> GAG = E->E

GTT -> CTT = V->L

TGG -> TGA = W->X

TGA -> CGA = X->R

What impact does the AA

change have? Damaging, benign

Is it a known SNP?

ACTACACGTGCAGGGACGT CTACGATCGATCGA AGACGCAGCTACTACACG

CTACGATCGATCTACGCAGCTACTACACGTGCTGGGACGC REF

ACCACACGTGCAGG TCGATCGACG

CTACG ATCGACGCAGCTACCA AGGGACGT

READS

Annotation – Annovar, SIFT, PERL

300,000 SNPs - 10,000 Indels

Variants list

Exome sequencing

cases

Coding variants

Controls Genetic variation DBs

Disease model Disease knowledge

Candidate genes

Family filters

The real work begins…

http://www.sciencedirect.com/science/article/pii/S0002929711003946

Variants filtering

Data visualization